Is skill dispersion a source of comparative advantage? In this paper we use microdata from the International Adult Literacy Survey to show that the effect of skill dispersion on trade flows is quantitatively similar to that of the aggregate endowment of human capital. In particular we investigate, and find support for, the hypothesis that countries with a more dispersed skill distribution specialize in industries characterized by lower complementarity of workers' skills. The result is robust to the introduction of controls for alternative sources of comparative advantage, as well as to alternative measures of industry-level skill complementarity. (JEL F14, F16, J24, J31)

This paper examines the equilibrium effects of alternative financial aid policies intended to promote college participation. We build an overlapping generations life-cycle, heterogeneous-agent, incomplete-markets model with education, labor supply, and consumption/saving decisions. Driven by both altruism and paternalism, parents make inter vivos transfers to their children. Both cognitive and non-cognitive skills determine the non-pecuniary cost of schooling. Labor supply during college, government grants and loans, as well as private loans, complement parental resources as means of funding college education. We find that the current financial aid system in the U.S. improves welfare, and removing it would reduce GDP by 4-5 percentage points in the long-run. Further expansions of government-sponsored loan limits or grants would have no salient aggregate effects because of substantial crowding-out: every additional dollar of government grants crowds out 30 cents of parental transfers plus an equivalent amount through a reduction in student's labor supply. However, a small group of high-ability children from poor families, especially girls, would greatly benefit from more generous federal aid.

Has the emergence of information technology changed the structure of employment and earnings in the US? We propose a new index of occupation-level IT intensity and document several long-term changes in the occupational landscape over the past decades. Using Census micro-data between 1970 and 2015, we show that: (i) the share of workers in IT-intensive jobs has expanded significantly, with little or no pause; (ii) IT jobs enjoy a large and growing earnings premium, even after controlling for general task requirements (e.g., cognitive, non-routine); and (iii) the rise of the IT employment share is closely associated with declines in the manufacturing employment share. Although the earnings premia for college-educated and high cognitive/non-routine skilled workers have declined in the aggregate since 2000, we show that they have continued growing in IT jobs. We subsequently introduce an equilibrium model of occupational sorting based on comparative advantage between IT and non-IT jobs to quantify the contribution of IT jobs towards accelerating the pace of structural transformation. Our results suggest that technological growth among IT jobs has played a major role in accounting for the surge in high tech service labor productivity since 1980.

We use a large, rich Canadian micro-level dataset to examine the channels through which family socio-economic status and unobservable characteristics affect children's decisions to drop out of high school. First, we document the strength of observable socio-economic factors: our data suggest that teenage boys with two parents who are themselves high school dropouts have a 16% chance of dropping out, compared to a dropout rate of less than 1% for boys whose parents both have a university degree. We examine the channels through which this socio-economic gradient arises using an extended version of the factor model set out in Carneiro, Hansen, and Heckman (2003). Specifically, we consider the impact of cognitive and non-cognitive ability and the value that parents place on education. Our results support three main conclusions. First, cognitive ability at age 15 has a substantial impact on dropping out. Second, parental valuation of education has an impact of approximately the same size as cognitive ability effects for medium and low ability teenagers. A low ability teenager has a probability of dropping out of approximately .03 if his parents place a high value on education but .36 if their education valuation is low. Third, parental education has no direct effect on dropping out once we control for ability and parental valuation of education. Our results point to the importance of whatever determines ability at age 15 (including, potentially, early childhood interventions) and of parental valuation of education during the teenage years. We also make a small methodological contribution by extending the standard factor based estimator to allow a non-linear relationship between the factors and a covariate of interest. We show that allowing for non-linearities has a substantial impact on estimated effects.

and seminar participants at CIFAR for helpful comments. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

In this paper we ask whether policies targeting a reduction in crime rates through changes in education outcomes can be considered an effective and cost-viable alternative to interventions based on harsher punishment alone. In particular we study the effect of subsidizing high school completion. Most econometric studies of the impact of crime policies ignore equilibrium effects and are often reduced-form. This paper provides a framework within which to study the equilibrium impact of alternative policies. We develop an overlapping generation, life-cycle model with endogenous education and crime choices. Education and crime depend on different dimensions of heterogeneity, which takes the form of differences in innate ability and wealth at birth as well as employment shocks. PSID, NIPA and CPS data are used to estimate the parameters of a production function with different types of human capital and to approximate a distribution of permanent heterogeneity. These estimates are used to pin down some of the model's parameters. The model is calibrated to match education enrolments, aggregate (property) crime rate and some features of the wealth distribution. In our numerical experiments we find that policies targeting crime reduction through increases in high school graduation rates are more cost-effective than simple incapacitation policies. Furthermore, the cost-effectiveness of high school subsidies increases significantly if they are targeted at the wealth poor. We also find that financial incentives to high school graduation have radically different implications in general and partial equilibrium (i.e. the scale of the programmes can substantially change its outcomes).

We use a large, rich Canadian micro-level dataset to examine the channels through which family socio-economic status and unobservable characteristics affect children's decisions to drop out of high school. First, we document the strength of observable socio-economic factors: our data suggest that teenage boys with two parents who are themselves high school dropouts have a 16% chance of dropping out, compared to a dropout rate of less than 1% for boys whose parents both have a university degree. We examine the channels through which this socio-economic gradient arises using an extended version of the factor model set out in Carneiro, Hansen, and Heckman (2003). Specifically, we consider the impact of cognitive and non-cognitive ability and the value that parents place on education. Our results support three main conclusions. First, cognitive ability at age 15 has a substantial impact on dropping out. The highest ability individuals are predicted never to drop out regardless of parental education or parental valuation of education. In contrast, the lowest ability teenagers have a probability of dropping out of approximately .36 if their parents have a low valuation of education. Second, parental valuation of education has a substantial impact on medium and low ability teenagers. A low ability teenager has a probability of dropping out of approximately .03 if his parents place a high value on education but .36 if their educational valuation is low. These effects are estimated while conditioning on ability at age 15. Thus, under some assumptions, they reflect parental influences during the upper teenage years and are in addition to any impact they might have in the early childhood years leading up to age 15. Third, parental education has no direct effect on dropping out once we control for ability and parental valuation of education. Overall, our results point to the importance of whatever determines ability at age 15 (including, potentially, early childhood interventions) and of parental valuation of education during the teenage years. Our work also provides a small methodological contribution by extending the standard factor based estimator to allow a more non-linear relationship between the factors and a co-variate of interest. We show that allowing for non-linearities has a substantial impact on estimated effects.

We estimate the costs of occupational mobility and quantify the relative importance of differences in task content as a component of total mobility costs. We use a novel approach based on a model of occupational choice which delivers a gravity equation linking worker flows to occupation characteristics and transition costs. Using data from the Current Population Survey and the Dictionary of Occupational Titles we find that task-specific costs account for no more than 15% of the total transition cost across most occupation pairs. Transition costs vary widely across occupations and, while increasing with the dissimilarity in the mix of tasks performed, are mostly accounted for by task-independent occupation-specific factors. The fraction of transition costs that can be attributed to task-related variables appears fairly stable over the 1994-2013 period.JEL Codes: J62, J24. . Financial support from CLSRN and SSHRC is gratefully acknowledged. We thank Dirk Krueger and four anonymous referees for extensive comments that significantly improved the paper. We are grateful to Christopher Nekarda for facilitating access to the matched CPS data and to Todd Schoellman for generously sharing his occupation licensing database. We also thank Nicole , and seminar participants at various universities and workshops for insightful comments and suggestions. Carlos Sanchez and Lijing (Emily) Wang provided valuable research assistance at different stages of this project.