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A Note on Nonparametric Estimation With Constructed Variables and Generated Regressors
Sperlich, Stefan - 2018
This article gives the asymptotic properties for nonparametric kernel based density and regression estimators when one of the variables, respectively regressors, had to be pre-estimated. Those variables are known as constructed variables or generatedregressors, and their impact on the -nal...
Persistent link: https://www.econbiz.de/10014224472
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Introducing Linear Regression : An Example Using Basketball Statistics
Arnold, Tom - 2011
context. This paper uses basketball statistics to demonstrate the purpose of linear regression and to explain how to interpret …
Persistent link: https://www.econbiz.de/10013131742
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Bootstrap tests for overidentification in linear regression models
Davidson, Russell; MacKinnon, James G. - 2014 - March 2014
limited-information maximum likelihood. We show that all the test statistics, like the ones used for inference on the … related to the well-known test statistic of Anderson and Rubin. The distributions of the overidentification statistics are …
Persistent link: https://www.econbiz.de/10010128349
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Model Specifications and Endogeneity
Nakamura, Alice Orcutt - 2013
This paper considers the treatment of endogenous explanatory variables in the work of the Cowles Commission and in Carl Christ's classic 1966 textbook, and certain problems that arise when this approach is followed in areas such as the study of female labor supply where a prior knowledge is...
Persistent link: https://www.econbiz.de/10013081125
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Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models
Cizek, Pavel - 2007
The binary-choice regression models such as probit and logit are used to describe the effect of explanatory variables on a binary response variable. Typically estimated by the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedasticity and data...
Persistent link: https://www.econbiz.de/10012730272
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Efficient Robust Estimation of Regression Models
Cizek, Pavel - 2007
This paper introduces a new class of robust regression estimators. The proposed twostep least weighted squares (2S-LWS) estimator employs data-adaptive weights determined from the empirical distribution, quantile, or density functions of regression residuals obtained from an initial robust fit....
Persistent link: https://www.econbiz.de/10012731904
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Sheep in wolf's clothing : using the least squares criterion for quantile estimation
Chen, Heng - 2014
statistics within these bins. The quantile coupling allows one to apply the standard Gaussian-based estimation and inference to …
Persistent link: https://www.econbiz.de/10010362928
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A new matrix statistic for the hausman endogeneity test under heteroskedasticity
Papadopoulos, Alecos - In: Econometrics : open access journal 11 (2023) 4, pp. 1-11
We derive a new matrix statistic for the Hausman test for endogeneity in cross-sectional Instrumental Variables estimation, that incorporates heteroskedasticity in a natural way and does not use a generalized inverse. A Monte Carlo study examines the performance of the statistic for different...
Persistent link: https://www.econbiz.de/10014507912
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Asymptotic Variance of Test Statistics in ML and QML Frameworks
Bera, Anil K. - 2020
In this study, we consider the test statistics that can be written as the sample average of data and derive their … some well-known test statistics: (i) the skewness statistic, (ii) the kurtosis statistic, (iii) the Cox statistic, (iv) the … the asymptotic variance of test statistics, and therefore, they are recommended for practical applications …
Persistent link: https://www.econbiz.de/10012853408
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Visualization and Statistical Modeling of Financial Big Data : Log-Linear Modeling With Skew Error
Jimichi, Masayuki - 2018
In this paper, we consider the visualization and statistical modeling of financial data (e.g., sales, assets) for many global firms which are listed and delisted. This study presents an exploratory data analysis carried out in the R programming language. The results show that a log-linear model...
Persistent link: https://www.econbiz.de/10012921034