Magazine article Policy Brief Series (Hamilton Project)

The Mobility Bank: Increasing Residential Mobility to Boost Economic Mobility

Magazine article Policy Brief Series (Hamilton Project)

The Mobility Bank: Increasing Residential Mobility to Boost Economic Mobility

Article excerpt


In August 2010y the unemployment rate in the Flint, Michigan, metropolitan area was 23.6 percent, well above the national average of 9.6 percent. Other cities around the country have been hit similarly hard and have had unemployment rates persistently above the national average. At the same time, numerous cities around the country have very low unemployment rates, at or below 6 percent. Given this substantial variation in local labor markets across different parts of the country, workers could benefit by moving from high-unemployment areas to areas with greater demand for workers; this move would help workers get back to work more quickly.

However, these benefits of labor-market mobility are not being fully realized. One reason is that an unemployed person who is thinking about moving for economic reasons faces a series of frontloaded costs, such as moving expenses and leaving familiar surroundings, which are incurred in exchange for potential longer-term benefits-a steady job. But unemployed workers have few resources and little ability to borrow from private lenders to finance this type of investment: they cannot use their future earnings as collateral to borrow money to finance a move. At a time when geographic mobility could help improve economic mobility, the mobility rate is at a historic low.

Authors Jens Ludwig and Steven Raphael propose a mobility bank to help individuals finance moves to areas of greater economic opportunity. In cities with unemployment rates in the top third nationally, residents could take out a loan to finance their move to an area where they believe they can more readily find a job. Repayment of the loan would not be required until the borrower found a job. Because the proposal provides a loan rather than a grant, it appears to be very cost effective compared to other job-creating programs. And by speeding the rate at which unemployed workers find jobs, it could help reduce overall unemployment.

The Challenge

Mobility is a key feature of an efficient labor market. In a mobile labor market, individuals move to areas where their skills are in higher demand, reaping benefits in the form of higher wages and greater employment stability. The national economy benefits from the increased demand these higher earnings generate, and the mobility can help regions adjust to local labor market shocks. Mass layoffs may have less of a deleterious effect on an area if some workers leave the area for new job opportunities, reducing the competition for scarce jobs and freeing up funds that would otherwise have to be spent on social services for the unemployed.

Ideally, mobility would rise during recessions when economic adjustments are needed. However, the opposite is true: faced with lower income, depleted savings, and reduced access to credit, individuals are less able to "invest" in moving. In the current recession, mobility is particularly low. In 2008, only 12.5 percent of U.S. residents changed residences during the year, down from about 15 percent in 2001 and 17 percent in the early 1990s.

Ludwig and Raphael view moving as if it were any other human capital investment, such as going to college. The benefits to an unemployed or underemployed worker of moving to a better labor market include the potential for a steady job and higher wages. However, a combination of low savings or a lack of access to credit makes it nearly impossible for most unemployed workers to finance a move. This may be particularly true for less-educated workers who have much lower mobility rates after job loss compared with college graduates.

Workers who cannot move are likely to suffer in terms of their reemployment prospects. Ludwig and Raphael find that the reemployment difference between those who move after a job loss and those who do not is about 12 percentage points, even when holding constant key factors such as educational attainment, duration of unemployment, gender, marital status, and household characteristics. …

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