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Bootstrapping a conditional moments test for normality after tobit estimation AgEcon
Drukker, David M..
Categorical and limited dependent variable models are routinely estimated via maximum likelihood. It is well-known that the ML estimates of the parameters are inconsistent if the distribution or the skedastic component is misspecified. When conditional moment tests were first developed by Newey (1985) and Tauchen (1985), they appeared to offer a wide range of easy-to-compute specification tests for categorical and limited dependent variable models estimated by maximum likelihood. However, subsequent studies found that using the asymptotic critical values produced severe size distortions. This paper presents simulation evidence that the standard conditional moment test for normality after tobit estimation has essentially no size distortion and reasonable...
Tipo: Journal Article Palavras-chave: Conditional moment tests; Bootstrap; Tobit; Normality; Research Methods/ Statistical Methods.
Ano: 2002 URL: http://purl.umn.edu/115956
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Generating Halton sequences using Mata AgEcon
Drukker, David M.; Gates, Richard.
This paper discusses the advantages of Halton sequences over pseudorandom uniform numbers when using simulation to approximate integrals numerically. We describe two types of sequences and give Mata examples. Finally, we document the Mata function halton(), currently in release 9.1 of Stata, which computes both a Halton sequence and its Hammersley variant. Options to use these point sets are available in the Stata 9 program asmprobit, a multinomial-probit estimator, and in the Stata 9.1 Mata function ghk(), the Geweke–Hajivassiliou–Keane multivariate-normal simulator.
Tipo: Journal Article Palavras-chave: Halton(); Halton set; Hammersley set; Quasirandom numbers; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/117570
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Implementing matching estimators for average treatment effects in Stata AgEcon
Abadie, Alberto; Drukker, David M.; Herr, Jane Leber; Imbens, Guido W..
This paper presents an implementation of matching estimators for average treatment effects in Stata. The nnmatch command allows you to estimate the average effect for all units or only for the treated or control units; to choose the number of matches; to specify the distance metric; to select a bias adjustment; and to use heteroskedastic-robust variance estimators.
Tipo: Journal Article Palavras-chave: Nnmatch; Average treatment effects; Matching; Exogeneity; Unconfoundedness; Ignorability; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116250
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Importing Federal Reserve economic data AgEcon
Drukker, David M..
This note describes freduse, which imports datasets from the Federal Reserve economic data (FRED®) repository.
Tipo: Journal Article Palavras-chave: Freduse; Federal Reserve economic data repository; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/117588
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Testing for serial correlation in linear panel-data models AgEcon
Drukker, David M..
Because serial correlation in linear panel-data models biases the standard errors and causes the results to be less efficient, researchers need to identify serial correlation in the idiosyncratic error term in a panel-data model. A new test for serial correlation in random- or fixed-effects one-way models derived by Wooldridge (2002) is attractive because it can be applied under general conditions and is easy to implement. This paper presents simulation evidence that the new Wooldridge test has good size and power properties in reasonably sized samples.
Tipo: Journal Article Palavras-chave: Panel data; Serial correlation; Specification tests; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116069
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