Murat Tasci

Diagnosing Labor Market Search Models: A Multiple-Shock Approach

We construct a multiple-shock version of the Mortensen-Pissarides labor market search model to investigate the basic model’s well-known tendency to underpredict the volatility of key labor market variables. Data on U.S. job-finding and job separation probabilities are used to help estimate the parameters of a three-dimensional shock process comprising labor productivity, job separation, and matching or “allocative” efficiency. Although our multiple-shock model generates some more volatility, it has counterfactual implications for the cyclicality of unemployment and vacancies. Our second exercise forces the model to be the data-generating process to uncover the necessary realizations of all three shocks. We show that the Mortensen-Pissarides labor market search model requires significantly procyclical and volatile matching efficiency and job separations to simultaneously account for high procyclical variations in job-finding probabilities as well as relatively small net employment changes in the data. Hence, the model is more fundamentally flawed than its inability to amplify shocks would suggest. We also show that variation in job separations accounts for most of the employment fluctuations, suggesting that endogenous separations could be the key feature of an improved model. This leads us to conclude that the model lacks mechanisms to generate procyclical matching efficiency and labor force reallocation. As for the latter, we conjecture that nontrivial labor force participation and job-to-job transitions are promising avenues of research. Note: This paper is a revised version of an earlier working paper of the same title, WP 07-20.

Search Frictions and the Labor Wedge

This paper shows that labor market search frictions do not explain fluctuations in the labor wedge per se. However, the introduction of extensive and intensive margin clarifies that measuring the MRS in terms of total hours artificially introduces procyclicality in the MRS. When the MRS is correctly measured in terms of hours per worker, the labor wedge obtained is less variable than the one of the competitive model. Finally, we show that it is possible to measure a strongly procyclical labor wedge when the actual data generating process is a search model that allows for movements in both margins.

The Cyclical Behavior of Equilibrium Unemployment and Vacancies across OECD Countries

We show that the inability of a standardly-calibrated stochastic labor search-and-matching model to account for the observed volatility of unemployment and vacancies extends beyond U.S. data to a set of OECD countries -- the volatility puzzle is ubiquitous. We also argue that using cross-country data is helpful in evaluating the relative merits of the model alternatives that have appeared in the literature. In illustrating this point, we take the solution proposed in Hagedorn and Manovskii (2008) and show that it continues to predict counterfactually low volatility in labor market variables for countries that exhibit sufficiently low persistence in their estimated productivity processes.

Positive and Normative Effects of a Minimum Wage

We review the positive and normative effects of a minimum wage in various versions of a search-theoretic model of the labor market.

Organizations, Skills, and Wage Inequality

We present a model with search frictions and heterogeneous agents that allows us to decompose the overall increase in US wage inequality in the last 30 years into its within- and between-firm and skill components. We calibrate the model to evaluate how much of the overall rise in wage inequality and its components is explained by different channels. Output distribution per firm-skill pair more than accounts for the observed increase over this period. Parametric identification implies that the worker-specific component is responsible for 85 percent of this, compared to 15 percent that is attributable to firm-level productivity shifts

Lessons for Forecasting Unemployment in the U.S.: Use Flow Rates, Mind the Trend

This paper evaluates the ability of autoregressive models, professional forecasters, and models that leverage unemployment flows to forecast the unemployment rate. We pay particular attention to flows-based approaches—the more reduced form approach of Barnichon and Nekarda (2012) and the more structural method in Tasci (2012)—to generalize whether data on unemployment flows is useful in forecasting the unemployment rate. We find that any approach that leverages unemployment inflow and outflow rates performs well in the near term. Over longer forecast horizons, Tasci (2012) appears to be a useful framework, even though it was designed to be mainly a tool to uncover long-run labor market dynamics such as the “natural” rate. Its usefulness is amplified at specific points in the business cycle when unemployment rate is away from the longer-run natural rate. Judgmental forecasts from professional economists tend to be the single best predictor of future unemployment rates. However, combining those guesses with flows based approaches yields significant gains in forecasting accuracy.

Unemployment Flows, Participation, and the Natural Rate for Turkey

This paper measures flow rates into and out of unemployment for Turkey and uses these rates to estimate the unemployment rate trend, that is the level of the unemployment rate the economy converges to in the long-run. In doing so, the paper explores the role of the labor force participation in determining the trend unemployment. We find an inverse V-shaped pattern for the unemployment rate trend over time in Turkey, currently standing between 8.5 and 9 percent, with an increasing labor market turnover. We also find that allowing for an explicit role for participation changes the results substantially, reducing the “natural” rate at first, but then getting closer to the baseline over time. Finally, we show that this parsimonious model can be used for forecasting unemployment in Turkey with relative ease and accuracy.