Search

We estimate the effect of economic conditions during the Great Recession on racial animus, as measured by Google searches for a commonly used anti-black racial slur and hate crimes against blacks. Our empirical strategy exploits pre-recession cross-state variation in the size of two economic sectors particularly affected by the Great Recession: manufacturing and real estate. We find that states that were dependent on these sectors were hit hardest by the Great Recession, experienced the largest increases in racist internet searches, and experienced the largest increases in hate crimes against blacks.

Post-election violence is a common form of conflict, but its underlying mechanisms are not well understood. Using data from the 2007 Philippine mayoral elections, this paper provides evidence that post-election violence is particularly intense after narrow victories by incumbents. Using a density test, the study shows that incumbents were substantially more likely to win narrow victories than their challengers, a pattern consistent with electoral manipulation. There is no evidence that the increase in post-election violence is related to the incumbents’ political platform or their performance in past elections. These results provide support for the notion that post-election violence is triggered by election fraud or by the failure of democratic ways of removing unpopular incumbents from office.

Many experts see a move toward high-value export crops, such as fruits and vegetables, as an important opportunity for economic growth and poverty reduction, but little is known about the effects of export crops in fragile and conflict-affected countries. We exploit movements in world market prices combined with geographic variation in crop production to show that increases in the value of bananas, the country’s biggest export crop, caused an increase in conflict violence and insurgent-controlled territory in the Philippines. This effect was concentrated in provinces where bananas are produced in large plantations with areas greater than 25 hectares. Our results are consistent with a mechanism in which insurgents fund their operations by extorting large agricultural export firms.

Micronutrients, often referred to as vitamins and minerals are vital to healthy development, disease prevention, and wellbeing. Although only required in small amounts, micronutrients are not produced in the body and must be derived from the diet. Commonly cited micronutrients include Iron, Vitamins A, B, D, Iodine, and Zinc. Malnutrition in micronutrients tends to trap populations in a vicious cycle of poverty, causing adults to be less productive and preventing children from reaching their full potential, and exacerbating household poverty in general. Addressing the problem of micronutrient malnutrition, therefore, provides substantial benefits to the cause of development (Ara et al. 2019). The fortification of staple food items including rice to deliver vital micronutrients offers a unique opportunity to target the vulnerable populace – mostly women, young children and female adolescents – at a low cost, and importantly, without forcing a change in dietary habits.2 Although considerable investments are currently being made to improve micronutrient nutrition outcomes around the world, such efforts generally take time to provide results.

Climate change is predicted to affect global rainfall patterns, but there is mixed evidence with regard to the effect of rainfall on civil conflict. Even among researchers who argue that rainfall reduces civil conflict, there is disagreement as to the underlying mechanism. Using data from the Philippines for the period 2001-2009, we exploit seasonal variation in the relationship between rainfall and agricultural production to explore the connection between rainfall and civil conflict. In the Philippines, above-average rainfall during the wet season is harmful to agricultural production, while above-average rainfall during the dry season is beneficial. We show that the relationship between rainfall and civil conflict also exhibits seasonality, but in the opposite direction and with a one-year lag. Consistent with the hypothesis that rebel groups gain strength after a bad harvest, there is evidence that lagged rainfall affects the number of violent incidents initiated by insurgents but not the number of incidents initiated by government forces. Our results suggest that policies aimed at mitigating the effect of climate change on agricultural production could weaken the link between climate change and civil conflict.

Integrating youth into communities and labor markets is a major challenge for developing countries, and incentives for community service are an increasingly popular tool to achieve this goal. We use a randomized controlled trial to evaluate the Kazakhstan Youth Corps (KYC), a program comprising cash grants for community service projects and life skills training, on social capital for a sample of youth aged 18–29. We find little evidence that engaging youth in civic service and training has any positive effects one year post-intervention; there is no shift in attitudinal indices of social capital and no reported increase in volunteering or donations. Moreover, there is no effect of the intervention on secondary outcomes (life skills and human capital), and some evidence of a negative effect of the training-only intervention on the probability of reporting any income-earning activity.

We estimate how a shift towards a more extractive resource policy, brought about by a regulatory reform of the mining sector, affected civil conflict in the Philippines. Our empirical strategy uses a difference-in-differences approach that compares provinces with and without mineral deposits before and after the reform. We find that the reform led to a large increase in conflict violence, most likely due to increased competition over control of resource-rich areas. The estimated welfare cost of this increase in violence is several orders of magnitude larger than the country's total revenue from taxes on mineral production.

Conditional cash transfer (CCT) programs are an increasingly popular tool for reducing poverty in conflict-affected areas. Despite their growing popularity, there is limited evidence on how CCT programs affect conflict and theoretical predictions are ambiguous. We estimate the effect of conditional cash transfers on civil conflict in the Philippines by exploiting an experiment that randomly assigned eligibility for a CCT program at the village level. We find that cash transfers caused a substantial decrease in conflict-related incidents in treatment villages relative to control villages in the first 9 months of the program. Using unique data on local insurgent influence, we also find that the program reduced insurgent influence in treated villages. An analysis of possible spillovers yields inconclusive results. While we find no statistical evidence of spillovers, we also cannot rule out that the village-level effect was due to displacement of insurgent activity from treatment to control villages.

We estimate the causal effect of a large development program on conflict in the Philippines through a regression discontinuity design that exploits an arbitrary poverty threshold used to assign eligibility for the program. We find that barely eligible municipalities experienced a large increase in conflict casualties compared to barely ineligible ones. This increase is mostly due to insurgent-initiated incidents in the early stages of program preparation. Our results are consistent with the hypothesis that insurgents try to sabotage the program because its success would weaken their support in the population. (JEL D74, F35, I32, I38, O15, O17, O18, O19)

The integrated assessment literature frequently replicates uncertainty by averaging Monte Carlo runs of deterministic models. This Monte Carlo analysis is, in essence, an averaged sensitivity analyses. The approach resolves all uncertainty before the first time period, drawing parameters from a distribution before initiating a given model run. This paper analyzes how closely a Monte Carlo based derivation of optimal policies is to the truly optimal policy, in which the decision maker acknowledges the full set of possible future trajectories in every period. Our analysis uses a stochastic dynamic programming version of the widespread integrated assessment model DICE, and focuses on damage uncertainty. We show that the optimizing Monte Carlo approach is not only off in magnitude, but can even lead to a wrong sign of the uncertainty effect. Moreover, it can lead to contradictory policy advice, suggesting a more stringent climate policy in terms of the abatement rate and a less stringent one in terms of the expenditure on abatement.

A series of influential papers have documented that state level mortality rates decrease during economic downturns. In this paper, we estimate the effect of education specific unemployment rates on mortality, which provide a more exact measure of the likelihood of being directly impacted by a recession. We find that the unemployment rate of an education group in a given state is positively related to mortality in that group. A 1% increase in the group-specific unemployment rate is associated with an approximately 0.015% increase in the group-specific mortality rate, which is consistent with the hypothesis that, while state-level unemployment may have indirect health benefits, being personally affected by a recession has a detrimental effect on health.

In this paper, we are concerned with the provision of schools in rural North India, particularly with whether such provision is determined by the demographic and economic characteristics of the region or whether local democracy also plays a role. We find that the probability that a governing party loses an election has a positive effect on the provision of schooling infrastructure, while the margin of victory of the governing party has a negative effect. Political reservation for members of the Scheduled Castes (SCs) has a positive effect on schooling infrastructure in villages with a large SC population, but a negative effect overall.

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

The fact that conflicts tend to cluster in space is well documented. It remains unclear, however, whether this clustering is a result of contagion or of unobserved shocks that are correlated across space. We present new evidence for contagion by exploiting a natural experiment that increased the intensity of one conflict but had no direct effect on a second ongoing conflict in the same area. In particular, we analyze a ruling by the Supreme Court of the Philippines, which disallowed a proposed peace treaty with the Moro-Islamic Liberation Front (MILF), a Muslim separatist insurgency, and led to an escalation of conflict with the MILF in provinces with a large Muslim population. Though the ruling had no direct bearing on the conflict with the New People's Army (NPA), a communist guerrilla group, we find that it also led to a substantial increase in conflict with the NPA in the same provinces. We test several mechanisms and conclude that contagion was most likely the result of strategic escalation by the NPA in an attempt to exploit the local weakness of the armed forces.

Drawing on county-level data from Kansas for the period 1977-2011, we examine whether plausibly exogenous increases in the number of establishments licensed to sell alcohol by the drink are related to violent crime. During this period, 86 out of 105 counties in Kansas voted to legalize the sale of alcohol to the general public for on-premises consumption. We provide evidence that these counties experienced substantial increases in the total number of establishments with on-premises liquor licenses (e.g., bars and restaurants). Using legalization as an instrument, we show that a 10 percent increase in drinking establishments is associated with a 4 percent increase in violent crime. Reduced-form estimates suggest that legalizing the sale of alcohol to the general public for on-premises consumption is associated with an 11 percent increase in violent crime.

Previous studies have documented a positive association between election fraud and the intensity of civil conflict. It is not clear, however, whether this association is causal or due to unobserved institutional and cultural factors. This paper examines the relationship between election fraud and post-election violence in the 2007 Philippine mayoral elections. Using the density test developed by McCrary (2008), we find evidence that incumbents were able to win tightly contested elections through fraud. In addition, we show that narrow incumbent victories were associated with an increase in post-election casualties, which is consistent with the hypothesis that election fraud causes conflict. We conduct several robustness tests and find no evidence that incumbent victories increased violence for reasons unrelated to fraud.

In volume 30, issue 4 of this journal Baris Yoruk and Ceren Yoruk (Y&EY) used data from the National Longitudinal Study of Youth, 1997 (NLSY97) and a regression discontinuity design to estimate the effect of the minimum legal drinking age on a variety of substances including marijuana. They obtained evidence that the probability of marijuana use increased sharply at the age of 21, consistent with the hypothesis that alcohol and marijuana are complements, but inadvertently conditioned on having used marijuana at least once since the last survey. Applying the Y&EY research design to all NLSY97 respondents ages 19 through 22, we find no evidence that alcohol and marijuana are complements.

The precise consequences of climate change remain uncertain. We incorporate damage uncertainty into a joint model of climate and the economy, an integrated assessment model. First, both the science and the integrated assessment community analyze uncertainty by means of sensitivity analysis and Monte-Carlo simulations. These methods have serious limitations in deriving a carbon tax or cap under uncertainty: they do not incorporate the interaction between stochastic climate impacts and economic policy. We derive the optimal climate policies accounting for the full interaction between uncertain damage realizations, optimal policy response, and climatic feedback. Second, state of the art integrated assessment relies on the standard economic model. Modern decision theory and its applications to finance show that this discounted expected utility model is incapable of simultaneously capturing adequate risk premia and a reasonable discount rate, leading to the equity premium and the risk-free rate puzzles. We follow the finance literature in disentangling risk aversion from the propensity to smooth consumption over time, which gives rise to a model reflecting correctly the risk-free discount rate and the risk premia. We find that optimal mitigation efforts are twice as high in the comprehensive risk model as compared to the entangled standard model.

This paper exploits the discontinuity created by the minimum legal drinking age of 21 years to estimate the causal effect of increased alcohol availability on marijuana use. We find that consumption of marijuana decreases sharply at age 21, while consumption of alcohol increases, suggesting that marijuana and alcohol are substitutes. We further find that the substitution effect between alcohol and marijuana is stronger for women than for men. Our results suggest that policies designed to limit alcohol use have the unintended consequence of increasing marijuana use.

The farm-level success of Bt-cotton in developing countries is well documented. However, the literature has only recently begun to recognise the importance of accounting for the effects of the technology on production risk, in addition to the mean effect estimated by previous studies. The risk effects of the technology are likely very important to smallholder farmers in the developing world due to their risk-aversion. We advance the emergent literature on Bt-cotton and production risk by using panel data methods to control for possible endogeneity of Bt-adoption. We estimate two models, the first a fixed-effects version of the Just and Pope model with additive individual and time effects, and the second a variation of the model in which inputs and variety choice are allowed to affect the variance of the time effect and its correlation with the idiosyncratic error. The models are applied to panel data on smallholder cotton production in India and South Africa. Our results suggest a risk-reducing effect of Bt-cotton in India, but an inconclusive picture in South Africa.