Object-oriented Computation of Sandwich Estimators
AbstractSandwich covariance matrix estimators are a popular tool in applied regression modeling for performing inference that is robust to certain types of model misspecification. Suitable implementations are available in the R system for statistical computing for certain model fitting functions only (in particular lm()), but not for other standard regression functions, such as glm(), nls(), or survreg(). Therefore, conceptual tools and their translation to computational tools in the package sandwich are discussed, enabling the computation of sandwich estimators in general parametric models. Object orientation can be achieved by providing a few extractor functions' most importantly for the empirical estimating functions' from which various types of sandwich estimators can be computed.
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Volume (Year): 16 ()
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- Kenneth D. West & Whitney K. Newey, 1995.
"Automatic Lag Selection in Covariance Matrix Estimation,"
NBER Technical Working Papers
0144, National Bureau of Economic Research, Inc.
- Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
- Achim Zeileis, . "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, American Statistical Association, vol. 11(i10).
- Ray C. Fair, 1976.
"A Theory of Extramarital Affairs,"
Cowles Foundation Discussion Papers
436, Cowles Foundation for Research in Economics, Yale University.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2002. "Heteroskedasticity-Autocorrelation Robust Testing Using Bandwidth Equal To Sample Size," Econometric Theory, Cambridge University Press, vol. 18(06), pages 1350-1366, December.
- Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-36, May-June.
- T. Lumley & P. Heagerty, 1999. "Weighted empirical adaptive variance estimators for correlated data regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 459-477.
- MacKinnon, James G. & White, Halbert, 1985.
"Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties,"
Journal of Econometrics,
Elsevier, vol. 29(3), pages 305-325, September.
- James G. MacKinnon & Halbert White, 1983. "Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties," Working Papers 537, Queen's University, Department of Economics.
- Donald W.K. Andrews, 1988.
"Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation,"
Cowles Foundation Discussion Papers
877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
- Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May.
- Cribari-Neto, Francisco, 2004. "Asymptotic inference under heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 215-233, March.
- Simon Jackman & Christian Kleiber & Achim Zeileis, 2007.
"Regression Models for Count Data in R,"
2007/24, Faculty of Business and Economics - University of Basel.
- Ajay Shah & Ila Patnaik, 2009.
"Does the Currency Regime Shape Unhedged Currency Exposure?,"
- Patnaik, Ila & Shah, Ajay, 2010. "Does the currency regime shape unhedged currency exposure?," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 760-769, September.
- Patnaik, Ila & Shah, Ajay, 2008. "Does the currency regime shape unhedged currency exposure," Working Papers 08/50, National Institute of Public Finance and Policy.
- Paola Brighi & Roberto Patuelli & Giuseppe Torluccio, 2012.
"Self-Financing of Traditional and R&D Investments: Evidence from Italian SMEs,"
Working Paper Series
61_12, The Rimini Centre for Economic Analysis.
- P. Brighi & R. Patuelli & G. Torluccio, 2012. "Self-Financing of Traditional and R&D Investments: Evidence from Italian SMEs," Working Papers wp845, Dipartimento Scienze Economiche, Universita' di Bologna.
- Kleiber, Christian & Zeileis, Achim, 2010.
"The Grunfeld Data at 50,"
20841, University Library of Munich, Germany.
- Claudio Lupi, . "Unit Root CADF Testing with R," Journal of Statistical Software, American Statistical Association, vol. 32(i02).
- Lupi, Claudio, 2009. "Covariate Augmented Dickey-Fuller Tests with R," Economics & Statistics Discussion Papers esdp09051, University of Molise, Dept. EGSeI.
- Millo, Giovanni, 2014. "Robust standard error estimators for panel models: a unifying approach," MPRA Paper 54954, University Library of Munich, Germany.
- Sarah Harris & Wendy Anderson & Musa Kilinc & Liam Fogarty, 2012. "The relationship between fire behaviour measures and community loss: an exploratory analysis for developing a bushfire severity scale," Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(2), pages 391-415, September.
- Achim Zeileis & Roger Koenker, . "Econometrics in R: Past, Present, and Future," Journal of Statistical Software, American Statistical Association, vol. 27(i01).
- Javier Contreras-Reyes & Wilfredo Palma, 2013. "Statistical analysis of autoregressive fractionally integrated moving average models in R," Computational Statistics, Springer, vol. 28(5), pages 2309-2331, October.
- Millo, Giovanni, 2014. "Maximum likelihood estimation of spatially and serially correlated panels with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 914-933.
- W. Lee, 2014. "Historical global analysis of occurrences and human casualty of extreme temperature events (ETEs)," Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(2), pages 1453-1505, January.
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