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Causal inference with observational data AgEcon
Nichols, Austin.
Problems with inferring causal relationships from nonexperimental data are briefly reviewed, and four broad classes of methods designed to allow estimation of and inference about causal parameters are described: panel regression, matching or reweighting, instrumental variables, and regression discontinuity. Practical examples are offered, and discussion focuses on checking required assumptions to the extent possible.
Tipo: Article Palavras-chave: Xtreg; Psmatch2; Nnmatch; Ivreg; Ivreg2; Ivregress; Rd; Lpoly; Xtoverid; Ranktest; Causal inference; Match; Matching; Reweighting; Propensity score; Panel; Instrumental variables; Excluded instrument; Weak identification; Regression; Discontinuity; Local polynomial; Research Methods/ Statistical Methods.
Ano: 2007 URL: http://purl.umn.edu/119292
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Erratum and discussion of propensity–score reweighting AgEcon
Nichols, Austin.
Tipo: Article Palavras-chave: Xtreg; Psmatch2; Nnmatch; Ivreg; Ivreg2; Ivregress; Rd; Lpoly; Xtoverid; Ranktest; Causal inference; Match; Matching; Reweighting; Propensity score; Panel; Instrumental variables; Excluded instrument; Weak identification; Regression; Discontinuity; Local polynomial; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122619
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From the help desk: Local polynomial regression and Stata plugins AgEcon
Gutierrez, Roberto G.; Linhart, Jean Marie; Pitblado, Jeffrey S..
Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964) and Watson (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local means, but local polynomial smooths have better statistical properties. The computational complexity may, however, be alleviated by using a Stata plugin. In this article, we describe the locpoly command for performing local polynomial regression. The calculations involved are implemented in both ado-code and with a plugin, allowing the user to assess the speed improvement obtained from using the plugin. Source code for the plugin is also provided as part of the...
Tipo: Journal Article Palavras-chave: Local polynomial; Local linear; Smoothing; Kernel; Plugin; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116196
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