In our markup paper, “The Cyclical Behavior of the Price-Cost Markup,” we re-estimated our marginal change in overtime hours using microdata from my Londitudinal Population Databse (LPD). We still find that markups are procyclical or acyclical, both unconditionally and conditional on demand shocks.

In our industry paper, “Industry Evidence on the Effects of Government Spending,” we significantly updated the theory and discussion, explored other industry characteristics associated such as unionization and concentration, and added analysis of the dynamic interactions. We now discuss how the growth of government spending across industries is correlated with technology and show how accounting for this correlation is essential for constructing a proper instrument for government demand.

Copies of either paper can be downloaded from my research page.

You can download a copy of the paper from the link above or on my Research page.

This paper investigates industry-level effects of government purchases in order to shed light on the transmission mechanism for government spending on the aggregate economy. We begin by highlighting the different theoretical predictions concerning the effects of government spending on industry labor market equilibrium. We then create a panel data set that matches output and labor variables to shifts in industry-specific government demand. The empirical results indicate that increases in government demand raise output and hours, but have no effect on real product wages, even over a five-year horizon. Government demand also appears to raise productivity and markups when they are measured using gross output. These results are inconsistent with standard neoclassical and New Keynesian models of government spending.

You can download a copy of the paper from the link above or on my Research page.

Jan. 4, 2:30 pm, Atlanta Marriott Marquis, Marquis Ballroom – Salon D
AEA
Fiscal Stabilization Policy (E6)
Presiding: STEVEN DAVIS, University of Chicago

ROBERT BARRO, Harvard University, CHARLES REDLICK, Harvard University – Fiscal Multipliers
GARY BECKER, University of Chicago, KEVIN M. MURPHY, University of Chicago, ROBERT H. TOPEL, University of Chicago – Evaluating the Fiscal Stimulus
CHRISTOPHER J. NEKARDA, Federal Reserve Board, VALERIE A. RAMEY, University of California-San Diego – Industry Evidence on the Effects of Government Spending
MICHAEL WOODFORD, Columbia University – Simple Analytics of the Government Expenditure Multiplier

Here is the abstract:

Countercyclical markups constitute the key transmission mechanism for monetary and other “demand” shocks in New Keynesian models. This paper tests the foundation of those models by studying the cyclical properties of the markup of price over marginal cost. The first part of the paper studies markups in the aggregate economy and the manufacturing sector. We use Bils’ (1987) insights for converting average cost to marginal cost, but do so with richer data. We find that all measures of markups are either procyclical or acyclical. Moreover, we show that monetary shocks lead markups to fall with output. The second part of the paper merges input-output information on shipments to the government with detailed industry data to study the effect of demand changes on industry-level markups. Industry-level markups are found to be decidedly procyclical in response to demand changes.

You can download a copy of the paper from the link above or on my Research page.

U.S. Migration Falls Sharply, by Conor Dougherty, WSJ:

Migration around the U.S. slowed to a crawl last year, especially for this decade’s boom towns, as a weak housing market and job insecurity forced many Americans to stay put.

Demographers say the dropoff in migration, shown in Census data to be released Thursday, is among the sharpest since the Great Depression. It marks the end of what Brookings Institution demographer William Frey calls a “migration bubble.”

As asset values rose fairly steadily in the past decade, Americans young and old moved around the country in search of jobs or better weather. In many cases, people living in higher-cost housing markets such as San Francisco and New York cashed in their real-estate winnings and moved to outlying counties, or to states like Florida and Nevada, hoping to find a cheaper house and pocket the difference. Now, “people are hanging tight; they’re too scared to do anything,” said Mr. Frey.

The data, covering the one-year period until July 1, 2008, show this effect across U.S. counties and metropolitan areas — another sign of how this recession has spared few industries or regions.

Migration typically slows during recessions. But in past downturns, the slowdown has been more regional in scope, with workers fleeing weaker job markets for places where companies were still hiring. In the deep 1980s recession, for instance, laid-off auto workers fled the industrial Midwest for energy-rich states in the South with more plentiful jobs.

What’s unique this time is migration has slowed almost everywhere. The sharpest year-to-year changes were among what demographers call “domestic migrants,” people who moved within the U.S. That doesn’t count population changes that result from births, deaths or immigration.

Although I agree with the trend behavior described above, Dougherty is incorrect about the cyclicality of geographic mobility. In fact, geographic mobility is moderately countercyclical—that is, more people move during recessions than during booms (relative to trend). This may seem counter-intuitive but makes economic sense.

Geographic mobility is a means of reallocating resources, in this case labor, to more efficient uses. In the past, 70 percent of people who move indicated having moved for economic reasons and up to 50 percent of those moves occurred because of a job separation [Lansing and Morgan (1967); Bartel (1979)]. In particular, there is a significant positive relationship between unemployment and geographic mobility [Bartel (1979); Schlottmann and Herzog Jr. (1981, 1984)]. Thus, countercyclical mobility is consistent with reallocation of idle workers across space.

I assess the cyclicality of geographic mobility in a recent working paper. I the measure the rate of geographic mobility as one minus the share of persons living at the same address one year later reported by the U.S. Census Bureau. These data come from the March supplement to the Current Population Survey, so the 2007 data do not reflect much of the distress in mortgage markets—and any concomitant effects on mobility—that began later in 2007.

Removing the low-frequency trend is important because it represents structural changes—such as demographic changes or, say, innovations in mortgage finance—that are unassociated with the business cycle. I isolate the component of the time series that moves at business cycle frequency using an unobserved components model (see paper for details). The figure below plots the cyclical component of the mobility rate together with that of the unemployment rate for comparison.

The cyclical component of mobility tends to follow the unemployment rate, indicating that more people move during recessions than during booms. This is consistent with geographic mobility as a means for reallocating idle labor to more productive uses. The contemporaneous correlation of the cyclical component of the mobility rate with the unemployment rate is 0.50, indicating moderate countercyclicality. Also note that mobility is substantially less volatile over the business cycle than unemployment.

Of course, the problems in the housing market beginning in 2007, notably the dramatic decline in prices, will undoubtedly reduce geographic mobility during this recession. This will further slow recovery because unemployed persons cannot move to areas with more favorable labor markets as easily or quickly as before.

Remember, Thursday will be an in-class review for the final exam.