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Estimating standard errors in finance panel data sets: comparing approaches.
 Review of Financial Studies
, 2009
"... Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solut ..."
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Cited by 890 (7 self)
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Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the FamaMacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use.
How much should we trust differencesindifferences estimates?
, 2003
"... Most papers that employ DifferencesinDifferences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in statelevel data on femal ..."
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Cited by 828 (1 self)
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Most papers that employ DifferencesinDifferences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in statelevel data on female wages from the Current Population Survey. For each law, we use OLS to compute the DD estimate of its “effect” as well as the standard error of this estimate. These conventional DD standard errors severely understate the standard deviation of the estimators: we find an “effect ” significant at the 5 percent level for up to 45 percent of the placebo interventions. We use Monte Carlo simulations to investigate how well existing methods help solve this problem. Econometric corrections that place a specific parametric form on the timeseries process do not perform well. Bootstrap (taking into account the autocorrelation of the data) works well when the number of states is large enough. Two corrections based on asymptotic approximation of the variancecovariance matrix work well for moderate numbers of states and one correction that collapses the time series information into a “pre” and “post” period and explicitly takes into account the effective sample size works well even for small numbers of states.
Robust Inference with Multiway Clustering
, 2006
"... In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables clusterrobust inference when there is twoway or multiway clustering that is nonnested. The variance estimator extends the standard clusterr ..."
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Cited by 363 (4 self)
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In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables clusterrobust inference when there is twoway or multiway clustering that is nonnested. The variance estimator extends the standard clusterrobust variance estimator or sandwich estimator for oneway clustering (e.g. Liang and Zeger (1986), Arellano (1987)) and relies on similar relatively weak distributional assumptions. Our method is easily implemented in statistical packages, such as Stata and SAS, that already offer clusterrobust standard errors when there is oneway clustering. The method is demonstrated by a Monte Carlo analysis for a twoway random effects model; a Monte Carlo analysis of a placebo law that extends the stateyear effects example of Bertrand et al. (2004) to two dimensions; and by application to two studies in the empirical public/labor literature where twoway clustering is present.
Economic Shocks and Civil Conflict: An Instrumental Variables Approach
 Journal of Political Economy
, 2004
"... Estimating the impact of economic conditions on the likelihood of civil conflict is difficult because of endogeneity and omitted variable bias. We use rainfall variation as an instrumental variable for economic growth in 41 African countries during 1981–99. Growth is strongly negatively related to c ..."
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Cited by 353 (13 self)
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Estimating the impact of economic conditions on the likelihood of civil conflict is difficult because of endogeneity and omitted variable bias. We use rainfall variation as an instrumental variable for economic growth in 41 African countries during 1981–99. Growth is strongly negatively related to civil conflict: a negative growth shock of five percentage points increases the likelihood of conflict by onehalf the following year. We attempt to rule out other channels through which rainfall may affect conflict. Surprisingly, the impact of growth shocks on conflict is not significantly different in richer, more democratic, or more ethnically diverse countries. I.
Some practical guidance for the implementation of propensity score matching
 IZA DISCUSSION PAPER
, 2005
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A Note on the Theme of Too Many Instruments
"... The Difference and System generalized method of moments (GMM) estimators are growing in popularity, thanks in part to specialized software. But as implemented in these packages, the estimators easily generate results by default that are at once invalid yet appear valid in specification tests. The cu ..."
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Cited by 227 (3 self)
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The Difference and System generalized method of moments (GMM) estimators are growing in popularity, thanks in part to specialized software. But as implemented in these packages, the estimators easily generate results by default that are at once invalid yet appear valid in specification tests. The culprit is their tendency to generate instruments that are a) numerous and, in System GMM, b) suspect. A large collection of instruments, even if individually valid, can be collectively invalid in finite samples because they overfit endogenous variables. They also weaken the Hansen test of overidentifying restrictions, which is commonly relied upon to check instrument validity. This paper reviews the evidence on the effects of instrument proliferation, and describes and simulates simple ways to control it. It illustrates the dangers by replicating two early applications to economic
Zeros, quality, and space: Trade theory and trade evidence
 American Economic Journal: Microeconomics
, 2011
"... Bilateral, productlevel data exhibit a number of strong patterns that can be used to evaluate international trade theories, notably the spatial incidence of “export zeros ” (correlated with distance and importer size), and of export unit values (positively related to distance). We show that leading ..."
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Cited by 218 (14 self)
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Bilateral, productlevel data exhibit a number of strong patterns that can be used to evaluate international trade theories, notably the spatial incidence of “export zeros ” (correlated with distance and importer size), and of export unit values (positively related to distance). We show that leading theoretical trade models fail to explain at least some of these facts, and propose a variant of the Melitz model that can account for all the facts. In our model, high quality firms are the most competitive, with heterogeneous quality increasing with firms ’ heterogeneous cost. (JEL F11, F14, F40) The gravity equation relates bilateral trade volumes to distance and country size. Countless gravity equations have been estimated, usually with “good ” results, and trade theorists have proposed various theoretical explanations for gravity’s success. However, the many potential explanations for the success of the gravity equation make it a problematic tool for discriminating among trade models. 1 As a matter of arithmetic, the value of trade depends on the number of goods
2006, “Disease and Development: The Effect of Life Expectancy on Economic Growth,” working paper
 Journal of Political Economy
, 2006
"... What is the effect of increasing life expectancy on economic growth? To answer this question, we exploit the international epidemiological transition, the wave of international health innovations and improvements that began in the 1940s. We obtain estimates of mortality by disease before the 1940s f ..."
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Cited by 213 (7 self)
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What is the effect of increasing life expectancy on economic growth? To answer this question, we exploit the international epidemiological transition, the wave of international health innovations and improvements that began in the 1940s. We obtain estimates of mortality by disease before the 1940s from the League of Nations and national public health sources. Using these data, we construct an instrument for changes in life expectancy, referred to as predicted mortality, which is based on the preintervention distribution of mortality from various diseases around the world and dates of global interventions. We document that predicted mortality has a large and robust effect on changes in life expectancy starting in 1940, but no effect on changes in life expectancy before the interventions. The instrumented changes in life expectancy have alargeeffect on population; a 1 % increase in life expectancy leads to an increase in population of about 1.5%. Life expectancy has a much smaller effect on total GDP both initially and over a 40year horizon, however. Consequently, there is no evidence that the large exogenous increase in life expectancy led to a significant increase in per capita economic growth. These results confirm that global efforts to combat poor health conditions in less developed countries can be highly effective, but also shed doubt on claims that unfavorable health conditions are the root cause of the poverty of some nations.