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Estimation of Educational Borrowing Constraints Using Returns to ...

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educational borrowing constraints 147<br />

set <strong>of</strong> wage predic<strong>to</strong>rs that capture more dimensions <strong>of</strong> ability than<br />

AFQT by itself.<br />

Panel E <strong>of</strong> the table summarizes the instruments used below for endogenous<br />

schooling. Local college is a binary indica<strong>to</strong>r for the presence<br />

<strong>of</strong> any college (either two-year or four-year) in the county <strong>of</strong> residence<br />

at age 17 (or age 16 for the handful who graduate from high school<br />

by age 17). 17 College identifiers were merged <strong>to</strong> NLSY annual county<br />

<strong>of</strong> residence measures from the Department <strong>of</strong> Education’s annual<br />

Higher Education General Information Survey (HEGIS) and the Integrated<br />

Postsecondary Education Data System’s (IPEDS) Institutional<br />

Characteristics surveys, which contain annual data on location, type <strong>of</strong><br />

institution, tuition, and other variables associated with colleges in the<br />

United States. 18<br />

Local labor market conditions were created from annual county-level<br />

labor market data on average annual earnings in industries dominated<br />

by unskilled workers. 19 Our proxy for forgone earnings is a static variable<br />

created from this series taken in a person’s county <strong>of</strong> residence at age<br />

17 (local earnings at age 17 in panel E <strong>of</strong> the table). The variable mean<br />

local earnings over working life is constructed in the following manner.<br />

We condition on the county in which a student lived at age 17. We then<br />

average the annually varying labor market measure <strong>of</strong> earnings for this<br />

county for the years during which this person works (starting at age 22)<br />

and appears in the sample (up <strong>to</strong> age 33). We also studied the local<br />

(county) unemployment rate in our schooling choice analysis, but results<br />

using this variable were very imprecise.<br />

Panel F shows means <strong>of</strong> annually varying variables used in the wage<br />

analysis. Hourly wage is the wage at the current or most recently held<br />

job as <strong>of</strong> the interview date in each year. Current local earnings is an<br />

annual measure constructed from the local annual earnings series just<br />

discussed. It is measured for the county in which a person currently<br />

lives and is discussed further below. Work experience is a measure <strong>of</strong><br />

potential work experience and is constructed as age minus schooling<br />

minus six.<br />

17<br />

We also explored a set <strong>of</strong> three indica<strong>to</strong>r variables for two-year college, four-year<br />

college, and both. Our conclusions below were unchanged, though standard errors <strong>of</strong><br />

estimates improved slightly in some cases when the three indica<strong>to</strong>rs were used <strong>to</strong>gether.<br />

18<br />

A number <strong>of</strong> specialty colleges, generally with enrollments less than 100, and federal<br />

institutions, such as the Naval Academy, were excluded.<br />

19<br />

The data are taken from annual Bureau <strong>of</strong> Economic Analysis data. Since the bureau’s<br />

data are reported by industry and not by occupation, we use average earnings in service,<br />

agriculture, and the wholesale and retail trade industries. A number <strong>of</strong> other labor market<br />

measures using a variety <strong>of</strong> industry aggregates were explored, with little difference <strong>to</strong> the<br />

estimates presented below. This was true apparently because, except for government jobs,<br />

average wages across a variety <strong>of</strong> industries in the same local labor market exhibit a high<br />

degree <strong>of</strong> correlation.

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