The Long-Run Labor-Market Consequences of Civil War: Evidence from the Shining Path in Peru

This study exploits district-level variation in the timing and intensity of civil war violence to investigate whether early-life exposure to civil wars affects labor-market outcomes later in life. In particular, we examine the impacts of armed conflict in Peru, a country that experienced the actions of a tenacious, brutally effective war machine, the Shining Path, between 1980 and 1995. This study finds that the most sensitive period to early-life exposure to civil war violence is the first 36 months of life. A one standard deviation increase in civil war exposure leads to a four percent fall in adult monthly earnings. Neither fetal, nor pre-school, periods significantly affect long-run earnings. Substantial heterogeneity in the earnings impacts emerge when considering variation in the types of civil war violence. Sexual violations disproportionally affected the wages of women, while torture and forced disappearances disproportionally affected the wages of men. Evidence on intervening pathways suggests that health rather than schooling is the most important channel in connecting early-life exposure to civil war and adult earnings

Household Wealth and Heterogeneous Impacts of a Market-Based Training Program: The Case of PROJOVEN in Peru

This paper analyzes the relationship between households' wealth and heterogeneous treatment impacts for a market-based training program that has benefited more than 40,000 disadvantaged individuals in Peru since 1996. We proxy long-run wealth by a linear index based on 21 households assets, and three main findings emerge. First, we find that voluntary choices among eligibles, rather than administrative choices, play a bigger role in explaining demographic disparities in program participation. Second, quantile treatment effects on the treated suggest important differences in program impacts at different quantiles of earnings, and strong differences in distributional impacts for men and women. Third, both parametric-based and semiparametric regression-matching estimates reveal that the poorest among the poor benefit the same from the program. It is the type of institution that provides the training services that largely accounts for the heterogeneity of the impacts.Training, program evaluation, factor analysis, poverty, quantiles, matching methods

Does the Quality of Training Programs Matter? Evidence from Bidding Processes Data

We estimate the effect of training quality on earnings using a Peruvian program, which targets disadvantaged youths. The identification of causal effects is possible because of two attractive features in the data. First, selection of training courses is based on public bidding processes that assign standardized scores to multiple proxies for quality. Second, the evaluation framework allows for the identification and comparison of individuals in treatment and comparison groups six, 12, and 18 months after the program. Using difference-indifferences kernel matching methods, we find that individuals attending high-quality training courses have higher average and marginal treatment impacts. External validity was assessed by using five different calls over a nine-year period

Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data

This paper addresses the selection of smoothing parameters for estimating the average treatment effect on the treated using matching methods. Because precise estimation of the expected counterfactual is particularly important in regions containing the mass of the treated units, we define and implement weighted cross-validation approaches that improve over conventional methods by considering the location of the treated units in the selection of the smoothing parameters. We also implement a locally varying bandwidth method that uses larger bandwidths in areas where the mass of the treated units is located. A Monte Carlo study compares our proposed methods to the conventional unweighted method and to a related method inspired by Bergemann et al. (2005). The Monte Carlo analysis indicates efficiency gains from all methods that take account of the location of the treated units. We also apply all five methods to bandwidth selection in the context of the data from LaLonde\u27s (1986) study of the performance of non-experimental estimators using the experimental data from the National Supported Work (NSW) Demonstration program as a benchmark. Overall, both the Monte Carlo analysis and the empirical application show feasible precision gains for the weighted cross-validation and the locally varying bandwidth approaches

The long-run labor-market consequences of civil war: Evidence from the shining path in peru

The article examines whether early life exposure to civil war in Peru affects labor-market earnings later in life, following the critical-period programming theory that highlights the role of early life circumstances in determining long-run economic outcomes The distinction between civil war and violence in civil wars has been largely overlooked in the microdata analysis of civil wars. Accounting for civil war violence has primarily been based on a single specific measure of violence that includes deaths and forced disappearances. The information on civil war measures comes from the Peruvian Truth and Reconciliation Commission, which collected a comprehensive data set based on the reconstruction of the civil war period. First, the most sensitive period to early life exposure to civil war violence is the first 36 months of life. A 1 standard deviation increase in early childhood exposure to violence leads to a 5% fall in adult monthly earnings, 3.5% reduction in the probability of working in formal jobs, and 6% reduction in the probability of working in large firms

Informality and Productivity in the Labor Market: Peru 1986 - 2001

Peru has one of the highest informality rates in Latin America, with almost 60 percent of the urban labor force working at the margins of labor market legislation or in microenterprises that lack basic labor market standards (Marcouiller, Ruiz de Castilla, and Woodruff, 1997). This paper identifies two factors that can explain the variation in informality rates in the 1990s. First, Peru experienced a steady increase in employment allocation in traditionally “informal” sectors—in particular, retail trade and transport. Second, there was a sharp increase in nonwage labor costs, despite a reduction in the average productivity of the economy. In addition, the paper illustrates the negative correlation between productivity and informality by evaluating the impacts of the PROJOVEN youth training program

Household Wealth and Heterogeneous Impacts of a Market-Based Training Program: The Case of Projoven in Peru

This paper analyzes the relationship between households\u27 wealth and heterogeneous treatment impacts for a market-based training program that has benefited more than 40,000 disadvantaged individuals in Peru since 1996. We proxy long-run wealth by a linear index based on 21 household assets, and three main findings emerge. First, we find that voluntary choices among eligibles, rather than administrative choices, play a bigger role in explaining demographic disparities in program participation. Second, quantile treatment effects on the treated suggest important differences in program impacts at different quantiles of earnings, and strong differences in distributional impacts for men and women. Third, both parametric-based and semiparametric regression-matching estimates reveal that the poorest among the poor benefit the same from the program. It is the type of institution that provides the training services that largely accounts for the heterogeneity of the impacts

Program quality and treatment completion for youth training programs

This paper analyzes the effects of training quality on the likelihood of treatment completion by estimating dose-response functions via a generalized propensity score. Results show a statistically positive relationship between training quality and treatment completion for youth participants in Peru

Digital labor-market intermediation and job expectations: Evidence from a field experiment

Subjective expectations are fundamental for understanding individual behavior. Yet, little is known about how individuals use new information to formulate and update their subjective expectations. In this study, we exploit data from a multi-treatment field experiment to investigate how job-market information sent to jobseekers via short text messages (SMS) influence subjective job gain expectations in Peru. Results show that jobseekers who received digital intermediation based on a large information set increased their before-after job gain expectations relative to the control group. Independently of the information channel, no significant effects were found when labor-market intermediation is based on a restricted (short) set of information