Search

Despite the importance of trade facilitation as an area of trade and development policy, there have been very few impact evaluations of specific trade facilitation reforms. This paper offers an evaluation of in-house clearance, a reform that allows qualified firms in Serbia to clear customs from within their own warehouse rather than at the customs office. The pooled synthetic control method applied here offers a novel solution to many of the empirical challenges that frustrate efforts to evaluate trade facilitation reforms. The method is used to estimate causal impacts on trade outcomes for 21 firms that adopted in-house clearance for import shipments. The program compressed the distribution of clearance times for adopting firms, but the estimated effects on median clearance times, inspection rates, and import value were not statistically significant. Tests for heterogeneous program impact do not indicate that the program affected adopting firms differently. Overall, the results suggest that the most evident benefit of the program for participating firms is reduced uncertainty about clearance times.

What are the common characteristics among radicalized individuals, willing to justify attacks targeting civilians? Drawing on information on attitudes toward extreme violence and other characteristics of 30,787 individuals from 27 developing countries around the world, and employing a variety of econometric techniques, this paper identifies the partial correlates of extremism. The results suggest that the typical extremist who supports attacks against civilians is more likely to be young, unemployed and struggling to make ends meet, relatively uneducated, and not as religious as others, but more willing to sacrifice own life for his or her beliefs. Gender and marital status are not found to explain significantly the individual-level variation in attitudes toward extremism. Although these results may vary in magnitude and significance across countries and geographic regions, they are robust to various sensitivity analyses.

A recent survey of rigorous impact evaluations of programs to help small and medium-size firms to formalize indicates that the programs do not seem to work for most informal firms. One of the few exceptions finds large effects of a tax simplification program in Brazil called SIMPLES on firms' formalization rates and performance indicators. Using the same data set but a different identification strategy, another study concludes that the program had limited effect on formalization rates. The aim of this paper is twofold. First, it revisits the two studies to reconcile their conflicting conclusions. Second, it investigates the validity of the identification strategy of both studies. The findings suggest that the conflicting results between the two studies are caused by the dates each used to identify when the program was put into effect. A robustness check indicates that data heaping and seasonality around November cast doubts on the identification strategy used in both studies to estimate the effect of this particular program.

Policy makers bemoan the lack of research findings to guide urgent decisions, whereas researchers' professional code puts rigor first. This article argues that provisional assessments, produced early in the research cycle, can bridge the gap. Numerous case studies point to the importance of early interaction with policy makers and the delivery of brief, policy-focused papers; but preliminary analyses may be flawed and so increase the chances of a wrong decision. This article demonstrates analytically that a preliminary assessment, supported by the offer of more refined research, provides an option that is superior, on average, to the current practice of submitting a final report at the end of the research cycle. Where practical implementation is concerned, it calls for donor-funded subsidies to promote the use of provisional assessments and for a rapid, independent, professional review process to ensure their quality. While the research-policy exchange in developing countries is a complex, context-specific phenomenon, the proposal offered here holds out some promise of improving decisions in the public sphere under a wide range of circumstances.

The collection of survey data from war zones or other unstable security situations is vulnerable to error because conflict often limits the implementation options. Although there are elevated risks throughout the process, this paper focuses specifically on challenges to frame construction and sample selection. The paper uses simulations based on data from the Mogadishu High Frequency Survey Pilot to examine the implications of the choice of second-stage selection methodology on bias and variance. Among the other findings, the simulations show the bias introduced by a random walk design leads to the underestimation of the poverty headcount by more than 10 percent. The paper also discusses the experience of the authors in the time required and technical complexity of the associated back-office preparation work and weight calculations for each method. Finally, as the simulations assume perfect implementation of the design, the paper also discusses practicality, including the ease of implementation and options for remote verification, and outlines areas for future research and pilot testing.

This paper investigates how land size measurements vary across three common land measurement methods (farmer estimated, Global Positioning System (GPS), and compass and rope), and the effect of land size measurement error on the inverse farm size relationship and input demand functions. The analysis utilizes plot-level data from the second wave of the Nigeria General Household Survey Panel, as well as a supplementary land validation survey covering a subsample of General Household Survey Panel plots. Using this data, both GPS and self-reported farmer estimates can be compared with the gold standard compass and rope measurements on the same plots. The findings indicate that GPS measurements are more reliable than farmer estimates, where self-reported measurement bias leads to over-reporting land sizes of small plots and under-reporting of large plots. The error observed across land measurement methods is nonlinear and results in biased estimates of the inverse land size relationship. Input demand functions that rely on self-reported land measures significantly underestimate the effect of land on input utilization, including fertilizer and household labor.

Biases from truncation caused by coresidency restriction have been a challenge for research on intergenerational mobility. Estimates of intergenerational schooling persistence from two data sets show that the intergenerational regression coefficient, the most widely used measure, is severely biased downward in coresident samples. But the bias in intergenerational correlation is much smaller, and is less sensitive to the coresidency rate. The paper provides explanations for these results. Comparison of intergenerational mobility based on the intergenerational regression coefficient across countries, gender, and over time can be misleading. Much progress on intergenerational mobility in developing countries can be made with the available data by focusing on intergenerational correlation.

Using household surveys for 24 countries over a 10-year period, this paper investigates why the elderly are more averse to open immigration policies than their younger peers. The analysis finds that the negative correlation between age and pro-immigration attitudes is mostly explained by a cohort or generational change. In fact, once controlling for year of birth, the correlation between age and pro-immigration attitudes is either positive or zero in most of the countries in the sample. Under certain assumptions, the estimates suggest that aging societies will tend to become less averse to open immigration regimes over time.

This paper looks at how individual preferences for the allocation of government spending change along the life cycle. Using the Life in Transition Survey II for 34 countries in Europe and Central Asia, the study finds that older individuals are less likely to support a rise in government outlays on education and more likely to support increases in spending on pensions. These results are very similar across countries, and they do not change when using alternative model specifications, estimation methods, and data sources. Using repeated cross-sections, the analysis controls for cohort effects and confirms the main results. The findings are consistent with a body of literature arguing that conflict across generations over the allocation of public expenditures may intensify in ageing economies.

This paper uses survey data from 120 developing countries to compare the role of institutions with firm characteristics at the time of creation of the firm in explaining the size, growth, and productivity of firms over their lifecycle. The study finds that firm-level characteristics have comparable, and sometimes even larger, power than institutional factors in predicting size and growth, but not productivity. In particular, size at birth plays a key role in predicting variation in firm size and growth since birth over the firm lifecycle, whereas country factors dominate in predicting variation in labor productivity over the firm lifecycle. The study also finds that older firms are larger, partly because of the selection of more efficient firms. The findings point to the importance of initial founding conditions in explaining variations in size and growth over the firm lifecycle across countries.

Catastrophe risk models are quantitative models used to estimate probabilistic loss distributions for a specified range of assets subject to a baseline level of disaster risk. While cat risk models are used extensively by the insurance and reinsurance industry to estimate expected losses to insured assets, their ability to estimate damages outside of a narrow range of physical assets such as buildings or infrastructure is still limited. This paper first provides a brief outline of cat risk models as they currently exist, and then outlines the major econometric issues involved in incorporating research from the growing literature on the microeconomic impacts of disasters into a cat model framework. Attention is specifically drawn to issues arising from the generally low recurrence frequencies of disasters, the likely role of difficult-to-document indirect damages in influencing total disaster costs, and issues related to generalizing disaster response functions across different domains. The paper ends by noting the large discrepancy between the current state of the literature on disaster impacts on microeconomic indicators and the level needed for adequate cat risk model performance, and suggests means of closing that gap as well as potential areas for future research.

This paper uses data from the Integrated Values Survey, the Life in Transition Survey, and the Russia Longitudinal Monitoring Survey to analyze the relation between age and subjective well-being in the Europe and Central Asia region. Although the results generally confirm the findings of previous studies of a U-shaped relation between subjective well-being and age for most of the lifecycle, the paper also finds that well-being declines again after people reach their 60s and 70s, giving rise to an S-shaped relation across the entire lifespan. This pattern generally remains robust for most of the cross-sectional and panel analyses. Hence, despite significant heterogeneity in the pattern of well-being across the lifespan in the Europe and Central Asia region, the paper does not observe high levels of cross-country or cross-cohort variation.

When measuring inequality of opportunity, researchers usually opt to eliminate within-type variation. Provided that in practice it is impossible to observe all circumstances, this implies that the researcher estimates a lower bound of the true level of inequality of opportunity. By using data drawn from 27 Demographic Household Surveys (circa 2008), it is found that lower bound estimates can have substantial measurement error, and that measurement error can vary considerably across countries. As a consequence, lower bound estimates of inequality of opportunity can demand too little redistribution to equalize inequalities due to circumstances and can make the “traditional” cross-country comparisons misleading.

We complement the empirical evidence on the sustainability of weight loss achieved through cash rewards and, for the first time, rigorously examine the potential of cash rewards to prevent weight cycling. In a three period randomized controlled trial, about 700 obese persons were first assigned to two treatment groups, which were promised cash contingent on the achievement of an individually assigned target weight, and to a control group. Successful participants were subsequently allocated to two treatment groups offered cash rewards for confirming the previously achieved target weight and to a control group. This is the first experiment of this kind that finds effects of weight loss rewards up to 18 months after they were removed. Additional rewards only significantly improve the sustainability of weight loss while they are in place. Die empirische Analyse untersucht zum einen die Nachhaltigkeit einer Gewichtsreduktion, die mittels Geldanreizen erzielt wurde, und zum anderen die Wirksamkeit von Geldanreizen zur Verhinderung des Jo-Jo-Effekts nach einer erfolgreichen Gewichtsreduktion. In einem drei-phasigen Feldexperiment wurden ca. 700 fettleibige Teilnehmer zunächst zufällig auf zwei Anreizgruppen und einer Kontrollgruppe verteilt. Unabhängig von der Gruppenzugehörigkeit sollten ein individuelles Gewichtsreduktionziel erreicht werden, wobei nur Mitglieder der Anreizgruppen eine Geldprämie für das Erreichen des Zieles erhalten konnten. Erfolgreiche Teilnehmer wurden danach erneut zufällig einer Kontrollgruppe und zwei Anreizgruppen zugewiesen, wobei das Halten des Zielgewichts nur für letztere durch eine Geldprämie inzentiviert wurde. Anders als in früheren Experimenten, können Effekt der Abnehmprämie selbst 18 Monate nach ihrem Auslaufen nachgewiesen werden. Monetäre Anreize zur Verhinderung des Jo-Jo-Effekt wirken hingegen nicht über ihr Auslaufen hinaus.

The paper estimates the effect of product standards on firms’ export decisions using two novel datasets. The first covers all exporting firms in 42 developing countries. The second covers pesticide standards for 243 agricultural and food products in 63 importing countries over 2006–12. The analysis shows that product standards significantly affect foreign market access. More restrictive standards in the importing country, relative to the exporting country, lower firms’ probability of exporting as well as their export values and quantities. The relative restrictiveness of standards also deters exporting firms from entering new markets and leads to higher exit rates from those markets. Moreover, firm characteristics mediate the effect of product standards on firms’ export decisions. Smaller exporters are more negatively affected in their market entry and exit decisions by the relative stringency of standards than larger exporters. Positive network effects of exporters from the same country may help reduce the burden of importing countries’ standards on firms’ decisions to enter new markets.

This paper develops a structural approach for modeling how respondents answer survey questions and uses it to estimate the proportion of respondents who are reticent in answering corruption questions, as well as the extent to which reticent behavior biases down conventional estimates of corruption. The context is a common two-step survey question, first inquiring whether a government official visited a business, and then asking about bribery if a visit was acknowledged. Reticence is a concern for both steps, since denying a visit sidesteps the bribe question. This paper considers two alternative models of how reticence affects responses to two-step questions, with differing assumptions on how reticence affects the first question about visits. Maximum-likelihood estimates are obtained for seven countries using data on interactions with tax officials. Different models work best in different countries, but cross-country comparisons are still valid because both models use the same structural parameters. On average, 40 percent of corruption questions are answered reticently, with much variation across countries. A statistic reflecting how much standard measures underestimate the proportion of all respondents who had a bribe interaction is developed. The downward bias in standard measures is highly statistically significant in all countries, varying from 12 percent in Nigeria to 90 percent in Turkey. The source of bias varies widely across countries, between denying a visit and denying a bribe after admitting a visit.

This paper is a practical guide for researchers and practitioners who want to understand spillover effects in program evaluation. The paper defines spillover effects and discusses why it is important to measure them. It explains how to design a field experiment to measure the average effects of the treatment on eligible and ineligible subjects for the program in the presence of spillover effects. In addition, the paper discusses the use of nonexperimental methods for estimating spillover effects when the experimental design is not a viable option. Evaluations that account for spillover effects should be designed such that they explain the cause of these effects and whom they affect. Such an evaluation design is necessary to avoid inappropriate policy recommendations and neglecting important mechanisms through which the program operates.

There is an inherent tension between traditional norms and survey protocols for quantitative data collected in the developing world. Unexpected interactions between the interviewer and respondent can lead to interviewer effects in the data, particularly in the case of subjective or sensitive questions. This paper makes use of a unique data set available from Timor-Leste containing subjective and objective questions to study these effects. In addition to their age and gender, data were collected from the interviewers regarding their opinions on the subjective questions prior to fieldwork. Fixed effects and mixed effects logit models are used to examine the main effects and interactions between interviewer and respondent characteristics. More objective measures serve as a pseudo control group. The paper finds interviewer effects in the both subjective and objective data, but the magnitude is considerably stronger for subjective questions. The paper also finds that female respondents are more susceptible to influence based on the interviewer's beliefs. Despite methodological shortcomings, the study highlights the need to consider more fully the impact of traditional cultural norms when conducting quantitative surveys in the developing world on topics that are outside the standard objective questions.