Unobserved Ability and the Return to Schooling

Belzil, Christian; Hansen, Jørgen

doi:10.1111/1468-0262.00365

Cited by 150 publications

(234 citation statements)

References 16 publications

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“…The parameter estimates (found in Table A2) indicate that, other things equal, the utility of attending school increases with parents' education and income. This is well documented in various reduced-form studies as well as in many structural studies (see Belzil and Hansen, 2001, Eckstein and Wolpin, 1999and Cameron and Heckman, 1998. The parameter estimates characterizing the distribution of all individual speci¯c intercept terms (school ability, employment and wage regression and type probabilities) are also found in Table A2.…”

Section: Structural Estimates and Goodness Of Fitsupporting

confidence: 61%

“…This does not require further discussion (see Belzil and Hansen, 2001). The identi¯cation of the degree of risk aversion (®) is also straightforward to establish given knowledge of the variance of earnings (see equation 8).…”

Section: Identi¯cationmentioning

confidence: 98%

“…The spline estimates of the local returns to schooling, also found in Table A2, can be transformed into local returns (after adding up the proper parameters). More details on the return to schooling can be found in Belzil and Hansen (2001). 12 The predicted schooling attainments, along with actual frequencies are found in Table 1, and allow us to evaluate the goodness of¯t.…”

Section: Structural Estimates and Goodness Of Fitmentioning

confidence: 99%

“…As a consequence, the link between education and wage/earnings dispersion is not trivial. 1 Modeling the level of risk involved in schooling decisions must however go beyond the e®ect of human capital on wages and employment and the di®erence in uncertainty between parental transfers and labor market wages. The possibility of interruption in the schooling accumulation process, due to various events such as health or personal problems, academic failure or other causes, can increase the risk associated to schooling as perceived by economic agents.…”

Section: Introductionmentioning

confidence: 99%

“…Although the estimation of structural dynamic programming of schooling decisions has become increasingly popular (Keane and Wolpin, 1997, Eckstein and Wolpin, 1999, Belzil and Hansen, 2001and Sauer, 2001), very few economists have investigated schooling decisions in a framework which allows for risk aversion or consumption smoothing. 2 Recently, Keane and Wolpin (2001), Sauer (2001) and Cameron and Taber (2001) have investigated the links between education¯nanc-ing and consumption smoothing and, more particularly, the e®ects of borrowing constraints on schooling decisions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Earnings Dispersion, Risk Aversion and Education

Belzil

Hansen²

Research in Labor Economics

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Section: Structural Estimates and Goodness Of Fitsupporting

confidence: 61%

Section: Identi¯cationmentioning

confidence: 98%

Section: Structural Estimates and Goodness Of Fitmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Earnings Dispersion, Risk Aversion and Education

Belzil

Hansen²

Research in Labor Economics

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Estimating the returns to schooling: a likelihood approach based on normal mixtures

Dagsvik

Hægeland

Raknerud

2011

J of Applied Econometrics

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Abstract:In this paper we develop likelihood based methods for statistical inference in a joint system of equations for the choice of length of schooling and earnings. The model for schooling choice is assumed to be an ordered probit model, whereas the earnings equation contains variables that are flexible transformations of schooling and experience, with corresponding coefficients that are allowed to be heterogeneous across individuals. Under the assumption that the distribution of the random terms of the model can be expressed as a particular finite mixture of multinormal distributions, we show that the joint probability distribution for schooling and earnings can be expressed on closed form. In an application of our method on Norwegian data, we find that the mixed Gaussian model offers a substantial improvement in fit to the (heavy-tailed) empirical distribution of log-earnings compared to a multinormal benchmark model.

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Fostering Educational Enrolment Through Subsidies: The Issue of Timing

Fiorini

2010

J of Applied Econometrics

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The purpose of this paper is to build a dynamic structural model of educational choices in which cognitive skills shape decisions. The model is estimated by maximum likelihood using cohort data where individuals are observed from birth to the middle of their working life. These data are unique in that they include cognitive skills test scores collected as early as age 7. We then investigate how alternative policies foster educational enrolment. In particular, we simulate the effect of two subsidies different in the timing of disbursement. The first consists of grants assigned directly to individuals aged between 16 and 18. The second is assigned to the parents earlier on, when the cohort is still in its childhood. The latter subsidy affects cognitive skills accumulation and in turn educational choices. Our results suggest that a grant fosters enrolment at the lowest cost but the parental income subsidy generates more welfare as measured by a class of social welfare functions. Nevertheless, these differences in costs and welfare are small. Overall, the results reinforce the view that government investments in cognitive skill accumulation during childhood are worthwhile. However, the results also indicate that such investments should be well structured to ensure a high return. 742FOSTERING EDUCATIONAL ENROLMENT which are the most relevant to the policy question addressed here. Section 3 describes the UK education system. Section 4 presents the cohort data that are used. Section 5 outlines the economics of the model, while Sections 6 and 7 explain, respectively, its identification and estimation. Section 8 begins by presenting the maximum likelihood estimates and the model fit, and then describes the simulations. Section 9 concludes. RELATED LITERATUREThe recent US literature on educational choices looks at the importance of financial incentives and budget constraints in schooling decisions. Keane and Wolpin (1997) investigate the educational and occupational decisions of a US male cohort born in the 1960s (NLSY79) in a dynamic discrete-choice structural model estimating the impact of a tuition fees subsidy on the college participation decision. In the model individuals are not financially constrained and from age 16 onwards decide year by year whether to stay in education, stay home, or work in a white-or blue-collar occupation. The model allows for ex ante (age 16) heterogeneity in endowment. Keane and Wolpin find that a $2000 college fee subsidy would increase high school graduation by 3.5 percentage points and increase college graduation rates by 8.4 percentage points. However, when analysing the lifetime utility effects, those who would benefit most from the subsidy are the individuals with high endowment for school education and white-collar occupations, who would have gone to college even without the subsidy. Those induced to go to college by the subsidy are individuals with low endowment for education and a comparative advantage in blue-collar occupations, with only a minor increase in their lifetime utility...

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Unobserved Ability and the Return to Schooling

Cited by 150 publications

References 16 publications

Earnings Dispersion, Risk Aversion and Education

Earnings Dispersion, Risk Aversion and Education

Estimating the returns to schooling: a likelihood approach based on normal mixtures

Fostering Educational Enrolment Through Subsidies: The Issue of Timing

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