Results 1  10
of
692
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 ..."
Abstract

Cited by 890 (7 self)
 Add to MetaCart
(Show Context)
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 ..."
Abstract

Cited by 828 (1 self)
 Add to MetaCart
(Show Context)
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.
Does foreign direct investment increase the productivity of domestic firms? In search of spillovers through backward linkages
 AMERICAN ECONOMIC REVIEW
, 2003
"... Many countries strive to attract foreign direct investment (FDI) in the hope that knowledge brought by multinationals will spill over to domestic industries and increase their productivity. In contrast with earlier literature that failed to find positive intraindustry spillovers from FDI, this stu ..."
Abstract

Cited by 433 (11 self)
 Add to MetaCart
Many countries strive to attract foreign direct investment (FDI) in the hope that knowledge brought by multinationals will spill over to domestic industries and increase their productivity. In contrast with earlier literature that failed to find positive intraindustry spillovers from FDI, this study focuses on effects operating across industries. The analysis, based on a firmlevel panel data set from Lithuania, produces evidence consistent with positive productivity spillovers from FDI taking place through contacts between foreign affiliates and their local suppliers in upstream sectors. The data indicate that such spillovers are associated with projects with shared domestic and foreign ownership but not with fully owned foreign investments. There is no indication of spillovers occurring within the same industry or through domestic firms sourcing inputs from multinationals.
Understanding Productivity: Lessons from Longitudinal Microdata
, 2000
"... This paper reviews research that uses longitudinal microdata to document productivity movements and to examine factors behind productivity growth. The research explores the dispersion of productivity across firms and establishments, the persistence of productivity differentials, the consequences of ..."
Abstract

Cited by 410 (5 self)
 Add to MetaCart
(Show Context)
This paper reviews research that uses longitudinal microdata to document productivity movements and to examine factors behind productivity growth. The research explores the dispersion of productivity across firms and establishments, the persistence of productivity differentials, the consequences of entry and exit, and the contribution of resource reallocation across firms to aggregate productivity growth. The research also reveals important factors correlated with productivity growth, such as managerial ability, technology use, human capital, and regulation. The more advanced literature in the field has begun to address the more difficult questions of the causality between these factors and productivity growth.
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 ..."
Abstract

Cited by 363 (4 self)
 Add to MetaCart
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.
BootstrapBased Improvements for Inference with Clustered Errors
, 2006
"... Microeconometrics researchers have increasingly realized the essential need to account for any withingroup dependence in estimating standard errors of regression parameter estimates. The typical preferred solution is to calculate clusterrobust or sandwich standard errors that permit quite general ..."
Abstract

Cited by 303 (12 self)
 Add to MetaCart
Microeconometrics researchers have increasingly realized the essential need to account for any withingroup dependence in estimating standard errors of regression parameter estimates. The typical preferred solution is to calculate clusterrobust or sandwich standard errors that permit quite general heteroskedasticity and withincluster error correlation, but presume that the number of clusters is large. In applications with few (530) clusters, standard asymptotic tests can overreject considerably. We investigate more accurate inference using cluster bootstrapt procedures that provide asymptotic refinement. These procedures are evaluated using Monte Carlos, including the muchcited differencesindifferences example of Bertrand, Mullainathan and Duflo (2004). In situations where standard methods lead to rejection rates in excess of ten percent (or more) for tests of nominal size 0.05, our methods can reduce this to five percent. In principle a pairs cluster bootstrap should work well, but in practice a wild cluster bootstrap performs better.
A generalized moments estimator for the autoregressive parameter in a spatial model
 International Economic Review
, 1999
"... This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed ..."
Abstract

Cited by 285 (24 self)
 Add to MetaCart
This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in the paper, the (quasi) maximum likelihood estimator may not be computationally feasible in many cases involving moderate or large sized samples. In this paper we suggest a generalized moments estimator that is computationally simple irrespective of the sample size. We provide results concerning the large and small sample properties of this estimator. 1 Introduction 1 There exists a large body of literature that considers autocorrelation of the disturbances across cross sectional units for panel data, i.e., data which are observed both across cross sectional units and over time. However, the estimation of models that permit for autocorrelation of the disturbances across
The Role of Income Aspirations in Individual Happiness
 Journal of Economic Behavior and Organization
, 2002
"... Does individual wellbeing depend on the absolute level of income and consumption or is it relative to one's aspirations? In a direct empirical test, it is found that higher income aspirations reduce people's utility, ceteris paribus. Thereby, individual data on reported satisfaction with ..."
Abstract

Cited by 228 (33 self)
 Add to MetaCart
(Show Context)
Does individual wellbeing depend on the absolute level of income and consumption or is it relative to one's aspirations? In a direct empirical test, it is found that higher income aspirations reduce people's utility, ceteris paribus. Thereby, individual data on reported satisfaction with life are used as a proxy measure for utility, and income evaluation measures are applied as proxies for people's aspiration level. Consistent with processes of adaptation and social comparison, income aspirations increase with people's income as well as with the average income in the community of their residence. (91 words) JEL classification: D60, D63, I31 Keywords: aspiration level, interdependent preferences, relative income, subjective wellbeing, utility Addresses: School of Law, University of California, 354 Boalt Hall, Berkeley, CA 947207200 (until November 2002) and Institute for Empirical Research in Economics, University of Zurich, Blmlisalpstrasse 10, CH8006 Zurich, Switzerland. Tel: ++411634 37 29/25; Fax: ++411634 49 07; Email: astutzer@iew.unizh.ch. I am grateful to Matthias Benz, Richard Easterlin, Robert Frank, Bruno S. Frey, Lorenz Gtte, Carol Graham and Bernard van Praag for helpful comments and the Swiss National Science Foundation for financial support.