It is the first study to look holistically at the impact of crossing an important high-stakes threshold on both academic and vocational education choices and ultimately labor market outcomes. It does so by comparing those on either side of a formerly important threshold in the English education system at the end of compulsory schooling (achieving five general certificate of secondary education A* to C passes), which was commonly regarded as the minimum benchmark for continuing into postcompulsory education.

I find that crossing this threshold led to a 6.3–6.7 percentage point increase in the proportion of men and women (respectively) going on to take academic qualifications, with little change in the proportion taking vocational qualifications, leading to a net increase in those staying on after compulsory schooling.

Women's daily earnings in 2017-18 (11-13 years after leaving compulsory schooling) were 3.1 percentage points higher for those just crossing the threshold, but men's early labor market outcomes were unchanged. The results for men can be explained by low returns to academic qualifications for marginal learners. The findings for women do not disappear after accounting for subsequent education choices, suggesting that crossing the threshold may play a signaling role for employers and education institutions.

However, when it comes to assessing their descendants' overeducation, evidence is remarkably scarce. Therefore, using granular employer–employee data for Belgium over the period 1999-2016 and generalized ordered logit regressions, we investigate the intergenerational relationship between overeducation and origin among tertiary-educated workers. We find that immigrant overeducation disappears across two generations, except for workers originating from the Maghreb. However, immigrant overeducation appears to be a persistent intergenerational issue within the cohort of parttime female and male workers.

In this presentation, I explore whether ties with origin countries, in terms of remittances, matter for the educational attainment of immigrant children. I focus on immigrant families living in Germany from 1984 to 2016, building on an individual-level panel dataset, the German Socio-Economic-Panel (GSOEP). I rely on two supporting identification strategies that exploit within-family variation and origin-country factors to identify the causal effect of remittances on secondary track school choice. I find that migrant remittances have an adverse effect on schooling, particularly by increasing the probability that children attend lower secondary schooling level. This suggests that remittances made during critical childhood ages are decisive in the children's subsequent educational attainment. The results prompt additional considerations about the effects of remittances.

Mexico, a megadiverse country with approximately 65 million hectares of forested area, has lost five million hectares of forest, and illegal logging is one of the key drivers of deforestation. The involvement of drug trafficking organizations in deforestation, coined as "Narco deforestation", is increasing in Central America and Mexico (McSweeney et al. 2014). The illegal logging activities in Jalisco and Michoacan states are controlled by cartels, and state authorities either stay passive or are not able to stop these illegal activities (Garcia-Jimenez and Vargas-Rodriguez 2021). The timber industry can be attractive for cartels as a means of diversifying their income and compensating for losses related to decreasing poppy cannabis prices.

This study uses heroin demand shocks in the United States to detect changes in cartel behavior. The findings suggest that lower levels of deforestation are observed in deciduous forests, which are less valuable for timber production, following decreasing poppy prices. In contrast, opposite results are observed in coniferous forests, which are the main timber supply for round wood production in Mexico, when a municipality has cartel presence. In other areas, deforestation levels remain stable or decrease following poppy demand shocks.

The results imply that cartels cope with income loss through illegal logging. The identification strategy is based on comparing poppy and cannabis-suitable municipalities, with the former impacted by U.S. heroin demand shocks and the latter not (Daniele et al. 2023). The presentation concludes that the U.S. heroin market significantly affects deforestation through Mexican cartels' adaptation strategies. The study highlights the importance of considering the indirect effects of drug demand on the deforestation.

The study utilizes a newly-built unique dataset of georeferenced crime reports from 14 major American cities matched with census data to identify gentrified areas in the 2010s. To causally evaluate the impact of gentrification on crime, I adopt state-of-the-art event-study models to causally evaluate the effects of gentrification, taking into account variations in the timing of this process across different cities and neighborhoods. The analysis reveals that gentrified areas experienced a statistically significant increase in crime ranging from 11% to 17%. The findings suggest that gentrification has a negative impact on neighborhoods, with property crimes showing the most significant increases. Overall, the study suggests that gentrification may have a criminogenic effect on neighborhoods, highlighting the need for further research and policy attention to this issue.

We focus our investigation first at daily level and secondly at monthly level. At daily level, we utilize autoregressive conditional heteroskedasticity (ARCH) estimation to factor in the deeply autoregressive nature of daily nightlights, to identify immediate (within-day) effects from hartals, individually for key subdistricts. At the monthly level, to factor in the emergent consequent spatial dependence, we analyze countrywide dynamics using a split-panel jackknife bias-corrected maximum-likelihood estimations to see overall effects from lagged hartal event counts. At daily level, over 2012–21, in the capital Dhaka, we find that daily hartals have an immediate statistically significant impact of -0.9 percent on daily nightlights. However, this effect does not hold across all subdistricts and only does so for a select number of subdistricts. At the monthly level, we find evidence of statistically significant countrywide effects of 1.6 percent.

We want the effect of a treatment on an outcome. When studying causal questions with repeated cross-sections or panel data, it is common for treatment timing to differ across groups. When this occurs, treatment effects may be heterogeneous across groups and time. Failing to account for effect heterogeneity will lead to inconsistent estimates. We show how to use heterogeneous difference in differences to estimate, visualize, infer, and aggregate heterogeneous treatment effects.

Do worries triggered by such topics affect the cognitive capacities of the youth? In an online experiment during the COVID-19 pandemic (N=1503), we test how the cognitive performance of university students responds when exposed to topics discussing current mental health issues related to social restrictions or future labor market uncertainties linked to the economic contraction. Moreover, we study how such response is affected by a performance goal. We find that the labor market topic increases cognitive performance when the latter is motivated by a goal. The positive reaction is mainly concentrated among students with larger financial and social resources, which points to an inequality-widening mechanism. Conversely, we find no effect after the mental health topic. We even find a weak negative response among those mentally vulnerable when payout is not conditioned on reaching a goal.

Using a regression discontinuity research design, we find that eligible household heads surveyed just after the disbursement of an unconditional cash transfer in Indonesia report a 0.3 standard-deviation improvement in sleep quality as compared with those surveyed just before the cash disbursement. The cash transfer appears to have alleviated financial concerns amongst household heads, who are responsible for satisfying the daily necessities of the household. Immediately after disbursement, eligible households report an increase in savings, and eligible household heads report feeling less worried, frustrated, and tired. Consistent with evidence from sleep medicine, eligible household heads displayed improved performance on memory and attention tests but not on reasoning or problem-solving tests. These patterns of results are not observed for household heads ineligible for the cash transfer, which suggests that our results are not driven by seasonal confounders or aggregate shocks. These results are also not observed for other members of eligible households, who are not responsible for satisfying the households' financial needs. We also argue that nutrition, time in bed, and labor supply cannot explain our results.

Despite the hype of this market, there is a substantial lack of information on consumers' attitudes and motivations toward light cannabis products. We conducted an ad-hoc online survey to investigate the characteristics of French and Italian users, focusing on smoking as the main mode of consumption. Logistic regressions are performed to explain the factors associated to light cannabis use as a substitution for any drug or for a specific substance. Our results indicate that one out of five current light cannabis users use it as a substitute (self-replacement therapy) for other substances. The reduction in substance use is more prevalent for regular cannabis, tobacco, and medications than for alcohol use. However, the use of light cannabis seems to facilitate alcohol consumption reduction, mostly among males with low income. Whereas sublingual oils are more likely to be used to substitute medications, smoking is the favorite means of substitution for tobacco and regular cannabis. Overall, the motivations behind consumption determine differential preferences across light cannabis users. This calls for a rethinking of the most adequate distribution channels for specific products based on the purpose of use. The goal should be to maximize the substitution with other addictive substances by providing a differential degree of quality and taxation across supply channels based on the expected harm.

In this presentation, both linear and quadratic equations are estimated to explore a comprehensive relationship between migrant share and native workers' wages in a city. My findings are twofold. In the ordinary least-squares regression model, every 10% increase in immigrants would lead to a 5.67% decrease in local labor wages. However, in the nonlinear model a turning point is observed. The average wage level decreases when the migrant share is lower than 27.82%, while increases with the migrant share larger than 27.82% are complementary, by IV regression.

One of the most significant policy changes, the Johnson-Reed Act of 1924, drastically limited the number of new immigrants per year, especially from Asia. In combination with the Emergency Quota Act of 1921, immigration per country was capped at 2 percent of the respective population in the 1890 census. In this presentation, I examine to what extent exemptions from immigration restrictions affected relative labor market outcomes of prior migration cohorts. Using decennial census data, I apply a difference-in-differences estimation, considering that restrictions initially did not apply to the Philippines, then a U.S. territory. My findings indicate that initial immigration restrictions impacted Filipinos, who were exempt from the policy, more severely, highlighting the impact of competition on their economic assimilation. In comparison with other migrants, relative log occupational income scores of Filipinos declined, while their labor force participation and employment status increased. These findings corroborate previous studies that emphasize the relevance of substitutability within and the vulnerability across immigrant cohorts. The effects are particularly strong for the year of 1930 and in California, which coincides with the timing of immigration policies and Filipinos' main destination. Individual panel-data analysis partially supports the findings in the cross-sectional evaluation.

In this presentation, we empirically assess the connection between ancestral diversity and the performance of sport teams. Focusing on football (soccer), we built a novel dataset of national teams of European countries having participated in the European and the World Championships since 1970. Ancestral diversity of national teams is based on augmenting the diversity index with genetic distance information on every player's origins in the team. Origins for each player are recovered using a matching algorithm based on family names. Performance is measured at the match level. Identification of the causal link relies on an instrumental-variable strategy based on past immigration at the country level about one generation before. Our findings indicate a positive causal link between ancestral diversity and teams' performance. We find that a one-standard increase in diversity can lead to ranking changes of two to three positions after each stage of a championship.

An estimator based on iterated principal component analysis is proposed, which is shown to be not only asymptotically normal but also under certain conditions free of the otherwise so common asymptotic incidental parameters bias. Interestingly, the conditions required to achieve unbiasedness become weaker the stronger the trends in the factors, and if the trending is strong enough, unbiasedness comes at no cost at all. The approach does not require any knowledge of how many factors there are or whether they are deterministic or stochastic. The order of integration of the factors is also treated as unknown, as is the order of integration of the regressors, which means that there is no need to pretest for unit roots or to decide on which deterministic terms to include in the model.

Nevertheless, there have been only a limited number of studies confirming the relevance of these factors for labor market outcomes. This presentation assesses the role of gender-specific preferences in the reservation wage gap during the job search. I use French administrative data from the unemployment insurance agency providing information on job search behavior and previous outcomes to assess which kind of occupations men and women apply for and the gap in their reservation wages. Employing text analysis, I build a novel dataset classifying occupations with respect to a number of characteristics and examine to which extent men and women differ in the occupation they are looking for. I document widespread gender differences in the occupation characteristics targeted by job seekers. Quantile decomposition methods allow me to document an unequal gap in reservation wage, intensifying along the distribution. After I adjust for occupation characteristics reflecting gender-biased preferences and household constraints, the unexplained part of the reservation wage gap is decreased by half. Investigating unemployment history and outcomes from previous interviews with firms, I do not find evidence of a female risk aversion to previous unemployment shocks or male overconfidence.

To tackle the endogeneity issue, we exploit the 2010 reform that introduced financial penalties for firms with 50 employees or more not complying with their obligation of negotiating on gender equality. This change led to a strong acceleration of gender equality bargaining after 2010 but only for firms with 50 employees or more. Thus, women who had their first child in concerned firms after 2010 are more likely to be employed in firms covered by a text related to gender equality. Controlling for firms' size effect and time trends as well as a set of other individuals' and firms' characteristics, we identify the causal effect of gender equality bargaining on earnings impact of motherhood. Our estimates show that forcing firms to promote measures related to gender equality has reinforced the motherhood penalty. While the causal effect of this reform is close to zero just after the first child's birth, it turns out to be significantly negative five years after. Our results suggest that some measures mentioned in texts related to gender equality, especially those favoring work–life balance, may act as an indirect discrimination towards mothers.

We use fine-grained longitudinal personnel data on workers from an Italian insurance company over the period 2014–2021 and assign to each worker the gender of the direct supervisor. We implement an individual worker's fixed-effect model, together with a dichotomous variable that captures pre- and post- COVID-19 period and time-varying individual characteristics. Our findings show that, although both male and female managers evaluate similarly the performance of male and female workers, female supervisors grant-lower amount of one-off bonus than male managers to both male and female workers. Moreover, both male and female workers have a lower probability of receiving a promotion from an employee of level VI to middle-managers when the manager is a female.s When exploiting a heterogeneous analysis by gender, results confirm that the gender of the supervisors does not affect workers' performance assessments, while it negatively impacts the total amount of bonus of both male and female workers. We interpret these results as evidence either that female managers are more severe to conform to a masculine gender stereotype associated with a leadership position that female managers are at the head of marginal areas and offices and hence receive less funds to provide bonuses and promotions to workers they supervise.

In an era of high financial integration, we investigate the relationship between the real exchange rate and international reserves using nonlinear regressions and panel threshold regressions over 110 countries from 2001 to 2020. We capture the buffer effect of international reserves, which is more pronounced in Europe and Central Asia, above a threshold of 17%. Unlike previous literature, our study shows how financial institution development plays an essential role in explaining the buffer effect of international reserves. Countries with low-developed financial institutions may use the international reserves as a shield to deal with the negative consequences of terms-of-trade shocks on the real exchange rate. We also found that the buffer effect is stronger in countries with intermediate levels of financial openness.

Originally conceived as a policy to regulate the foreign control of sensitive industries for national security reasons, ISMs have proliferated across broader sectors of national economies. We formally analyze the sectoral-level choice of ISM adoption in a model that emphasizes norms within networks of international relations as the driving force behind the diffusion of ISMs. We argue that as leading economies adopt ISMs across sectors of the economy, the cost of violating norms of economic openness decreases for the other networked economies, and ISM adoption spreads. We then empirically scrutinize the role of network effects using a unique country-sector-level panel data set on ISM adoption. Examining a broad variety of network linkages—bilateral trade relations, membership in the EU, geographic and political distances, and linkages to the world's major economic powers—we conclude that network effects explain ISM adoption and that economic linkages are more important than political linkages.

We find that having a financially literate colleague improves the borrowing decision of financially less literate co-workers. The interest rate of the mortgage loan of these co-workers is significantly lower than similar employees at other companies who do not have such a colleague. The magnitude of the effect is economically significant, roughly one-fourth of the standard deviation of mortgage loan interest rates. Placebo and robustness tests verify our results. Roughly one-third of the effect is due to which bank is chosen by the borrower. The results are heterogeneous in the strength of competition among banks. In those districts where the competition is lower, the peer effect is considerably higher.

The literature has devoted substantial effort to devising methods that correct for this bias as a means to salvage standard inferential procedures. The chief purpose of this presentation is to show that the (recursive, parametric) bootstrap replicates the asymptotic distribution of the (uncorrected) maximum-likelihood estimator and of the likelihood-ratio statistic. This justifies the use of confidence sets and decision rules for hypothesis testing constructed via conventional bootstrap methods. No modification for the presence of bias needs to be made.

Regional cost-of-living indices are however not always available or may not be updated as regularly as national CPI series. We propose a simple approach for calculating regional cost-of-living deflators that do not require access to data on prices and that can be implemented directly from standard surveys on income and living conditions. To calculate the regional cost-of-living index, we apply methods proposed for the similar problem of estimating equivalence scale parameters: we use subjective satisfaction data to capture indirect utility and adopt nonparametric matching methods to construct regional cost-of-living indices. As an illustration, we construct price indices for Russian regions from the Russian Longitudinal Monitoring Survey for the period 2000–2015 and compare our cost-of-living deflators with those from the Statistical Office of Russia (available from 2009 only). Over the years, covered by both series, the indices correlate highly but not perfectly. Application of regional price indices does not appear to alter inequality trends but income levels.

Chinese SOEs are a heritage of the planned economic system, and their role in today's state capitalism is not clearly defined. Using a rich dataset of Chinese firms, we investigate the role played by SOEs in the Chinese industrial policy stated in the 10th 5-year plan. We find that the Chinese government has relied heavily on SOEs to achieve the objective of the 10th FYP. We also find evidence for spillover effects from SOEs' productivity and the private sector's productivity within the targeted industry. These results provide evidence that SOEs are a ”tool” of economic state-craft (as it was during Mao's era) for the Chinese government to implement its industrial policies.

According to this view, one limiting factor for ending open defecation lies in the capacity of the community for collective action: Each member of a community bears the private cost of contributing by washing hands and using latrines, but benefits through better health outcomes depend on whether other community members also opt out from open defecation. We rely on a community-based intervention carried out in Mali as an illustrative example (Community Led Total Sanitation or CLTS). Using a series of experiments conducted in 121 villages and designed to measure the willingness of community members to contribute to a local public good, we investigate the process of participation in a collective action problem setting. Our focus is on two types of activities: gathering of community members to encourage public discussion of the collective-action problem and facilitating the adoption of individual actions to attain the socially preferred outcome. When the facilitator starts by introducing a topic and a group discussion follows, can the facilitator further improve outcomes? Will a group discussion that follows facilitation improve, reduce, or have no effect on collective action? We find evidence that cheap talk raises public good provision and that facilitation by a community member does not improve upon open discussion.

As these potentially decrease trust in digital services, especially in developing countries, avoiding victimization has become an important policy objective. In an online experiment, we first investigate how well individuals in Kenya identify phone scams using a novel measure of scam identification ability. We then test the effectiveness of scam education, a commonly used approach by banks and institutions for fraud and scam prevention. We find that common tips on how to spot scams do not significantly improve individuals' scam identification ability, for example, the distinction of scams from genuine messages. This null effect is driven by an increase in correctly identified scams and a decrease in correctly identified genuine messages. We interpret this as an increase in caution. In addition, we find suggestive evidence that genuine messages that contain scamlike features are more likely to be misclassified, highlighting the importance of a careful design of official communication.

I use the hypothetico-deductive methodology, and faced with panel data, this study uses logistic regression models (fixed effect, random effect, and mixed effect), covering the period 2010–2019 for 20 WCA countries (West and Central Africa). To my knowledge, this study is among the first to explore the factors upstream of the deployment of local crowdfunding platforms, based on basic infrastructure, technological and communication innovation, education, the legal framework, and financial system. This research contributes to the current debate on the development of crowdfunding in sub-Saharan Africa as well as to the future models to be adopted so that this activity is sustainable at the local level.

The study points out that the infrastructure of information and communication technologies, based on the penetration of the Internet and mobile telephony, significantly influences the deployment of the national platform. Nevertheless, the basic infrastructure such as electricity and urbanization variables, a legal framework based on the business creation score, education, and the weakness of the financial development system constitute an obstacle to claiming development in long-term and sustainable local crowdfunding activities. Following these striking results, the study highlights a series of levers on which legislators in WCA countries can act to meet the crowdfunding challenges of tomorrow.

By proposing three research levels, this study should promote and support the development of crowdfunding from a pedagogical point of view by emphasizing entrepreneurship and emerging technologies in education at the level of professional or university training, from the infrastructure, access to physical and digital infrastructure by emphasizing the importance of regional partnerships, creating partnerships with traditional African banks, to prevent risks, build trust, and ensure the security of investments, decision makers must establish the law on alternative finance activities (crowdfunding, cryptocurrency).

Human capital theory asserts training is procyclical; firms reduce training expenditure amid economic downturns as future cash flows become increasingly uncertain, affecting labor demand dynamics. A conflicting strand of literature asserts that training provision is countercyclical. In recessions, the cost of labor inputs diminishes as labor markets become looser. Firms durably secure their future labor force at cheaper prices.

We execute multiway fixed-effects regressions applied to both Swiss survey and administrative data, using unemployment, and subsequently the Swiss KOF business situation indicator, as proxies for the business cycle. Unemployment is consistently negatively, however insignificantly, related to the supply of dual VET positions. On the other hand, the sign of the effect of the business situation indicator on the supply of dual VET positions varies, albeit in our sample, the business situation indicator does not significantly affect the supply of dual VET positions. We do not find evidence that the impact of the business cycle, as proxied by the aforementioned variables, on dual VET positions supply is significantly heterogenous between knowledge-intensive and nonknowledge-intensive business services sectors. The impact of the business situation indicator on the supply of dual VET positions is significantly more negative on the construction sector than in the manufacturing sector; however, this impact is not heterogeneous across other sectors.

I exploit the massive burst in the Spanish construction sector during the Great Recession. For identification, I leverage regional variation in the intensity of the employment decline among Spanish provinces and detailed longitudinal administrative data. The construction workers in heavily exposed provinces suffered a significant decline in total earnings between 2007 and 2012, consistent with the workers experiencing long periods of unemployment rather than wage cuts. I find evidence that the short-term labor market adjustment was intersectoral rather than interregional, even under asymmetric exposure. In order to understand the role of sectoral composition in an individual worker's response to the shock, I construct a reallocation index. This index captures the degree to which workers from the construction sector can reallocate into other sectors. Then, I examine how sectoral composition contributes to ameliorating the shock's impact. I provide evidence that workers' likelihood of changing sectors depends on having better outside opportunities in other sectors, which varies across provinces and workers' characteristics. Individuals with more evenly distributed characteristics across sectors were less affected by the shock because they were more likely to change sectors. This implies that, on average, workers are less likely to adapt to shocks when a region has a high level of sectoral concentration.

Using a variety of data sources, I evaluate the effects of increasing firing taxes across the United States on wages of high- and low-educated workers. In particular, I analyze how changes in the regulation of the employment-at-will across states affected the wages between 1970–1995. Application of quasiexperimental methods yields results suggesting a negative effect for low-educated workers and no significant effects for the highly educated. The standard search and matching model with endogenous search extended to account for two types of agents points as well to a negative effect of the firing costs on wages, with a more pronounced effect for low-educated workers.

With this aim, we analyze information about the population of all Spanish municipalities and flood events from 1877 to 2011. Using recent developments in difference-in-differences estimation methods, we find a negative and significant impact of floods on population in the long term when there are casualties involved. Therefore, and in line with the results of other types of shocks, we provide evidence that shocks related to natural disasters have a demographic transitory effect.

Duration models are used for modeling: hazard and survival functions are studied for giving birth to a second child. The empirical study is carried out on the microdata of the RLMS-HSE from 2000 to 2019, the regional data from Rosstat, and the data on the region's maternity capital programs amount by years from the open sources. We find that the indexation of the federal Maternity Capital program leads to a 2.1% increase in the hazard of a second birth; however, there was no indexation from 2015 until 2019. We also show that regional Maternity Capital programs affect the probability of a second birth, and the estimated value is two times bigger than for federal program, but regional government does not treat the programs with attention. The last important factor negatively affecting fertility is the economic recession of 2014. Results are robust to different metrics (proportional hazard and accelerated failure time), functional forms (parametric and nonparametric), and subsamples (married women and working women).

These laws made interracial marriages “prohibited and void”, making them a cornerstone policy of segregation. Exploiting variations in introduction and coverage, I study how these laws shaped family structures and reinforced differences in economic outcomes across racial groups. To do this, I combined information on state-level antimiscegenation laws with longitudinal data from U.S. censuses (1850–1940). This dataset allows me to follow more than 30 million men over time. My preliminary results suggest that the implementation of antimiscegenation laws changed the composition of marriages and increased out-of-state migration of individuals targeted by the laws, in particular, individuals in mixed marriages but also black men overall. Moreover, codifying race was a key necessity to enforce interracial marriage bans so that miscegenation laws included the blood purity rules. In line with this, I find that racial identity changes of initially black individuals, a nonnegligible phenomenon, declined when miscegenation laws were introduced. The laws also had an impact on keeping an exploitative agricultural economic model in place.