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Let's get LADE: Robust estimation of semiparametric multiplicative volatility models
Koo, Bonsoo; Linton, Oliver - 2013
robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …
Persistent link: https://www.econbiz.de/10010318677
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Identification, data combination and the risk of disclosure
Komarova, Tatiana; Nekipelov, Denis; Yakovlev, Evgeny - 2011
Businesses routinely rely on econometric models to analyze and predict consumer behavior. Estimation of such models may require combining a firm's internal data with external datasets to take into account sample selection, missing observations, omitted variables and errors in measurement within...
Persistent link: https://www.econbiz.de/10010288308
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A Bayesian mixed logit-probit model for multinomial choice
Burda, Martin; Harding, Matthew; Hausman, Jerry - 2008
driving distance to the supermarket based on their respective locations. Our semi-parametric approach allows us to identify a …
Persistent link: https://www.econbiz.de/10010288443
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On the identification of structural linear functionals
Escanciano, Juan Carlos; Li, Wei - 2013
This paper asks which aspects of a structural Nonparametric Instrumental Variables Regression (NPIVR) can be identified well and which ones cannot. It contributes to answering this question by characterizing the identified set of linear continuous functionals of the NPIVR under norm constraints....
Persistent link: https://www.econbiz.de/10010368214
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Using penalized likelihood to select parameters in a random coefficients multinomial logit model
Horowitz, Joel; Nesheim, Lars - 2019
The multinomial logit model with random coefficients is widely used in applied research. This paper is concerned with estimating a random coefficients logit model in which the distribution of each coefficient is characterized by finitely many parameters. Some of these parameters may be zero. The...
Persistent link: https://www.econbiz.de/10012146402
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Partial independence in nonseparable models
Masten, Matthew A.; Poirier, Alexandre - 2016
We analyze identification of nonseparable models under three kinds of exogeneity assumptions weaker than full statistical independence. The first is based on quantile independence. Selection on unobservables drives deviations from full independence. We show that such deviations based on quantile...
Persistent link: https://www.econbiz.de/10011594336
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Set inferences and sensitivity analysis in semiparametric conditionally identified models
Escanciano, Juan Carlos; Zhu, Lin - 2013
semiparametric models. The main working assumption is that the finite-dimensional parameter of interest and the possibility infinite … semiparametric two-step GMM estimators, and it uses the uniformity to establish set inferences, including confidence regions for the …
Persistent link: https://www.econbiz.de/10010368225
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Inference on breakdown frontiers
Masteny, Matthew A.; Poirierz, Alexandre - 2017
A breakdown frontier is the boundary between the set of assumptions which lead to a specific conclusion and those which do not. In a potential outcomes model with a binary treatment, we consider two conclusions: First, that ATE is at least a specific value (e.g., nonnegative) and second that the...
Persistent link: https://www.econbiz.de/10011941455
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Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models
Chen, Le-yu; Lee, Sokbae - 2017
This paper studies inference of preference parameters in semiparametric discrete choice models when these parameters … the semiparametric modeling restrictions, we show that the identified set can be equivalently formulated by moment … variety of semiparametric models under which the sign of conditional expectation of a certain transformation of the outcome is …
Persistent link: https://www.econbiz.de/10011941518
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Locally robust semiparametric estimation
Chernozhukov, Victor; Escanciano, Juan Carlos; … - 2016
This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions …
Persistent link: https://www.econbiz.de/10011594341