Classical and Bayesian Inference for Income Distributions using Grouped Data
Bibliographic Data
| ID | 21512876 |
|---|---|
| Authors | Tobias Eckernkemper (Institute of Econometrics and Statistics University of Cologne Universitaetsstr. 22a D‐50937 Cologne Germany, corresponding author), Bastian Gribisch (0000-0002-6289-1799, Institute of Econometrics and Statistics University of Cologne Universitaetsstr. 22a D‐50937 Cologne Germany, corresponding author) |
| Year | 2021 |
| Volume | 83 |
| Issue | 1 |
| Pages | 32-65 |
| Publication date | 2021-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Oxford Bulletin of Economics and Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0305-9049 • E-ISSN: 1468-0084 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/obes.12396 |
| OpenAlex | W3083297324 |
| Language | EN |
| Citations received | 3 |
| References cited | 24 |
We propose a general framework for Maximum Likelihood (ML) and Bayesian estimation of income distributions based on grouped data information. The asymptotic properties of the ML estimators are derived and Bayesian parameter estimates are obtained by Monte Carlo Markov Chain (MCMC) techniques. A comprehensive simulation experiment shows that obtained estimates of the income distribution are very precise and that the proposed estimation framework improves the statistical precision of parameter estimates relative to the classical multinomial likelihood. The estimation approach is finally applied to a set of countries included in the World Bank database PovcalNet
Bayes estimator · Bayesian inference · Bayesian probability · Data set · Econometrics · Estimator · Grouped data · Inference · Markov chain Monte Carlo · Multinomial distribution · Statistical inference · Statistics · Computer Science · Financial Risk and Volatility Modeling · Income, Poverty, and Inequality · Mathematics · Statistical Distribution Estimation and Applications · Artificial Intelligence
Stochastic Volatility
Some Generalized Functions for the Size Distribution of Income
Some Generalized Functions for the Size Distribution of Income
Distribution-Free Statistical Inference with Lorenz Curves and Income Shares
A Unified Approach to Estimating and Testing Income Distributions With Grouped Data
Inference for Income Distributions Using Grouped Data
Estimating and Combining National Income Distributions Using Limited Data
Global Income Distributions and Inequality, 1993 and 2000
China's Income Distribution, 1985–2001
Advanced Econometrics
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,6 |
| Citation span | 2021 - 2025 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |