economics case study 2022

What’s the Latest Research in Development Economics? A Roundup from NEUDC 2022

Almedina music, david evans.

What’s the latest in international economic development research? Last weekend was the North East Universities Development Consortium annual conference , often called NEUDC. With more than 135 papers presented (and almost all of them available for download ), it’s a great way to see recent trends in the international development research by economists and to learn about new findings.

The studies come from all over the world, as you can see in Figure 1 below. Just like last year , the plurality of studies take place in India (30 studies). Kenya is next (12), then Bangladesh (8), Brazil (7), China (7), and Indonesia (7). More than 40 countries are represented overall, from almost all regions of the world.

Figure 1: Where are recent development economics studies focused?

Source: This map draws on a sample of 139 studies from the NEUDC 2022 conference. Studies that covered more than three countries (often broad global or regional analyses) were excluded.

Researchers draw on a wide range of empirical methods. Nearly a third of studies reported on the results of a randomized controlled trial (43 studies). Other commonly used methods include difference-in-differences, fixed effects, and instrumental variables.

Figure 2: What empirical methods do recent development economics papers used?

Source: This chart draws on a sample of 139 studies from the NEUDC 2022 conference. Some studies used more than one method.

Below, we provide a quick takeaway from every paper in the conference for which we could find a digital copy. As you read our takeaways, keep the following in mind. First, we can’t capture all the nuance of a paper in a couple of lines. Second, our takeaway may not be the authors’ takeaway. Third, some of the papers are marked as preliminary and not ready for formal citation (you can see which if you follow the paper links). Fourth, we largely take the findings of these papers at face value: most have not yet been through peer review, so feel free to dig into the data and analysis to decide how confident you are in the results.

Our takeways are sorted by topic. If your principal interest is in a country or region, you can also read the takeaways sorted by country . We provide some indication of the empirical method used (for empirical papers) with hashtags at the end of the takeaways. Some papers fit into more than one category: for example, is a paper about the impact of free childcare on mothers’ careers about labor or about gender? It’s about both! In those cases, we’ve repeated studies in multiple sections below so if you’re focused on health, you’ll find all the health-related papers in the health section. The second or third time a paper appears, we put an asterisk after the summary so you can skip it if you’re reading straight through.

Happy learning!

Guide to the methodological hashtags: #DID = Difference-in-differences, #FE = Fixed effects, #IV = Instrumental variables, #LIF = Lab in the field, #PSM = Propensity score matching, #RCT = Randomized controlled trial, #RD = Regression discontinuity, #Other = Other

Households and human capital

Education and Early Childhood Development

·        How critical are family conditions in early years for child development? Better weather (which means more agricultural income and better nutrition) at age 2 in Indonesia leads to higher adult cognitive ability. When households face hard times at earlier ages, they compensate with prolonged breastfeeding. ( Webb ) #FE

·        Data from Indonesia suggest that parental education and parental income are the main drivers of differences in skills once kids grow up. ( Thomas ) #Other

·        “Many teachers [in India and Bangladesh] underestimate the share of low performers in their classrooms, and...they believe that those students will perform better than they actually do. These results are not driven by less educated, trained, or experienced teachers or explained by biases against female, low-income, or lower caste students.” ( Djaker, Ganimian, and Sabarwal ) #Other

·        A 1985 change in Indian law discouraging the payment of dowries led to a 24 percent drop in dowry payments, but it also led to an 18 percent reduction in girls' education attainment (with no impact on boys' education). ( Jha ) #DID

·        Providing information about a learning app in Bangladesh didn't lead more people to use it, but it did lead some parents to arrange more tutoring, resulting in "lasting math learning gains, concentrated among richer households." ( Beam, Mukherjee, and Navarro-Sola ) #RCT

·        Students in Kenya often apply to secondary schools with little information about the available schools. Providing information to students "led them to apply to" schools that were closer to home "without compromising school quality." Adding parents to those information meetings "led students to enroll in lower cost schools." ( Bonds ) #RCT

·        Among students in 9th grade in India, student test scores rose similarly whether they were exposed to "rigidly defined remedial lessons that take time away from the curriculum" and "teacher determined remedial lessons," which allow teachers more flexibility. ( Beg et al. ) #RCT

·        Parental aspirations for their children matter, but they may not be enough on their own. “In rural Gambia, families with high aspirations for their children’s future education and career, measured before children start school, go on to invest substantially more than other families in the early years of their children’s education. Despite this, essentially no children are literate or numerate three years later. When villages receive a highly-impactful, teacher-focused supply-side intervention, however, children of these families are 25 percent more likely to achieve literacy and numeracy than other children in the same village.” ( Eble and Escueta ) #RCT

·        A ten day increase in the overlap between school days and peak farming periods in Malawi translates to children losing about a third of a year of schooling. ( Allen ) #IV

·        Eliminating school fees for secondary school in Tanzania led not only to increased secondary school enrollments; it also increased primary school pass rates. ( Sandholtz ) #DID

·        Indonesia's major school construction program from the 1970s led to eight percent overall higher national output forty years later, and much of that comes through migration from rural to urban areas. ( Hsiao ) #DID

·        Phone call tutorials during COVID-19 were effective at boosting learning in India, Kenya, Nepal, Philippines, and Uganda, whether implemented by government teachers or non-government organization instructors. ( Angrist et al. ) #RCT

·        An affirmative action policy in Brazil was effective at redistributing university spots to low-income students, with little drop in average achievement. "The policy also reduced the gap in applications to selective majors" between poor and rich students by more than 50 percent, but note that those are applications: many of those major-choice changes were among students unlikely to be accepted into a highly selective major. The policy worked, but it could work even better. ( Melo ) #DID

·        Peru shut down a bunch of low-quality universities in 2015. Graduates from surviving universities experienced an increase in wages and higher employment rates. ( Vivar, Flor-Toro, and Magnaricotte ) #DID

·        An influx of Syrian refugees in Jordan reduced school enrollment among Jordanians, particularly boys and kids with less-educated parents. More young Jordanians went to work instead. ( Almuhaisen ) #DID

·        An edutainment program in Bangladeshi schools to trace school-to-home transmission of handwashing find that children are induced to wash more at school but less at home, yielding a net negative effect of the program ( Hussam and Oh ) #RCT

·        Removing English language study from pubic primary schools in West Bengal, India, increased private school enrollment and---for those still in public schools---increased private tutoring among the richest households. ( Nandwani and Sen ) #FE

·        In utero exposure to high ocean salinity levels (induced by climate change) reduces a child’s height-for-age z-score in Bangladesh, and increased prevalence of stunting and severe stunting due to nutritional deficiencies by age five. ( Guimbeau et al. ) #FE

·        In Indonesia, “remittances increase household consumption, reduce poverty, and stimulate growth. Households send more children to school, and district governments increase public schools at the primary and junior secondary levels.” ( Hilmy ) #FE

·        The tariff reduction from the U.S-Vietnam Bilateral Trade Agreement decreased school attendance and increased children’s work, mainly in non-wage and household business jobs. Effects were stronger for boys, older children and households where the head had little education. ( Nguyen ) #DID

·        Giving a widely known award "to top performers on a mandatory nationwide exam in Colombia" boosts their earnings by between 7 and 12 percent, and the effect endures for 5 years after graduation. It helps students graduating from low-reputation colleges the most. ( Busso, Montaño, Muñoz-Morales ) #RD

Health (including mental health)

·        A national vaccine program in Burkina Faso in 1984 boosted the country’s child vaccination rate (against measles, yellow fever, and meningitis) from 17 percent to 77 percent in a few months. Child mortality fell, primary school completion rose, and—when the children reached adulthood—employment and agricultural productivity rose. ( Daramola et al. ) #DID

·        School-based deworming in western Kenya—nearly a quarter of a century later—reduced under-5 mortality of the beneficiaries’ children by 24 percent! ( Walker et al. ) #RCT

·        In Ecuador, letting employees use work time to get a flu vaccine boosted vaccination rates, but employees got sick about as much. Why? Some evidence suggests that employees engaged in “riskier health behaviors after getting vaccinated.” ( Hoffman, Mosquera, and Chadi ) #RCT

·        In Kenya, “both patient subsidies and pharmacy incentives for diagnostic testing significantly increase usage of testing and may encourage malaria positive individuals to purchase high quality antimalarials.” ( Dieci ) #RCT

·        Women who were babies in utero during a cholera epidemic in Peru in the 1990s were nearly 20 percent more likely to die of COVID-19. ( Ritter and Sanchez ) #DID

·        After four years of using iron and iodine fortified salt in school lunches in India, children have lower likelihood of anemia, higher hemoglobin levels, but no differences in cognitive or educational outcomes. ( Grafenstein et al. ) #RCT

·        Gold mining in the Philippines created new bodies of stagnant water, which boosted malaria cases by nearly a third (relative to provinces without gold deposits). ( Pagel ) #DID

·        Giving households a flyer about mobile health services in rural Bangladesh didn't get them to use it more, but offering to save the access numbers in the participants' phone boosted take-up by 22 percent in the succeeding 2 months and reduced health expenditure, since households were less likely to go to "informal providers who usually overprescribe medicines." ( Sardar ) #RCT

·        A drug procurement program in China "brought down the prices of 10 chronic condition drugs by an average of 78" percent. As a result, "drug adherence was improved for the uninsured who had poorer adherence" before the price reduction. ( He and Yang ) #DID

·        In Dakar, Senegal, it can be hard to find someone to desludge your septic pit. Providing subsidies to use a government run call center to connect households with desludgers increases use, and that use continues for a while after the subsidies end. Later, a city-wide subsidy increased adoption most in those communities that had received subsidies earlier. ( Deutschmann ) #RCT

·        How critical are family conditions in early years for child development? Better weather (which means more agricultural income and better nutrition) at age 2 in Indonesia leads to higher adult cognitive ability. When households face hard times at earlier ages, they compensate with prolonged breastfeeding. ( Webb ) #FE *

Fertility and family planning

·        "Learning about government mistreatment of citizens undermines trust in institutions. In Perú, “disclosure of information about illegal sterilization reduced usage of contraceptive methods, prenatal and delivery services, and the demand for medical services, resulting in worsened child health."" ( León-Ciliotta, Zejcirovic, and Fernandez ) #DID

·        During the colonial period in the Congo, greater exposure to Catholic nuns increased women’s fertility (as opposed to exposure to Protestant or male Catholic missionaries). Catholic nuns likely promoted the image of an ideal Christian woman which explains the results. ( Guirkinger and Villar ) #DID

Households and marriage

·        Households in Bangladesh reduced their monthly residential electricity use by 15.8 percent (≈37 kWh) when they switched from postpaid electricity metering system to prepaid metering. ( Das ) #IV

·        A new method to infer causal effects on choices that exploits relationships between choices and hypothetical evaluations “can recover treatment effects even if the treatment is assigned endogenously and standard estimation methods are poorly suited, or if the treatment does not vary.” ( Bernheim, et al. ) #Other

·        In the Democratic Republic of the Congo, 73 percent of households provided with access to childcare centers use them.  Both parents “increase their engagement in commercial activities, leading to gains in agricultural productivity, household income and women’s subjective well-being." Women reported increases in their concentration and sense of control.  Using the centers also led to  significant gains in early childhood development outcomes, particularly for younger children.  ( Donald and Vaillant ) #RCT

·        Can commitment-saving ahead of a lean season alter consumption downfalls among the ultra-poor? In Bangladesh, a temporary savings subsidy doubled formal savings, and resulted in increased food and non-food expenditure by 8.6-12.6 percent during the lean season, with no lasting post-lean season impact. ( Takahashi et al. ) #RCT

·        An “edutainment” intervention designed to reduce child marriage in rural Pakistan, significantly reduces marriage of girl adolescents. Targeting men alone reduced child marriage in sample households, while targeting women or men & women jointly reduces child marriage at the village level. ( Cassidy et al. ) #RCT

·        In Kenya, workshops and couples’ therapy sessions to decrease alcohol consumption lowered prevalence of sexual intimate partner violence (IPV) by 0.21 standard deviations, with smaller or no effects on physical and emotional IPV. ( Castilla, Aqeel, and Murphy ) #RCT

Migration and refugees

·        Can temporary foreign work permits “throttle human smugglers’ businesses? “Combining internal and external controls with a regulated market for temporary visas alleviates the policy trade-off between migration control and ending human smuggling.” Data from migration between Senegal & Spain and the Democratic Republic of the Congo & South Africa. ( Auriol, Mesnard, and Perrault ) #Other

·        Massive exodus of Venezuelans in Colombia had a larger negative effect on the lower tail of the natives’ wage distribution, increasing inequality in the host economy. Due to formal restrictions, immigrants ended up working in more routine and low-paying jobs. “A large-scale amnesty program reduced the magnitude of downgrading, mitigating the unequalizing impact of the exodus.” ( Lombardo et al. ) #IV

·        In Mexico, children in households with return migrants (from the U.S.) “benefit from an increase in school attendance and a decrease in the probability of schooling delay relative to children in non-migrant households.” However, females in return migrant households are likely to complete a lower grade relative to non-migrant households. ( Chakraborty, Bucheli, and Fontenla ) #IV

·        An evaluation of a large-scale migration loan program in Bangladesh revealed that capacity constraints at scale lead effort to be directed toward those already planning to migrate without a loan. ( Mitchell et al. ) #RCT

·        A Zambian fertilizer subsidy program led to “some households to intensify their agricultural activity, and others to out-migrate.” The subsidy increased the share of households with outmigrants by 40 percentage points and doubled the number of outmigrants net of in-migrants. ( Diop ) #DID

·        Clearance of slums in Santiago, Chile, and families’ relocation to public housing in low-income areas led to displaced children having 10 percent lower earnings and 0.5 fewer years of education as adults than non-displaced. ( Rojas-Ampuero and Carrera ) #FE

·        In refugee camps and surrounding communities in Uganda and Kenya, refugee children can be up to three times more likely to be poor than adults. Child’s age, household composition, and access to sanitation and clean water, predict child poverty in refugee settlements well, often better than per-capita household expenditure. ( Beltramo et al. ) #ML

·        In Indonesia, “remittances increase household consumption, reduce poverty, and stimulate growth. Households send more children to school, and district governments increase public schools at the primary and junior secondary levels.” ( Hilmy ) #FE *

·        During WWII, nine ethnic groups were entirely deported from the Soviet Union to Central Asia. In the 50s, five returned to their former homeland, while the other four remained marginalized in internal exile. Locals in host regions had significantly higher levels of education two generations later. “A strong positive effect on higher education is found among returnees to origin regions, suggesting that these ethnic groups hedged against further negative shocks.” ( Zimmermann ) #IV

·        An influx of Syrian refugees in Jordan reduced school enrollment among Jordanians, particularly boys and kids with less-educated parents. More young Jordanians went to work instead. ( Almuhaisen ) #DID *

·        Pairing employers in Uganda with a refugee and providing an incentive to offer a free internship to that refugee "improves employers’ beliefs about refugees’ skills, but it does not change their willingness to hire new refugees," but certain types of matches (depending on employer and refugee characteristics) do result in more refugee hires. ( Loiacono and Silva-Vargas ) #RCT

·        In India, Hindu women are subject to caste “purity” norms, while Adivasi, or Indigenous, women are not. “Having more Adivasi neighbors leads to: (i) higher rates of Hindu women’s paid work and lower perceived stigma of such work; and (ii) lesser adherence to a range of purity norms, including the practice of untouchability towards Adivasis.” ( Agte and Bernhardt ) #FE

·        Does free childcare improve mothers’ careers? Yes. In Sao Paulo, Brazil, mothers in sub-districts with above median childcare availability have a persistent increase of 8 percent in earnings, driven by 1 percentage point higher labor force participation and 4 percent longer hours. ( Garcia, Latham-Proença, and Mello ) #FE

·        Can cash transfers influence gender roles? In Chad, cash transfers increased women’s business profits (0.6 SD) as well as marital separation. The program also “led to large improvements (0.3-0.7 SD) in a broad set of women’s subjective well-being, including self-efficacy, depressive symptoms, and perceived social status.” ( Kandpal, Schnitzer, and Dayé ) #RD

·        In Nigeria, women prefer to defer budget allocation decisions to their husband even when deferral is costly and is not observed by the husband; the reverse is true for husbands. A randomized cash transfer receipt increases women’s demand for agency: if the decision is hidden from the husband, women want to make their own budget decisions, even if it is the same as their husband’s. ( Bakhtiar et al. ) #LIF

·        Showing teachers in Pakistan a pro-women’s rights award-winning movie (the 2011 film Bol) increased their own and students’ support for women’s rights, being unbiased in gender Implicit Association Tests, and willingness to petition parliament for greater gender equality. ( Mehmood, Naseer, and Chen ) #RCT

·        Profiles for women who signal on an online Indian matchmaking site that they want to work after marriage receive up to 22 percent less interest from men than those of women who have never worked. Women willing to give up work after marriage face a lower penalty. ( Dhar ) #RCT

·        In Chile, informing outstanding students in mathematics and science about their relative performance and presenting STEM majors as a feasible option, led to women applying more, but only in health-related majors, and not in STEM majors. ( Ramirez-Espinosa ) #RCT

·        In Brazil, union bargaining that prioritized women’s needs increased female-centric amenities (like longer maternity leave with job protection) at work. These led to women queueing for jobs at treated establishments and separating from them less, which are both indicators of firm value. ( Corradini, Lagos, and Sharma ) #DID

·        While both gender barriers to occupational choices and wage penalties persist across countries, the “reduction in wage gaps between 1980-2000 was primarily driven by economic channels while the more recent decline between 2000-2015 was driven by changes in gender barriers.” ( Chiplunkar and Kleineberg ) #Other

·        “A program targeting ultra-poor women in Uganda” paired “business and entrepreneurship skills development with psychological empowerment.” It increased profits by 105 percent. ( Lang and Seither ) #RCT

·        Expansion of the coffee mills in Rwanda led to increased “women’s paid employment, women’s and their husbands’ earnings and decreases domestic violence.” Decline in violence is driven by women’s increased bargaining power and their contribution to household earnings, not exposure reduction between couples. ( Sanin ) #DID

·        Sharing a hyperlocal digital job search platform with couples as well as the wives' social networks in Delhi, India, increased husband's labor market outcomes (including working hours and total earnings), but only home-based self-employment among the women, potentially due to social norms. ( Afridi et al. ) #RCT

·        New data from more than 90 countries demonstrates three things: (1) the shift out of agriculture that happens as countries grow richer is driven by whole households (not just individuals within households), (2) "in the poorest countries, the gap between female and male market employment is only large for married urban women," and (3) "countries where employment rates of urban married women are low relative to their rural counterparts also see low urbanization rates of married men." ( Doss et al. ) #Other

·        In Kenya, workshops and couples’ therapy sessions to decrease alcohol consumption lowered prevalence of sexual intimate partner violence (IPV) by 0.21 standard deviations, with smaller or no effects on physical and emotional IPV. ( Castilla, Aqeel, and Murphy ) #RCT *

·        A 1985 change in Indian law discouraging the payment of dowries led to a 24 percent drop in dowry payments, but it also led to an 18 percent reduction in girls' education attainment (with no impact on boys' education). ( Jha ) #DID *

Working and saving

Banking and credit

·        In India "delinquent borrowers who are offered a debt moratorium by their lender are 4 percentage points (6.9 percent) less likely to default on their loan, while forbearance has no effect on repayment if it is granted by the regulator.” ( Fiorin, Hall, and Kanz ) #RCT

·        What are the household welfare gains from financial inclusion? Applying a new approach using demand estimates from three RCTs (on retirement savings in the United States, commitment savings in the Philippines, and microfinance in Mexico) , welfare gains per dollar lent or saved are small as compensated demand elasticities are large, but still correspond to large aggregate welfare gains from financial inclusion. ( Loeser ) #Other

·        In Ghana, microenterprises receiving joint liability loans reported higher profits six to ten months after borrowing. Effects are driven by borrowers whose applications were not endorsed by political party operatives. ( Boso, Burlando, and Abdul-Rahaman ) #FE

·        A self-help group lending program in rural Bihar, India, “significantly improved risk-sharing in regions where the program had greater institutional capacity and was better implemented.” ( Attanasio et al. ) #FE #IV

·        In Kenya, “performance-contingent microfinance contracts can encourage investment and increase profits – and, as a result, increase household consumption.” ( Cordaro et al. ) #RCT

·        In India, “plants exposed to banking shocks redistribute this liquidity through the supply chain. As a result, firms extending trade credit can increase their own sales as their customers are able to purchase on credit. Downstream firms are able to increase their own sales, employment, and productivity.” ( Chakraborty et al. ) #DID

·        In India, “risk pooling creates a distortion in consumption such that food consumption is better protected from aggregate village shocks than nonfood consumption.” ( Fafchamps and Shrinivas ) #Other

Cash transfers

·        Can cash transfers influence gender roles? In Chad, cash transfers increased women’s business profits (0.6 SD), and marital separation. The program also “led to large improvements (0.3-0.7 SD) in a broad set of women’s subjective well-being, including self-efficacy, depressive symptoms, and perceived social status.” ( Kandpal, Schnitzer, and Dayé ) #RD *

Firms and microenterprises

·        In India, “larger cultural proximity [by way of caste and religion] between a pair of firms reduces prices and fosters trade at both the intensive and extensive margins.” ( Fujiy, Khanna, and Toma ) #FE

·        After close elections in India, entrepreneurs from the same social group as the winning candidate are more likely to start businesses. ( Bhalla et al. ) #FE

·        Politically connected firms in India were more likely to get access to short-term credit from banks and to be able to delay short-term payments to suppliers and creditors during the surprise demonetization of 2016. ( Chen et al. ) #Other

·        Variation of COVID lockdowns over time and across parts of India reveal that inputs delivered by suppliers within the same industry are complements (rather than substitutes), which means that "shocks propagate through supply chains," increasing the shock to overall GDP. ( Fujiy, Ghose, and Khanna ) #FE

·        "Starting in 1997, India dismantled its policy of product reservation whereby hundreds of products had been reserved for exclusive production by small firms." The effect? "entry in the downstream product market increases with no observable decline in quality of entrants." ( Rastogi ) #Other

·        Inviting Zambian farmers to participate in a simple budgeting exercise (i.e., think through their budget and formulate a spending plan) increased how much they expected to spend for the coming year by 20-60 percent and lowered their willingness to pay for a nonessential item of clothing by 34 percent. By the end of the year, farmers decreased their expenditures by 15 percent and ended up with one additional month of savings. ( Augenblick et al. ) #RCT

·        A new way to measure productivity of retailers in low- or middle-income countries captures their three-fold need to attract customers, manage a storefront, and maintain inventory across many products. In Malawi, "the three dimensions of productivity are correlated with one another" but not perfectly, so that a training that focuses on just one may fail to boost overall productivity. ( Huntington ) #Other

·        In Mexico, a rise in gas prices led to an increase in mom-and-pop shops but "their average size and quality fell." ( Ramos-Menchelli and Sverdlin-Lisker ) #IV

·        Waiving competitive bidding for small-value purchases in Brazil led to 23 percent more expensive purchased products. At least half of this overpricing is explained by discretion allowing agencies to purchase higher-quality products. ( Fazio ) #FE

·        “A program targeting ultra-poor women in Uganda” paired “business and entrepreneurship skills development with psychological empowerment.” It increased profits by 105 percent. ( Lang and Seither ) #RCT *

Labor (including child labor)

·        A late 1990s labor market reform in China led to tens of millions of layoffs in a short period. That led to a drop in employment for workers who did not finish high school—by 20 percent in the industrial sector—and a 5 percent increase in the high school completion rate. ( Zhao ) #DID

·        “A 2014 Bolivian law that recognized the work of children as young as 10 years old, whose age placed them below the minimum working age of 14 years old, enabling them to legally work (subject to a work permit) while simultaneously extending benefits and protections to child workers” (such as adult minimum wages) actually decreased work for children under 14. ( Lakdawala, Martínez Heredia, and Vera-Cossio ) #Other

·        A federal policy that set minimum fares for drivers of motorcycle taxis on a ridesharing app in Indonesia led to higher trip prices but not driver earnings, both because more drivers signed on for any given day AND drivers logged onto the app for more hours, meaning that each driver got fewer rides. ( Nakamura and Siregar ) #DID #SC

·        Providing mentorship to vocational students in Uganda to help with their training-to-work transition increased their likelihood of working a few months later by more than a quarter and also boosted their incomes after a year. Why? It's mostly through info about how the entry-level job market works (not through referrals): As a result, mentored youth "turn down fewer job offers." ( Alfonsi, Namubiru, and Spaziani ) #RCT

·        College students in Mumbai, India, were less likely to share information about jobs if they knew they'd have to compete for them, and the men in particular tended not to share the information with the peers they viewed as having high abilities. ( Chiplunkar, Kelley, and Lane ) #RCT

·        Why do "workers in richer countries experience faster rates of wage growth over their lifetimes than workers in poorer countries"? Cross-country data suggest that workers in rich countries received more training from the firms they work for, and that this is a major component of workers' skills. "Firm-provided training accounts for 38% of cross-country wage growth differences." ( Ma, Nakab, Vidart ) #Other

·        Many interventions help workers with job searches. Doing that without increasing the number of jobs could limit the effectiveness of those interventions. On the other hand, "making it easier for firms to find qualified workers could reduce the cost of hiring" and generate more jobs. With an intervention to subsidize job searches for people in Ethiopia, the lack of jobs ends up limiting the effectiveness. ( Van Vuren ) #RCT

·        A survey in Accra, Ghana, showed that lots of job vacancies were not widely circulated, and---as a result---many employers are unable to find qualified workers during six months. But publishing detailed advertisements on a state-operated online portal increases both the likelihood of finding workers and of those workers being suitable for the jobs. ( Lambon-Quayefio et al. ) #RCT

·        The timing of when auctions for public procurement contracts end in Brazil is random, which permits comparison of winners and runners-up. "Winning a government contract increases wages." ( Carvalho, Galindo da Fonseca, and Santarrosa ) #IV

·        In rural Kenya, a “future orientation” workshop that teaches participants techniques to imagine a positive future, lay out concrete short-term steps to achieve their vision, and plan for obstacles, lifted aspirations and expectations. It led to increased labour supply and spending on productive inputs. The “intervention is at least twice as cost-effective as an (unconditional) cash transfer.” ( Orkin et al. ) #RCT

·        Peru shut down a bunch of low-quality universities in 2015. Graduates from surviving universities experienced an increase in wages and higher employment rates. ( Vivar, Flor-Toro, and Magnaricotte ) #DID *

·        Does free childcare improve mothers’ careers? Yes. In Sao Paulo, mothers in sub-districts with above median childcare availability have a persistent increase of 8 percent in earnings, driven by 1 percentage point higher labor force participation and 4 percent longer hours. ( Garcia, Latham-Proença, and Mello ) #FE *

·        Can temporary foreign work permits “throttle human smugglers’ businesses? “Combining internal and external controls with a regulated market for temporary visas alleviates the policy trade-off between migration control and ending human smuggling.” Data from migration between Senegal & Spain and the Democratic Republic of the Congo & South Africa. ( Auriol, Mesnard, and Perrault ) #Other *

·        Pairing employers in Uganda with a refugee and providing an incentive to offer a free internship to that refugee "improves employers’ beliefs about refugees’ skills, but it does not change their willingness to hire new refugees," but certain types of matches (depending on employer and refugee characteristics) do result in more refugee hires. ( Loiacono and Silva-Vargas ) #RCT *

·        Expansion of the coffee mills in Rwanda led to increased “women’s paid employment, women’s and their husbands’ earnings and decreases domestic violence.” Decline in violence is driven by women’s increased bargaining power and their contribution to household earnings, not exposure reduction between couples. ( Sanin ) #DID *

·        Sharing a hyperlocal digital job search platform with couples as well as the wives' social networks in Delhi, India, increased husband's labor market outcomes (including working hours and total earnings), but only home-based self-employment among the women, potentially due to social norms. ( Afridi et al. ) #RCT *

·        Giving a widely known award "to top performers on a mandatory nationwide exam in Colombia" boosts their earnings by between 7 and 12 percent, and the effect endures for 5 years after graduation. It helps students graduating from low-reputation colleges the most. ( Busso, Montaño, Muñoz-Morales ) #RD *

·        New data from more than 90 countries demonstrates three things: (1) the shift out of agriculture that happens as countries grow richer is driven by whole households (not just individuals within households), (2) "in the poorest countries, the gap between female and male market employment is only large for married urban women," and (3) "countries where employment rates of urban married women are low relative to their rural counterparts also see low urbanization rates of married men." ( Doss et al. ) #Other *

Poverty Measurement

·        Poverty is often measured using annual income. But using monthly data from India shows that “experiences of poverty are substantially more common than annual measures suggest; entry into and exit from poverty are much less clear than typically assumed;” and the use of monthly poverty measures “is a stronger predictor of development outcomes – child weight and height – than conventional” annual measures. ( Merfeld and Morduch ) #Other

·        Are poverty lines real? This study articulates social and theoretical underpinnings for such a distinction between the poor and the nonpoor. ( Dutta et al. )

·        Many social programs identify their beneficiaries collaboratively with multiple community members together. Comparing the judgments that the same individuals make about who to target when they’re deciding collaboratively versus individually in Indonesia suggests that gains from collaborative targeting are negligible. “These results suggest that policymakers should think carefully before asking community members to invest valuable time in participating in [community-based targeting] exercises.” ( Trachtman ) #Other

Governments, institutions, and conflict

Conflict and crime

·        A national-level electoral reform in Mexico that increased politicians’ cost of accepting bribes decreased the number of suspicious financial reports by around 4 percent ( ∼ 650 fewer reports), while the number of attacks by violent groups increased by approximately 2 percent ( ∼ 44 more attacks), in places with the presence of criminal organizations. ( Rámon Enríquez ) #DID

·        How does ethnic violence and subsequent segregation shape children’s lives? In India, Muslims perform better in cities that were more susceptible to (Hindu) communal violence in terms of early education outcomes. ( Kalra ) #PSM

·        In India, judges are more likely to convict offenders in cases of sexual crimes (excluding rape) if they are exposed to more media coverage about sexual crimes that are unrelated to the case on trial. A central mechanism behind this result is heightened judicial scrutiny in response to greater media coverage. ( Vasishth ) #DID

·        During WWII, nine ethnic groups were entirely deported from the Soviet Union to Central Asia. In the 50s, five returned to their former homeland, while the other four remained marginalized in internal exile. Locals in host regions had significantly higher levels of education two generations later. “A strong positive effect on higher education is found among returnees to origin regions, suggesting that these ethnic groups hedged against further negative shocks.” ( Zimmermann ) #IV *

·        In Colombia, close family connections in the public administration are pervasive and they weaken performance. “Connected bureaucrats receive higher salaries and are more likely to be hierarchically promoted but are negatively selected in terms of public sector experience, education, and records of misconduct.” A 2015 anti-nepotism legislation had limited effectiveness. ( Riaño ) #RCT

·        In China, after a high-profile corruption inspection, labor “strikes experienced a twofold increase within six months and a threefold increase in two years.” ( Chen ) #Other

·        Reducing corruption in China "induces positive selection for integrity and public-mindedness into the state sector, which remains present even when conditioning on ability and family background." ( Hong ) #DID

·        Do autocrats favor their supporters during economic shocks? The Maduro regime was more likely to exempt regime-supporting regions affected by the Venezuelan blackout from later power rationing. In Sub-Saharan Africa, “droughts magnify differences in development, protests and state-coercion outcomes in favor of leaders’ home regions.” ( Morales-Arilla ) #FE

·        In Brazil, a 1 percentage point increase in the share of Pentecostals increased Evangelical and far-right candidates’ vote share by 18 percent and 16 percent, respectively. These effects are larger in municipalities with less educated, poorer, and more rural populations. ( Solá Cámpora ) #DID

·        During a social media ban at the climax of the Uganda 2021 election campaign, those maintaining access through the use of virtual private networks (VPNs)—who are more likely to be opposition partisans—came to view the dominant National Resistance Mmovement party relatively positively. This is driven by an increase in pro-NRM social media content during the ban. ( Bowles, Marshall, and Raffler ) #DID

Taxes and subsidies

·        Simulations suggest that removing subsidies for electric vehicles in China would raise the effective marginal costs of vehicle production, reducing total welfare by 7.4 billion yuan (RMB) per quarter, amounting to 13.9 percent of the total subsidy expenditure. ( Kwon ) #IV

·        In South Africa, "firms with paid tax practitioners exhibit sharper bunching, driven primarily by a lower lumpiness parameter rather than by a different income elasticity." ( Anagol et al. ) #Other

·        In Liberia, creating a new property database and including identifying information from it (the name of the owner and a property photograph) in tax bills more than quadruples the tax payment rate, from 2 percent to almost 10 percent, when the notice also includes details on the penalties for noncompliance. Compliance goes up even more when the tax bill warns delinquent property owners that they’re in the “next batch” of properties designated for “intensive follow-up.” ( Okunogbe ) #RCT

·        An increase in the subsidy for liquefied natural gas (LNG) in India leads to a surprising decrease in LNG purchases by poor households. Why? The subsidy goes up when the market price rises—i.e., the government keeps the price to consumers stable—but consumers only receive the subsidy as a refund a few days after they purchase the LNG, and “poor households may find it difficult to pay the higher unsubsidized price upfront.” ( Afridi, Barnwal, and Sarkar ) #FE

Regulation and government

·        In Argentina, “serving in the military leads to stronger national identity and openness to fellow countrymen several decades after serving.” ( Ronconi and Ramos-Toro ) #FE

·        In Pakistan, policymakers who received a special training in econometrics are twice as likely to actually choose policies for which there is evidence from randomized controlled trials. They triple the funding for those same policies. ( Mehmood, Naseer, and Chen ) #RCT

·        In Brazil, state judges with higher grades on admission examinations perform better than their lower-ranked peers. ( Dahis, Schiavon, and Scot ) #FE

·        In India, improving the maintenance of fee-funded community toilets improved delivery and reduced free riding, but excludes a share of residents from using the service. ( Armand et al. ) #RCT

·        In, Kenya’s nationwide electrification program, imposing audits improved network size, voltage, household connectivity, and electricity usage at African Development Bank (AfDB) sites. (World Bank sites already had lots of inspections, so random audits didn’t affect those.) The World Bank’s procedures delayed construction at the average site by 9.6 months relative to AfDB sites but improved construction quality by 0.6 standard deviations. ( Wolfram et al. ) #RCT

·        In Bihar, India, instituting a complaint filing system for politicians who run into bureaucratic obstacles in the implementation of their projects led to a 26 percent rise in the implementation of public projects in constituencies run by low-caste local politicians. ( Kumar and Sharan ) #RCT

·        Informing government agents about illegal (gold) mining in Colombia, reduced illegal mining by 11 percent in the disclosed locations and surrounding areas. ( Saavedra ) #ML

·        In India, switching the approving authority of economic development projects that require forest diversion from central to state government “leads to a modestly adverse impact on forest conservation while approving lower quality development work.” ( Chiplunkar and Das ) #DID

·        When two districts in India share groundwater resources, extraction is more likely to be unsustainable and districts are more likely to have defunct wells. ( Bhogale and Khedgikar ) #DID

Agriculture, infrastructure, and the environment

Agriculture and land

·        In Mozambique, contract farming has spillover effects: “both contracted farmers and non-contracted farmers from villages with contracted farmers earn approximately 11 percent more in price per kilogram of maize” than farmers in areas without contract farming. ( Ingram ) #FE

·        The vanilla price boom in Madagascar led to increased asset accumulation and higher informal savings, improved performance on cognitive tests, well-being, and optimism. There were positive effects for smallholder vanilla farmers, but without spillover benefits on non-producing households. ( Boone, Kaila, and Sahn ) #FE

·        In Rwanda, using text messages to remind agricultural extension workers of their self-set goals increased their performance by 0.08 SD. ( Abel et al. ) #RCT

·        How do rural marketplaces shape local development? In Kenya, “while rural population quadrupled, two thirds of weekly markets operating in 1970 no longer do so today.” Population concentrated around markets that were active in 1970, and markets further from large cities saw the most population concentration. ( von Carnap ) #FE

·        If you rely on farmer reports on what seeds they’re using in Ethiopia, you’ll see apparently small, negative returns to using new seed varieties. But that’s because farmers are including “older and genetically diluted varieties, for which” they “may be paying a premium.” If you just look at seed varieties with “higher-purity germplasm, drought-tolerant maize, and newly released varieties,” you do see positive returns. ( Michuda et al. ) #Other

·        How much is one farmer in Uganda willing to pay for their neighbor to use a pest-control technology? A “novel incentive-compatible elicitation mechanism” finds that “a farmer’s willingness-to-pay for one other farmer [to use the technology] is equal to two days’ wage on average, about half the willingness-to-pay for self.” ( Lerva ) #RCT

·        Maybe farmers don’t train their workers in modern planting technologies because they know they won’t get all the benefits of that training: the workers may go and use it somewhere else. In Burundi, providing a contract that guaranteed farmers the benefit from training their workers increased farmers’ willingness to train their workers by about 90 percentage points! ( Cefala et al. ) #RCT

·        In Odisha, India, villages with more variation in castes have lower adoption of flood-resistant seeds. Adoption is more likely to spread within castes and less likely to spread to castes with lower status. ( de Janvry, Rao, and Sadoulet ) #RCT

·        In India, bureaucrats who are assigned to their home states decrease protests or riots in opposition to land acquisition projects by 9-12 percent. ( Tóth ) #DID #RD

·        Lake Chad shrunk by 90 percent between the 1960s and the late 1980s: the reduced water supply had negative effects for neighboring communities in Cameroon, Chad, Nigeria and Niger—25 percent of sub-Saharan Africa’s population—on fishing, in addition to farming and herding which outweighed any positive land supply effects. ( Jedwab et al. ) #DID

Climate and pollution

·        Lake Chad shrunk by 90 percent between the 1960s and the late 1980s: the reduced water supply had negative effects for neighboring communities in Cameroon, Chad, Nigeria and Niger—25 percent of sub-Saharan Africa’s population—on fishing, in addition to farming and herding which outweighed any positive land supply effects. ( Jedwab et al. ) #DID *

·        Households from heavily damaged communities in Indonesia after the 2004 Indian Ocean Tsunami saw a 75 percent decline in real wealth immediately after the tsunami. The large adverse effects persisted 10 years after the tsunami. ( Lombardo et al.) #FE

·        In India and Pakistan, the incidence of fires from crop burning drops by 10 percent when air pollution is likely to be borne by the bureaucrats’ own constituents. “Reduction in fires is present or larger when bureaucrats can better monitor (due to road proximity) or manage fires (due to changes in experience during a turnover), and when they have incentives to act (e.g., when pollution is most visible).” ( Dipoppa and Gulzar ) #DID

·        In utero exposure to high ocean salinity levels (induced by climate change) reduces a child’s height-for-age z-score in Bangladesh, and increased prevalence of stunting and severe stunting due to nutritional deficiencies by age five. ( Guimbeau et al. ) #FE *

Infrastructure

·        In Kenya and Ethiopia, the “impact of bundled road and electricity investments on reducing the sectoral employment share in agriculture is … 2.5 times larger than the impact of roads alone.” ( Dappe and Lebrand ) #FE #IV

·        Aerial bundled cables (an infrastructure improvement) in Karachi, Pakistan, reduced utility losses and increased revenue recovery, with the greatest gains in the worst-performing areas pre-intervention. Gains come via two channels: the formalization of customers previously informally (illegally) connected and the improvement in payment behaviors among existing, formal consumers. ( Ahmad et al. ) #DID

·        A large-scale roll-out of electric transmission infrastructure in Nigeria from 2009 to 2015 increased individuals’ likelihood of migrating by 6 percent and reduced household size by 0.8 individuals, mainly driven by young adults and older teenagers. ( Budjan ) #DID #IV

·        How does transportation infrastructure investment affect spatial inequality of opportunity in Benin, Cameroon, and Mali? “On average only 6 of the top 10 aggregate opportunity-increasing roads also decrease inequality of opportunity.” ( Milsom ) #IV

·        In Dakar, Senegal, it can be hard to find someone to desludge your septic pit. Providing subsidies to use a government run call center to connect households with desludgers increases use, and that use continues for a while after the subsidies end. Later, a city-wide subsidy increased adoption most in those communities that had received subsidies earlier. ( Deutschmann ) #RCT *

Macroeconomics

Growth and inequality

·        Gaining subnational capital status leads to an influx of public investments, an increased population, skilled migration and foreign investments, with positive spillovers to nearby cities. ( Bluhm, Lessmann, and Schaudt ) #FE #DID

·        In China, state-level special economic zones (SEZs)—"geographically delimited areas targeted by governments to implement” policies like tax incentives, government innovation grants, and policies that favor human capital mobility—"have a positive and significant impact on patent output,” but SEZs established at geographic areas smaller than the state don’t have significant impacts. ( Wu, Lu, and Zhao ) #DID

·        Initial foreign direct investment into China “was mainly driven by the Chinese diaspora,” particularly to prefectures in China that members of the diaspora came from. Later, foreign investment that didn’t come from the diaspora was more likely to enter those same prefectures. ( Chen, Xiong, and Zhang ) #DID

·        “Countries are more likely to enter ‘nearby’ industries, i.e., industries that require fewer new occupations.” Also, “countries are more likely to diversify into products that require fewer new inputs,” which means that countries can get stuck on particular paths in their quest toward industrial development, “with certain routes leading to stagnation and others on a pathway to prosperity.” ( Diodato, Hausmann, and Schetter ) #Other

·        “The construction process of many residential buildings in African cities proceeds very slowly and may take over a decade.” Data from Nairobi plus a new theoretical model suggest that “improvements in credit provision can (a) substantially speed up the expansion of the aggregate housing stock which facilitates rural-urban migration, and (b) increase the city’s density by enabling the construction of taller buildings.” ( Gomtsyan ) #Other

·        Giving information about market prices and official border costs to traders in Kenya increases switches across markets and routes, leading to a large improvement in traders’ profits and significant formalization of trade. ( Wiseman ) #RCT

·        Can temporary trade disruptions lead to a persistent change in domestic trade? Yes. In India, COVID-19 induced lockdowns led to a collapse in trade across states, driven by plants reorienting “trade towards their home states to ... insure against any future disruptions.” ( Chakrabati, Mahajan, and Tomar ) #DID

·        The 2001 US-Vietnam Bilateral Trade Agreement reduced US import tariffs from Vietnam, leading to rapid Vietnamese export growth with “entry responses, driven by foreign and Vietnamese private firms. Entrants—rather than incumbents—drive the tariff-induced employment growth, particularly foreign entrants.” ( McCaig, Pavcnik, and Wong ) #FE

·        The tariff reduction from the U.S-Vietnam Bilateral Trade Agreement decreased school attendance and increased children’s work, mainly in non-wage and household business jobs. Effects were stronger for boys, older children and households where the head had little education. ( Nguyen ) #DID *

·        In India, “larger cultural proximity [by way of caste and religion] between a pair of firms reduces prices and fosters trade at both the intensive and extensive margins.” ( Fujiy, Khanna, and Toma ) #FE *

The order of authors on this blog was determined by a virtual coin flip. This blog post benefited from research assistance from Amina Mendez Acosta .

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2022 in Review: A Year of Uncertainty | The Development Podcast

FEATURING: Indermit Gill, Chief Economist of the World Bank Group and Senior Vice President for Development Economics / Dareen Akkad, Egyptian baker and restaurant owner.

[01:23] Putting 2022 in context

[02:31] What were we expecting 2022 to look like in January?

[03:47] The economic impact of Russia's invasion of Ukraine

[05:02] Are we looking at a recession next year that's getting worse?

[06:47] Policy steps being taken

[09:28] Monetary tightening, raising interest rates, subsidies, inflation

[16:07] Stories of people's lives

[17:30] Inflation and food security: Visions from a pizza baker in Cairo

[19:42] Closing and thanks for tuning in!

The past twelve months have been turbulent for the global economy. Conflict, inflation, food supply crises and the long tail of the Covid-19 pandemic have caused shockwaves across the world . In this episode of The Development Podcast we speak to World Bank Group chief economist Indermit Gill , and take stock of the last twelve months , while looking ahead to 2023.

Indermit explains why forecasts at the start of the year were wrong, and why he remains optimistic for the coming year. We also reflect on one of the biggest stories of 2022, food prices . We get an update from Egyptian baker and restaurant owner Dareen Akkad. Listen now! 

Tell us what you think  of our podcast  here >>> . We would love to hear from you!  

Featured Voices

• Indermit Gill , Chief Economist of the World Bank Group and Senior Vice President for Development Economics. 
• Dareen Akkad , Egyptian baker and restaurant owner. 

[00:00] Paul Blake: Hello. And welcome to The Development Podcast coming to you from our headquarters in Washington, DC and beyond. I'm Paul Blake alongside Raka Banerjee.

Raka Banerjee: Today, a reflection on the extraordinary year that was 2022, the post pandemic recovery, the wartime economy and more with World Bank Chief Economist Indermit Gill .

Indermit Gill: I think that the last two years will become a case study of how the world forgot Economics 101, and I think it was because of fear, it was because of the disease, it was because of the war, but it was also because of impatience, and I'm hoping that 2023 will not be part of this case study.

Paul Blake: Plus an update from Cairo, how global events have driven a tremendous food price shock.

Dareen Akkad: The businesses that survive are those that are able to change and adapt. We've already made plans to create food that is completely locally sourced.

Raka Banerjee: All that and more, here on The Development Podcast from the World Bank Group. 

[01:23] Raka Banerjee: Well, it was just one year ago that we were all asking how the newly emerged Omicron variant might prolong the COVID-19 Pandemic.

Assorted speakers (Footage audio): This variant is a cause for concern, not a cause for panic. We don't yet know whether Omicron is associated with more transmission, more severe diseases, more risk of re infections.

Paul Blake: The fast moving variant threatened to drag out one of the biggest global economic disruptions since World War II. It was the biggest story in January.

Raka Banerjee: And then February came.

Assorted speakers (Footage audio): Today, what was unthinkable for many, particularly in Ukraine itself, has happened. An invasion by Russian forces.

Assorted speakers (Footage audio): One more Russian missile strike. It brings terror to the streets of Kyiv.

Paul Blake: Russia's invasion of Ukraine shocked the world and sent reverberations through every level of the global economy.

Raka Banerjee: These two stories, I think, framed the uncertainty around 2022 .

Paul Blake: Indeed, the long tail of the pandemic and the fresh shock of a major ground war in Europe fundamentally changed the global economic narrative.

[02:31] Raka Banerjee: To understand just how COVID and conflict changed economic history in 2022, let's bring in World Bank Chief Economist in Indermit Gill . Indermit, thinking back to January 22, it was a completely different world. What were we expecting 2022 to look like in January?

Indermit Gill: Well, back in January, we actually put out our Global Economic Prospects report. And I was looking at that, and we were expecting the world economy to grow at around 4%, and we expected the US and the EU to grow by about that much too. And we thought China would grow at 5%, Indonesia by a bit more, and India would grow at nearly 9%. So if you look at things today, we expect the global economy to grow by less than 3%, so we've sliced off about a quarter of the expected growth, and next year will be even worse. We've actually sliced off nearly a third of the growth for 2023. So the world faces record debt levels, it faces declining investment rates, high inflation, widespread hunger, poverty reduction has come to a grinding halt. And as a result of all of these things, there is actually growing political instability. Things have become a lot worse in these 11 months.

[03:47] Paul Blake: Russia's invasion of Ukraine , obviously a incredible human tragedy. Tens of thousands of lives needlessly lost. We can all comprehend the human tragedy I think, but help us understand what has the economic impact of that conflict been?

Indermit Gill: So the best way to think about this, Paul, is to think about what share of the world economy are the US, the European Union and China, and things that happen in these three parts of the world will affect the world economy. If you add up the share of global economic output, it adds up to more than 60%. So then if you look to see what exactly happened in these places, so the first one, as you mentioned, you had the invasion of Ukraine, and that plunged Europe into an energy crisis. Second one is China decided to kill COVID-19, which is a mutating virus, which is a very difficult thing to do. And then the third one was that the US decided to kill inflation. This was after feeding it for years through easy money and big government spending, so as a result of it, suddenly you had these three big shocks basically, all of them essentially happening in 2022. So it's not just the crisis in Ukraine, though, that's a big part of it, but you also had these other two things happening at the same time.

[05:02] Raka Banerjee: We'd had a podcast earlier this year about stagflation . There's obviously fears of a global recession. Are we looking at a recession next year that's getting worse? I mean, how can this be turned around?

Indermit Gill: So I thought that you would say, "Well, if you were so wrong 11 months ago, then why are you forecasting?"

Paul Blake: We wouldn't phrase it that way.

Indermit Gill: But I think that the answer is related to that. We were wrong about things because we didn't anticipate a few of these really bad things that happened. And by the same token, I think if we end up getting an end to some of these things, I think that already we are getting some good news out of China in the sense that they've stopped this trying to kill COVID off down to zero. And then if you look at the United States, again, we are starting to get good news here. So the best way to think about this is that the world has never gone into a recession, or at least in living memory, unless the US also goes into a recession, and I don't think the US is going to go into recession. You've got about, I would say about 45% of the world's economy in some kind of trouble or the other.

And the big problem that we faced over the last six months or so was inflation. High inflation usually means that you have too much money chasing, too few goods and services, so too much demand and too little supply. But I think ideally what we really want to do is we want a balance up policies that try to moderate demand because we overstimulated it in the past two years. But then by the same token, because we dampen supply so much, we want to do things that actually increase supply as well-

Paul Blake: So you meet in the middle.

Indermit Gill: ... so you meet in the middle.

[06:47] Raka Banerjee: And do you feel like that's happening right now? Are these policy steps being taken? Do you think that's likely? 

Indermit Gill: So honestly, I would say that we are doing too much of cutting demand and not enough of stimulating supply. Raising interest rates, cutting government spending, increasing tax rates, these are all supply killers. And then if you look at demand side things, I mean, what you really want to do demand, you want freer trade, so you don't want to impose trade restrictions because they tend to cut supply, that's one thing. The other thing is that if you cramp down on people's economic freedoms or what they can do with their time and their money, and their investments and so on, you're going to get less supply. The other thing is that many of the countries, because they had these mandated lockdowns, what they also did was they actually paid people to stay at home. And I think the tail end of that hasn't yet disappeared in the sense that you really want to not pay people to stay at home. You want people to go out and work. I guess, if you're asking me to give grades on the demand side, I would say it's like an A-, but on the supply side, I think that I would give the world a C right now. So I think that we made policy mistakes. I think-

Paul Blake: The world leaders, [inaudible]

Indermit Gill: ... well, world leaders generally speak. And I mean, essentially I don't think it's a private sector that's making the mistakes.

Raka Banerjee: And you highlighted the invasion of Ukraine, policies contributing to high inflation in the US, and China's decisions around COVID, three big ones that are made by governments.

Indermit Gill: Right. These are the three big ones. But by the way, I could add to that list. I could go down the list of the other countries, not the big three, but the other countries, they've done things like actually try to put trade restrictions on the exports of food grains and things like that. I mean, those are things that lead to all kinds of problems, especially for poor people in poor countries because they raise the price of food grains, and they actually cut the supply of food grains. In a general sense, I would actually say that I think that the last two years will become a case study of how the world forgot Economics 101. And I think it was because of fear. It was because of the disease. It was because of the war, but it was also because of impatience, and I'm hoping that 2023 will not be part of this case study. So it would just be 2020, 2021, and maybe 2022. If you keep interest rates low, if you tell people to stay home, and if you pump in trillions of dollars and euros and yuan in stimulus spending, you will engineer a situation in which demand will outstrip supply, so you'll get inflation.

[09:28] Paul Blake: ... I visited Colombia and Poland over the past year, and one of the things that was very striking to me was how average people who were talking about Central Bank interest rates. And my understanding is that countries like Poland, Colombia are having to dramatically react to the Fed. Can you explain what exactly the Fed's aggressive monetary tightening, raising interest rates means for middle income countries, even high income countries that have to compete?

Indermit Gill: So the first thing, Paul, you cannot blame the Fed for doing what is its job. Its job is that when you have too high inflation rates or too persistent inflation rates and so on, that's what they will do.

Paul Blake: They will push the lever up on rates.

Indermit Gill: They push the lever up on rates, and that's their job and so on. And I think it was expected by most countries that this would happen sooner or later. The issue then is, exactly what does this do to two people in the developing world? What does it do to countries? What does it do to the government, and what does it do to the people? So for the governments, there's a very straightforward effect of this.

The straightforward effect of this is that, they end up having to pay more for their debts. So most countries have to roll over their debts each year, every month, and so on, and then as these interest rates rise, they tend to make rolling over those debts more expensive. So what happens is that public investment and private investment both fall at the same time. And so as a result of it, these countries end up having a slower growth rate because everything is driven by investment mostly. For countries that actually borrowed for the right reason, I think for them, this is not as serious a problem, but for countries that borrowed in order to finance consumption, this is a problem.

Paul Blake: So unnecessary subsidies .

Indermit Gill: Yeah. Because public investment, because when you invest in things that lead to an increase in the productive capacity of the economy, it increases the capacity of the economy to pay back. I think times like this remind you of some basic principles. I think one of the basic principles is that governments should not borrow to consume things. They should be borrowing to make well considered investments in roads, in education, in health and things like that. The second thing, I think governments have to realize that... I think that what has happened across the world, this is not, I wouldn't blame the US or anybody else in particular, but across the world, governments took a lot of their freedoms from people because of good reasons and bad. But as a result of it, there has been a pullback of economic freedom that usually means that people aren't necessarily doing the things that are good for them. So then you say, "Okay, have governments been a really good protector of the private interest or the public interest?" And I would say, no, not during the last three years.

Paul Blake: Build on this a little bit, if you don't mind.

Indermit Gill: I mean, for example, closing a restaurant or having blanket lockdowns or not allowing people to travel for business because they have not been vaccinated, etcetera. Now, I'm not saying that they haven't been driven by good reason, but the net effect of it is that they're fairly blanket restrictions, so what you're doing is that you are actually, in a sense... Another way to put it is we thought that during the last 30 years, before 2020, these were the best years for economic development across the world. The most progress in recorded history.

Paul Blake: The best time to be born, alive, a human being in human history, I think so.

Indermit Gill: Absolutely. I mean, we took it for granted that things were going to be like that. If you look at that, you say, what was it that actually led to that? The first one was a realization that the commanding heights of the economy should be given to the private sector. It should not be the government that should control the commanding heights. And if you look at the last few years, there's been a reversion of that. You've seen the government actually taking over a lot of things, that's one. The second thing was free trade. You found that poorer countries, actually, as soon as they started to free up their private sector and so on, you immediately got a private sector response. The problem is that countries become suppliers much more quickly than they become big demanders. So as a result, you needed to be able to supply these things to people who had the purchasing power, for that you needed trade because these people were somewhere else. The third thing, which was a very important thing, is that we had accepted that look, macro stability, low inflation rates, not very big fiscal deficits and so on. These are good things for everybody [inaudible].

Paul Blake: I mean, in mid 2010s, there was talk about inflation being too low [inaudible].

Indermit Gill: That was in advanced economies, Paul. In the developing countries, inflation was still 4, 5%, but they were moderate levels. Last year there were more countries that had doubled digit inflation than single digit inflation.

Paul Blake: Wow.

Indermit Gill: So as a result of it, now you create a very uncertain atmosphere for private investors because they have to figure out whether or not it makes sense to do all this stuff. You make it really bad for poor people because the richer people tend to find good hedges against inflation, so in a sense, I think what we are trying to do is go back to that macro stability. I have a feeling that the world will get back to that fairly quickly. The second thing is, go back to actually greater economic freedom to people. That should be the natural, I mean, trust the people. I think that'll happen too over time. I think the third part, to actually have an environment, a worldwide economy in which free trade is a rule rather than the exception. That is the thing that should worry us all because right now, because of the politics of things and so on, there's a worry that the world would split into camps. If we don't end up having all three of these conditions and not just two, it's going to be bad for the poorest country, especially the countries that we care the most about right now. I think these are countries in Sub-Saharan Africa.

Raka Banerjee: Do you think that, I guess, there's going to be a return to the lessons of Economics 101.

Indermit Gill: I'm going to do my best. I'm going to scream this from rooftops.

Raka Banerjee: Indermit, thank you so much for taking the time to speak with us today. This was just an awesome conversation. We really appreciate your time and your perspectives.

Indermit Gill: It was a pleasure. Thank you all so much for this time.

Paul Blake: Indermit Gill is the World Bank's Chief Economist. He joined us in our studio here in Washington. 

[16:07] Paul Blake: Well, behind all the big trends in economics are the stories of people's lives .

Raka Banerjee: Over the past year , we've talked to several people from around the world to get their insights into some of these big complex topics.

Paul Blake: For instance, prominent Mexican economist, Enrique Cárdenas told us in July how the so-called lost decade of the 1980s compares to today.

Enrique Cárdenas: In terms of recession, just people had lower incomes. They were not very happy. You went into the underground in the subway in Mexico City, you would see pale faces and not very happy faces.

Raka Banerjee: From rural India, we heard from Reema Nanavaty about how renewable energy has the power to transform lives for the better, but that any transition away from traditional energy sources would need to be just.

Reema Nanavaty: What alternatives could be there for the workers who are working currently, maybe in the coal mines? What are the alternatives which are also designed and worked out while the country is transitioning?

Raka Banerjee: And in our November edition, we shared the story of Sonia Cifuentes , who spoke of the difficulty of feeding her family in the post pandemic economy.

Sonia Cifuentes: Well, I never imagined we were going to be left without a job. During the pandemic, I was in need of food and I had to ask my mother to help feed my children because I had no money to buy food.

[17:30] Raka Banerjee: Indeed, that was one of the most significant and maybe scariest trends of 2022, the shock in agricultural prices .

Paul Blake: And specifically what that shock meant for food security .

Raka Banerjee: In June, our colleague Sarah Treanor, caught up with Dareen Akkad , a pizza baker in Cairo, Egypt .

Paul Blake: Well, Sarah joins us now. Sarah, remind us what Dareen had to say back then.

Sarah Jane Treanor: Hi, both. Yes. So Dareen gave us a peek into her kitchen where she's a passionate bread maker, and where she decided to turn her passion into a business. She told me how she's really struggling to source ingredients, that prices keep going up. She doesn't know where she's going to get some of her staple ingredients like flour from, and she was worried at the time that she was going to have to pass on price increases to her customers who were also struggling with increases in food prices across the board.

Dareen Akkad: This is something that's been a daily topic of conversation for the last five years. I think the daily conversation is how much worse, when is the price hike going to stop?

Sarah Jane Treanor: Well, since June, wheat prices have continued to be volatile. I wanted to check in with Dareen and see how things are going for her in her restaurant, and whether she's still finding it a challenge to source the product she needs.

Dareen Akkad: We've had to take some measures to make sure we stay alive. We don't know, we can't even reprice our menu enough times. My biggest issue has been having to change the brand of flour that we use every couple of weeks, maybe. But at the same time, since we've last spoken, I remember last time we spoke about trying to produce more of our ingredients in Egypt. We've had a great development. We've had an Italian producer set up shop here to make mozzarella. The businesses that survive are those that are able to change and adapt. We've already made plans to create food that is completely locally sourced.

Raka Banerjee: Dareen Akkad, owner of What The Crust Restaurant in Cairo, Egypt, speaking to Sarah Treanor, as we wrap up our 2022 special.

[19:42] Paul Blake: That's it for The Development Podcast in 2022 . We hope you've enjoyed joining us for this episode and throughout the past year.

Raka Banerjee: As always, you can email us. We'd love to hear from you at [email protected] .

Paul Blake: Until 2023, goodbye.

Raka Banerjee: Goodbye.

Sarah Jane Treanor: See you next year. Goodbye.

ABOUT THE DEVELOPMENT PODCAST

This international development podcast brings together the data, research—and solutions—that can pave the way to a sustainable future. Through conversations focused on revealing the latest data, the best research, and cutting-edge solutions, let us introduce you to the folks working to make the world a better place. Don't miss an episode!  Listen and subscribe for free  on your favorite platform. And rate our show! ;)

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Data Visualizations | 2022: The Year in Review

View this post on Instagram A post shared by World Bank (@worldbank)

Why the world “forgot economics 101” over the last two years and how it can get back on track. In the latest #DevelopmentPodcast we get a scorecard for the global economy from @WorldBank Chief Economist @IndermitGill . Listen now: https://t.co/un3eJfH2iB pic.twitter.com/xy63dPyRAw — World Bank (@WorldBank) January 3, 2023

Related Resources

2022 has been a year of uncertainty. View a snapshot of this work in nine charts.

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• All Headlines

Top 40 Case Studies of 2022-23

A case about a unique partnership to bring public toilet facilities to Indian slums earned the top spot in the 2022-23 Top 40 Yale case studies round up.

Delving into the complex project management landscape of a partnership between governments, designers, academic, and NGOs in India, the Project Sammaan case study jumped to the #1 spot this year from #30 in 2021 based largely on its strong sales to academic institutions.

Cases on the uses of debt and equity at Hertz that took the top two spots last year continued their strong showing this year at #2 and #3.

Surprisingly, the abridged version of the Toyota 2010 case leapt from #40 in last year’s roundup to #4; perennial favorite Coffee 2016 took #5 and cases involving search funds, private equity, and Cadbury, another perennial favorite, rounded out the top 10.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

Other year-end data for 2022-23 showed that:

• 26K case users from 156 countries and all 50 U.S. states interacted with 191 Yale cases.
• Over fifty percent of case users came from outside the U.S. with India, Tanzania, and the Philippines making up the bulk.
• 22 cases on the list are "raw" and 18 "cooked."
• The top 40 cases were supervised by 21 different Yale SOM current and former faculty members, several supervising multiple cases.

All of the 2022-23 Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases for 2022-23 are:

1 Project Sammaan

2 Hertz Global Holdings (A): Uses of Debt and Equity

3 Hertz Global Holdings (B): Uses of Debt and Equity 2020

4 Toyota 2010 (Abridged)

5 Coffee 2016

6 Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

7 Gardner Denver

8 Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

10 Suwanee Lumber Company (B)

11 Marina Bay Sands

12 IBM Corporate Service Corps

13 Shake Shack IPO

14 Children's Premier

15 Hirtle Callaghan & Co

16 Volkswagen

18 Commonfund ESG

19 Alternative Meat Industry

20 Mastercard

21 Palm Oil 2016

22 Design at the Mayo Clinic

23 Mercy Corps

24 Mike Erwin: An accidental social entrepreneur

25 DonorsChoose.org

28 The Alibaba Group

29 Giant Bicycle: Bike-Sharing in Taipei

30 American Greetings

31 Air Canada

32 Achievement First

33 Tesla in Germany

34 Nielsen: How Will the Company Maintain Its Commitments to Multiple Stakeholder Groups?

35 Climate Change Capital

36 2011 Debt Limit Crisis: How Should the Fed Respond?

37 The Future of Malls: Was Decline Inevitable?

39 Herman Miller

40 AXA: Creating the New CR Metrics

Home > Case Studies

Case Studies

Discover all the ways our 2,000 customers succeed, thrive and grow with Oxford Economics. Read success stories from Oxford Economics' clients in sectors such as pensions, energy and Real Estate. Learn how they solved their business challenges, supported their businesses' growth and adapted to new markets using Oxford Economics market-leading consulting and subscription services.

Case Study | European Digital Payment Industry Alliance

Investigating the environmental footprint of payment systems

Using Oxford Economics’ new Lifecycle Assessment (LCA) tool to evaluate the carbon emissions of the payment system, and whether digitalisation would reduce environmental impacts.

Case Study | US-China Business Council

Modelling the costs of US-China tariffs

Businesses are increasingly concerned about a possible escalation of US-China trade policy, given their supply-chain dependencies on China. We quantify this risk by simulating higher tariffs leveraging state-of-the-art trade and macro models.

Case Study | Tata Steel

Transitioning towards a clean, green and circular future

Examining the socioeconomic effects of decarbonisation investments in the steel industry and the impact these can have on the national economy.

Case Study | AVSIS

Understanding the importance of a rapid action plan to fight climate change in Italy

Leveraging the Global Climate Service scenarios to evaluate the macroeconomic implication of mitigation policies and global warming

Case Study | Multinational Drinks Company

Bespoke dashboards and agile on-demand economics support

Background Today’s turbulent macroeconomic and consumer environment makes strategy and planning particularly difficult for firms in the business-to-consumer sector. The pandemic, major global conflicts and geopolitical tensions have caused major supply-side disruptions. At the same time, the ever-changing consumer environment, recent unprecedented levels of inflation and the ensuing cost of living crisis have been a...

Case Study | Royal London

Exploring the implications of higher pension contributions

Many households fail to save adequately for retirement. Using in-house models, the study assesses the impact of higher pension contributions on both pension savings and UK economic growth.

Case Study | A global aggregate and building materials provider

Constructing Success by Capitalising on Long-Term Opportunities

Helping a strategy department identify its 10-year growth opportunities

Case Study | Semiconductor Industry Association

A unique policy-driven impact scenario for CHIPS Act

How Oxford Economics engaged the world’s largest chip manufacturers to develop an industry-wide impact assessment of the CHIPS and Sciences Act.

Case Study | Building material manufacturer

Benchmarking Success: Building a Global Market Demand Indicator

Creating a new demand measure to enable a building material manufacturer to gauge its performance.

Case Study | Multinational services company

Quantifying the impact of climate on customers

Leveraging industry-specific climate forecasts to future-proof revenue.

Case Study | Energy UK

Achieving net zero advocacy goals

Highlighting the economic opportunities the energy transition presents and the consequences of not grasping them.

Charting a course for global growth in the shipping industry

Empowering a leading shipping company to enhance its strategic planning and identify new routes for growth

Global macroeconomic and risk scenario tool

Enabling a major automotive manufacturer to anticipate and respond effectively to evolving market dynamics across its global operations.

Risk signal identification, prioritisation and monitoring evaluation model

Despite existing internal risk management processes, a major automotive manufacturer was unprepared for and failed to anticipate and mitigate significant risks and shocks that have significantly affected its operations in recent years, including its sales, supply chain and financing.

Bespoke automotive sector sales forecasting

Automotive companies face many challenges: regulations, emission controls, litigation, political uncertainty, complex and problematic supply chains and disruptive technology are perhaps among the most pressing.

Case Study | Australian Finance Industry Association

The economic impact of Buy Now Pay Later in Australia

Governments globally are realising the importance of payments and financial services efficiency to economic growth, financial wellbeing and social participation.  The Australian Finance Industry Association (AFIA) recognises innovation, competition, market efficiency, economic growth and consumer protection are interrelated and, therefore, must be addressed collectively. An informed understanding of the Buy Now Pay Later (BNPL) sector...

Case Study | City of Sydney

City of Sydney’s 2022 Business Needs Survey Report

The City of Sydney required an advisor with the capability to develop a high-impact, user-focused report to: The report had to be engaging and highly visual, containing a range of different devices to communicate economic insights to a range of readers. The solution Oxford Economics Australia developed a rich and compelling report to engage and...

Case Study | Leading Australian Law Firm

Expert Witness Report on property market influences and outlook

The repudiation of an existing development agreement resulted in Supreme Court proceedings whereby residential property market forecasts were required to demonstrate the outlook for the Darwin residential market at that time. Separate sale price and rent projections were needed (on an annual basis) for detached house and attached dwellings for the period of 2017-2030. Importantly,...

Case Study | QBE LMI

The Annual Housing Outlook 2022 – the Green Edition

The objective of this work was to reinforce QBE LMI’s position by providing an outlook of housing market performance and stimulate informed discussion about environmental sustainability within the housing market and a state by state performance analysis of housing market prices and rents. The solution The project was approached collaboratively with the QBE LMI project...

Case Study | Australia Energy Market

Forecasts and scenarios to inform the future of Australia’s energy market

Oxford Economics Australia was commissioned to produce macroeconomic and commodity scenario projections that could be used to generate long-term gas and electricity demand and supply projections across a range of energy transition scenarios. The solution We worked closely with the client’s team and their stakeholders to produce long-term (30-year) macroeconomic and commodity price forecasts, across...

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2022 Search Fund Study: Selected Observations

The 2022 Search Fund Study reports on the financial returns and key qualities of search funds formed in the United States and Canada since 1984. This report updates the previous 2020 study with data through December 31, 2021.

Learning Objective

This study provides data to support the search fund community including current searchers, CEOs, investors and entrepreneurs evaluating whether they want to pursue a search fund.

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Microeconomics →

• 29 Nov 2022
• Research & Ideas

How Much More Would Holiday Shoppers Pay to Wear Something Rare?

Economic worries will make pricing strategy even more critical this holiday season. Research by Chiara Farronato reveals the value that hip consumers see in hard-to-find products. Are companies simply making too many goods?

• 07 Jan 2019

The Better Way to Forecast the Future

We can forecast hurricane paths with great certainty, yet many businesses can't predict a supply chain snafu just around the corner. Yael Grushka-Cockayne says crowdsourcing can help. Open for comment; 0 Comments.

Articles on Macroeconomics

Displaying 1 - 20 of 97 articles.

10 reasons why Canadians are still dissatisfied with the economy, despite the upswing

Anup Srivastava , University of Calgary ; Felipe Bastos Gurgel Silva , University of Missouri-Columbia ; Luminita Enache , University of Calgary , and Manuela Dantas , California State University, Northridge

New data reveal US space economy’s output is shrinking – an economist explains in 3 charts

Jay L. Zagorsky , Boston University

Tinubu inherits Nigeria’s high debt – an economist analyses what this means for the country’s future

Stephen Onyeiwu , Allegheny College

AI will increase inequality and raise tough questions about humanity, economists warn

Yingying Lu , CSIRO

A basic income grant for South Africa: more money in poor people’s pockets, but at a heavy cost

Hylton Hollander , Stellenbosch University ; Daan Steenkamp , Stellenbosch University , and Roy Havemann , Stellenbosch University

Three reasons a weak pound is bad news for the environment

Katharina Richter , University of Bristol ; Alix Dietzel , University of Bristol , and Alvin Birdi , University of Bristol

When the IMF comes to town: why they visit and what to watch out for

Danny Bradlow , University of Pretoria

Why the cost of climate change can’t be boiled down to one right number, despite some economists’ best attempts

Matthew E. Kahn , USC Dornsife College of Letters, Arts and Sciences

Remembering Geoff Harcourt, the beating heart of Australian economics

John Hawkins , University of Canberra and Selwyn Cornish , Australian National University

Racial income and wealth gaps are huge – but the Fed doesn’t have the right tools to fix them

Paul Wachtel , New York University

For the EU’s ‘Green Deal’ to succeed, economic theory must take into account qualitative growth

Sergio Focardi , Pôle Léonard de Vinci ; Davide Mazza , Pôle Léonard de Vinci , and Manon Rivoire , Pôle Léonard de Vinci

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Empirical Regional Economics

Economic Base Theory, Models and Applications

• © 2022
• Richard S. Conway Jr. 0

Dick Conway & Associates, Seattle, USA

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• Provides a sound basis for regional economics and regional economic analysis
• Includes practical methods of regional forecasting and analysis
• Presents numerous regional economic case studies

Part of the book series: Springer Texts in Business and Economics (STBE)

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This textbook offers an introduction to empirical regional economics, including a comprehensive and systematic overview of the fundamentals, history, development, and applications of economic base models. It not only provides a sound basis for regional economics and regional economic analysis, but it also includes numerous applications of the underlying theory. The book has an empirical orientation, highlighting the value of observation and testing in order to explain regional economic behavior. Theory plays an important role in this study, but it is only a starting point.

The book is divided into three parts: the first discusses the economic base theory of regional growth and the empirical evidence supporting it, while the second part covers the specification and application of four increasingly complex regional economic models: the economic base model, the input-output model, the interindustry econometric model, and the structural time-series model. Lastly, the third part presents forty-eight regional economic case studies organized under seven headings, including economic cycles, economic policy, and regional forecasting.

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Regional Science Research and the Practice of Regional Economic Forecasting: Less Is Not More

Regional Growth and Convergence Empirics

• Regional economic theory
• Regional economic growth
• Regional and spatial science
• Regional economic forecasting
• Input-output analysis
• Urban economics
• Structural time-series model

Table of contents (13 chapters)

Front matter, regional economic base theory, economic base theory of regional growth.

Richard S. Conway Jr.

Economic Base Theory Empirical Evidence

Regional economic models and applications, economic base model, input–output model, interindustry econometric model, structural time-series model, regional economic case studies, u. s. and world economy, regional economic behavior and welfare, urban and rural economies, economic cycles, economic policy, regional housing market, regional forecasting.

“This textbook is a welcome addition to the field of regional science. The textbook fits a unique niche: an introductory textbook with sufficient modeling depth and case study breadth. Conway's clear, concise teaching style and detailed examples will appeal to educators … . Finally, regional scientists and scholars interested in the Puget Sound region will find an impressive amount of information, ensuring the textbook also serves as a handy reference well beyond its in‐class use.” (Courtney Bower, growth and change, February 9, 2024)

“ERE is in many ways a true labor of love and a gift to regional economic practitioners. … ERE is an incredible how-to, a rich legacy from one who knows, and in its own unassuming way, a tribute to an incredible and successful career in regional economics.” (Randall Jackson, Economic Development Quarterly, October 3, 2023)

“It is a valuable textbook suggested for regional scientists, as it provides a comprehensive empirical overview of regional economics, by (i) emphasizing the use of empirical methods and data towards the understanding of regional economics; (ii) providing insights into the modern aspects of regional economics and their policy implementation; and (iii) highlighting the importance of endogenous characteristics of regions towards economic growth and development.” (Dimitrios Tsiotas, Regional Science Inquiry, Vol. 15 (1), 2023)

Authors and Affiliations

Dick conway & associates, seattle, usa, about the author, bibliographic information.

Book Title : Empirical Regional Economics

Book Subtitle : Economic Base Theory, Models and Applications

Authors : Richard S. Conway Jr.

Series Title : Springer Texts in Business and Economics

DOI : https://doi.org/10.1007/978-3-030-76646-7

Publisher : Springer Cham

eBook Packages : Economics and Finance , Economics and Finance (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

Hardcover ISBN : 978-3-030-76645-0 Published: 24 April 2022

eBook ISBN : 978-3-030-76646-7 Published: 23 April 2022

Series ISSN : 2192-4333

Series E-ISSN : 2192-4341

Edition Number : 1

Number of Pages : XIII, 275

Number of Illustrations : 44 b/w illustrations, 1 illustrations in colour

Topics : Regional/Spatial Science , Geography, general , Economic Growth

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Announcements Online Submission editorial board Editor-in-Chief Assoc. Prof. Qingyang Gu  Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore 2572-7923 (Print) 2572-7931 (Online) Publication Frequency Article Processing Charges (APCs) Other Journals Mega sporting events and their socio-economic impact: Case study of the 2022 FIFA World Cup Almeida AM (2019). Economic impact of sporting events—Evaluation criteria and indicators of interest in the case of Madeira. Motricidade 15(2): 6–10. Amponsah CT, Ahmed G, Kumar M, Adams S (2018). The business effects of mega-sporting events on host cities: An empirical view. Problems and Perspectives in Management 16(3): 324–336. doi: 10.21511/ppm.16(3).2018.26 Azzali S (2019). Spaces of mega sporting events versus public spaces: Qatar 2022 World Cup and the City of Doha. The Journal of Public Space 4(2): 57–80. doi: 10.32891/jps.v4i2.1204 Baker W (2019). The Economic Impact of Mega Sport Event [Bachelor’s thesis]. Trinity College. Available online: https://digitalrepository.trincoll.edu/theses/793 (accessed on 18 February 2023). Barajas A, Coates D, Sanchez-Fernandez P (2016). Beyond retrospective assessment. Sport event economic impact studies as a management tool for informing event organization. European Research on Management and Business Economics 22(3): 124–130. doi: 10.1016/j.iedee.2015.05.001 Bas D, Martin M, Pollack C, Venne R (2020). The impact of COVID-19 on sport, physical activity and well-being and its effects on social development. Policy Brief No 73. Available online: http://www.un.org/development/desa/dspd/wp-content/uploads/sites/22/2020/05/PB_73.pdf (accessed on 22 March 2023). Blake A (2005). Economic impact of the London 2012 Olympics. Available online: https://opus.lib.uts.edu.au/handle/2100/994 (accessed on 3 April 2023). Bohlmann H, Van Heerden J (2005). The impact of hosting a major sport event on the South African economy. Available online: https://www.up.ac.za/media/shared/61/WP/wp-9.zp39542.pdf (accessed on 28 March 2023). Brunet F (1995). An economic analysis of the Barcelona’92 Olympic Games: Resources, financing and impact. In: de Moragas M, Botella M (editors). The Keys of Success: The Social, Sporting, Economic and Communications Impact of Barcelona’92. Servei de Publicacions de la UAB. pp. 203–237. Chanaron J (2014). Technology and economic impacts of mega-sports events: A key issue? Exploratory insights from literature. Megatrend Revija 11(4): 9–30. doi: 10.5937/megrev1404009c Chankuna D (2022). Socio-economic impacts of FIFA World Cup Qatar 2022: A study in Chon Buri sports city residents. Preprints 2022120285. doi: 10.20944/preprints202212.0285.v1 Chatzitheodoridis F, Kontogeorgos A (2020). Exploring of a small-scale tourism product under economic instability: The case of a Greek rural border area. 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Available online: https://www.nber.org/system/files/working_papers/w16721/w16721.pdf (accessed on 25 February 2023). Jensen CT (2021). Local sport event policies and sustainability: A puzzle approach. Frontiers in Sports and Active Living 3: 667762. doi: 10.3389/fspor.2021.667762 Kalfas D, Kalogiannidis S, Chatzitheodoridis F, Toska E (2023). Urbanization and land use planning for achieving the sustainable development goals (SDGs): A case study of Greece. Urban Science 7(2): 43. doi: 10.3390/urbansci7020043 Kalogiannidis S, Kontsas S, Konteos G, Chatzitheodoridis F (2022a). A small city rebranding: Another view of the territorial marketing. Wseas Transactions on Environment and Development 18: 686–701. doi: 10.37394/232015.2022.18.65 Kalogiannidis S, Kontsas S, Konteos G, Chatzitheodoridis F (2022b). Investigation of the redesigning process of the development identity of a local government regional unit (city): A case study of Kozani regional unit in Greece. 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Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/416279/A_review_of_the_Social_Impacts_of_Culture_and_Sport.pdf (accessed on 9 March 2023). Theodoraki E (2016). The problem with sporting mega-event impact assessment. In: Transparency International (editor). Global Corruption Report: Sport. Routledge. doi: 10.4324/9781315695709 United Nations Alliance of Civilizations (UNAOC) (2021). Guide on the Security of Major Sporting Events: Promoting Sustainable Security and Legacies. Available online: https://www.unaoc.org/resource/guide-on-the-security-of-major-sporting-events-promoting-sustainable-security-and-legacies/ (accessed on 16 April 2023). Walo M, Bull A, Breen H (1996). Achieving economic benefits at local events: A case study of a local sports event. Festival Management and Event Tourism 4(3–4): 95–106. doi: 10.3727/106527096792195353 Wikarya U, Widyasanti AA, Revindo MD, et al. (2022). Impact of international sports event on local businesses: Insight from the stallholders and official partners of the 2018 Asian Games. JEJAK 15(2): 336–353. doi: 10.15294/jejak.v15i2.36216 Yamane T (1967) Statistics: An Introductory Analysis, 2nd ed. Harper and Row. Young H (2022). Using sport as a tool for sustainable development: International organizations and sustainability. Independent Study Project (ISP) Collection. Available online: https://digitalcollections.sit.edu/isp_collection/3444 (accessed on 2 May 2023). There are currently no refbacks. This site is licensed under a Creative Commons Attribution 4.0 International License . myCBSEguide Class 12 Economics Case... Class 12 Economics Case Study Questions Table of Contents myCBSEguide App Download the app to get CBSE Sample Papers 2023-24, NCERT Solutions (Revised), Most Important Questions, Previous Year Question Bank, Mock Tests, and Detailed Notes. In this article, we will discuss how to download CBSE class 12 Economics Case Study Questions from the myCBSEguide App and our Student Dashboard for free. For the students appearing for class 12 board exams from the commerce/ humanities stream, Economics is a very lucrative and important subject. It is a very high-scoring subject that aids the students to increase their percentile and excel in academics. The exam is divided into 2 parts: Macro Economics Indian Economics Development 12 Economics Case Study Questions CBSE introduced case-based questions for class 12 in the year 2021-22 to enhance critical thinking in students. CBSE introduced a few changes in the question paper pattern to enhance and develop analytical and reasoning skills among students. Sanyam Bharadwaj, controller of examinations, CBSE quoted that the case-based questions would be based on real-life situations encountered by students. The purpose was to drift from rote learning to competency and situation-based learning. He emphasized the fact that it was the need of the hour to move away from the old system and formulate new policies to enhance the critical reasoning skills of students. Introducing case study questions was a step toward achieving the goals of the National Education Policy (NEP) 2020. What is a Case Study Question? As part of these questions, the students would be provided with a comprehensive passage, based on which analytical questions will have to be solved by them. The students will have to read the given passage thoroughly before attempting the questions. In The current examination cycle (2021-22), case-based questions have a weightage of around 20%. Types of Case Study Questions in Economics CBSE plans to increase the weightage of such questions in the following years, so as to enhance the intellectual and analytical abilities of the students. Case-based questions are predominantly of 3 types namely: Inferential Local questions Local questions can be easily solved as the answers are there in the given passage itself. Global Questions For Global questions, the students will have to read the passage in depth, analyze it and then solve it. Inferential questions Inferential questions are the ones that would require the student to have complete knowledge of the topic and could be answered by application of the concepts. The answers to such questions are tricky and not visible in the given passage, though the passage would highlight the concept on which the questions would be asked by CBSE. HOTS Questions in Class 12 Economics Personally, the concept of case-based questions is not new since CBSE has always included questions based on Higher Order Thinking Skills (HOTs). Though now we will have an increased percentage of such questions in the question paper. Advantages of Case-based Questions Class 12 Economics has two books and CBSE can ask Case study questions from any of them. Students must prepare themselves for both the books. They must practice class 12 Economics case-based questions as much as possible. Case study questions: Enhance the intellectual and analytical abilities of the students. Provide a complete and deeper understanding of the subject. Inculcate intellectual reasoning and scientific temperamental in students. Help students retain knowledge for a longer time. Would definitely help to discard the concept of memorizing insanely and cramming without a factual understanding of the content. The questions would help to terminate the existing system of education in India that promotes rote learning. Sample case study questions (Economics) class 12 Here are some case study questions for CBSE class 12 Economics. If you wish to get more case study questions and other related study material, download the myCBSEguide App now. You can also access it through our Student Dashboard. Case Study 1 Keeping in view the continuing hardships faced by banks in terms of social distancing of staff and consequent strains on reporting requirements, the Reserve Bank of India has extended the relaxation of the minimum daily maintenance of the CRR of 80% for up to September 25, 2020. Currently, CRR is 3% and SLR is 18.50%. “As announced in the Statement of Development and Regulatory Policies of March 27, 2020, the minimum daily maintenance of CRR was reduced from 90% of the prescribed CRR to 80% effective the fortnight beginning March 28, 2020 till June 26, 2020, that has now been extended up to September 25, 2020,” said the RBI. Q.1 The full forms of CRR and SLR are: Current Reserve Ratio and Statutory Legal Reserves Cash Reserve Ratio and Statutory Legal Reserves Current Required Ratio and Statutory Legal Reserves Cash Reserve Ratio and Statutory Liquidity Ratio (ans) Q.2 What will be the value of the money multiplier? None of these Q.3 SLR implies: a) Certain percentage of the total banks’ deposits has to be kept in the current account with RBI b) Certain percentage of net total demand and time deposits have to be kept by the bank themselves (ans) c) Certain percentage of net demand deposits has to be kept by the banks with RBI d) None of the above Q.4 Decrease in CRR will lead to __. a) fall in aggregate demand in the economy b) rise in aggregate demand in the economy (ans) c) no change in aggregate demand in the economy d) fall in the general price level in the economy Case Study 2 An important lesson that the COVID-19 pandemic has taught the policymakers in India is to provide greater impetus to sectors that make better allocation of resources and reduce income inequalities. COVID-19 has also taught a lesson that in crisis the population returns to rely on the farm sector. India has a large arable land, but the farm sector has its own structural problems. However, directly or indirectly, 50 percent of the households still depend on the farm sector. Greater support to MSMEs, higher public expenditure on health and education and making the labour force a formal employee in the economy are some of the milestones that the nation has to achieve. One of the imminent reforms to be done in the country is labour reforms. Labour laws are outmoded in India, and some of these date back to the last century. India’s complex labour laws have been blamed for keeping manufacturing businesses small and hindering job creation. Industry hires labour informally because of complex laws and that is responsible for low wages. Which types of structural problems are faced by the agricultural sector? “It is necessary to create employment in the formal sector rather than in the informal sector.’’ Defend or refute the given statement with valid argument. Hired labour comes in …………………. (Informal organisation / formal organisation) What do you mean by MSMEs? Case Study 3 People spend to acquire information relating to the labour market and other markets like education and health. This information is necessary to make decisions w.r.t investment in human capital and its efficient utilization. Thus, expenditure incurred for acquiring information relating to the labour market and other markets is also a source of human capital formation. Q1. Which of the following is the source of human capital formation in India? Acquiring information All of these (ans) Q2. Education provides Private benefit Social benefit Both 1) and 2) (ans) Q3. __ persons contribute more to the growth of an economy. Q4. Training given by a company to its employees is generally__________ Investment (ans) Social wastage Both 1) and 2) Tips to Solve Case Study Questions in Economics Let’s understand how you can solve case study questions in class 12 Economics. The two books are Macroeconomics and Indian Economic Development. Read the passage thoroughly Can follow a reversal pattern, especially macroeconomics questions, i.e. read questions first and then look for the answers in the passage. In case the question asked is about Indian Economic Development, read the passage very carefully as most of the answers would be hidden in the passage itself. Macro Economics questions will be more application-based and would test your conceptual clarity. Answer briefly and precisely. Important Chapters – Economics Case Study Questions Following are some of the very important topics that need to be prepared very thoroughly under CBSE class 12 Economics. We expect that CBSE will certainly ask case-based questions from these chapters. National income and its aggregates Government budget Current challenges faced by the Indian economy “Stop waiting for tomorrow, Start now” Test Generator Create question paper PDF and online tests with your own name & logo in minutes. Question Bank, Mock Tests, Exam Papers, NCERT Solutions, Sample Papers, Notes Related Posts Competency Based Learning in CBSE Schools Class 11 Physical Education Case Study Questions Class 11 Sociology Case Study Questions Class 12 Applied Mathematics Case Study Questions Class 11 Applied Mathematics Case Study Questions Class 11 Mathematics Case Study Questions Class 11 Biology Case Study Questions Class 12 Physical Education Case Study Questions 3 thoughts on “Class 12 Economics Case Study Questions” thanks for your information, dont forget to visit airlangga university website https://www.unair.ac.id/mahasiswa-unair-dan-y20-indonesia-diskusikan-isu-resesi-ekonomi/ thank you for Economics MCQs https://mcqquestions.net/economics Leave a Comment Save my name, email, and website in this browser for the next time I comment. Screen Reader Skip to main content Text Size A Language: English Case Studies EXIM Procedure Media & Events Image Gallery Media Coverage Other Links GI of India Experience India Indian Trend Fair 2022 India Organic Biofach 2022 Gulfood Dubai 2023 Not a member Programmes & Qualifications Cambridge igcse economics (0455). Past papers, examiner reports and specimen papers You can download one or more papers for a previous session. Please note that these papers may not reflect the content of the current syllabus. Unlock more content This is only a selection of our papers. Registered Cambridge International Schools can access the full catalogue of teaching and learning materials including papers from 2018 through our School Support Hub . Past papers -->June 2022 Mark Scheme Paper 11 (PDF, 154KB) -->June 2022 Mark Scheme Paper 21 (PDF, 511KB) Examiner reports -->June 2022 Examiner Report (PDF, 2MB) Specimen papers -->2020 Specimen Paper 1 Mark Scheme (PDF, 897KB) -->2020 Specimen Paper 2 Mark Scheme (PDF, 172KB) Stay up to date Sign up for updates about changes to the syllabuses you teach Syllabus overview Published resources Identifying the socio-economic factors of deforestation and degradation: a case study in Gilgit Baltistan, Pakistan Ullah, Saif Rauf, Tariq Sikandar, Furqan Liu, Jia Qi Noor, Rana Shahzad Deforestation remains a major ecological problem in most developing countries especially, Pakistan has a very high deforestation rate. Various socioeconomic factors determine deforestation and degradation. Therefore, this study was aimed to evaluate the causes of deforestation in Basho forest, Gilgit Baltistan, Pakistan. This study collected data on factors of deforestations and degradation resulting in environmental problems such as air pollution, soil erosion, temperature rise and to recommend practices for sustainable forests. A questionnaire survey of 220 respondents was conducted including; educated locals of different age group and forest officials (forest engineers, civil servants and workers) in Forestry service division. Descriptive statistics and a logistic regression model were applied on the collected data and Likert scale method to determine the mean score of socio-economic factors encouraging deforestation. More than 70% respondents were below 30 years old, while 14.6% and 12.6% respondents from 31–40 to 41–50 age groups, respectively. 65.9% and 34.1% of the respondents were male and female respectively. Only 26.8% of the respondents were university graduates, while below 50% (48.6%) of respondents were primary school graduates. According to the analysis, the respondents were completely dependent on the forest for their livelihood needs. The socioeconomic factors such as rapid population growth, livelihood activities, lack of education, Poor forest management, Fuel wood consumption and Period of residence were found to be the prominent factors for deforestation. Results of the logit regression established reward socioeconomic factors were statistically significant variable at (p < 0.05). Based on study results, the deforestation activities cannot be entirely eradicated but it can be reduced to the level of sustainable forest through convenient forest conservation policies and application of efficient and energy conservation technologies. Adequate economic incentives and applied technologies for locals could be a productive approach to reduce deforestation rate. Basho factors; Deforestation and degradation; Socio-economic factors; Logistic regression and likert scale method; Sustainable forest practices Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Loading metrics Open Access Peer-reviewed Research Article Quantitative evaluation of science and technology financial policies based on the PMC-AE index model: A case study of China’s science and technology financial policies since the 13th five-year plan Contributed equally to this work with: Hongyuan Shen, Panyu Xiong Roles Conceptualization, Formal analysis, Methodology, Supervision, Validation, Writing – review & editing * E-mail: [email protected] Affiliation School of Economics and Management, Southwest University of Science and Technology, Mianyang, China Roles Conceptualization, Formal analysis, Project administration, Supervision, Visualization, Writing – review & editing Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing – original draft Roles Conceptualization, Investigation, Resources, Supervision, Validation Affiliation China Three Gorges Group Basin Management Center, Yibin, China Hongyuan Shen,  Panyu Xiong,  Linfeng Yang,  Published: August 1, 2024 https://doi.org/10.1371/journal.pone.0307529 Reader Comments The formulation of science and technology financial policies directly influences the direction of national economic development. Quantitative evaluation of these policies is an important method to reflect the consistency and strengths and weaknesses of policy interrelations. This paper analyzes 16 science and technology financial policy documents issued by the Chinese central government from 2016 to 2022, using text analysis and content analysis to extract keyword frequencies, and constructs 9 primary variables and 34 secondary variables. For the first time, a PMC-AE index model for science and technology financial policies is established, and a quantitative evaluation is conducted on 5 significant policy documents out of the 16. The results show that, from an overall analysis, Policy 1 and Policy 4 are at a good level, while the other three policies are at an excellent level. From the analysis of individual policy PMC-AE indexes, the rankings in descending order are: P2 > P5 > P3 > P4 > P1. Overall, the policies effectively meet the needs of China’s science and technology financial development, with P2, P3, and P5 being at an excellent level, P4 at a good level, and P1 at an acceptable level, mainly reflecting the need for improvement in aspects such as policy synchronization with the current stage, targeted entities, guiding fields, and policy content. It is recommended that Chinese government departments should focus on five aspects in policy formulation: building a talent system for science and technology finance, improving the quality of financial services, coordinating central and local financial policies, protecting intellectual property rights in science and technology finance, and strengthening financial supervision. This will be conducive to the effective implementation of science and technology financial policies. Citation: Shen H, Xiong P, Yang L, Zhou L (2024) Quantitative evaluation of science and technology financial policies based on the PMC-AE index model: A case study of China’s science and technology financial policies since the 13th five-year plan. PLoS ONE 19(8): e0307529. https://doi.org/10.1371/journal.pone.0307529 Editor: Mihajlo Jakovljevic, University of Kragujevac: Univerzitet u Kragujevcu, SERBIA Received: November 29, 2023; Accepted: July 5, 2024; Published: August 1, 2024 Copyright: © 2024 Shen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the manuscript. Funding: This study was funded by the National Social Science Foundation of China (Grant No. 21BGL213). Competing interests: The authors have declared that no competing interests exist. Introduction As society progresses, the economy develops, and technological advancements have given rise to a series of financial instruments serving various aspects of our lives, making significant contributions to the nation’s economic take-off and people’s well-being. The organic integration of the Internet+ and artificial intelligence has accelerated the application of science and technology financial services in various social fields. At the same time, it has also brought certain risks and challenges. How to assess the security and guidance of current science and technology financial policies is a difficult question that lies before us. Looking back at the implementation history of China’s science and technology finance, it can be divided into three periods: the nascent period (1985–2008), the initial stage (2009–2014), and the rapid development period (2015–2024). During the nascent period, the overall characteristic of China’s financial technology was the "technology-first" + "government-led" model, where the government was the main driver of financial support for technology, primarily through increased fiscal spending in the field of science and technology and proposing a series of science and technology financial measures such as guiding financial institutions to increase investment in high-tech industries and enhancing fiscal support for technological innovation. In the initial stage, the overall characteristic was the "financial empowerment" plus "regional pilot" model, which for the first time clearly defined science and technology finance, pointing out that innovations in various financial tools such as credit, investment, and insurance promote technological development, committed to broadening the funding sources for technology enterprises, constructing a multi-level capital market, and formulating a series of science and technology financial policies conducive to "technological empowerment". During the rapid development period, the overall characteristic of science and technology finance was "integration of science and finance" plus "multi-stakeholder participation, multi-level market, diversified tools". In this period, the focus of science and technology financial policies shifted from constructing to perfecting the science and technology financial system, with corresponding policies being more regional, targeted, and innovative. Looking at the three important periods of China’s science and technology finance, the evolution of policies has shown a transformation from abstract to concrete, from discrete to comprehensive, and from fragmented to integrated. In this process, the Chinese government or departments have issued a series of guiding policies on science and technology finance, clarifying specific contents, such as in 1993 when the State Council issued the "Decision of the State Council on Financial System Reform". In 2014 and 2016, the content of financial technology was clarified in the form of government reports and the "13th Five-Year" Science and Technology Innovation Plan, and in 2019, the first top-level document "Financial Technology Industry Development Plan (2019–2021)" was released. Following this, six national ministries approved a one-year financial technology application pilot in 10 places including Beijing, Shanghai, and Sichuan. The pilot cities subsequently introduced financial technology policies with the aim of promoting the development of science and technology finance to improve quality and efficiency. According to statistics from the China Banking and Insurance Regulatory Commission, as of July 28, 2023, China has established over 1000 science and technology branches and specialized science and technology financial institutions. According to data released by the People’s Bank of China, as of the end of June 2023, the balance of medium and long-term loans in the high-tech manufacturing industry reached 2.5 trillion yuan, with a year-on-year increase of 41.5%, maintaining a high growth rate of over 30% for three consecutive years, and the role and influence of science and technology finance have gradually become apparent. Up to now, the discussions on science and technology finance among policy makers, academia, and industry have mostly focused on how science and technology finance supports technology enterprises and innovation. However, there is still a lack of research findings on the evaluation of the effectiveness of science and technology financial policies. In light of this, it is very urgent to study the effects of financial technology-related policies, which plays a crucial role in guiding China’s science and technology financial market. Currently, science and technology financial policies cover a wide range of content: this includes policy effectiveness, whether policy supervision is in place, the consistency of related policies, the level of policy issuance, knowledge, property rights, financial talent, financial intermediaries, and more. Based on the collation of science and technology financial policy documents, this paper explores whether the execution effects of science and technology financial policies are reasonable and can have policy guidance. It conducts scientific quantitative analysis and evaluation research, which is of great practical significance for the steady advancement of China’s current science and technology financial policies, solving the problems of unbalanced and insufficient development of financial technology, and improving the policy and regulatory standards system. The main sections of the paper are arranged as follows: the first part is literature review, the second part is materials and methods, the third part is quantitative evaluation of science and technology financial innovation policies, the fourth part is discussion, and the fifth part is research conclusions and recommendations. Literature review Looking back at the research achievements in science and technology finance, Schumpeter [ 1 ] was one of the first to propose that the new economy requires the reintegration of a series of newly formed production economic elements and external conditions into the existing production and operation system to stimulate economic development, which then leads to financial innovation. With the development of the social economy [ 2 ], technological innovation has become the new engine of social development. Combining it with financial innovation can further promote the development of emerging industries. However, market failures may occur during the development of emerging industries. At this time, timely government intervention in the market economy, macroeconomic regulation, and the introduction of corresponding industry regulatory policies to improve "general policies + specific policies" measures in response to market failures can not only solve the problems of limited growth of a large number of small and medium-sized enterprises in the post-pandemic era and optimize the national innovation environment but also achieve market supply and demand balance and improve the efficiency of resource allocation [ 3 ]. Reviewing the science and technology financial policies introduced since the reform and opening up, it has been found that these policies have been analyzed from different perspectives [ 4 ], and research methods such as co-word analysis and social network mapping have been used to study the policy theme changes in science and technology finance [ 5 ]. Research findings also indicate that there are differences in the implementation effects of science and technology financial policies on enterprises of heterogeneous nature and market types [ 6 ]. With the rapid development of China’s economy, various regions across the country have successively introduced related science and technology financial policies. A considerable amount of research has been conducted by scholars on how to measure the implementation effects of these policies. For instance, the level of development of science and technology finance in Guangdong Province has consistently been at the forefront nationally, but the problem of uneven development within the province is severe [ 7 ]. The provincial capital, Guangzhou, places great emphasis on the integration of science and technology with finance, achieving leapfrog development, thereby leading the way in the level of science and technology financial development. In contrast, some other areas have less than ideal development in financial technology [ 8 ]. In some provinces, due to a lack of emphasis on the integration of science and technology with finance, not only are there disparities in economic development levels between provinces, but significant differences also exist within the regions of each province. Local governments should analyze specific problems in detail and formulate a series of policies suitable for the local development of science and technology finance. Taking Jiangsu Province as an example, the provincial government has played different roles in financing roadshows for science and technology finance projects, thus alleviating the financing difficulties of technology-based SMEs and creating broad development space for them [ 9 ]. Besides, although some regions have a relatively complete system of science and technology financial policies, the synergy between these policies is not strong, such as in Shanghai [ 10 ]. Some areas even experience a general situation where coordinated development and policy impact efficiency are both low, such as in Hebei Province [ 11 ]. So, how to solve the problem of policy impact efficiency? Pang and Zhang [ 12 ] believe that by strengthening the coordination horizontally and vertically among departments, the efficiency of policy transmission from the provincial level to the municipal level can be improved. Given the differences in development among China’s provinces, those with lower development efficiency can formulate local policies based on regional development advantages and find paths that are conducive to their own efficient development of science and technology finance [ 13 ]. For a long time, the geographical position of the eastern region has been superior to that of the western region, and the eastern coastal areas, with their numerous ports, facilitate trade with countries around the world. Not only do the eastern coastal cities have advantageous geographical locations, but they also place emphasis on the development of financial technology, becoming economically developed regions [ 14 ]; whereas in the western region, cities such as Chengdu and Chongqing, despite having introduced corresponding policies for technological innovation to support technology enterprises and build innovation platforms, still exhibit low efficiency in science and technology finance [ 15 ]. In contrast, some western provinces with geographical environments slightly inferior to Chengdu and Chongqing, such as Jiangxi and Guizhou, have low levels of development in science and technology finance, yet the growth rate of their financial efficiency is fast. Huang and Qiu [ 16 ] evaluated the efficiency of China’s science and technology finance, suggesting that science and technology finance overall does not significantly enhance technological innovation and efficiency. With the strengthening of centrality in the capital network, macro-orientation, financial support, and policies for technical and financial patent protection will significantly improve the innovation performance of enterprises [ 17 ]. Science and technology financial policies can be used to promote enterprises in pilot cities, enhance innovation efforts, and improve innovation performance, accelerating the transformation and upgrading of industrial structures [ 18 – 20 ]. In line with the development requirements of China’s "13th Five-Year Plan," the financial industry should first meet the development needs of real enterprises and accelerate the construction of new science and technology financial service platforms [ 21 ]. As China’s economic development enters a new normal, practicing green finance and the concept of low-carbon development, science and technology finance has accelerated the process of high-quality economic development in China [ 22 – 25 ], improving the investment efficiency of corporate green innovation [ 26 ] and the driving effect of green development [ 27 ]. Meanwhile, the promoting effect of green technology innovation in science and technology finance exhibits spatial heterogeneity, with the eastern region showing an increasing marginal effect, and the central region displaying an inverted "U" characteristic [ 28 ], which is conducive to the risk resistance level of enterprises [ 29 ], providing strong support for the development of new productive forces [ 30 ]. However, some scholars believe that the excessive financialization of science and technology finance may have a negative impact on the real economy [ 31 ]. Policy evaluation not only has a direct promoting effect on policy formulation, implementation, and feedback adjustment [ 32 ], but also has a significant impact on the understanding of global trends and the establishment and adjustment of national science and technology financial strategies [ 33 ]. Policy evaluation originated with Suchman’s [ 34 ] five categories of evaluation, followed by Poland’s [ 35 ] "Three E’s" evaluation framework and Wollmann’s [ 36 ] classical policy evaluation. With the continuous exploration of policy evaluation methods, many methods of policy assessment have emerged. Shen et al. [ 37 ] used the difference-in-differences approach to empirically analyze the policy effects of the energy rights trading system, and applied the Analytic Hierarchy Process (AHP) to evaluate China’s military-civil fusion policies [ 38 ]. Feng et al. [ 39 ] constructed a BP neural network-based model for predicting carbon emissions in the electricity sector; some scholars used the Delphi method and Fuzzy Analytic Hierarchy Process (FAHP) to assess the main factors and sub-factors of green finance [ 40 ]; analyzed the risks related to China’s green infrastructure financing and prioritized them [ 41 ], as well as evaluating the environmental, social, and governance (ESG) factors and policy choices in China’s green finance investment decisions [ 42 ]. Currently, many evaluation methods have certain flaws, mainly reflected in the inevitable subjectivity and lower precision. The PMC index model method, however, obtains original data through text mining, which can largely avoid subjectivity and improve the precision of policy evaluation. The PMC method is based on the Omnia Mobilis (everything is in motion) assumption proposed by Ruiz Estrada et al. [ 43 ] when studying the application in Cartesian space, and has constructed the PMC index model, innovating the single policy evaluation method. This method judges the consistency of policies from a multidimensional perspective and directly observes the strengths and weaknesses of policy texts by constructing the concave and convex shapes of the PMC surface [ 44 , 45 ]. Since then, this method has been widely applied to policy evaluation research: for example, in the construction industry [ 46 ]; nursing insurance policies [ 47 ] and farmland protection policies [ 48 ]; China’s pork industry [ 49 ]; the efficiency of green development in the Yangtze River Economic Belt [ 50 ]; China’s watershed ecological compensation policies [ 51 ] and the effectiveness evaluation of provincial public funding policies for private colleges in China [ 52 ]. The PMC method has been used to study the effectiveness of related policies, providing a good evaluation of the consistency and deficiencies of different policies during the specific implementation process. In summary, scholars have made rich comparisons of the results from the perspective of the role of science and technology financial policies in promoting economic development, as well as the changes in the policy themes of science and technology finance, with a focus on elucidating the impact of science and technology finance on regional economic development and revealing the problems of unevenness and low efficiency in policy execution across different regions. With the robust development of China’s economy, the Chinese government or relevant departments have introduced a series of policies emphasizing the importance of science and technology finance, making the evaluation of the effectiveness of these policies particularly urgent. There are many existing evaluation methods, each with its own shortcomings. The Analytic Hierarchy Process (AHP) analyzes the correlation of a limited number of variables in a time series, which is limited by the number of variables and neglects the influence of some factors that are small yet actually present. The subjectivity of the Fuzzy Comprehensive Evaluation and Grey Comprehensive Evaluation methods is strong, and their resolution is poor [ 53 ]. Although the PMC method has been widely used in evaluating policies in many fields, its application in the evaluation of China’s science and technology financial policies is still a blank area. This paper attempts to use the PMC method to evaluate the effectiveness and consistency of science and technology financial policies, thereby analyzing whether the policy itself has any shortcomings in its guiding effectiveness. In view of this, the marginal contribution of this paper lies in: first, constructing for the first time a PMC-AE index model to quantitatively evaluate the science and technology financial policies issued by the central government since the "13th Five-Year Plan" of China, by extracting high-frequency words to construct 9 primary variables and 34 secondary variables, and establishing a multiple input-output table; second, judging the policy execution effects based on the intuitive concave and convex shapes of the PMC surface, and evaluating the consistency and effectiveness of science and technology financial policies; third, proposing five reasonable suggestions for the central government functional departments formulating science and technology financial policies. This is conducive to the Chinese government’s revision of science and technology financial policies, improving the policies, and enhancing the execution effects of science and technology financial policies. Materials and methods Mechanism of action for science and technology financial policy. Once the science and technology financial policy is enacted and implemented, it will have significant impacts on the economy, society, technology, politics, and the environment. During the implementation of the science and technology financial policy, it is influenced by factors such as the market, regulation, laws and regulations, timeliness, and talent. This also reflects a series of issues. By analyzing and judging the effectiveness of policy implementation, constructive feedback can be provided to the relevant departments. This is conducive to the further improvement of science and technology financial policies and promotes national economic development, thereby forming a complete cycle chain, as shown in Fig 1 . PPT PowerPoint slide PNG larger image TIFF original image https://doi.org/10.1371/journal.pone.0307529.g001 Statistical analysis Pmc-ae index model.. https://doi.org/10.1371/journal.pone.0307529.g002 In the aforementioned formula, X = ( x 1 , x 2 , x 3 ⋯, x n ) T represents the established multi-dimensional indicators for evaluating science and technology financial policies, while Y = ( y 1 , y 2 , y 3 ⋯, y n ) T denotes the corresponding values of the output layer nodes. The activation functions for the hidden layer and output layer, denoted by f and g respectively, are typically Sigmoid, Tanh, or Softplus functions, among others, and may be identical or distinct. C = ( c 1 , c 2 , c 3 ⋯, c m ) T signifies the values of the hidden layer nodes; W and W T represent the weight matrices between the input and hidden layers and between the hidden and output layers, respectively. The dimensions of these matrices are determined by the number of neurons in the preceding layer (rows) and the subsequent layer (columns). The bias vectors b = ( b 1 , b 2 , b 3 ⋯, b m ) T and B = ( B 1 , B 2 , B 3 ⋯, B n ) T pertain to the input-to-hidden and hidden-to-output layer transitions, with dimensions corresponding to the number of nodes in the subsequent layer neurons. The objective of Autoencoder (AE) training is to minimize the discrepancy between Y and X [ 54 ]. When the dimensionality of the original data is excessively high, or when a lower-dimensional representation is required, the neural network architecture can be modified by increasing the number of layers and progressively reducing the number of neural unit nodes. Consequently, after training, X is transformed into C through a nonlinear combination, C is then transformed into Y through another nonlinear combination, with the aim of achieving Y = X. Hence, C can be regarded as the nonlinear embodiment of X, and Y is derived from the decoding of C. Thus, C can serve as the composite score of policy texts after the integration of various indicators [ 55 ]. The construction of the PMC-AE index model mainly consists of the following four basic steps: (1) Classification of variables, calculation, and determination of model parameters. (2) Establishment of a multi-parameter input-output table for science and technology financial innovation policies, and assignment using text refinement techniques. (3) Fusion of multiple parameters using the autoencoder technology of neural networks to calculate the PMC-AE index. (4) Drawing of the PMC-AE index surface to evaluate the merits of science and technology financial innovation policies. The principle of constructing the PMC-AE index model is shown in Fig 3 . https://doi.org/10.1371/journal.pone.0307529.g003 Data acquisition and preparation. This article takes the beginning year of China’s "Thirteenth Five-Year Plan" as the base point, mainly selecting relevant policies on science and technology financial innovation issued by the Central Committee of the Communist Party of China, the State Council, and the innovation demonstration zones. The policy data sources include official websites such as the State Council, the People’s Bank of China, Shanghai, Guangzhou, and the Shenzhen Special Economic Zone. By collecting, organizing, and screening, we ensure the accuracy of the policy texts. To ensure that the content of policy information is consistent with the theme of science and technology financial innovation, the following principles were adhered to when organizing and selecting policy texts: First, choose policies closely related to science and technology financial innovation, excluding those that only mention science and technology financial innovation. Secondly, the types of texts are general document management systems that have been published, involving outlines, plans, proposals, opinions, suggestions, notices, etc. To ensure the timeliness of policy research, 16 policy documents related to science and technology financial innovation were ultimately selected to construct a database of policies on science and technology financial innovation (see Table 1 ). https://doi.org/10.1371/journal.pone.0307529.t001 Policy content keyword. In recent years, many citation analysis software tools such as CiteSpace and VOSviewer have emerged domestically and internationally. These tools can construct a comprehensive knowledge unit of literature, informing us of the key research areas in a discipline. However, such citation software has a problem of being "too broad" in determining research content. ROSTCM, on the other hand, can analyze the key research content of a field in more detail by capturing literature abstracts. The software is powerful and easy to operate, and the text mining process is shown in Fig 4 . Based on the research results of previous scholars [ 56 ], and in combination with the mechanism of action of science and technology financial policies mentioned above, this paper has established 9 primary indicators that are broad and universal. The setting of secondary indicators is through comprehensive reference to relevant domestic and international literature [ 57 ], and in conjunction with the specific policy content of the relevant policy documents in this paper. Using ROSTCM6 software, the content of 16 policies is imported into the text mining database for word segmentation and screening. After effectively removing interference words such as "implement," "promote," and "improve," the high-frequency words are extracted (see Table 2 ). The document set is segmented, followed by word frequency statistics, which are displayed from high to low frequency, and a social network graph is established (see Fig 5 ). https://doi.org/10.1371/journal.pone.0307529.g004 https://doi.org/10.1371/journal.pone.0307529.g005 https://doi.org/10.1371/journal.pone.0307529.t002 To explore the operational level of policy tools, based on cybernetics and within the framework of "standard information behavior," this paper studies policy tools [ 58 ]. According to the mechanism of action of science and technology financial policies, different keywords are selected from the basic elements of policy orientation to analyze the basic elements of policy tools. Then, through comparison and classification, the main axis and selection codes of policy tools are formed. Firstly, looking at the distribution of high-frequency words, financial and market vocabulary appears more than 300 times, indicating that the focus of the policy is very clear, reflecting the core idea of the financial marketization trend; the frequency of words such as enterprise, innovation, and technology exceeds 200 times, indicating that the documents focus on execution efficiency, while the remaining frequencies mainly reflect the scope of policy application. Secondly, based on the Omnia mobilis hypothesis and combining the research findings of Ruiz Estrada et al. [ 43 ], related literature, and the results of vocabulary processing from text statistics, it is found that policy texts are centered on "innovation," with finance and technology as the core, deriving keywords such as talent, institutions, markets, and enterprises. Based on the aforementioned research, 9 primary variables and 34 secondary variables are set. The primary variables include: policy timeliness (X1); policy nature (X2); policy content (X3); policy field (X4); target of action (X5); perspective of action (X6); policy system (X7); issuing institution (X8); effectiveness level (X9). The secondary variables contained within each primary variable are as follows: Policy Timeliness (X1) includes three secondary indicators: (X1:1) Long-term (>5 years); (X1:2) Medium-term (3–5 years); (X1:3) Short-term (1–3 years), which are used to define whether the timeliness of the science and technology financial policy is long-term, short-term, or medium-term. Policy Nature (X2) includes six secondary indicators: (X2:1) Forecast; (X2:2) Suggestion; (X2:3) Identification; (X2:4) Regulation; (X2:5) Description; (X2:6) Guidance. These are used to evaluate whether the policy possesses functions of suggestion, forecast, identification, regulation, description, or guidance. Policy Content (X3) includes six secondary indicators: (X3:1) Finance; (X3:2) Technology; (X3:3) Market; (X3:4) Knowledge; (X3:5) Service Industry; (X3:6) Property Rights. These six indicators are used to evaluate the content included in a science and technology financial policy. Finance refers to financial policies issued by central documents (investment and financing, loans, interest rates, monetary tools, etc.); Technology refers to policies introduced to promote scientific and technological innovation (corporate scientific research, scientific and technological productivity, etc.); Market mainly involves China’s multi-level capital markets; Knowledge refers to systems such as science and technology finance talent and theories; Service Industry refers to the service industries related to finance, such as insurance, accounting, auditing, securities, and other financial services; Property Rights mainly refer to aspects such as the definition of property rights for technology-based enterprises. Policy Field (X4) includes five secondary indicators: (X4:1) Finance; (X4:2) Technology; (X4:3) Talent; (X4:4) Market; (X4:5) Industry, which are used to measure whether a science and technology financial policy involves the fields of finance, technology, talent, market, and industry. Target of Action (X5) includes four secondary indicators: (X5:1) Enterprises; (X5:2) Banks; (X5:3) Government; (X5:4) Other Financial Institutions. These four indicators are used to measure whether a science and technology financial policy involves these entities. Perspective of Action (X6) includes two secondary indicators: (X6:1) Micro; (X6:2) Macro. Policy System (X7) includes four secondary indicators: (X7:1) Clear Objectives; (X7:2) Feasible Scheme; (X7:3) Adequate Basis; (X7:4) Conformity with National Conditions. These four indicators are used to measure whether a science and technology financial policy has clear objectives, an adequate basis, a feasible scheme, and conforms to national conditions. Issuing Institution (X8) includes four secondary indicators: (X8:1) State Council; (X8:2) Ministry of Finance; (X8:3) Central Bank; (X8:4) Securities Regulatory Commission, Banking and Insurance Regulatory Commission, and other financial departments. The data selected in this paper mainly comes from policies enacted at the central level. Effectiveness Level (X9) includes five secondary indicators: (X9:1) Laws and Regulations; (X9:2) Administrative Regulations; (X9:3) Departmental Rules; (X9:4) Normative Documents; (X9:5) Industry Regulations. These five secondary indicators are used to evaluate the effectiveness level of a science and technology financial policy, and the levels of effectiveness decrease in the order listed. The setup of each level of variables in the index model for the science and technology financial policies is shown in Table 3 . https://doi.org/10.1371/journal.pone.0307529.t003 Setting of secondary variable parameters. The calculation of the PMC-AE Index Model uses binary for the setting of secondary variable parameters, with efficacy indicators exhibiting progressive and exclusive characteristics. If the content is present in the policy document, it is counted as 1; otherwise, it is counted as 0. The score results of the secondary variable parameters are shown in Table 4 . https://doi.org/10.1371/journal.pone.0307529.t004 Establishment of multiple input-output tables. Multiple input-output tables are an optional data analysis framework that can store a large amount of data and measure the variables of science and technology finance innovation policy evaluation from multiple dimensions, reflecting the evolution process of a certain policy. These tables consist of several primary variables and an unlimited number of secondary variables. This article combines the indicators of China’s science and technology finance innovation policy to establish multiple input-output tables (see Table 5 ). https://doi.org/10.1371/journal.pone.0307529.t005 Calculation of PMC-AE index. The first step is to calculate the PMC-AE index. The specific steps are: first, place primary and secondary variables into the multiple input-output table; second, calculate the specific values of the secondary variables; third, calculate the specific values of the primary variables; fourth, calculate the PMC-AE index. The calculation steps and methods are shown in Table 6 , where in the third and fourth steps of the formula, i stands for a primary variable, i = 1, 2, 3,…, m; j stands for a secondary variable, j = 1, 2, 3,…, n. https://doi.org/10.1371/journal.pone.0307529.t006 PMC-AE index scoring standards. Based on Table 6 , after assigning and calculating values one by one, since this article has selected 9 primary evaluation indicators, according to the evaluation standards of Ruiz Estrada [ 45 ], the calculated PMC-AE index ranges between 0–9. The specific values of the PMC-AE index are then classified into levels (see Table 7 ). https://doi.org/10.1371/journal.pone.0307529.t007 Drawing of PMC-AE surface. The PMC surface is based on the PMC-AE index, presenting the policy evaluation effect in a graphical form. The purpose of constructing the PMC surface is to reflect the research results more vividly and intuitively. To construct the PMC surface, it is first necessary to build the PMC matrix based on the obtained PMC-AE index (Formula 4 ). This article sets 9 primary variables, thus forming a third-order matrix. Then, according to the calculation results of Table 6 , the PMC surface is drawn, which visually displays the policy evaluation effect. Quantitative evaluation of technology finance innovation policies The fundamental idea behind the PMC index model is not to overlook potential related variables. Subjective selection of policy texts can lead to biases in policy evaluation models. Therefore, when choosing policy samples, it is not necessary to follow a specific pattern, nor is it required to classify policies according to criteria such as issuing institutions or levels of efficiency. The PMC-AE index model is developed through an unsupervised data dimension reduction technique that extracts the data characteristics of the main variables. Regardless of the sample selection, the core variables of the database are preserved. The PMC model can be used to evaluate both national and regional policies. In order to ensure the authoritative and instructive nature of policy text evaluations, this paper, based on the aforementioned considerations, randomly selects five major science and technology finance policies introduced at the central level in recent years for quantitative analysis, which reflects the specific implementation of policy texts. These policies play a major role in better evaluating China’s technology finance innovation policies, and the selected texts are shown in Table 8 . https://doi.org/10.1371/journal.pone.0307529.t008 Based on the multiple input-output tables and policy texts, variables are set to obtain the multiple input-output tables for the five technology finance innovation policies, as shown in Table 9 . https://doi.org/10.1371/journal.pone.0307529.t009 Scores from the five policy texts were used to construct a neural network model using autoencoder technology, and its parameters were learned. The data fusion process includes two stages. The first stage involves merging the scores of the second-level variables for each strategy to obtain the scores for the nine first-level variables of each strategy. In the second stage, the scores of the nine first-level variables are merged to derive the PMC-AE index for the five policies (see Table 10 ), which are then ranked according to Table 7 . https://doi.org/10.1371/journal.pone.0307529.t010 Drawing PMC surface charts PMC surface charts provide a comprehensive analysis of science and technology finance innovation policies based on intuitive visualization results, with the depth of the concavity negatively correlated with policy ratings. The PMC matrix of the science and technology finance policies can be derived from Table 10 (see Table 11 ). Based on the aforementioned calculated data, the surface charts for the five science and technology finance policies can be obtained, from Figs 6 – 10 . https://doi.org/10.1371/journal.pone.0307529.g006 https://doi.org/10.1371/journal.pone.0307529.g007 https://doi.org/10.1371/journal.pone.0307529.g008 https://doi.org/10.1371/journal.pone.0307529.g009 https://doi.org/10.1371/journal.pone.0307529.g010 https://doi.org/10.1371/journal.pone.0307529.t011 Empirical results The PMC-AE index of the above five policies was calculated, and surface plots were created. Overall, the results indicate that Policy 1 and Policy 4 are at a good level. The remaining three are at an excellent level, and the primary indicators of each of the five sample policies can be intuitively represented through Figs 6 to 10 . In terms of the timeliness of Policy X1, it is mainly based on medium- and long-term planning, with a lack of short-term targets. A combination of policies for different time periods should be adopted to meet the needs of various economic development stages. Regarding the nature of Policy X2, the predictive, advisory, regulatory, and guiding functions of the policy are quite excellent, but there is a need for further strengthening in identification and description. Policy X3 is rated as excellent, but there are slight deficiencies in knowledge and property rights, which necessitates focusing on the cultivation of knowledgeable talents in the field of science and technology finance and clearly defining the property rights issues of small and medium-sized science and technology enterprises. In terms of Policy X4’s domain, it basically covers all aspects of China’s economic development. As for the target of Policy X5, there is less policy planning for banking institutions, which should focus on the intermediary role of banks in financial innovation and maximize the support of finance for technology. Policy X6, from the perspective of impact, considers both the micro and macro economy and emphasizes the applicable levels of science and technology finance. Policy X7’s system is based on the current economic development status of China, conforms to the national conditions, with clear and reasonable plans, and effectively promotes innovation in science and technology finance. Regarding the issuing body of Policy X8, there are few issuing bodies, mainly central ones, and there should be a focus on the synergistic effects of policies, combining the actual conditions of central and local governments. For the effectiveness level of Policy X9, it is mainly composed of regulations with lower levels, and there should be an emphasis on improving the effectiveness level of the policies. From the analysis of individual policies, P2, P3, and P5 are all rated as excellent, while P4 and P1 are rated as good. The average score is in the excellent range, which overall effectively meets the current needs of China’s technological financial development. The PMC index rankings decrease in the following order: P2 > P5 > P3 > P4 > P1. Policy P2 has the highest index with a score of 7.32, indicating the best implementation effect. Only X1 scored below the average, but since the "14th Five-Year Plan" itself is a short to medium-term policy, P2 is considered to be of a particularly excellent level. Policy P5 has an index of 7.03, which is relatively high, but the score for X4 is below average, indicating a need to strengthen the construction of the talent cultivation system. Policy P3 has an index score of 6.04, which is moderate, but scores below the average in aspects X2, X3, X4, X5, and X7, requiring a focus on enhancing the predictive, advisory, and regulatory functions of the policy, and addressing issues in policy content and areas such as knowledge, financial services, and corporate property rights. Policy P4 scored 5.87, which is a good level, but except for X6 and X8, all other items scored below the average. It is suggested to strengthen long-term planning in terms of timeliness, to consider both macro and micro perspectives in terms of the target, and to integrate talent and industrial resources in policy content. Policy P1 scored 5.03, which is relatively low. It performs well in X2, X4, and X8, but scores low in other areas. It is believed that there should be a focus on the coordination between policy and the development of time, and areas such as the target, domain, and content urgently need to be improved. The detailed analysis of individual policy items shows: Policy 1 is an opinion on market-oriented element allocation, which is primarily reflected in the comprehensive coverage of policy areas (X4:1~X4:5). However, there is a lack of expression regarding the Ministry of Finance, the central bank, and financial institutions (X8:2~X8:4) marked as 0, which may be because the policy-making department does not belong to these financial sectors. The policy is issued by the State Council and is highly directive; legal, administrative regulations, and departmental rules (X9:1~X9:3) are not involved and marked as 0. Other sub-items are at a medium level, with an overall score of 5.03, on the edge of good. Policy 2 is the "14th Five-Year Plan and Long-Term Objectives," mainly reflected in the lack of involvement of financial and fiscal departments (X8:2~X8:4) marked as 0. Almost all other sub-items of the policy are involved, reflecting the comprehensiveness and foresight of the planning objectives, with an evaluation score of 7.32, which is rated as excellent. Policy 3 focuses on the construction of the marketization system, with missing items in the advisory significance (X2:2) and the descriptive meaning of financial technology (X2:5); knowledge content (X3:3); service content (X3:4) not involved and marked as 0; financial policies not targeting banks (X5:2) and enterprises (X5:3) marked as 0; policies still do not involve financial and fiscal departments (X8:2~X8:4) marked as 0. Other sub-items scored high, with an overall policy score of 6.04, on the edge of excellent. Policy 4 is a special plan for financial technology, with missing options in policy identification (X2:3), descriptive meaning (X2:5), property rights content (X3:6), and market requirements (X4:4); no measures for banks (X5:2) and the government (X5:3); lack of clear interpretation in the sufficiency of policy basis (X7:3); the policy formulation does not include the State Council (X8:1), the Ministry of Finance (X8:2), or other financial departments (X8:4) marked as 0. The document is only a normative file with a score of 5.87, in the good range. The national unified large market document does not involve policy identifiability (X2:3), talent elements (X4:3), bank specificity (X5:2), and laws, administrative regulations, and departmental rules (X9:1~X9:3) marked as 0. Other sub-items of the policy are highly directive with high scores. Issued and implemented by the State Council to accelerate the domestic and international dual circulation and build an element circulation system, including guidance on science and technology finance policies, it covers a wide range and has strong directivity with a high evaluation score of 7.03, rated as excellent. The emergence of technology finance originally stemmed from the national demand for planning and construction of scientific and technological innovation. From the perspective of building an innovative country, the government has, in accordance with the needs of different stages, systematically matched different financial systems with a focus on priority and sequence, committed to achieving the deep integration of financial empowerment of technology and technology finance. A series of policy documents have been formulated to guide the work in various provinces (cities), achieving some results. Through the analysis of 16 documents, we extracted 9 primary variables and 34 secondary variables. Then, we randomly selected 5 national-level texts for evaluation using the PMC-AE model index, which provides a useful reference for assessing the effectiveness of China’s policies on financial innovation in technology. This will promote the improvement of a multi-level technological financial service system and strive to provide strong financial support for the accelerated construction of a modern industrial system. In the course of our research, we found that China’s policies on financial innovation in technology have played a good guiding role in the specific implementation process. Evaluating five policies, three were rated as excellent and two as good, indicating that the policies were comprehensive and consistent in their effects. In fact, the different combinations of technology finance policies reflect the scientific nature of these policies. The objectives, target subjects, policy content, target goals, and policy system of the policy are clear and have played a significant role in guiding China’s economic development, social progress, and the development of small, medium, and micro enterprises, as well as the financial and technological sectors. China has set the strategic goal of building an innovative country at the national level, elevating scientific and technological innovation to a national strategic status. It emphasizes the need to guide financial institutions to further optimize products, markets, and service systems according to the different needs of technology enterprises at different development stages, providing a more favorable environment for scientific and technological innovation and a platform for orderly competition in the financial industry. With the successive introduction of science and technology finance policies, the guiding effect of the policies has gradually become apparent. According to data from the People’s Bank of China, by the end of June 2023, the balance of medium and long-term loans in China’s high-tech manufacturing industry reached 2.5 trillion yuan, and the balance of loans for technology-based SMEs was 2.36 trillion yuan. The dividends of policy guidance have gradually emerged, stimulating new momentum for economic growth and achieving a virtuous cycle of finance in the technology industry. Our policy document research shows that X2 (nature of policy), X3 (content of policy), and X6 (target subjects) scored relatively high [ 53 , 57 ], covering a wide range of content. Overall, China’s policy combination is basically consistent with the model of technological finance innovation and development found in existing research. Science and technology financial innovation policies are generally aimed at cutting-edge technology innovation projects, which often involve large investments, long cycles, high risk, and significant uncertainty in research and development outcomes. The intrinsic value of technology companies is more reflected in the intangible assets formed by innovation. The development of technology finance urgently needs to strengthen the overall planning and policy coordination at the national level, balance the mechanisms for sharing benefits of innovation across different regions, and require regulatory authorities to view and steadily promote the development of technology finance rationally and objectively, maintaining the sustainable development of the technology finance system. This study indicates that the policy samples scored low in X8 (publishing structure) and X9 (effectiveness level) [ 56 ], reflecting a lack of unified scheduling and guidance. Especially, financial institutions in the specific practice process should fully understand the national policy intentions and, under the premise of controllable financial risks, boldly attempt to form a combination of punches with science and technology financial innovation policies. This study also has some limitations: First, a high PMC-AE index value for a policy model indicates that the policy modeling research has considered a comprehensive set of variables with high consistency, and thus is superior. However, policy modeling is not the same as policy itself, so the appropriateness of transplanting the PMC index model method to policy evaluation is worth discussing. Second, in the target literature, there is ambiguity in the operability of some indicators’ design. For instance, the secondary indicators "finance, technology, market" under the primary indicator "policy content" overlap with the secondary indicators under the primary indicator "policy field" [ 53 ]. Despite different focuses in data mining, this can cause interference in the recognition by the autonomous learning module, affecting the accuracy of the evaluation. Third, this paper reviews the policies on technology finance since the 13th Five-Year Plan period, with fewer policies related to the 14th Five-Year Plan period being considered, which may lead to an incomplete analysis of technology finance policies. The use of the PMC model only considers single indicators, lacking a comprehensive grasp and precise quantification of policies. We attempt to address these issues in future similar research by seeking other more advanced methods to avoid deficiencies in research methodology and data processing. Research findings and insights Research conclusions. The policy of innovation in science and technology finance is an important document guiding the development of China’s economy, and the evaluation of the guiding effectiveness of policy texts is particularly urgent. To achieve this goal, based on 16 representative policy texts on technology finance issued by China’s central authorities from 2015 to 2022, we used text analysis and content analysis methods to extract keyword frequencies, constructed 9 primary variables and 34 secondary variables, and then, for the first time, built the PMC-AE index model for technology finance policy. We randomly selected 5 of the most recently published important policy texts on technology finance for quantitative evaluation. The study shows that from an overall analysis, Policy 1 and Policy 4 are at a good level, while the remaining 3 are at an excellent level. Looking at the policies in detail, there are issues such as unclear legal boundaries of policies, a lack of professional talent in technology finance, weak service consciousness, and the need for stronger financial regulation, with market elements not being clearly defined. Through text analysis, we gained a deeper understanding of the inadequacies in the textual expression of China’s policies on innovation in technology finance. The research results can provide valuable insights for policymakers, help to improve related policies, form sustainable policy guidance texts, and assist in making policy texts more targeted in guiding China’s financial market and rapid economic development. Moreover, as China is in a stage of rapid development, the completeness of policies is conducive to the orderly development of the national economy. This study mainly focuses on the policy texts on innovation in technology finance, revealing the strengths and weaknesses of the policies, which have good guiding effectiveness. The practical results are also consistent with policy evaluation. In the future, national or local governments will also introduce related policies, such as new productive forces, the Internet, AI technology, and other economic entities. Our research can provide references for them and can also be used to evaluate policy texts. Policy insights First, strengthen the construction of the science and technology finance talent system (Policy P5’s score for X4 is below average, which requires strengthening the talent training system). (1) Conduct thorough research on the current implementation of science and technology finance, establish the demand for science and technology finance talent over the next ten years, the employment scenarios for science and technology finance talent, integrate science and technology finance talent into various levels of employers, form a tiered talent scale, guide science and technology finance talent to continuously recharge and learn, master high-tech financial auxiliary facility skills, adapt well to the organic combination of traditional models and Internet+, establish a long-term mechanism, so that financial technology talent can better serve society and improve the efficiency of financial technology policy implementation; (2) Strengthen incentives for science and technology talent, guide employers at the national level to introduce specific measures to incentivize financial technology talent, adopt flexible, attractive, and challenging policy measures to encourage financial technology talent to stay, and equip a series of auxiliary incentive models such as: settlement issues in major cities like Beijing, Shanghai, Guangzhou, and Shenzhen, housing subsidies, salary rewards, etc., insist on implementation, and establish a more comprehensive talent incentive and protection policy. Second, improve the level of financial services (Policy X2 needs further strengthening in terms of identification and description functions). (1) Policy formulation needs to clearly define the target audience, in response to the current difficulties and high costs of financing for small and medium-sized technology enterprises, introduce a more specific science and technology finance policy system to enhance the feasibility and identifiability of the policy; (2) Fully utilize technological means to aid the efficiency of financial services, increase the empowerment of payment services by technology, explore multi-channel identity verification based on cross-industry data resources, enhance the efficiency of financial service customer identification, and leverage the customer aggregation effect; (3) Enhance the inclusiveness of science and technology finance for the benefit of the people’s livelihood, use different scenarios for publicity, promote the functions and applicable methods of science and technology finance, penetrate customer groups, popularize the convenient functions of science and technology finance, not only play the advantages of the Internet in enterprises and groups but also increase the experience functions in the vast grassroots social groups, empowering every aspect of people’s lives. Third, improve the coordination between central and local financial policies (There are few issuing institutions in aspect X8). (1) Among the existing policy measures, those with guidance are concentrated at the national level and cover a wide range of content. However, the technology finance field is broad, and there are relatively few instructive and operational documents from various ministries and commissions, leading to a lack of guidance at both macro and micro levels, or in interpretative documents. It is necessary to improve communication between ministries and related functional departments and to formulate practical guiding documents, such as the financial department issuing documents on loans, interest subsidies, tax subsidies, and tax reductions for technology finance enterprises to enhance the practicality of the documents; (2) The current technology finance policies do not provide strong support for local enterprises, small and medium-sized enterprises, and private enterprises. It is necessary to conduct serious research and fully utilize financial derivative tools such as guarantees and trusts to ensure advanced technical means, secure funding, and controlled risks. Financial technology policies should serve the local economy well, strengthening the consistency and coordination between central and local financial policies. Fourth, strengthen the enforcement of policies protecting intellectual property rights in technology finance (There is a slight lack in the area of knowledge and property rights in policy content X3). (1) Fully utilize market regulation, industrial and commercial, and technical investigative methods for joint enforcement, to punish in a timely manner the false information and methods in technology finance that violate regulations and disrupt the good order of technology finance, maintain the national economic order, define the boundaries of intellectual property rights, build a full-chain intellectual property financial service system, and create an environment that respects intellectual property rights; (2) Increase the punishment for illegal activities in technology finance that have caused significant economic losses, using judicial procedures to compensate first and stop losses in a timely manner. Fifth, increase the intensity of financial regulation (Policy P3 scores below average in aspects X2, X3, X4, X5, and X7, and needs to focus on strengthening the policy’s predictive, advisory, and regulatory functions). (1) Financial departments should establish market supervision institutions to inspect the implementation of technology finance operations, prepare pre-emptive plans, regularly publish inspection results, grade and rate them, and award credit ratings during the operation of technology finance, advocating for departments and individuals to maintain the order of technology finance operations; (2) Improve the regulatory function system of technology finance, use existing technological means and the authority of big data information to uncover covert illegal activities, enhance full-process regulatory capabilities, and form a joint supervision system with consistent information sharing and coordination between financial departments and law enforcement agencies; (3) Each department should form work reports for routine and emergent events, propose constructive suggestions, and submit them to the financial department to establish basic and general applicable requirements. 1. 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Visit our dedicated information section to learn more about MDPI. JSmol Viewer Case study of the impact of new brazilian legislation in the year 2023 on the economic feasibility of photovoltaic microgeneration: homes in the city of fortaleza. 1. Introduction 2. growth of solar energy in brazil, 3. specific incentives for dmmg. “Art. 8. The rates of the Contribution to PIS/Pasep and the Contribution for the Financing of Social Security—COFINS, applicable to the active electrical energy supplied by the distributor to the consumer unit, are reduced to zero, corresponding to the sum of the active electrical energy injected into the distribution network by the same consumer unit with the active energy credits originated in the same consumer unit in the same month, in previous months, or in another consumer unit under the same ownership, according to the Net Metering System for microgeneration and distributed mini generation, as regulated by the National Electric Energy Agency—ANEEL.” ( translated from Portuguese ) “[…] on the electrical energy supplied by the distributor to the consumer unit, in the amount corresponding to the sum of the electrical energy injected into the distribution network by the same consumer unit with the active energy credits originated in the same consumer unit in the same month, in previous months, or in another consumer unit under the same ownership, according to the Net Metering System established by Regulatory Resolution No. 482, dated April 17, 2012.” ( translated from Portuguese ) 4. Distributed Microgeneration and Mini-Generation (DMMG) in Brazil: What Has Changed Since 2023 5. methodology, 5.1. study site mapping, 5.2. generation of photovoltaic plants, 5.3. economic viability, 5.3.1. payback method, 5.3.2. net present value (npv). NPV = net present value ATn = after-tax cash flow in year n i = attractiveness rate n = project life in years x = total analysis period in years 5.3.3. Internal Rate of Return (IRR) NPV = Net present value (R $ ) I 0 = Investment (R $ ) F t = Cash flow in the period (R $ ) n = Generator lifetime (years) IRR = Internal rate of return (% per year) 5.4. Sensitivity Analysis 6.1. variation of ±0.5% of the interest rate per month of the financing, 6.2. reduction of the financing period to 3 years, 6.3. variation of ±7% in the annual tariff adjustment, 7. discussion, 8. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest. 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Click here to enlarge figure Energy Energy Transport Transport Itaipu Basic Network Itaipu Losses Captive Market Basic Network Charges FCUWR—Financial Compensation for the Utilization of Water Resources SSC/REC—System Service Charge/Reserve Energy Charge R&D/EE—Research and Development/Energy Efficiency Energy Development Account (EDA) Transport High Voltage Wire (FIO A) Low Voltage Wire (FIO B) Losses Techniques Non-technical BN/D Losses (Basic Network/Distribution) Unrecoverable revenues Charges ESSF—Electricity Services Supervision Fee ONS RD/EE—Research and Development/Energy Efficiency EDA—Energy Development Account PROINFA Federal PIS/Pasep and COFINS State ICMS Municipal CIP Starting from Year TUSD [%] 2023 15 2024 30 2025 45 2026 60 2027 75 2028 90 2029 100 Topic Before Law No. 14.300/2022 From Law No. 14.300/2022 and ANEEL Resolution No. 1.059/2023 Installed power Distributed generation: greater than 75 kW and less than or equal to 5 MW and utilizing qualified cogeneration or renewable sources of electric energy. Article 2, XXIX-B [ ] Distributed generation: having installed power in alternating current greater than 75 kW and less than or equal to: (a) 5 MW for dispatchable source generating plants. (b) 3 MW for other sources not classified as dispatchable source generating plants; or. (c) 5 MW for consumer units already connected on January 7, 2022, or that submit a connection request for quotation […], until 7 January 2023, regardless of the classification as dispatchable source generating plants. Net Metering System (SCEE) [ ] Full compensation of all components linked to TUSD. Some components are no longer compensated on a staggered and gradual basis. Compensation modalities [ ] Shared Generation: “[…] characterized by the gathering of consumers within the same concession or permission area, through a consortium or cooperative, composed of individuals or legal entities, who have a consumer unit with microgeneration or distributed mini generation in a location different from the consumer units where the surplus energy will be compensated.” Article 2, XXII-A [ ] Shared Generation: “[…] characterized by the gathering of consumers, through a consortium, cooperative, voluntary civil condominium or building, or any other form of civil association established for this purpose, composed of individuals or legal entities that own a consumer unit with microgeneration or distributed mini generation.” Availability cost [ ] In practice, charged doubly It ceases to be charged doubly and the new rule applies Procurement of ancillary services [ ] Not covered Article 23 [ ] Allows distributors, through a public call, to contract DMMG for ancillary services. Exclusively by the distributor, in case of non-adherence to public calls. [ , ] Prohibited Article 24 [ ] Possible through a public call by the distributor. “The electricity distribution concessionaire or permittee must promote public calls for the accreditation of interested parties to commercialize the surplus of power generation from de projects of micro-generators and mini generators distributed, in their concession areas, for the subsequent purchase of these surplus energies, in the form of regulation by ANEEL.” Hybrid systems and storage [ ] Not covered by legal provisions There is legal provision for such systems. Valuation of Distributed Generation Benefits [ ] There is none. There is provision for valuing the benefits of GD, and possibly consumer–generators will have some benefits. Opinion on access [ ] Allowed for commercialization, although the practice is not encouraged. Article 6 [ ] Prohibited the commercialization of access opinions. Transfer of CU ownership [ ] Allowed at any time, starting from the signing of the CUSD and the CCER. Article 5 [ ] Allowed after the request for inspection of the connection point to the distributor. Performance Bond (PB) [ ] No need to provide guarantees Article 4 [ ] Projects exceeding 500 kW and less than 1000 kW, GFC of 2.5% of the connection budget, and with 1000 kW or more, 5% of the budget. The GFC is refundable. Shared generation and EMUC modalities do not require PB. B option [ ] Not allowed to be a B option with mini-generation. Article 292, § 3 [ ] Allows a local self-consumption mode using transformers with power up to 112.5 kVA. Incentive for low-income consumers [ , ] Nonexistent Art. 36 [ ] Foresees the Social Renewable Energy Program (PERS) aimed at consumers in the low-income residential subclass. Environmental and social attributes [ ] Not valued Art. 28 [ ] It is expected that valuation will occur and that consumer–generators will have some benefit. Plant 1 Plant 2 Price R$20,000.00 R$26,000.00 Local Fortaleza-Ce Fortaleza-Ce Number of modules 12 10 Module power (Wp) 330 550 Qty. of inverters 3 3 Brand of inverters Hoymiles Deye Rated power (kW) 3.6 4.8 Peak power (kWp) 3.96 5.5 Estimated monthly generation (kWh) 518 722 Plant 1 Plant 2 +0.5% −0.5% +0.5% −0.5% 8 years and 4 months 6 years and 6 months 7 years and 6 months 5 years and 10 months 28.59% 41.86% 32.95% 51.93% 149,538.97 159,706.66 227,504.28 240,722.28 11 years and 9 months 9 years and 3 months 9 years and 5 months 7 years and 4 months 18.88% 25.08% 24.55% 34.15% 83,065.77 93,233.46 160,206.62 173,424.62 9 years and 4 months 7 years and 3 months 8 years and 4 months 6 years and 5 months 25.11% 34.95% 28.92% 42.34% 130,640.98 140,808.68 202,349.11 215,567.10 Plant 1 Plant 2 6 years and 6 months 5 years and 10 months 33.01% 37.72% 159,680.63 240,688.34 9 years and 3 months 7 years and 4 months 22.34% 28.59% 93,207.44 173,390.67 7 years and 3 months 6 years and 5 months 29.14% 33.32% 140,782.65 215,533.16 In Cash Financing +7% −7% +7% −7% 4 years and 4 months 5 years and 6 months 6 years and 5 months 9 years and 4 months 38.03% 24.20% 45.82% 21.72% 476,971.06 61,008.59 463,655.10 47,692.62 6 years and 1 month 8 years and 7 months 8 years and 7 months 14 years and 11 months 30.13% 16.52% 31.16% 11.90% 301,194.37 32,356.17 287,878.41 19,040.21 4 years and 10 months 6 years and 3 months 7 years 10 years and 9 months 35.47% 21.56% 40.18% 18.02% 438,861.72 51,341.62 425,545.76 38,025.65 In Cash Financing +7% −7% +7% −7% 3 years and 11 months 4 years and 10 months 5 years and 10 months 8 years and 2 months 40.89% 27.01% 53.48% 26.36% 707,599.23 93,580.08 690,288.42 76,269.27 4 years and 11 months 6 years and 5 months 7 years and 1 month 10 years and 11 months 35% 21.23% 39.37% 17.57% 529,645.39 64,572.29 512,331.58 47,261.48 4 years and 4 months 5 years and 5 months 6 years and 4 months 9 years and 3 months 38.29% 24.36% 46.3% 21.98% 656,759.02 80,726.79 639,448.21 63,415.99 The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. Share and Cite Lima Porfirio de Sousa, B.; Lopes, F.; Jaramillo Loayza, D.M.; Yepes Maya, D.M.; Garcia Pabon, J.J. Case Study of the Impact of New Brazilian Legislation in the Year 2023 on the Economic Feasibility of Photovoltaic Microgeneration: Homes in the City of Fortaleza. Energies 2024 , 17 , 3784. https://doi.org/10.3390/en17153784 Lima Porfirio de Sousa B, Lopes F, Jaramillo Loayza DM, Yepes Maya DM, Garcia Pabon JJ. Case Study of the Impact of New Brazilian Legislation in the Year 2023 on the Economic Feasibility of Photovoltaic Microgeneration: Homes in the City of Fortaleza. Energies . 2024; 17(15):3784. https://doi.org/10.3390/en17153784 Lima Porfirio de Sousa, Brunna, Flávia Lopes, David Mickely Jaramillo Loayza, Diego Mauricio Yepes Maya, and Juan Jose Garcia Pabon. 2024. "Case Study of the Impact of New Brazilian Legislation in the Year 2023 on the Economic Feasibility of Photovoltaic Microgeneration: Homes in the City of Fortaleza" Energies 17, no. 15: 3784. https://doi.org/10.3390/en17153784 Article Metrics Article access statistics, further information, mdpi initiatives, follow mdpi. Subscribe to receive issue release notifications and newsletters from MDPI journals 143 IMAGES CASE Study Economic laws Case Study Index Nov 2022 Economics guide Class 12 Economics Economics and Quantitative Analysis Case Study 2022 CASE Study 1 VIDEO APPLIED ECONOMICS AS Economics Case Study Specimen 2023 new paper pattern case study March 2024 AS Economics Paper 2 case study solved 9708 #Class 11 #Micro Economics #Case Study #Assertion Reason #NCERT #CBSE #MCQs Chapter Crypto ETFs Explained : A Simpler Approach To Investing! 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