Heterogeneity and Unemployment Dynamics

Hie Joo Ahn,James D Hamilton

doi:10.17016/feds.2016.012r1

Abstract

This paper develops new estimates of flows into and out of unemployment that allow for unobserved heterogeneity across workers as well as direct effects of unemployment duration on unemployment-exit probabilities. Unlike any previous paper in this literature, we develop a complete dynamic statistical model that allows us to measure the contribution of different shocks to the short-run, medium-run, and long-run variance of unemployment as well as to specific historical episodes. We find that changes in the inflows of newly unemployed are the key driver of economic recessions and identify an increase in permanent job loss as the most important factor.

Highlights

What accounts for the sharp spike in the unemployment rate during recessions? The answer traditionally given by macroeconomists was that falling product demand leads firms to lay off workers, with these job separations a key driver of economic downturns
We have shown how the time series of unemployment levels by different duration categories can be used to infer inflows and outflows from unemployment for workers characterized by unobserved heterogeneity
In contrast to other methods, our approach uses the full history of unemployment data to summarize inflows and outflows from unemployment and allows us to make formal statistical statements about how much of the variance of unemployment is attributable to different factors as well as identify the particular changes that characterized individual historical episodes

Summary

Introduction

What accounts for the sharp spike in the unemployment rate during recessions? The answer traditionally given by macroeconomists was that falling product demand leads firms to lay off workers, with these job separations a key driver of economic downturns. That view has been challenged by Hall (2005) and Shimer (2012), among others, who argued that cyclical fluctuations in the unemployment rate are instead primarily driven by declines in the job-finding rates for unemployed workers This debate has become important for understanding the Great Recession and its aftermath. Looking at observable characteristics of the unemployed, such as gender, age, education, occupation, industry, or reason for unemployment, we find that the duration of unemployment rises significantly for almost every observable characteristic during the Great Recession and compositional shifts in the unemployment of different groups explain little of the observed increase in average duration of unemployment This observation seems to suggest that the rise in unemployment duration is driven by aggregate factors that affect many workers in a similar way. In spite of the intensive research in this topic, simple averaging has been the most popular method for forecast combination since it performs relatively well compared to other approaches, often known as ”forecasting combination puzzle”, and is easy to implement in practice

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