|
|
|
Registros recuperados: 23 | |
|
| |
|
| |
|
| |
|
|
Grendar, Marian; Judge, George G.. |
Methods, like Maximum Empirical Likelihood (MEL), that operate within the Empirical Estimating Equations (E3) approach to estimation and inference are challenged by the Empty Set Problem (ESP). We propose to return from E3 back to the Estimating Equations, and to use the Maximum Likelihood method. In the discrete case the Maximum Likelihood with Estimating Equations (MLEE) method avoids ESP. In the continuous case, how to make ML-EE operational is an open question. Instead of it, we propose a Patched Empirical Likelihood, and demonstrate that it avoids ESP. The methods enjoy, in general, the same asymptotic properties as MEL. |
Tipo: Working or Discussion Paper |
Palavras-chave: Maximum likelihood; Estimating equations; Empirical likelihood; Research Methods/ Statistical Methods. |
Ano: 2010 |
URL: http://purl.umn.edu/56691 |
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
|
Golan, Amos; Judge, George G.; Perloff, Jeffrey M.. |
Using a maximum entropy technique, we estimate the market shares of each firm in an industry using the available government summary statistics such as the four-firm concentration ratio (C4) and the Herfindahl-Hirschmann Index (HHI). We show that our technique is very effective in estimating the distribution of market shares in 20 industries. Our results provide support for the recent practice of using HHI rather than C4 as the key explanatory variable in many market power studies, if only one measure is to be used. |
Tipo: Working or Discussion Paper |
Palavras-chave: Industrial Organization; Marketing. |
Ano: 1995 |
URL: http://purl.umn.edu/25081 |
| |
|
|
Judge, George G.; Swanson, E.R.. |
Agricultural economists are often interested in characterizing or summarizing how economic processes and institutions have changed through time as well as what paths they are likely to take in future time periods. Given this interest or objective, we are therefore interested in methods of analysis that will accomplish these purposes and that are simple to apply. Within this context the major purpose of this paper is to discuss the concept of a Markov chain process and to indicate its potential usefulness in analyzing problems where detailed time-ordered data exist over some time span. As a particular vehicle for the discussion, a limited example concerning the past and potential size distribution of a sample of hog-producing firms in central Illinois will... |
Tipo: Journal Article |
Palavras-chave: Research Methods/ Statistical Methods. |
Ano: 1962 |
URL: http://purl.umn.edu/22465 |
| |
|
| |
|
| |
|
|
Lee, Joanne; Cho, Wendy K.; Judge, George G.. |
In 1881, Newcomb conjectured that the first significant digits (FSDs) of numbers in statistical tables would follow a logarithmic distribution with the digit “1” occurring most often. However, because Newcomb’s proposal was not presented with a theoretical basis, it was not given much attention. Fifty-seven years later, Benford argued for the same principle and showed it was relevant to a large range of data sets, and the logarithmic FSD distribution became known as “Benford’s Law.” In the mid-1940s, Stigler claimed Benford’s Law contained a theoretical inconsistency and supplied an alternative derivation for the distribution of FSDs. In this paper, we examine the theoretical basis of the Stigler distribution and extend his reasoning by incorporating FSD... |
Tipo: Working or Discussion Paper |
Palavras-chave: Benford's law; Stigler's law; Power law; Maximum entropy; Distance measures; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; C10; C24. |
Ano: 2009 |
URL: http://purl.umn.edu/47000 |
| |
|
|
Grendar, Marian; Judge, George G.. |
Criterion choice is such a hard problem in information recovery and in estimation and inference. In the case of inverse problems with noise, can probabilistic laws provide a basis for empirical estimator choice? That is the problem we investigate in this paper. Large Deviations Theory is used to evaluate the choice of estimator in the case of two fundamental situations-problems in modelling data. The probabilistic laws developed demonstrate that each problem has a unique solution-empirical estimator. Whether other members of the empirical estimator family can be associated a particular problem and conditional limit theorem, is an open question. |
Tipo: Working or Discussion Paper |
Palavras-chave: Research Methods/ Statistical Methods. |
Ano: 2006 |
URL: http://purl.umn.edu/25084 |
| |
Registros recuperados: 23 | |
|
|
|