Research Interests

Primary: Macroeconomics, labor markets
Secondary: Applied econometrics, time series

Publications

Industry Evidence on the Effects of Government Spending

with Valerie A. Ramey
January 2011
American Economic Journal: Macroeconomics, 3(1), pp. 36-59.

This paper investigates the effects of government purchases at the industry level in order to shed light on the transmission mechanism for government spending on the aggregate economy. We create a new panel dataset that matches output and labor variables to industry-specific shifts in government demand. An increase in government demand raises output and hours, lowers real product wages and labor productivity, and has no effect on the markup. The estimates also imply approximately constant returns to scale. The findings are more consistent with the effects of government spending in the neoclassical model than the textbook New Keynesian model. (JEL E12, E23, E62, H50)

Online appendix (.zip)
Data set (.zip)

Working Papers

Click on the title to download the paper. All papers are posted in PDF format.

Using Labor Force Flows to Forecast the Labor Market

with Regis Barnichon
January 2012

This paper presents a simple nonlinear forecasting model of unemployment based on labor force flows data that, in real time, dramatically outperforms the Survey of Professional Forecasters, the Federal Reserve Board’s Greenbook forecast, and basic time series models for short-term forecasts. Our model reduces the mean squared error of the best forecast by 30 to 40 percent. The model also does a good job at identifying turning points several quarters ahead of other forecasters and models. Further, because our model uses information on worker flows typically ignored by other approaches, a combined forecast including our model and the Greenbook forecast yields improvement of about 50 percent for same-quarter forecast, 40 percent for next quarter forecast, and even slight improvements at longer horizons.

The Cyclical Behavior of the Price-Cost Markup

with Valerie A. Ramey
June 2010

Countercyclical markups constitute the key transmission mechanism for monetary and other “demand” shocks in textbook 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’s (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 last 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 acyclical in response to demand changes.

Understanding Unemployment Dynamics: The Role of Time Aggregation

June 2009

This paper uses weekly data from the Survey of Income and Program Participation (SIPP) to estimate the role of time aggregation in measuring gross labor force flows and unemployment dynamics. Time aggregation is substantial: gross flows estimated from monthly data understate the true number of transitions by 15–24 percent. Time aggregation in both separations to unemployment and accessions from unemployment comoves positively with the business cycle. The effect from time aggregation on separations is roughly offset by its effect on accessions, however, creating no meaningful cyclical bias in measured gross flows or hazard rates. Contrary to claims by Hall (2006) and Shimer (2007), separation hazard rates calculated from the SIPP and the Current Population Survey are strongly countercyclical and remain so after adjusting for time aggregation. In addition, the separation hazard rate contributes fully one-half of the cyclical variance of the steady-state unemployment rate after adjusting for time aggregation.

A Longitudinal Analysis of the Current Population Survey: Assessing the Cyclical Bias of Geographic Mobility

May 2009

This paper assesses the implications of geographic mobility for the measurement of U.S. labor market dynamics using the Current Population Survey (CPS). Because the CPS does not follow individuals that move, estimates may be biased if the labor market behavior of movers differs systematically from that of nonmovers. I create a new database, the Longitudinal Population Database (LPD), that utilizes all longitudinal information in the CPS to form a panel data set. I use the LPD to identify persons who move and therewith estimate a bound on the bias from geographic mobility. I find that the cyclical bias arising from geographic mobility is small. At business cycle frequencies, the difference between the separation hazard rate calculated from the entire CPS sample and from a subset that are known not to have moved never exceeds 4 percent. There is little effect of mobility on the job finding hazard rate. I conclude that geographic mobility does not significantly affect CPS labor market dynamics.

Weekly Time Series of the U.S. Labor Market

December 2008

Data from the Survey of Income and Program Participation (SIPP) are used to create a new data set of U.S. labor market behavior at weekly frequency, including the number of direct employment-to-employment (EE) transitions. The paper documents difficulties encountered creating the weekly series and discusses the strengths and weaknesses of the SIPP data relative to the CPS. Overall the SIPP labor force stocks, gross flows, and cyclical dynamics compare favorably with those from the Current Population Survey (CPS). Abstracting from labor force participation, direct EE transitions account for one-half of all separations from employment. Although CPS–based estimates of EE flows are nearly twice as high, the CPS overstates EE flows because of time aggregation. Separations to a new job are strongly procyclical while separations to unemployment are strongly countercyclical. The combination yields a nearly acyclical total separation rate.

The Cyclicality of Worker Flows: New Evidence from the SIPP

with Shigeru Fujita and Garey Ramey
January 2007

Drawing on CPS data, Fujita and Ramey (2006) show that total monthly job loss and hiring among U.S. workers, as well as job loss hazard rates, are strongly countercyclical, while job finding hazard rates are strongly procyclical. They also find that total job loss and job loss hazard rates lead the business cycle, while total hiring and job finding rates trail the cycle. In the current paper we use information from the Survey on Income and Program Participation (SIPP) to reevaluate these findings. SIPP data are used to construct new longitudinally-­consistent gross flow series for U.S. workers, covering 1983-2003. The results strongly validate the Fujita-­Ramey findings, with two important exceptions: (1) total hiring leads the cycle in the SIPP data, and (2) the job loss rate is substantially more volatile than the job finding rate at business cycle frequencies.