Papers Containing Tag(s): 'Employer-Household Dynamics'
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Viewing papers 11 through 15 of 15
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Working PaperThe Recent Decline of Single Quarter Jobs
January 2015
Working Paper Number:
CES-15-05
Rates of hiring and job separation fell by as much as a third in the U.S. between the late 1990s and the early 2010s. Half of this decline is associated with the declining incidence of jobs that start and end in the same calendar quarter, employment events that we call 'single quarter jobs.' We investigate this unique subset of jobs and its decline using matched employer-employee data for the years 1996-2012. We characterize the worker demographics and employer characteristics of single quarter jobs, and demonstrate that changes over time in workforce and employer composition explain little of the decline in these jobs. We find that the decline in these jobs accounts for about a third of the decline in the fraction of the population that holds a job in the private sector that occurred from the mid 2000s to the early 2010s. We also find little evidence that single quarter jobs are stepping stones into longer-term employment. Finally, we show that the inclusion or exclusion of these single quarter jobs creates divergent trends in average earnings and the dispersion of earnings for the years 1996-2012. To the extent that administrative records measure the volatile tail of the employment distribution better thanconventional household surveys, these findings show that measurement of short duration jobs matters for economic analysis.View Full Paper PDF
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Working PaperMeasuring U.S. Innovative Activity
March 2007
Working Paper Number:
CES-07-11
Innovation has long been credited as a leading source of economic strength and vitality in the United States because it leads to new goods and services and increases productivity, leading to better living standards. Better measures of innovative activities'activities including but not limited to innovation alone'could improve what we know about the sources of productivity and economic growth. The U.S. Census Bureau either currently collects, or has collected, data on some measures of innovative activities, such as the diffusion of innovations and technologies, human and organizational capital, entrepreneurship and other worker and firm characteristics, and the entry and exit of businesses, that research shows affect productivity and other measures of economic performance. But developing an understanding of how those effects work requires more than just measures of innovative activity. It also requires solid statistical information about core measures of the economy: that is, comprehensive coverage of all industries, including improved measures of output and sales and additional information on inputs and purchased materials at the micro (enterprise) level for the same economic unit over time (so the effects can be measured). Filling gaps in core data would allow us to rule out the possibility that a measure of innovative activity merely proxies for something that is omitted from or measured poorly in the core data, provide more information about innovative activities, and strengthen our ability to evaluate the performance of the entire economy. These gaps can be filled by better integrating existing data and by more structured collections of new data.View Full Paper PDF
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Working PaperThe LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators
January 2006
Working Paper Number:
tp-2006-01
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, has built a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. Beginning in 2003 and building on this infrastructure, the Census Bureau has published the Quarterly Workforce Indicators (QWI), a new collection of data series that offers unprecedented detail on the local dynamics of labor markets. Despite the fine detail, confidentiality is maintained due to the application of state-of-the-art confidentiality protection methods. This article describes how the input files are compiled and combined to create the infrastructure files. We describe the multiple imputation methods used to impute in missing data and the statistical matching techniques used to combine and edit data when a direct identifier match requires improvement. Both of these innovations are crucial to the success of the final product. Finally, we pay special attention to the details of the confidentiality protection system used to protect the identity and micro data values of the underlying entities used to form the published estimates. We provide a brief description of public-use and restricted-access data files with pointers to further documentation for researchers interested in using these data.View Full Paper PDF
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Working PaperWage Dispersion, Compensation Policy and the Role of Firms
November 2005
Working Paper Number:
tp-2005-04
Empirical work in economics stresses the importance of unobserved firm- and person-level characteristics in the determination of wages, finding that these unobserved components account for the overwhelming majority of variation in wages. However, little is known about the mechanisms sustaining these wage di'er- entials. This paper attempts to demystify the firm-side of the puzzle by developing a statistical model that enriches the role that firms play in wage determination, allowing firms to influence both average wages as well as the returns to observable worker characteristics. I exploit the hierarchical nature of a unique employer-employee linked dataset for the United States, estimating a multilevel statistical model of earnings that accounts for firm-specific deviations in average wages as well as the returns to components of human capital - race, gender, education, and experience - while also controlling for person-level heterogeneity in earnings. These idiosyncratic prices reflect one aspect of firm compensation policy; another, and more novel aspect, is the unstructured characterization of the covariance of these prices across firms. I estimate the model's variance parameters using Restricted (or Residual) Maximum Likelihood tech- niques. Results suggest that there is significant variation in the returns to worker characteristics across firms. First, estimates of the parameters of the covariance matrix of firm-specific returns are statistically significant. Firms that tend to pay higher average wages also tend to pay higher than average returns to worker characteristics; firms that tend to reward highly the human capital of men also highly reward the human capital of women. For instance, the correlation between the firm-specific returns to education for men and women is 0.57. Second, the firm-specific returns account for roughly 9% of the variation in wages - approximately 50% of the variation in wages explained by firm-specific intercepts alone. The inclusion of firm-specific returns ties variation in wages, otherwise attributable to firm-specific intercepts, to observable components of human capital.View Full Paper PDF
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Working PaperIs it Who You Are, Where You Work, or With Whom You Work? Reassessing the Relationship Between Skill Segregation and Wage Inequality
June 2002
Working Paper Number:
tp-2002-10
In a recent paper, Kremer & Maskin (QJE, forthcoming) develop an assignment model in which increases in the dispersion and mean of the skill distribution can lead simultaneously to increases in wage inequality and skill segregation. They then present evidence that, concurrent with rising wage inequality, wage segregation increased for production workers in the United States between 1975 and 1986. My paper argues that relying on wages as a proxy for skill may be problematic. Using a newly developed longitudinal dataset linking virtually the entire universe of workers in the state of Illinois to their employers, I decompose wages into components due, not only to person and firm heterogeneity, but also to the characteristics of their co-workers. Such "co-worker effects" capture the impact of a weighted sum of the characteristics of all workers in a firm on each individual employee's wage. While rising wage segregation can result from greater skill segregation, it may also be due to changes in the variance of co-worker effects in the economy, or to changes in the covariance between the person, firm, and co-worker components of wages. Due to the limited availability of demographic information on workers, I rely on the person specific component of wages to proxy for co-worker "skills." Because these person effects are unknown ex ante, I implement an iterative estimation approach where they are first obtained from a preliminary regression that excludes any role for co-workers. Because virtually all person and firm effects are identified, the approach yields consistent estimates of the co-worker parameters. My estimates imply that a one standard deviation increase in both a firm's average person effect and experience level is associated, on average, with wage increases of 3% to 5%. Firms that increase the wage premia they pay workers appear to do so in conjunction with upgrading worker quality. Interestingly, the average effect masks considerable variation in the relative importance of co-workers across industries. After allowing the co-worker parameters to vary across 2 digit industries, I find that industry average co-worker effects explain 26% of observed inter-industry wage differentials. Finally, I decompose the overall distribution of wages into components due to persons, firms, and coworkers. While co-worker effects do indeed serve to exacerbate wage inequality, the tendency for high and low skilled workers to sort non-randomly into firms plays a considerably more prominent role.View Full Paper PDF
