Author: Kazuhiro Ōtani
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
Book Description
Exact Distribution of a Pre-test Estimator for Regression Error Variance when There are Omitted Variables
Developing Econometrics
Author: Hengqing Tong
Publisher: John Wiley & Sons
ISBN: 1119960908
Category : Business & Economics
Languages : en
Pages : 489
Book Description
Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.
Publisher: John Wiley & Sons
ISBN: 1119960908
Category : Business & Economics
Languages : en
Pages : 489
Book Description
Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.
The Exact Density and Distribution Functions of the Inequality Constrained and Pre-test Estimators
Author: Alan T. K. Wan
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 40
Book Description
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 40
Book Description
Quantitative Econometrics
Author:
Publisher: Allied Publishers
ISBN: 9788170238171
Category :
Languages : en
Pages : 402
Book Description
Publisher: Allied Publishers
ISBN: 9788170238171
Category :
Languages : en
Pages : 402
Book Description
The Exact Powers of Some Autocorrelation Tests when Relevant Regressors are Omitted
Author: John P. Small
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 32
Book Description
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 32
Book Description
The Exact Distribution of a Simple Pre-test Estimator
Author: David E. A. Giles
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 36
Book Description
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 36
Book Description
Mathematical Reviews
Finite Population Corrections of the Horvitz-Thompson Estimator and Their Application in Estimating the Variance of Regression Estimators
Author: Zhao Ouyang
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 16
Book Description
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 16
Book Description
The Exact Distribution of a Least Squares Regression Coefficient Estimator After a Preliminary T-test
Author: David E. A. Giles
Publisher:
ISBN:
Category : Least squares
Languages : en
Pages : 17
Book Description
Publisher:
ISBN:
Category : Least squares
Languages : en
Pages : 17
Book Description
Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator
Author: Charles R. Nelson
Publisher:
ISBN:
Category : Instrumental variables (Statistics)
Languages : en
Pages : 34
Book Description
New results on the exact small sample distribution of the instrumental variable estimator are presented by studying an important special case. The exact closed forms for the probability density and cumulative distribution functions are given. There are a number of surprising findings. The small sample distribution is bimodal. with a point of zero probability mass. As the asymptotic variance grows large, the true distribution becomes concentrated around this point of zero mass. The central tendency of the estimator may be closer to the biased least squares estimator than it is to the true parameter value. The first and second moments of the IV estimator are both infinite. In the case in which least squares is biased upwards, and most of the mass of the IV estimator lies to the right of the true parameter, the mean of the IV estimator is infinitely negative. The difference between the true distribution and the normal asymptotic approximation depends on the ratio of the asymptotic variance to a parameter related to the correlation between the regressor and the regression, error. In particular, when the instrument is poorly correlated with the regressor, the asymptotic approximation to the distribution of the instrumental variable estimator will not be very accurate.
Publisher:
ISBN:
Category : Instrumental variables (Statistics)
Languages : en
Pages : 34
Book Description
New results on the exact small sample distribution of the instrumental variable estimator are presented by studying an important special case. The exact closed forms for the probability density and cumulative distribution functions are given. There are a number of surprising findings. The small sample distribution is bimodal. with a point of zero probability mass. As the asymptotic variance grows large, the true distribution becomes concentrated around this point of zero mass. The central tendency of the estimator may be closer to the biased least squares estimator than it is to the true parameter value. The first and second moments of the IV estimator are both infinite. In the case in which least squares is biased upwards, and most of the mass of the IV estimator lies to the right of the true parameter, the mean of the IV estimator is infinitely negative. The difference between the true distribution and the normal asymptotic approximation depends on the ratio of the asymptotic variance to a parameter related to the correlation between the regressor and the regression, error. In particular, when the instrument is poorly correlated with the regressor, the asymptotic approximation to the distribution of the instrumental variable estimator will not be very accurate.