The effect of population composition by age on government spending policy

There is a recurrent assertion that the elderly want more public resources to be spent on social protection and health, the young want more on education, and such preferences are reflected in the actual government spending policy. This study aims to empirically confirm whether the assertion is valid in OECD countries. For that goal, we propose an estimation method to exploit the comparison of the actual share of government expenditure and its theoretical share by using aggregate data. The empirical finding is consistent with the recurrent assertion in the sense that the fraction of the young has a significantly negative effect of the spending share of social protection and health but a positive effect on the spending share for education even though we can not find a significant effect of the elderly. In particular, ageing leads to a smaller fraction of the young and a larger fraction of the elderly. Hence, the empirical finding predicts that the ageing trend is likely to bring more public resources to the social protection and health areas, and less public resources to education. © 2020, Korean Econometric Society. All rights reserved

AMH Copula ML Estimation for the Sample Selection Model

In this paper, we propose a copula ML estimation method for the sample selection model using the Ali-Mikhail-Haq (AMH) copula. The proposed AMH copula ML estimation is compared with the well-known bivariate ML estimation and Heckman's two-step estimation. Monte Carlo experiments are conducted to compare their performance in terms of the mean squared error (MSE) depending on the following 2 conditions: (i) whether the imposed distributional assumption is correct, and (ii) whether some regressors of the participation and outcome equation are correlated. The results of the experiments show that the estimation results for the proposed method can be better than those of the two well-known methods, particularly when the imposed distributional assumption is incorrect and some regressors of the two equations are correlated. Hence, the proposed method can be a practically useful alternative for the sample selection model

자기 실현적인 위기로서의 1997년 한국의 통화위기 분석 : 투자자들의 기대와 예금은행을 통한 단기 자본 이동을 중심으로

학위논문(석사)--서울대학교 대학원 :경제학부 경제학전공,1999.Maste

Tests for Detecting Probability Mass Points

The objective of this paper is developing test statistics to detect the presence of mass points when data are possibly generated by a mixture of a continuous and a discrete distribution. To serve our purpose we propose two versions of the probability mass point (PMP) test. We derive the limiting distributions of the PMP test statistics under the null and alternative hypothesis by exploiting the asymptotic difference between two kernel density estimators with different bandwidths. Specifically, the proposed PMP test statistic is shown to converge to either the standard normal distribution or a linear transformation of a positive Poisson distribution at a non-mass point depending on bandwidths choice, while it diverges to infinity at a mass point. Numerical experiments are conducted to demonstrate the validity of our proposed tests. Korean taxpayers' bunching behavior is considered as an empirical application

Semi-nonparametric estimation of independently and identically repeated first-price auctions via an integrated simulated moments method

In this paper we propose to estimate the value distribution of independently and identically repeated first-price auctions directly via a semi-nonparametric integrated simulated moments sieve approach. Given a candidate value distribution function in a sieve space, we simulate bids according to the equilibrium bid function involved. We take the difference of the empirical characteristic functions of the actual and simulated bids as the moment function. The objective function is then the integral of the squared moment function over an interval. Minimizing this integral to the distribution functions in the sieve space involved and letting the sieve order increase to infinity with the sample size then yields a uniformly consistent semi-nonparametric estimator of the actual value distribution. Also, we propose an integrated moment test for the validity of the first-price auction model, and an data-driven method for the choice of the sieve order. Finally, we conduct a few numerical experiments to check the performance of our approach. © 2011 Elsevier B.V. All rights reserved

Monte carlo evidences on finite sample performances of the simulated integrated conditional moment estimator for the binary choice model

In this paper, I propose a simulated integrated conditional moment (SICM) estimator for the binary choice model. The asymptotic property of the proposed SICM estimator is explored via Monte Carlo experiment since its asymptotic theory has not been fully developed. In particular, the SICM estimator is compared with method of simulated moment (MSM) and ML estimators by adopting a simple parametric distributional setup in the experiment. The experiment results show that the proposed SICM estimator is valid in the sense that it is consistent and its Monte Carlo variance decreases by 1/n times as the sample size increases. In particular, it is found that the variance of the SICM estimator is approximately twice that of the MSM estimator with one simulator. © 2019, Korean Econometric Society. All rights reserved

A univariate sieve density estimation based on a simulated Kolmogorov-Smirnov test

This paper proposes a simulated Kolmogorov-Smirnov (KS)-based sieve density estimation method. It exploits an objective function which is the difference of two empirical distribution functions, one involved with actual observations and the other with simulated observations. By minimizing the objective function with respect to the sieve parameters, a sieve density/distribution estimator is obtained. The equivalence of the sieve distribution estimator and the true distribution can be tested by the KS test since the KS test statistic is easily obtained from the objective function. The resulting sieve density estimator is shown to be consistent. Numerical experiments are conducted to verify the performance of the proposed method. Furthermore, the proposed method is applied to estimate the income density in South Korea. Whether the actual observations can be rationalized by the estimated distribution can be tested by the proposed bootstrap test. © 2015, Korean Econometric Society. All rights reserved

Estimation of the impact of the statutory labor hours cut on labor earnings in Korea

In this paper we estimate the impact of the statutory labor hours cut in Korea on monthly labor earnings by the regression discontinuity design (RDD) method. The implementation of the statutory labor hours cut policy was sequentially extended based on the number of corporation’s employees. The estimation results show that the statutory labor hours cut did not make the workers receiving the treatment better off on average throughout the entire period of 2004-2008 in the sense that it raised monthly labor earnings. However, the policy intervention is found to substantially improve the welfare of workers in the treatment group in 2007 and 2008. © 2017, Korean Econometric Society. All rights reserved