Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data

Driscoll, John C.; Kraay, Aart

doi:10.1162/003465398557825

Cited by 4,218 publications

(2,539 citation statements)

References 20 publications

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“…The test reveals that cross-section correlation is present. To account for this, we applied the estimator proposed by Driscoll and Kraay (1998). This nonparametric estimator corrects the variance-covariance matrix for heteroscedasticity, auto-and panel correlation.…”

Section: Methodsological Robustnessmentioning

confidence: 99%

On the political economy of national tax revenue forecasts: evidence from OECD countries

Jochimsen

Lehmann

2016

Public Choice

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Section: Methodsological Robustnessmentioning

confidence: 99%

On the political economy of national tax revenue forecasts: evidence from OECD countries

Jochimsen

Lehmann

2016

Public Choice

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“…In the following analysis, we will consider Random Effect (RE) correcting the standard error by the Newey-West method and the Fixed Effect (FE) analysis using Driscoll and Kraay (1998) standard errors. The error structure is assumed heteroskedastic, autocorrelated up to two lags and possibly correlated between the firms (panels).…”

Section: Panel Data Analysismentioning

confidence: 99%

“…The error structure is assumed heteroskedastic, autocorrelated up to two lags and possibly correlated between the firms (panels). The Driscoll and Kraay (1998) Equation (2) is modified as: Driscoll and Kraay (1998) standard error is simply the square root of the diagonal elements of the following asymptotic (robust) covariance matrix:…”

Section: Panel Data Analysismentioning

confidence: 99%

Reexamining sports-sentiment hypothesis: Microeconomic evidences from Borsa Istanbul

Fung

Demir

Lau

et al. 2015

Journal of International Financial Markets, Institutions and Mo

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This paper examines the impact of international soccer matches on the Turkish stock market using firm-level and sorted-portfolio data. Applying Edmans et al. (2007) estimation method, we found a significant negative loss effect. However, once using panel data analysis as well as modeling spatial and temporal effects explicitly, the sportssentiment effect disappeared. The same conclusions could be made by replacing win (loss) dummies with unexpected win (loss) variables, removing Monday matches, dropping sports-related firms, and sorting portfolio returns by market capitalization and past returns. Hence, there is very limited micro-evidence to support the 'overreaction' hypothesis of individual investors using Borsa Istanbul data. However, we found evidence that sporting events have a larger impact on stock return volatility for firms with smaller market capitalization and lower past returns.

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“…It is robust to heteroskedasticity of unknown form as well as to within-cluster correlation. The estimator (21) was first proposed by Froot (1989), introduced into Stata by Rogers (1993), and extended to allow for serial correlation of unknown form, as in HAC estimation, by Driscoll and Kraay (1998). It is widely used in applied work.…”

Section: Cluster-robust Covariance Matricesmentioning

confidence: 99%

Thirty Years of Heteroskedasticity-Robust Inference

MacKinnon

2012

Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revolutionary idea of inference that is robust to heteroskedasticity of unknown form, an idea that was very soon extended to other forms of robust inference and also led to many new estimation methods. This paper discusses the development of heteroskedasticity-robust inference since 1980. There have been two principal lines of investigation. One approach has been to modify White's original estimator to improve its finite-sample properties, and the other has been to use bootstrap methods. The relation between these two approaches, and some ways in which they may be combined, are discussed. Finally, a simulation experiment compares various methods and shows how far heteroskedasticity-robust inference has come in just over thirty years. Terms of use: Documents in EconStor may

show abstract

Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data

Cited by 4,218 publications

References 20 publications

On the political economy of national tax revenue forecasts: evidence from OECD countries

On the political economy of national tax revenue forecasts: evidence from OECD countries

Reexamining sports-sentiment hypothesis: Microeconomic evidences from Borsa Istanbul

Thirty Years of Heteroskedasticity-Robust Inference

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