Myoung Jae Lee

Analysis of private transfers with panel fixed-effect censored model estimator

Abstract Understanding private transfer is important for safety-net policies because private transfer provides economic benefits similar to those of public programs such as unemployment insurance and pension. Applying Honore’s [Econometrica 60 (1992) 533] panel fixed-effect censored model estimator to Korean data, we show that private transfer is altruistically motivated and there is a strong crowding-out effect of public transfer on private transfer. We also find that low-income people suffered to different degrees during the financial crisis period of 1997 to 1998. This finding and the crowding-out effect may be taken as failures of the Korean public transfer programs during the period.

Semiparametric Estimators for Limited Dependent Variable (LDV) Models with Endogenous Regressors

This article reviews semiparametric estimators for limited dependent variable (LDV) models with endogenous regressors, where nonlinearity and nonseparability pose difficulties. We first introduce six main approaches in the linear equation system literature to handle endogenous regressors with linear projections: (i) ‘substitution’ replacing the endogenous regressors with their projected versions on the system exogenous regressors x, (ii) instrumental variable estimator (IVE) based on E{(error) × x} = 0, (iii) ‘model-projection’ turning the original model into a model in terms of only x-projected variables, (iv) ‘system reduced form (RF)’ finding RF parameters first and then the structural form (SF) parameters, (v) ‘artificial instrumental regressor’ using instruments as artificial regressors with zero coefficients, and (vi) ‘control function’ adding an extra term as a regressor to control for the endogeneity source. We then check if these approaches are applicable to LDV models using conditional mean/quantiles instead of linear projection. The six approaches provide a convenient forum on which semiparametric estimators in the literature can be categorized, although there are a few exceptions. The pros and cons of the approaches are discussed, and a small-scale simulation study is provided for some reviewed estimators.

Generalized Difference in Differences with Panel Data and Least Squares Estimator.

With one treated and one untreated periods, difference in differences (DD) requires the untreated response changes to be the same across the treatment and control groups, if the treatment were withheld contrary to the fact. A natural way to check the condition is to backtrack one period and examine the response changes in two pretreatment periods. If the condition does not hold in the pretreatment periods, then a modified DD takes the form of “generalized difference in differences (GDD),” which is a triple difference (TD) with one more time-wise difference than DD. GDD generalizes DD with a weaker identification condition in the sense that a time-constant, but not necessarily zero, time/selection effect is allowed. One more time-wise differencing (quadruple difference [QD]) than GDD allows for the time/selection effect even to change over time, which makes it possible to test for the GDD identification condition. Simple panel least squares estimators (LSEs)/tests for DD and GDD are proposed and an empirical illustration is presented.

PERFORMANCE OF VARIOUS ESTIMATORS FOR CENSORED RESPONSE MODELS WITH ENDOGENOUS REGRESSORS

The paper reviews four approaches (substitution (SUB), control function (CF), system reduced form (SRF) and artificial instrumental regressor (AIR)) dealing with endogenous regressors in censored response models, and compares them through a simulation. Based on mean-squared-error type criteria, CF and AIR perform better than SUB and SRF; in terms of computation, however, SUB and CF are the easiest, closely followed by SRF. Although CF does well in both accounts, its assumptions are restrictive, and CF provides very different results from the other estimators when a real data set is used. Therefore, although the choice of an estimator among the four should be case-specific, for practitioners, we would recommend SUB.

Regression‐Kink Approach for Wage Effect on Male Work Hours

In finding the effect of after-tax wage rate on work hours, the main difficulty is the endogeneity of after-tax wage rate that equals ‘one minus average tax rate’ times wage rate. To overcome this endogeneity problem, we take advantage of jumps in the marginal income tax rate, which is a regression discontinuity (RD) idea. This RD, in turn, makes the average income tax rate ‘kink-continuous’, which is a regression kink (RK) idea. We provide a simple economic model resulting in the RD and RK features, explain how to implement RK in practice, and then apply our methods to Korean male data. Our main RK-based labour supply elasticity estimate 7.16% turned out to be insignificant with t-value 1.52, but it is much larger than most estimates in the literature. This may be attributed to, among other things, the facts that the RK instrument is unique, that RK identifies only the local elasticity at the kink point and that RK requires large data as regression derivatives are estimated.

Finding dynamic treatment effects under anticipation: the effects of spanking on behaviour

Summary.  The dynamic treatment effect literature considers multiple treatments administered over time, with some treatments affected by interim outcomes. But the literature overlooks the possibility of individuals acting in anticipation of future treatments. This lack of anticipation aspect may not matter in the drug–response relationships which motivated the literature. But human beings (or animals with some intelligence) do not just respond to current and past treatments, but also ‘reflect and anticipate’ future treatments. For example, a punishment or reward is likely to prompt forward looking. Even if no personal punishment or reward is involved, people may take action in anticipation of a future government policy, which would be an important concern for policy makers. The paper explores how to find dynamic treatment effects allowing for forward looking or anticipation by extending available dynamic treatment effect approaches in the literature. Then the methods proposed are applied to the effects of spanking on a childs bad behaviour where a child may act better in anticipation of future spanking, which is analogous to the relationship between punishment and crime.

Control Function Approach for Partly Ordered Endogenous Treatments: Military Rank Premium in Wage

In treatment effect analysis, there are many cases where the treatment of interest is ordered (e.g. general-education years or medicine doses) and the control treatment is not zero, but a different type of treatment (a vocational training or a surgery). We develop an approach to find effects of partly ordered treatments, while correcting for possible treatment endogeneity with nearly parametric control functions. We use this control function approach, along with its supplementary version, to estimate effects of military ranks (ordered treatments) on wage relative to non-veteran status (control treatment) with the Wisconsin Longitudinal Study data. In our empirical analysis, the military rank effects differ much: officer has large positive effects, but enlisted ranks have small or no effects.

Estimation of Binary Response Models with Endogenous Regressors

This paper reviews six approaches to binary response (y 1 ) structural forms with an endogenous regressor y 2 : (i) the two-stage least squares estimator-like substitution approach, (ii) the control function approach, (iii) the system reduced-form approach, (iv) the artificial instrumental regressor approach, (v) the transformed-response instrumental variable estimator approach and (vi) the classical maximum likelihood estimator approach. The applicability of the six methods differs greatly, depending on whether y 2 is a continuously distributed random variable or a discrete transformation of a latent y 2 . We conduct a real-data-based simulation study, and provide an empirical illustration. Our overall recommendation is using (i) and (ii), as the others have undesirable features such as analytic complexity in (iii), computational difficulty in (iv) and (vi), and poor finite-sample performance in (v).

Does Television Viewing Affect Children's Behaviour?

Using three-period panel data drawn from the National Longitudinal Survey of Youth 1979, we investigate whether television (TV) viewing at ages 6–7 and 8–9 years affects childrens social and behavioural development at ages 8–9 years. Dynamic panel data models are estimated to handle the unobserved child-specific factor, endogeneity of TV viewing, and the dynamic nature of the causal relation. Special emphasis is placed on this last aspect, focusing on how early TV viewing affects interim child behavioural problems and in turn affects future TV viewing. Overall, we find that TV viewing during ages 6–7 and 8–9 years increases child behavioural problems at ages 8–9 years, and that the effect is economically sizable.

THE EFFECTS OF EDUCATION ON FERTILITY: EVIDENCE FROM TAIWAN

This study investigates the impact of womens education on fertility. For identification, we use the 1968 compulsory education law change in Taiwan, which generated a regression discontinuity design (RDD) setting. We use the whole population of women from the 1980 and 2010 Population Censuses. Results of our RDD estimation using the exact date of birth suggest that the law change was effective in boosting womens education, but it did not have any impact on fertility. This is in stark contrast to most previous studies using only the birth year as the running variable or using it to construct instruments, which find that womens education depresses fertility. This study demonstrates that using a discrete running variable in RDD may generate a false discontinuity for an otherwise continuous regression function. (JEL J13, C21, I2)