Estimating a class of triangular simultaneous equations models without exclusion restrictions

This paper provides a control function estimator to adjust for endogeneity in the triangular simultaneous equations model where there are no available exclusion restrictions to generate suitable instruments. Our approach is to exploit the dependence of the errors on exogenous variables (e.g. heteroscedasticity) to adjust the conventional control function estimator. The form of the error dependence on the exogenous variables is subject to restrictions, but is not parametrically specified. In addition to providing the estimator and deriving its large-sample properties, we present simulation evidence which indicates the estimator works well.

Supporting text mining for e-Science: the challenges for Grid-enabled natural language processing

Over the last few years, language technology has moved rapidly from 'applied research' to 'engineering', and from small-scale to large-scale engineering. Applications such as advanced text mining systems are feasible, but very resource-intensive, while research seeking to address the underlying language processing questions faces very real practical and methodological limitations. The e-Science vision, and the creation of the e-Science Grid, promises the level of integrated large-scale technological support required to sustain this important and successful new technology area. In this paper, we discuss the foundations for the deployment of text mining and other language technology on the Grid - the protocols and tools required to build distributed large-scale language technology systems, meeting the needs of users, application builders and researchers

A Parametric Control Function Approach to Estimating the Returns to Schooling in the Absence of Exclusion Restrictions: An Application to the NLSY

We estimate the return to education using a sample drawn from the National Longitudinal Survey of Youth 1979 (NLSY79). Rather than accounting for the endogeneity of schooling through the use of instrumental variables we employ a parametric version of the Klein and Vella (2006a) estimator. This estimator bypasses the need for instruments by exploiting features of the conditional second moments of the errors. As the Klein and Vella (2006a) procedure is semi-parametric it is computationally demanding. We illustrate how to greatly reduce the required computation by parameterizing the second moments. Accounting for endogeneity increases the estimate of the return to education by 5 percentage points, from 7.6% to 12.7%.return to education, heteroskedasticity, endogeneity

Does increasing parents' schooling raise the schooling of the next generation? Evidence based on conditional second moments

This paper investigates the degree of intergenerational transmission ofeducation for individuals from the National Longitudinal Survey of Youth1979. Rather than identifying the causal effect of parental education viainstrumental variables we exploit the feature of the transmissionmechanism responsible for its endogeneity. More explicitly, we assume theintergenerational transfer of unobserved ability is invariant to the economicenvironment. This, combined with the heteroskedasticity resulting from theinteraction of unobserved ability with socioeconomic factors, identifies thiscausal effect. We conclude the observed intergenerational educationalcorrelation reflects both a causal parental educational effect and a transferof unobserved ability.Intergenerational mobility, endogeneity, conditional correlation

Does Increasing Parents' Schooling Raise the Schooling of the Next Generation? Evidence Based on Conditional Second Moments

This paper investigates the degree of intergenerational transmission of education for individuals from the National Longitudinal Survey of Youth 1979. Rather than identifying the causal effect of parental education via instrumental variables we exploit the feature of the transmission mechanism responsible for its endogeneity. More explicitly, we assume the intergenerational transfer of unobserved ability is invariant to the economic environment. This, combined with the heteroskedasticity resulting from the interaction of unobserved ability with socioeconomic factors, identifies this causal effect. We conclude the observed intergenerational educational correlation reflects both a causal parental educational effect and a transfer of unobserved ability.intergenerational mobility, endogeneity, conditional correlation

Subjective Health Assessments and Active Labor Market Participation of Older Men: Evidence from a Semiparametric Binary Choice Model with Nonadditive Correlated Individualspecific Effects

We use panel data from the US Health and Retirement Study 1992-2002 to estimate the effect of self-assessed health limitations on active labor market participation of men around retirement age. Self-assessments of health and functioning typically introduce an endogeneity bias when studying the effects of health on labor market participation. This results from justification bias, reflecting an individual’s tendency to provide answers which "justify" his labor market activity, and individual-specific heterogeneity in providing subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure which incorporates potentially nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health and functioning play a major role in the labor market exit decisions of older men.

A Parametric Control Function Approach to Estimating the Returns to Schooling in the Absence of Exclusion Restrictions: An Application to the NLSY

An innovation which bypasses the need for instruments when estimating endogenous treatment effects is identification via conditional second moments. The most general of these approaches is Klein and Vella (2010) which models the conditional variances semiparametrically. While this is attractive, as identification is not reliant on parametric assumptions for variances, the non-parametric aspect of the estimation may discourage practitioners from its use. This paper outlines how the estimator can be implemented parametrically. The use of parametric assumptions is accompanied by a large reduction in computational and programming demands. We illustrate the approach by estimating the return to education using a sample drawn from the National Longitudinal Survey of Youth 1979. Accounting for endogeneity increases the estimate of the return to education from 6.8% to 11.2%.return to education, heteroskedasticity, endogeneity

Factors Affecting the Output and Quit Propensities of Production Workers

We have used a proprietary data set of newly hired semi-skilled production workers at one location of a large unionized firm to investigate several issues in labor economics. This data set is unique in several respects: the workers in our sample faced the same wage schedules, had the same promotional opportunities, the same job tenure (zero), similar working conditions, and had jobs for which we were able to record their physical output. We analyze these data by formulating a simultaneous equation model to explain wages, output, education, and a worker's quit decision. The model is estimated by maximum likelihood and subjected to a variety of specification tests. Such tests include a comparison of the standard error estimates that form the basis for White's information test, and White's version of a Hausman specification test. Our principal findings are: 1. Individuals that choose more education than we would expect from their observed characteristics have lower than expected quit propensities. We argue that this low quit propensity is one of the unmeasured (and unobserved) attributes that sorting models posit are correlated with education and hence distort the usual estimates of rates of return to education. 2. The performance of non-whites in our sample was no lower than that of whites. However, on their previous jobs non-whites received lower wages than did whites. 3. The output per hour of males in our sample was higher than that of females; however, we were unable to conclude from our data whether these productivity differences could explain the higher wages received by men on their previous jobs. Moreover, this output difference may be transitory and may diminish with on-the-job learning. 4. The expected value of alternative wages had a positive (but not statistically very significant) effect on quit rates. Workers with better alternative opportunities were more likely to quit (all workers had the same opportunities on their current job). 5. Finally we found that workers with high output levels were more likely to quit than were workers with average output levels.