윤정모 교수
Jungmo Yoon
한양대학교 경제금융학부 · 수학
연구실 소개
윤정모 교수의 연구실은 기업 집단, 특히 한국의 재벌집단(차베올)의 성과와 내재적 문제에 중점을 두고 있으며, 경제 성과를 재정적 효율성보다 생산성 효율성 기준으로 분석합니다. 기업의 투자 비효율성과 기술 역량의 변화가 위기 후 성과에 미치는 영향을 분석하는 데 초점을 맞추고 있으며, 패널 데이터 분석에서의 이질적 분산과 자기상관 문제를 해결하기 위한 고급 통계적 방법론 개발에도 기여하고 있습니다. 특히, 양자화 회귀 모델의 표준오차 보정 및 균일 추론 기법 개발을 통해 경제학적 분석의 정확성과 신뢰성을 제고하고자 합니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15This article differentiates itself from the large volume of existing literature on business groups, such as Korean chaebols, in several aspects. First, it uses productive efficiency rather than financial efficiency as a performance measure. Second, it defines chaebols in three alternative ways and checks whether the results are robust. Third and most important, it explains the sources of the post‐crisis change in the performance of Korean chaebols in terms of technological capabilities and inves
The existence of the business groups has been associated with market failure in emerging economies, and thus their performance has been argued and found to have declined with development of market institutions surrounding them. This paper takes up this issue of long-term performance of the business groups but argues that it has also to do with the internal problems, such as changes in the ownership and governance structure. It finds, with the Korea data and new method and theoretical grounds, th
This study develops methods for conducting uniform inference on quantile treatment effects for sharp regression discontinuity designs. We develop a score test for the treatment significance hypothesis and Wald-type tests for the hypotheses related to treatment significance, homogeneity, and unambiguity. The bias from the nonparametric estimation is studied in detail. In particular, we show that under some conditions, the asymptotic distribution of the score test is unaffected by the bias, withou
This study develops cluster robust inference methods for panel quantile regression (QR) models with individual fixed effects, allowing for temporal correlation within each individual. The conventional QR standard errors can seriously underestimate the uncertainty of estimators and, therefore, overestimate the significance of effects, when outcomes are serially correlated. Thus, we propose a clustered covariance matrix (CCM) estimator to solve this problem. The CCM estimator is an extension of th
The English rule prescribes that the loser of a lawsuit pays the winner's litigation costs. Previous research on the English rule finds that plaintiffs win more often at trial, receive higher awards, and receive larger settlements. Theory predicts that the English rule discourages settlement by raising the threshold payment necessary for settlement. In this paper, we reexamine the Florida experiment with the English rule by placing bounds on the selection effects. We find that the mean and media
This study considers an estimator for the asymptotic variance-covariance matrix in time-series quantile regression models which is robust to the presence of heteroscedasticity and autocorrelation. When regression errors are serially correlated, the conventional quantile regression standard errors are invalid. The proposed solution is a quantile analogue of the Newey-West robust standard errors. We establish the asymptotic properties of the heteroscedasticity and autocorrelation consistent (HAC)
This paper presents estimation methods and asymptotic theory for the analysis of a nonparametrically specified conditional quantile process. Two estimators based on local linear regressions are proposed. The first estimator applies simple inequality constraints while the second uses rearrangement to maintain quantile monotonicity. The bandwidth parameter is allowed to vary across quantiles to adapt to data sparsity. For inference, the paper first establishes a uniform Bahadur representation and
Abstract Some linkages between kernel and penalty methods of density estimation are explored. It is recalled that classical Gaussian kernel density estimation can be viewed as the solution of the heat equation with initial condition given by data. We then observe that there is a direct relationship between the kernel method and a particular penalty method of density estimation. For this penalty method, solutions can be characterized as a weighted average of Gaussian kernel density estimates, the
Replication Data for: Estimating the Effects of the English Rule on Litigation Outcomes
The English rule for fee allocation prescribes that the loser of a lawsuit pay the winner’s litigation costs. Economic theory predicts that the English rule discourages settlement, increases litigation costs and encourages meritorious claims. The principal empirical work on the impact of the English rule by Hughes and Snyder (1990, 1995) relies on data from Florida’s use of the Rule for medical malpractice claims between 1980 and 1985. The principal findings are that plaintiffs win more often at
대표 연구 분야
윤정모 교수의 연구를 Nubint에서 더 깊이 살펴보세요
이 연구실의 논문을 앱에서 열어 AI와 함께 읽고, 핵심을 요약하고, 내 글에 인용하세요.