Labor market inefficiency and economic restructuring: evidence from cross-sectoral data.

• Author: Cotti, Chad D.

1. Introduction

   It has been widely noted that the U.S. labor market was relatively weak during the recovery from the 2001 recession. Although the recession itself was comparatively mild and short-lived (March-November 2001, according to the National Bureau of Economic Research), and although four million additional workers entered the labor force during the recovery, even by the most generous measure employment did not return to prerecession levels for over two and a half years. (1) One might imagine that the "jobless recovery" reflected a weak macroeconomy, but real gross domestic product growth averaged a healthy 3.2% in the three years after the recession. Nevertheless, job creation was weak, and unemployment rates recovered slowly even after employers began to post vacant jobs.

   Because there was also a considerable reallocation of jobs across industries during this period, some economists have recently speculated that the two trends might be related (Groshen and Potter 2003; Minehan 2004; Groshen, Potter, and Sela 2005). According to the "Sectoral Shift Hypothesis" (generally attributed to Lilien [1982]), extensive restructuring can create inefficiencies in the labor market, either by causing a skills mismatch between employers and employees or by forcing them to search in less familiar territory. If so, changes in relative labor demand across industries would raise unemployment, even if there were no change in aggregate labor demand. Consequently, aggregate demand stimulus would likely not be effective in combating unemployment, but there may be more useful roles for retraining programs or industrial policy that attempted to balance growth (or even contraction) more evenly across sectors of the economy.

   That said, such restructuring is only one of the possible explanations for the jobless recovery. For example, Minehan (2004) also discusses potential roles for trends in international trade, labor costs, and an increase in uncertainty caused by geopolitical events. If such factors proved to be more important, policy discussions might focus more fruitfully on topics like trade agreements, exchange rate policy, the financing of health care and pensions, payroll taxes, diplomacy, the treatment of investments in the tax code, or interest rates.

   This paper contributes to that debate by presenting new evidence on the relevance of the Sectoral Shift Hypothesis during this business cycle. Previous empirical work on the hypothesis has produced mixed results--many papers find support for the hypothesis, but many others find evidence against it. As Schwerin (2003) has argued in his extensive literature review, one explanation for this inconsistency could be that the hypothesis has greater merit in some periods than others. For example, the nature of structural change likely varies across business cycles, and its effects might well depend on the similarity between the skills demanded by expanding and contracting industries, the extent of job-specific human capital or on-the-job training, or the geographical composition of the structural change.

   Accordingly, it would seem desirable to use an empirical methodology that allows the effects of restructuring to vary over time. Unfortunately, until recently, that has been difficult because the best data available consisted of aggregate time series. That data permitted researchers to address the Sectoral Shift Hypothesis by looking for a relationship between the timing of changes in some measure of labor market inefficiency (often just aggregate unemployment rates) and some economy-wide index of structural change (e.g., a dissimilarity index of industries' growth rates). However, given sample size limitations, the only reasonable identification strategy rested on an implicit assumption that a given degree of reallocation has similar effects on unemployment across different business cycles. If that assumption were violated, researchers could reject the Sectoral Shift Hypothesis as a general proposition even if it had substantial explanatory power in some subset of business cycles.

   To avoid this concern, this paper takes a different approach, one that is more nearly cross-sectional than intertemporal. Thanks to new data, we are able to disaggregate across supersectors of the U.S. economy. The additional sample size this provides allows us to examine a single business cycle in isolation, and we can then test the hypothesis by quantifying the changes in the inefficiency of sectoral labor markets and comparing them to the extent of structural change in those sectors. In essence, we ask whether reallocation and increased inefficiency happen not only at the same time, but in the same sectors. We know of only one previous paper that has attempted to address the Sectoral Shift Hypothesis with disaggregated data; part of a paper by Abraham (1987) analyzes unemployment and vacancy rates across U.S. states. We argue that the approach in this paper provides a more direct test of the Sectoral Shift Hypothesis.

   The outcome of that test will cast doubt on the relevance of this hypothesis in the business cycle that started with the 2001 recession. The analysis will reveal that the sectors that experienced the largest structural change did not have unusually large changes in inefficiency, and that most of the sectors that suffered the largest increases in labor market inefficiency had relatively mild structural change. Admittedly, this conclusion emerges from a sample of just 12 sectors, so it would be reasonable to regard it with some caution. That said, previous studies based their conclusions on just one (aggregate) data series, albeit over a few business cycles.

   In addition to the main finding, this paper also makes two ancillary contributions. First, it develops a new method to measure changes in labor market inefficiency: a variation on principal components analysis. This method allows us to identify the relationship between unemployment and vacancies (what is often called the "Beveridge curve" or "u-v curve") with relatively sparse data and without strong identifying assumptions. Changes in unemployment and vacancy rates can then be decomposed into two parts, one reflecting changes in the position of the Beveridge curve relative to the origin (which will serve as our measure of labor market inefficiency) and the other reflecting movements along the Beveridge curve (and thus "pure" business cycle effects, holding labor market inefficiency constant). Because this is a nonstandard approach, we also attempt to gauge the potential for bias and conclude that it is unlikely to affect our results materially.

   The other ancillary contribution is to present the first evidence on sectoral Beveridge curves, something that is only possible because of the new data set we examine. Although we will find that Beveridge curves have similar slopes across sectors, we will document substantial differences in the efficiency of sectoral labor markets and the extent to which that efficiency fluctuated over this business cycle. At the least, these findings should provide a useful point of comparison for future studies of sectoral labor markets during business cycles yet to come.

   The presentation proceeds as follows. Section 2 introduces the underlying theory and outlines the paper's empirical strategy. The data used in the empirical analysis are described in section 3, and section 4 explains the method we use to quantify labor market inefficiency and investigates the potential for bias. Section 5 presents results of that methodology, with an emphasis on cross-sectoral differences in the extent to which labor market inefficiency rose over this business cycle. We then use those measured increases in sectoral labor market inefficiency to test the Sectoral Shift Hypothesis in section 6. Specifically, the first subsection of section 6 shows that the cross-sectoral variation in those fluctuations cannot be explained by an important alternative explanation, but a second subsection shows that it also does not correlate well with the extent of sectoral reallocation--which is why we conclude that there is little support for the Sectoral Shift Hypothesis. The argument is summarized in section 7, and the paper ends with a brief discussion of the implications and issues for future research.

2. Background

   The Sectoral Shift Hypothesis (Bowden 1980; Lilien 1982) posits that labor markets clear more slowly in the presence of economic restructuring. The idea is that there is an important difference between workers who are unemployed because of purely temporary fluctuations and those who are unemployed because of a structural change that reallocates jobs between sectors (or for that matter, between industries within the same sector). In contrast to the former group, structurally unemployed workers cannot reasonably hope to be rehired when the economy rebounds, so they are forced to cast a wider net. During the time needed to realize that the shock is persistent, skills are mismatched and there is a general lack of familiarity with the expanding employers, so such workers are unlikely to find new jobs as quickly as other unemployed workers.

   The hypothesis thus proposes a specific reason for an increase in what is often called "matching inefficiency." That term refers to any factors that slow the rate at which new employment matches form from given stocks of unemployed workers and vacant jobs. In other words, the hypothesis proposes a reason why search frictions are more severe in some situations than in others.

   Matching inefficiency is difficult to observe directly, so we shall infer it by observing the behavior of sectoral Beveridge curves and ruling out some other major explanations for what we find. Once it is established that the observed patterns could plausibly represent matching inefficiency, we can test the Sectoral Shift Hypothesis by asking whether the increases in matching inefficiency are larger in...