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Robust Inference on Income Inequality : t-Statistic Based Approaches
Ibragimov, Rustam; Kattuman, Paul; Skrobotov, Anton - 2021
Empirical analyses on income and wealth inequality and those in other fields in economics and finance often face the … of the recently developed \textit{t}-statistic based robust inference approaches in the analysis of inequality measures … equality of two parameters of interest (e.g., a test of equality of inequality measures in two regions or countries considered …
Persistent link: https://www.econbiz.de/10013228108
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Visualizing and Testing Convergence Between Two Income Distributions
Bishop, John A.; Chow, K. Victor; Zeager, Lester A. - In: Journal of Income Distribution 19 (2010) 1, pp. 2-19
We use the Interdistributional Lorenz Curves (ILCs) of Butler and McDonald (1987) to visualize convergence or divergence between income distributions. To illustrate the idea, we compare income distributions from Spain, Italy, and Germany. We also offer methods to test for significant differences...
Persistent link: https://www.econbiz.de/10010711979
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A nifty fix for published distribution statistics : simplified distribution-free statistical inference
Beach, Charles M. - 2021
This paper applies the tool box measures of disaggregative income inequality characterization and the statistical …
Persistent link: https://www.econbiz.de/10012670923
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Sample sizes for reliably estimating lower and upper income shares in income distribution analysis
Beach, Charles M. - 2023
published by statistical agencies as measures of the distribution of income inequality - to calculate how large a survey sample …
Persistent link: https://www.econbiz.de/10014253712
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More on confidence intervals for partially identified parameters
Stoye, Jörg (contributor) - 2008
This paper extends Imbens and Manski’s (2004) analysis of confidence intervals for interval identified parameters. For their final result, Imbens and Manski implicitly assume superefficient estimation of a nuisance parameter. This appears to have gone unnoticed before, and it limits the...
Persistent link: https://www.econbiz.de/10003739665
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Predictive inference for integrated volatility
Corradi, Valentina (contributor);  … - 2006
In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...
Persistent link: https://www.econbiz.de/10003698497
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Intersection bounds : estimation and inference
Chernozhukov, Victor; Lee, Sokbae; Rosen, Adam M. - 2011
asymptotically valid inference based on these processes. Our construction also provides new adaptive inequality/moment selection …
Persistent link: https://www.econbiz.de/10009375645
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A practical asymptotic variance estimator for two-step semiparametric estimators
Ackerberg, Daniel A.; Chen, Xiaohong; Hahn, Jinyong - 2010 - Final Version: July, 2010
The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the...
Persistent link: https://www.econbiz.de/10009230390
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Practical and theoretical advances in inference for partially identified models
Canay, Ivan A.; Shaikh, Azeem M. - 2016
This paper surveys some of the recent literature on inference in partially identified models. After reviewing some basic concepts, including the definition of a partially identified model and the identified set, we turn our attention to the construction of confidence regions in partially...
Persistent link: https://www.econbiz.de/10011417422
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Inference under covariate-adaptive randomization
Bugni, Federico A.; Canay, Ivan A.; Shaikh, Azeem M. - 2015
This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so...
Persistent link: https://www.econbiz.de/10011309722