Why Do So Few Women Work in New York (And So Many in Minneapolis)?

Nice paper from  Dan A. Black, Natalia Kolesnikova and Lowell J. Taylor.

The results are pretty intuitive. They say cities which have larger commuting time have fewer working women:

This paper documents a little-noticed feature of U.S. labor markets|very large variation in the labor supply of married women across cities. We focus on cross-city differences in commuting times as a potential explanation for this variation. We start with a model in which commuting times introduce non-convexities into the budget set. Empirical evidence is consistent with the model’s predictions: Labor force participation rates of married women are negatively correlated with the metropolitan area commuting time. Also, metropolitan areas with larger increases in average commuting time in 1980-2000 had slower growth in the labor force participation of married women.

The results show large effects:

For women, the effects of commute times are quite large. From Table 5 we see that a 1-minute increase in an MSA’s commute time is associated with an approximately 0.3 per- centage point decline in the labor force participation of women with a high school education.   Table 4 indicates that the difference in commute times, from the shortest-commute MSA to the longest-commute MSA, is 33 minutes. Taking our estimates at face value, this variation might be expected to lead to a 10 percentage point difference in participation across cities. Commute time di®erences across MSAs thus plausibly \explain” a fair amount of the cross-MSA variation in participation observed in Table 1.

It might be reasonable to ask, indeed, if our estimates are \too big.” One might reason that a 30-minute increase in commute time presents an opportunity cost of only $10 daily for a woman who earns $20/hour. Could such a modest factor plausibly have such a large impact on behavior? In thinking about that issue it is important to recognize that the cost to a typical mother of living in a high-commute MSA extends far beyond the increased time she spends commuting if she works. As we noted above, in congested cities there will be additional time required for travel to the grocery store, piano lessons, or little league baseball. If she chooses to commute a long distance to work, a mother will likely be farther from her children’s school, which can make life difficult when she needs to be available for a parent-teacher conference or a class play. Our estimates are not picking up the pure effect of the commute time of the participation decision, but the total impact of congestion on the participation decision.

Policy implications:

One implication of our work concerns the century-long increase in the female labor force participation|the increase in married women’s participation from only about 7 percent in 1900 to current rates (near 70 percent). There are doubtless many factors contributing to this trend, many of which have received careful examination in the literature. Little attention has been given, though, to the possibility that part of this trend is due to the reduction in commuting costs, owing to improvements in transportation technology|the expansion of modern public transportation, the introduction and continued improvement in automotive technology, improvements in roads, and so on|and changes in residential patterns.

Our findings about the wide cross-city variation in the labor force participation of married women also introduce a new dimension to the current discussion about trends in the female labor supply. In particular, these ¯ndings complicate discussions about women having reached a \natural rate” of labor force participation. The issue is how close to 1 we can expect this participation rate to be. Goldin (2006), Juhn and Potter (2006), and others show that labor force participation rates depend on a combination of demographic factors such as age, presence of children, education, and race. The \natural rate” of participation is expected to be different for di®erent groups. Our research suggests that the maximum achievable rate of labor force participation for each group would also vary across cities (and also across countries) because of di®erences in commuting time.

Of course, commuting times in local communities also depend on population density, the resources devoted to transportation, and local planning (e.g., zoning laws that may sometimes serve to isolate residential communities from job locations). Thus, from a public policy perspective, it may be that targeted actions that reduce commuting times would thereby increase labor force participation by women. Yet another open policy issue concerns the importance of variation in labor supply across cities for tax and welfare policy. It would be interesting to analyze how differences in the time cost of commuting affect labor supply responses to changes in such policies. 

Interesting paper..

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: