Using plant-level data from the Plant Capacity Utilization (PCU) Survey, we examine how manufacturing plants' use of temporary workers is associated with the nature of their output fluctuations and other plant characteristics. We find that plants tend to hire temporary workers when their output can be expected to fall, a result consistent with the notion that firms use temporary workers to reduce costs associated with dismissing permanent employees. In addition, we find that plants whose future output levels are subject to greater uncertainty tend to use more temporary workers. We also examine the effects of wage and benefit levels for permanent workers, unionization rates, turnover rates, seasonal factors, and plant size and age on the use of temporary workers; based on our results, we discuss various views of why firms use temporary workers.
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Strong Employers and Weak Employees:
How Does Employer Concentration Affect Wages?
April 2018
Working Paper Number:
CES-18-15
We analyze the effect of local-level labor market concentration on wages. Using plant-level U.S. Census data over the period 1977'2009, we find that: (1) local-level employer concentration exhibits substantial cross-sectional and time-series variation and increases over time; (2) consistent with labor market monopsony power, there is a negative relation between local-level employer concentration and wages that is more pronounced at high levels of concentration and increases over time; (3) the negative relation between labor market concentration and wages is stronger when unionization rates are low; (4) the link between productivity growth and wage growth is stronger when labor markets are less concentrated; and (5) exposure to greater import competition from China (the 'China Shock') is associated with more concentrated labor markets. These five results emphasize the role of local-level labor market monopsonies in influencing firm wage-setting.
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Predictive Analytics and Organizational Architecture:
Plant-Level Evidence from Census Data
January 2019
Working Paper Number:
CES-19-02
We examine trends in the use of predictive analytics for a sample of more than 25,000 manufacturing plants using proprietary data from the US Census Bureau. Comparing 2010 and 2015, we find that use of predictive analytics has increased markedly, with the greatest use in younger plants, professionally-managed firms, more educated workforces, and stable industries. Decisions on data to be gathered originate from headquarters and are associated with less delegation of decision-making and more widespread awareness of quantitative targets among plant employees. Performance targets become more accurate, long-term oriented, and linked to company-wide performance, and management incentives strengthen, both in terms of monetary bonuses and career outcomes. Plants increasing predictive analytics become more efficient, with lower inventory, increased volume of shipments, narrower product mix, reduced management payroll and increased use of flexible and temporary employees. Results are robust to a specification based on increased government demand for data.
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Professional Employer Organizations: What Are They, Who Uses Them and Why Should We Care?
September 2010
Working Paper Number:
CES-10-22
More and more U.S. workers are counted as employees of firms that they do not actually work for. Among such workers are those who staffed by temporary help service (THS) agencies and leased employees who are on the payroll of professional employment organizations (PEOs) but work for PEOs' client firms. While several papers study firms' use of THS services, few examine firms' use of PEO services. In this article, we summarize PEOs' business practices and examine how the intensity of their use varies across industries, geographic areas, and establishment characteristics using both public and confidential data.
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HUMAN CAPITAL LOSS IN CORPORATE BANKRUPTCY
July 2013
Working Paper Number:
CES-13-37
This paper quantifies the 'human costs of bankruptcy' by estimating employee wage losses induced by the bankruptcy filing of employers using employee-employer matched data from the U.S. Census Bureau's LEHD program. We find that employee wages begin to deteriorate one year prior to bankruptcy. One year after bankruptcy, the magnitude of the decline in annual wages is 30% of pre-bankruptcy wages. The decrease in wages persists (at least) for five years post-bankruptcy. The present value of wage losses summed up to five years after bankruptcy amounts to 29-49% of the average pre-bankruptcy market value of firm. Furthermore, we find that the ex-ante wage premium to compensate for the ex-post wage loss due to bankruptcy can be of similar magnitude with that of the tax benefits of debt.
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Computer Networks and U.S. Manufacturing Plant Productivity: New Evidence from the CNUS Data
January 2002
Working Paper Number:
CES-02-01
How do computers affect productivity? Many recent studies argue that using information technology, particularly computers, is a significant source of U.S. productivity growth. The specific mechanism remains elusive. Detailed data on the use of computers and computer networks have been scarce. Plant-level data on the use of computer networks and electronic business processes in the manufacturing sector of the United States were collected for the first time in 1999. Using these data, we find strong links between labor productivity and the presence of computer networks. We find that average labor productivity is higher in plants with networks. Computer networks have a positive and significant effect on plant labor productivity after controlling for multiple factors of production and plant characteristics. Networks increase estimated labor productivity by roughly 5 percent, depending on model specification. Model specifications that account for endogenous computer networks also show a positive and significant relationship. Our work differs from others in several important aspects. First, ours is the first study that directly links the use of computer networks to labor productivity using plant-level data for the entire U.S. manufacturing sector. Second, we extend the existing model relating computers to productivity by including materials as an explicit factor input. Third, we test for possible endogeneity problems associated with the computer network variable.
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Why Are Plant Deaths Countercyclical: Reallocation Timing or Fragility?
November 2006
Working Paper Number:
CES-06-24
Because plant deaths destroy specific capital with large local economic impacts and potentially important macroeconmic effects, understanding the causes of deaths and, in particular, why they are concentrated in cyclical downturns, is important. The reallocationtiming hypothesis posits that plants suffering adverse permanent demand/productivity shocks delay shutdowns until cyclical downturns when plant capacity is less valuable, while the fragility hypothesis posits that shutdowns occur in downturns because the option value of maintaining the plant through low profitability periods is too small. I show that the effect that a plant's specific capital has on the timing of plant deaths differs across these two hypotheses and then use this insight to test the hypotheses' relative importance. I find that fragility is the dominant cause of the countercyclical behavior of plant deaths. This suggests that the endogenous destruction of capital is likely an important amplification and propagation mechanism for cyclical shocks and that stabilization policies have the benefit of reduced capital destruction.
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Technology Use and Worker Outcomes: Direct Evidence from Linked Employee-Employer Data
August 2000
Working Paper Number:
CES-00-13
We investigate the impact of technology adoption on workers' wages and mobility in U.S. manufacturing plants by constructing and exploiting a unique Linked Employee-Employer data set containing longitudinal worker and plant information. We first examine the effect of technology use on wage determination, and find that technology adoption does not have a significant effect on high-skill workers, but negatively affects the earnings of low-skill workers after controlling for worker-plant fixed effects. This result seems to support the skill-biased technological change hypothesis. We next explore the impact of technology use on worker mobility, and find that mobility rates are higher in high-technology plants, and that high-skill workers are more mobile than their low and medium-skill counterparts. However, our technology-skill interaction term indicates that as the number of adopted technologies increases, the probability of exit of skilled workers decreases while that of unskilled workers increases.
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How Does Labor Market Size Affect Firm Capital Structure? Evidence from Large Plant Openings
November 2015
Working Paper Number:
CES-15-38
I examine how the labor market in which firms operate affects their capital structure decisions. Using the US Census Bureau data, I exploit a large plant opening as an abrupt increase in the size of a local labor market. I find that a new plant opening leads to a 2.6% to 3.9% increase in the debt-to-capital ratio of existing firms in the 'winner' county relative to the 'runner-up' choice. This result is consistent with larger labor markets making a job loss less costly, which in turn reduces indirect costs of financial distress. Moreover, this spillover effect is larger for firms 1) that have a larger fraction of employees in the affected county, 2) that employ the same type of workers as the new plant, and 3) that have larger unexploited benefits of debt.
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Firms and Layoffs: The Impact of Unionization on Involuntary Job Loss
March 2003
Working Paper Number:
CES-03-09
This paper focuses on the impact of unionization on involuntary job loss using establishment data from the 1997 National Employer Survey (NES-II) and merging those data with contextual data at the industry level as well as with local labor market data. The estimated logit models included information on unionization rates and employment security provisions present in collective bargaining agreements as factors influencing layoff rates for individual establishments, controlling for establishment size, firm structure, use of non-regular employees, product/service demand and local employment. Results show that the impact of unionization is not significant except for (1) establishments that operate in the non-manufacturing sector; and (2) establishments operating in industries that have major collective bargaining agreements which contain moderate employment security provisions. Under those conditions, unionization decreases layoff rates; otherwise, unionization has no effect on layoff rates. These results provide some evidence that unions may have placed increased emphasis on employment security in order to protect members against involuntary job loss. This is in contrast to earlier studies which found a positive relationship between unionization and layoffs. In addition, establishments in Right-to-Work states have higher rates of involuntary job loss.
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Are All Trade Protection Policies Created Equal? Empirical Evidence for Nonequivalent Market Power Effects of Tariffs and Quotas
September 2010
Working Paper Number:
CES-10-27
The steel industry has been protected by a wide variety of trade policies, both tariff- and quota-based, over the past decades. This extensive heterogeneity in trade protection provides the opportunity to examine the well-established theoretical literature predicting nonequivalent effects of tariffs and quotas on domestic firms' market power. Robust to a variety of empirical specifications with U.S. Census data on the population of U.S. steel plants from 1967-2002, we find evidence for significant market power effects for binding quota-based protection, but not for tariff-based protection. There is only weak evidence that antidumping protection increases market power.
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