황윤재 교수
Yoon Jae Whang
서울대학교 경제학부 · 수학
연구실 소개
황윤재 교수의 연구실은 경제학적 이론과 실증 분석을 융합하여 소득 불평등, 기업결합의 경쟁효과, 통신시장의 수요 구조, 시장의 경계 설정, 정책 평가를 위한 행정데이터 활용 등 다양한 분야에서 실증적 연구를 수행하고 있습니다. 특히 가구 내 소득 공유 메커니즘과 정책적 영향을 분석하는 데 초점을 맞추며, 시계열 및 패널 데이터 기반의 고도화된 계량경제모형을 활용합니다. 또한 증거기반 정책 수립을 위한 정부 데이터의 활용 가능성과 공적 자원의 효율적 배분을 모색하는 연구도 활발히 진행 중입니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15This paper derives the asymptotic distribution of a smoothing-based estimator of the Lyapunov exponent for a stochastic time series under two general scenarios. In the first case, we are able to establish root-T consistency and asymptotic normality, while in the second case, which is more relevant for chaotic processes, we are only able to establish asymptotic normality at a slower rate of convergence. We provide consistent confidence intervals for both cases. We apply our procedures to simulate
This book offers an up-to-date, comprehensive coverage of stochastic dominance and its related concepts in a unified framework. A method for ordering probability distributions, stochastic dominance has grown in importance recently as a way to measure comparisons in welfare economics, inequality studies, health economics, insurance wages, and trade patterns. Whang pays particular attention to inferential methods and applications, citing and summarizing various empirical studies in order to relate
We develop a general class of nonparametric tests for treatment effects conditional on covariates. We consider a wide spectrum of null and alternative hypotheses regarding conditional treatment effects, including (i) the null hypothesis of the conditional stochastic dominance between treatment and control groups; ii) the null hypothesis that the conditional average treatment effect is positive for each value of covariates; and (iii) the null hypothesis of no distributional (or average) treatment
This paper develops a test of autocorrelation in the presence of heteroskedasticity of unknown form in the nonlinear regression model. The test statistic is based on the sample autocovariance of the residuals standardized by a nonparametric kernel estimate of the unknown heteroskedasticity function. Under appropriate conditions, the test statistic is shown to have a limiting chi-square distribution. Local power and consistency results for the test are also established. Monte Carlo experiments sh
This book, Topics in Advanced Econometrics , is written primarily as a textbook for an advanced graduate econometrics course. The topics covered include consistent model specification testing, unit roots and cointegration, and nonparametric regression estimation; they are mainly the topics in which Professor Bierens has made significant contributions to the literature over the last 15 years. This book is unusual as a textbook in the sense that it treats both cross-sectional and time series (i.e.
This chapter considers specification testing for a linear quantile regression model. The null hypothesis of interest is that the linear quantile regression function is correctly specified. The alternative hypothesis is the negation of the null hypothesis – that is, that the quantile regression function is not linear.
AND KEYWORDS Abstract We propose a new test of the stochastic dominance efficiency of a given portfolio over a class of portfolios. We establish its null and alternative asymptotic properties, and define a method for consistently estimating critical values. We present some numerical evidence that our tests work well in moderate sized samples. Free Keywords Stochastic Dominance, Portfolio Diversification, Asset Pricing, Portfolio Analysis Availability The ERIM Report Series is distributed through
We provide a test of the Monday effect in daily stock index returns. Unlike previous studies we define the Monday effect based on the stochastic dominance criterion. This is a stronger criterion than those based on comparing means used in previous work and has a well defined economic meaning. We apply our test to a number of stock indexes including large caps and small caps as well as UK and Japanese indexes. We find strong evidence of a Monday effect in many cases under this stronger criterion.
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