Results 251 to 260 of about 6,038,834 (301)
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American Economic Review, 2023
We propose a nonparametric test for the exclusion and monotonicity assumptions invoked in instrumental variable (IV) designs based on the random assignment of cases to judges. We show its asymptotic validity and demonstrate its finite-sample performance in simulations. We apply our test in an empirical setting from the literature examining the effects
Brigham Frandsen +2 more
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We propose a nonparametric test for the exclusion and monotonicity assumptions invoked in instrumental variable (IV) designs based on the random assignment of cases to judges. We show its asymptotic validity and demonstrate its finite-sample performance in simulations. We apply our test in an empirical setting from the literature examining the effects
Brigham Frandsen +2 more
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Latent Variable Models with Fixed Effects
Biometrics, 1996We discuss latent variable models that allow for fixed effect covariates, as well as covariates affecting the latent variable directly. Restricted maximum likelihood and maximum likelihood are used to estimate model parameters. A generalized likelihood ratio test can be used to test significance of the covariates effecting the latent outcomes.
Sammel, Mary Dupuis, Ryan, Louise M.
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Fixed Effects and Random Effects
2008One of the major benefits from using panel data as compared to cross-section data on individuals is that it enables us to control for individual heterogeneity. Not controlling for these unobserved individual specific effects leads to bias in the resulting estimates.
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Fixed- and Random-Effects Models
2021Deciding whether to use a fixed-effect model or a random-effects model is a primary decision an analyst must make when combining the results from multiple studies through meta-analysis. Both modeling approaches estimate a single effect size of interest.
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Are Fixed Effects Fixed? [PDF]
, 1997 In attempts to overcome the problem of omitted variables, the assumption of fixed effects is widely implemented when working with panel data. This paper examines the validity of this technique, in the context of estimating a production function using panels of US textile plants.
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Fixed-Effects Regression Modeling
2020This chapter presents fixed-effects regression modeling as a family of methods that describe a dependent variable in terms of one or more independent variables. The chapter focuses on multiple linear regression and on binomial logistic regression, discussing examples of regression analyses on the basis of corpus-linguistic data.
Martin Hilpert, Damián E. Blasi
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Fixed Effect Models and Fixed Coefficient Models
1992As noted in the introductory chapter, the simplest and most intuitive way to account for individual and/or time differences in behaviour, in the context of a panel data regression problem, is to assume that some of the regression coefficients are allowed to vary across individuals and/or through time.
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Spurious Fixed Effects Regression*
Oxford Bulletin of Economics and Statistics, 2011AbstractThis article shows that spurious regression results can occur for a fixed effects model with weak time series variation in the regressor and/or strong time series variation in the regression errors when the first‐differenced and Within‐OLS estimators are used. Asymptotic properties of these estimators and the related t‐tests and model selection
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Random Effects, Fixed Effects, Convolution, and Separation
Econometrica, 1981Mundlak, Yair, Yahav, Joseph A
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