• Title/Summary/Keyword: instrumental variable

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The Effect of the Minimum Wage on Employment Using Instrumental Variable (도구변수를 이용한 최저임금의 고용효과)

  • Kang, Seungbok
    • Journal of Labour Economics
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    • v.40 no.3
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    • pp.105-131
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    • 2017
  • This study analyses the effect of a minimum wage on employment by using the government's progressiveness as an instrumental variable. The Ordinary Least Squares regression (OLS) can result in upward biased employment effect due to the endogeneity among variables. Therefore, it is necessary to analyse the casuality that removed endogeneity between variables by using proper instrumental variables. The analysis using instrumental variable shows that the growth of the increasing rate of the minimum wage reduces employment. The negative effect of employment depending on the increase of minimum wage corresponds with the predictions of Neoclassical Economics.

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Strengthening Causal Inference in Studies using Non-experimental Data: An Application of Propensity Score and Instrumental Variable Methods (비실험자료를 이용한 연구에서 인과적 추론의 강화: 성향점수와 도구변수 방법의 적용)

  • Kim, Myoung-Hee;Do, Young-Kyung
    • Journal of Preventive Medicine and Public Health
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    • v.40 no.6
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    • pp.495-504
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    • 2007
  • Objectives : This study attempts to show how studies using non-experimental data can strengthen causal inferences by applying propensity score and instrumental variable methods based on the counterfactual framework. For illustrative purposes, we examine the effect of having private health insurance on the probability of experiencing at least one hospital admission in the previous year. Methods : Using data from the 4th wave of the Korea Labor and Income Panel Study, we compared the results obtained using propensity score and instrumental variable methods with those from conventional logistic and linear regression models, respectively. Results : While conventional multiple regression analyses fail to identify the effect, the results estimated using propensity score and instrumental variable methods suggest that having private health insurance has positive and statistically significant effects on hospital admission. Conclusions : This study demonstrates that propensity score and instrumental variable methods provide potentially useful alternatives to conventional regression approaches in making causal inferences using non-experimental data.

Interpersonal support, Tension in life changes & Life satisfaction in Urban Housewives (도시주부의 대인적 지지, 생활긴장감 및 만족도)

  • ;吳京姬
    • Journal of Families and Better Life
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    • v.16 no.4
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    • pp.83-83
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    • 1998
  • The purpose of this study is to investigate interpersonal support, tension in lifechanges & satisfaction. The selected sample is composed of 387 housewives in ChongJoo city. SAS pc program was used for the statistical analysis of the data. Data was analyzed by frequency, F-test, percentage, mean, Duncan's Multiple Range Test, Pearson's correlation coefficient, Regression Analysis. Major findings as follows: 1)At wedding & funeral ceremony, kin networks of her parents & parents-in law side were variables to have influence on tension in life changes. And the number of social organization participated were a variable to have influence on the satisfaction. The age of couple, education of couple, duration of marriage, income, family lifecycle, the number of children, pattern of family were variables to influence tension in life changes, but were not variables to influence on the satisfaction. 2) At usual or wedding & funeral ceremony, kin networks of her parents side were variables to influence on instrumental & companionship support. And the number of friends was a variable to influence on companionship & informational support. The number of neighbors was a variable to influence on instrumental, companionship & informational support. The number of social organization participated was a variable to influence on companionship & emotional support. The age of couple, education of couple,income, duration of marriage, family life cycle, number of children, family size, family type were variables to influence on interpersonal support. 3)The relationship between tension and satisfaction in life changes was negative, and between instrumental support and satisfaction was negative also. But between companionship support and satisfaction was positive relationship and between tension of personal &social life and instrumental support was positive relationship. The relationship between tension of marriage life and companionship support was negative and between tension of family life and information support was negative relationships. The received companionship support was lower tension in life changes than not received it. But the received instrumental support was higher tension of personal & social life. The received companionship & informational support was higher satisfaction than not received them. But the received instrumental support was lower satisfaction than not received it. 4) Instrumental & companionship support, at usual kin network of her parents in taw side, at wedding & funeral ceremony kin network of her parents side,were variables to influence on tension in life changes. Instrumental, companionship& informational support, at wedding & funeral ceremony kin network of her parents side, were variables to influence on the satisfaction

An Analysis on the Employment Relationship of Domestic and Foreign Workers in the Regional Labor Market Using Instrumental Variable Method (도구변수법을 이용한 지역 노동시장의 내외국인근로자 고용관계 분석)

  • Cho, Eunji;Lee, Chanyoung
    • Journal of Labour Economics
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    • v.44 no.2
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    • pp.33-69
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    • 2021
  • This study estimates the employment relationship of domestic and foreign workers by establishing 16 municipal and provincial panel data for the period 2010-2018. It attempts to analyze industry-specific (manufacturing and construction), scale-specific (5-29, 5-29, 5-299 and 5 above) and uses the foreign worker's national share (foreigner's concentration index) as an instrumental variable to control the endogeneity of foreign workers. Finally, it compares the results of panel GLS, which does not consider the endogeneity of foreign workers, with the results using instrumental variable method that considers it. As a result of the analysis, the complementary relationship between domestic and foreign workers was confirmed in the panel GLS analysis. However, although the employment relationship between domestic and foreign workers was not statistically significant in the instrumental variable method, the analysis of the combination of manufacturing and construction industry showed a statistically significant substitute relationship. This study is highly regarded for the first time in Korea that an instrumental variable method was created to identify and control the endogeneity of foreign workers in estimating employment relationships between domestic and foreign workers.

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Modified Instrumental Variable Methods for ARMA Spectral Estimation (ARMA 스펙트럼 추정을 위한 변형기구 변수법에 관한 연구)

  • 양흥석;정찬수;남도현;김국헌
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.35 no.10
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    • pp.438-444
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    • 1986
  • The signal can be modeled as a linear combination of its past values and present and past values of a hypothetical input to system whose output is given signal. Using this model spectral estimation problem can be reduced to estimate the ARMA parameters. This paper presents recursive modified instrumental variable algorithm which can estimate AR and MA parameters. For more accurate estimation, overdetermined modified IV algorithm is also derived. Computer simulations are presented to illustrate the above methods.

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A Study on Model Identification of Electro-Hydraulic Servo Systems (전기-유압 서보 시스템의 모델규명에 관한 연구)

  • 엄상오;황이철;박영산
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.4
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    • pp.907-914
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    • 1999
  • This paper studies on the model identification of electro-hydraulic servo systems, which are composed of servo valves, double-rod cylinder and load mass. The identified plant is described as a discrete-time ARX or ARMAX model which is respectively obtained from the identification algorithms of least square error method, instrumental variable method and prediction error method. where a nominal model and the variation of model parameters are quantitatively evaluated.

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A New Estimator for Seasonal Autoregressive Process

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.30 no.1
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    • pp.31-39
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    • 2001
  • For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

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Parameter Estimation in a Complex Non-Stationary and Nonlinear Diffusion Process

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.29 no.4
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    • pp.489-499
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    • 2000
  • We propose a new instrumental variable estimator of the complex parameter of a class of univariate complex-valued diffusion processes defined by the possibly non-stationary and/or nonlinear stochastic differential equations. On the basis of the exact finite sample distribution of the pivotal quantity, we construct the exact confidence intervals and the exact tests for the parameter. Monte-Carlo simulation suggests that the new estimator seems to provide a viable alternative to the maximum likelihood estimator (MLE) for nonlinear and/or non-stationary processes.

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Sign IV Cointegration Tests

  • Oh, Yu-Jin
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.707-711
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    • 2009
  • We propose new cointegration tests using signs of the regressors as instrumental variable. Our tests have the asymptotic standard normal distribution and are free from the dimension of regressors under the null hypothesis of no cointegration. A Monte-Carlo simulation shows that the proposed tests have a stable size and an improved power. Particulary, the tests have better power for small numbers of observations.

Covariance Lattice Instrumental Variable Algorithm for Spectral Estimation (스펙트럼 추정을 위한 공분산 기구변수 격자 앨고리즘)

  • 양흥석;남현도;김진기
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.35 no.4
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    • pp.156-162
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    • 1986
  • The last few years have seen a rapid development of so-called lattice algorithms for the fast solution of finite date algorithms. So far, most of the work on ladder form has been done for the prewindowed case. In this paper, the covariance lattice algorithm for instrumental variable recusions is presented. This algorithm can be used in various areas of adaptive signal processing, spectral estimation and system identification. The behavior of the proposed algorithm is illustrated by some simulation results for spectral estimation.

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