We build a dynamic model of migration where, in addition to standard relocation costs, workers face spatial frictions that decrease their ability to compete for distant job opportunities. We estimate the model on a matched employer–employee panel dataset describing labour market transitions within and between the 100 largest French cities. Our identification strategy is based on the premise that frictions affect the frequency of job transitions, while mobility costs impact the distribution of accepted wages. We find that: (1) controlling for spatial frictions reduces mobility cost estimates by one order of magnitude; (2) the urban wage premium is driven by better opportunities for local job-to-job transitions in larger cities; (3) migration reduces lifetime inequalities by providing insurance against unsatisfactory initial location draws; (4) labour mobility policies based on relocation subsidies are inefficient, unlike switching from nationwide to local minimum wages.
Using data from a Canadian field experiment designed to elicit risk and time preferences and quantify financial barriers to higher education, we estimate the distribution of the value of financial aid for prospective students, and relate it to parental socio-economic background, individual skills, risk and time preferences. Our results point to credit constraints affecting a sizable share of prospective students. We find that most of the individuals are willing to pay a sizable interest premium above the prevailing market rate for the option to take-up a loan, with a median interest rate wedge equal to 6.6 percentage points for a $1,000 loan. The willingness-to-pay for financial aid is also highly heterogeneous across students, with preferences, in particular discount factors, playing a key role in accounting for this variation.
Using data from a Canadian field experiment on the financial barriers to higher education, we estimate the distribution of the value of financial aid for prospective students, and relate it to parental socio-economic background, individual skills, risk and time preferences. Our results point out that a considerable share of prospective students are affected by credit constraints. We find that most of the individuals are willing to pay a sizable interest premium above the prevailing market rate for the option to take up a loan, with a median interest rate wedge equal to 6.6 percentage points for a $1,000 loan. The willingness-to-pay for financial aid is highly heterogeneous across students, with preferences and in particular discount factors, playing a key role in accounting for this variation.
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