Found 8 article(s) for author 'Maximilian Kasy'

Optimal Taxation and Insurance Using Machine Learning

Optimal Taxation and Insurance Using Machine Learning. Maximilian Kasy, April 10, 2017, Paper, “How should one use (quasi-)experimental evidence when choosing policies such as tax rates, health insurance copay, unemployment benefit levels, class sizes in schools, etc.? This paper suggests an approach based on maximizing posterior expected social welfare, combining insights from (i) optimal policy theory as developed in the field of public finance, and (ii) machine learning using Gaussian process priors. We provide explicit formulas for posterior expected social welfare and optimal policies in a wide class of policy problems.Link

Tags: , , , , , , ,

How to use Economic Theory to Improve Estimators, with an Application to Labor Demand and Wage Inequality

How to use Economic Theory to Improve Estimators, with an Application to Labor Demand and Wage Inequality. Maximilian Kasy, March 12, 2016, Paper. “Economic theory, when it has empirical content, provides testable restrictions on empirically identified objects. These empirical objects might be estimated in an unrestricted way, leading to estimates of potentially large variance, or subject to the theoretical restrictions, leading to estimates of lower variance that are potentially biased, inconsistent, and non-robust.Link

Tags: , , , ,

How to use economic theory to improve estimators, with an application to labor demand and wage inequality in Europe

How to use economic theory to improve estimators, with an application to labor demand and wage inequality in Europe. Maximilian Kasy, August 28, 2015, Paper. “Economic theory, when it has empirical content, provides testable restrictions on empirically identified objects. These empirical objects might be estimated in an unrestricted way, leading to estimates of potentially large variance, or subject to the theoretical restrictions, leading to estimates of lower variance which are potentially biased, inconsistent, and non-robust. We propose an alternative approach, based on the empirical Bayes paradigm, which avoids both large variance…Link

Tags: , ,

Empirical research on economic inequality

Empirical research on economic inequality. Maximilian Kasy, April 7, 2015, Paper. “These are lecture notes for a course on ‘Empirical research on economic inequality.’ The purpose of this class is twofold. First, to teach you about economic inequality, some of its causes, and how it is affected by policy. Second, to teach you econometric methods that have been used in the literature on economic inequality, which will help prepare youto conduct your own research on this or related topics, perhaps in an undergrad thesis. These lecture notes are intended to accompany the reading of the original articles assigned for this class and listed in section 1.3, rather than serving as a stand-alone textbook…” Link

Tags: ,

Labor demand and wage inequality in Europe – an empirical Bayes approach

Labor demand and wage inequality in Europe – an empirical Bayes approach, Maximilian Kasy, February 25, 2015, Paper, To what extent can changes in the distribution of wages be explained by changes in labor supply of various groups (due to demographic change, migration, or expanded access to education), and to what extent are other factors (technical and institutional change) at work? We develop a flexible methodology for answering this central question of labor economics, using an empirical Bayes approach, without imposing the restrictions on heterogeneity and on cross-elasticities of labor demand assumed by the literatureLink

Tags: , , , , ,

Who Wins, Who Loses? Tools for Distributional Policy Evaluation

Who Wins, Who Loses? Tools for Distributional Policy Evaluation, Maximilian Kasy, July 28, 2014, Paper. “Most policy changes generate winners and losers. Political economy and optimal policy suggest questions such as: Who wins, who loses? How much? Given a choice of welfare weights, what is the impact of the policy change on social welfare? This paper proposes a framework to empirically answer such questions…” Link

Tags: , ,

Using data to inform policy

Using data to inform policy. Maximilian Kasy, June 16, 2014, Paper. “In this paper, a general framework is proposed for the use of (quasi-) experimental data when choosing policies such as tax rates or the level of inputs in a production process. The data are used to update expectations about social welfare as a function of policy, and the policy is chosen to maximize expected social welfare. We characterize the properties of the implied decision function…” Link Verified October 13, 2014

Tags: , , ,