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Registros recuperados: 11
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Stata tip 38: Testing for groupwise heteroskedasticity AgEcon
Baum, Christopher F..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/119249
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Stata tip 45: Getting those data into shape AgEcon
Baum, Christopher F.; Cox, Nicholas J..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2007 URL: http://purl.umn.edu/119275
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Residual diagnostics for cross-section time series regression models AgEcon
Baum, Christopher F..
These routines support the diagnosis of groupwise heteroskedasticity and cross-sectional correlation in the context of a regression model fit to pooled cross-section time series (xt) data.
Tipo: Journal Article Palavras-chave: Fixed effects; Groupwise heteroskedasticity; Contemporaneous correlation; Research Methods/ Statistical Methods.
Ano: 2001 URL: http://purl.umn.edu/115940
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Evaluating concavity for production and cost functions AgEcon
Baum, Christopher F.; Linz, Teresa.
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2009 URL: http://purl.umn.edu/122709
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Instrumental variables and GMM: Estimation and testing AgEcon
Baum, Christopher F.; Schaffer, Mark E.; Stillman, Steven.
We discuss instrumental variables (IV) estimation in the broader context of the generalized method of moments (GMM), and describe an extended IV estimation routine that provides GMM estimates as well as additional diagnostic tests. Stand-alone test procedures for heteroskedasticity, overidentification, and endogeneity in the IV context are also described.
Tipo: Journal Article Palavras-chave: Instrumental variables; Generalized method of moments; Endogeneity; Heteroskedasticity; Overidentifying restrictions; Clustering; Intra-group correlation; Research Methods/ Statistical Methods.
Ano: 2002 URL: http://purl.umn.edu/116029
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Enhanced routines for instrumental variables/generalized method of moments estimation and testing AgEcon
Baum, Christopher F.; Schaffer, Mark E.; Stillman, Steven.
We extend our 2003 paper on instrumental variables and generalized method of moments estimation, and we test and describe enhanced routines that address heteroskedasticity- and autocorrelation-consistent standard errors, weak instruments, limited-information maximum likelihood and k-class estimation, tests for endogeneity and Ramsey’s regression specification-error test, and autocorrelation tests for instrumental variable estimates and panel-data instrumental variable estimates.
Tipo: Article Palavras-chave: Ivactest; Ivendog; Ivhettest; Ivreg2; Ivreset; Overid; Ranktest; Instrumental variables; Weak instruments; GMM; Endogeneity; Heteroskedasticity; Serial correlation; HAC standard errors; LIML; CUE; Overidentifying restrictions; Frisch–Waugh–Lovell theorem; RESET; Cumby–Huizinga test; Research Methods/ Statistical Methods.
Ano: 2007 URL: http://purl.umn.edu/119291
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Stata tip 63: Modeling proportions AgEcon
Baum, Christopher F..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122595
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Stata tip 37: And the last shall be first AgEcon
Baum, Christopher F..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/119248
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Stata tip 73: append with care! AgEcon
Baum, Christopher F..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2009 URL: http://purl.umn.edu/122710
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Stata tip 40: Taking care of business AgEcon
Baum, Christopher F..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2007 URL: http://purl.umn.edu/119261
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Stata: The language of choice for time-series analysis? AgEcon
Baum, Christopher F..
This paper discusses the use of Stata for the analysis of time series and panel data. The evolution of time-series capabilities in Stata is reviewed. Facilities for data management, graphics, and econometric analysis from both official Stata and the user community are discussed. A new routine to provide moving-window regression estimates—rollreg—is described, and its use illustrated.
Tipo: Journal Article Palavras-chave: Time-series analysis; Time-series data; Time-series modeling; Moving-window regression; Rolling regression; Research Methods/ Statistical Methods.
Ano: 2005 URL: http://purl.umn.edu/117499
Registros recuperados: 11
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