Poverty, Political Freedom, and the Roots of Terrorism

This article provides an empirical investigation of the determinants of terrorism at the country level. In contrast with the previous literature on this subject, which focuses on transnational terrorism only, I use a new measure of terrorism that encompasses both domestic and transnational terrorism. In line with the results of some recent studies, this article shows that terrorist risk is not significantly higher for poorer countries, once the effects of other country-specific characteristics such as the level of political freedom are taken into account. Political freedom is shown to explain terrorism, but it does so in a non-monotonic way: countries in some intermediate range of political freedom are shown to be more prone to terrorism than countries with high levels of political freedom or countries with highly authoritarian regimes. This result suggests that, as experienced recently in Iraq and previously in Spain and Russia, transitions from an authoritarian regime to a democracy may be accompanied by temporary increases in terrorism. Finally, the results suggest that geographic factors are important to sustain terrorist activities.

Bootstrap Tests for the Effect of a Treatment on the Distribution of an Outcome Variable

This paper considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) non-randomized but there is a binary instrument available for the researcher. Such scenario is common in observational studies and in randomized experiments with imperfect compliance. One possible approach to this problem is to compare the counterfactual cumulative distribution functions of the outcome with and without the treatment. Here, it is shown how to estimate these distributions using instrumental variable methods and a simple bootstrap procedure is proposed to test distributional hypotheses, such as equality of distributions, first-order stochastic dominance and second order stochastic dominance. These tests and estimators are applied to the study of the effects of veteran status on the distribution of civilian earnings. The results show a negative effect of military service in Vietnam that appears to be concentrated on the lower tail of the distribution of earnings. First order stochastic dominance cannot be rejected by the data.

Semiparametric Estimation of Instrumental Variable Models for Causal Effects

This article introduces a new class of instrumental variable (IV) estimators of causal treatment effects for linear and nonlinear models with covariates. The rationale for focusing on nonlinear models is to improve the approximation to the causal response function of interest. For example, if the dependent variable is binary or limited, or if the effect of the treatment varies with covariates, a nonlinear model is likely to be appropriate. However, identification is not attained through functional form restrictions. This paper shows how to estimate a well-defined approximation to a nonlinear causal response function of unknown functional form using simple parametric models. As an important special case, I introduce a linear model that provides the best linear approximation to an underlying causal relation. It is shown that Two Stage Least Squares (2SLS) does not always have this property and some possible interpretations of 2SLS coefficients are brie y studied. The ideas and estimators in this paper are illustrated using instrumental variables to estimate the effects of 401(k) retirement programs on savings.

The Economic Costs of Conflict: A Case-Control Study for the Basque Country

This paper investigates the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study. Our analysis rests on two different strategies. First, we use a combination of other regions to construct a 'synthetic' control region which resembles many relevant economic characteristics of the Basque Country before the outset of political terrorism in the 1970's. The subsequent economic evolution of this 'counterfactual' Basque Country without terrorism is compared to the actual experience of the Basque Country. We find that, after the outbreak of terrorism, per capita GDP in the Basque Country declined about 10 percent points relative to the synthetic control region. Moreover, this gap seemed to widen in response to spikes in terrorist activity. The second part of this study uses the truce declared in September 1998 as a natural experiment to estimate the effects of the conflict. If the terrorist conflict was perceived to have a negative impact on the Basque economy, stocks of firms with a significant part of their business in the Basque Country should have shown a positive relative performance as the truce became credible, and a negative relative performance at the end of the cease-fire. We find evidence that is consistent with this conjecture using event study methods.

Terrorism and the World Economy

Published as an article in: European Economic Review, 2008, vol. 52, issue 1, pages 1-27.terrorism, growth, FDI, international diversification

Is Terrorism Eroding Agglomeration Economies in Central Business Districts? Lessons from the Office Real Estate Market in Downtown Chicago

The attacks of September 11, 2001, and more recently the Madrid and London downtown train bombings, have raised concerns over both the safety of downtowns and the continuous efforts by terrorists to attack areas of such high density and significance. This article employs building-level data on vacancy rates to investigate the impact of an increased perception of terrorist risk after 9/11 on the office real estate market in downtown Chicago. Chicago provides the perfect laboratory to investigate the effects of an increase in the perceived level of terrorist risk in a major financial district. Unlike in New York, the 9/11 attacks did not restrict directly the available office space in downtown Chicago. Moreover, the 9/11 attacks induced a large increase in the perception of terrorist risk in the Chicago Central Business District, which includes the tallest building in the U.S. (the Sears Tower) and other landmark buildings which are potential targets of large-scale terrorist attacks. Our results show that, following the 9/11 attacks, vacancy rates experienced a much more pronounced increase in the three most distinctive Chicago landmark buildings (the Sears Tower, the Aon Center and the Hancock Center) and their vicinities than in other areas of the city of Chicago. Our results suggest that economic activity in Central Business Districts can be greatly affected by changes in the perceived level of terrorism.

The Impact of Presumed Consent Legislation on Cadaveric Organ Donation: A Cross Country Study

In the U.S., Great Britain, and in many other countries, the gap between the demand and the supply of human organs for transplantation is on the rise, despite the efforts of governments and health agencies to promote donor registration. In some countries of continental Europe, however, cadaveric organ procurement is based on the principle of presumed consent. Under presumed consent legislation, a deceased individual is classified as a potential donor in absence of explicit opposition to donation before death. This article analyzes the impact of presumed consent laws on donation rates. For this purpose, we construct a dataset on organ donation rates and potential factors affecting organ donation for 22 countries over a 10-year period. We find that while differences in other determinants of organ donation explain much of the variation in donation rates, after controlling for those determinants presumed consent legislation has a positive and sizeable effect on organ donation rates.

A Martingale Representation for Matching Estimators

Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has been derived only for particular cases (Abadie and Imbens, 2006). This article establishes a martingale representation for matching estimators. This representation allows the use of martingale limit theorems to derive the asymptotic distribution of matching estimators. As an illustration of the applicability of the theory, we derive the asymptotic distribution of a matching estimator when matching is carried out without replacement, a result previously unavailable in the literature.matching, martingales, treatment effects, hot-deck imputation

On the Failure of the Bootstrap for Matching Estimators

Matching estimators are widely used for the evaluation of programs or treatments. Often researchers use bootstrapping methods for inference. However, no formal justification for the use of the bootstrap has been provided. Here we show that the bootstrap is in general not valid, even in the simple case with a single continuous covariate when the estimator is root-N consistent and asymptotically normally distributed with zero asymptotic bias. Due to the extreme non-smoothness of nearest neighbor matching, the standard conditions for the bootstrap are not satisfied, leading the bootstrap variance to diverge from the actual variance. Simulations confirm the difference between actual and nominal coverage rates for bootstrap confidence intervals predicted by the theoretical calculations. To our knowledge, this is the first example of a root-N consistent and asymptotically normal estimator for which the bootstrap fails to work.