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Mixed-Effects Methods For Search and Matching Research
September 2023
Working Paper Number:
CES-23-43
We study mixed-effects methods for estimating equations containing person and firm effects. In economics such models are usually estimated using fixed-effects methods. Recent enhancements to those fixed-effects methods include corrections to the bias in estimating the covariance matrix of the person and firm effects, which we also consider.
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Building the Census Bureau Index of Economic Activity (IDEA)
March 2023
Working Paper Number:
CES-23-15
The Census Bureau Index of Economic Activity (IDEA) is constructed from 15 of the Census Bureau's primary monthly economic time series. The index is intended to provide a single time series reflecting, to the extent possible, the variation over time in the whole set of component series. The component series provide monthly measures of activity in retail and wholesale trade, manufacturing, construction, international trade, and business formations. Most of the input series are Principal Federal Economic Indicators. The index is constructed by applying the method of principal components analysis (PCA) to the time series of monthly growth rates of the seasonally adjusted component series, after standardizing the growth rates to series with mean zero and variance 1. Similar PCA approaches have been used for the construction of other economic indices, including the Chicago Fed National Activity Index issued by the Federal Reserve Bank of Chicago, and the Weekly Economic Index issued by the Federal Reserve Bank of New York. While the IDEA is constructed from time series of monthly data, it is calculated and published every business day, and so is updated whenever a new monthly value is released for any of its component series. Since release dates of data values for a given month vary across the component series, with slight variations in the monthly release date for any one component series, updates to the index are frequent. It is unavoidably the case that, at almost all updates, some of the component series lack observations for the current (most recent) data month. To address this situation, component series that are one month behind are predicted (nowcast) for the current index month, using a multivariate autoregressive time series model. This report discusses the input series to the index, the construction of the index by PCA, and the nowcasting procedure used. The report then examines some properties of the index and its relation to quarterly U.S. Gross Domestic Product and to some monthly non-Census Bureau economic indicators.
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Releasing Earnings Distributions using Differential Privacy: Disclosure Avoidance System For Post Secondary Employment Outcomes (PSEO)
April 2019
Working Paper Number:
CES-19-13
The U.S. Census Bureau recently released data on earnings percentiles of graduates from post secondary institutions. This paper describes and evaluates the disclosure avoidance system developed for these statistics. We propose a differentially private algorithm for releasing these data based on standard differentially private building blocks, by constructing a histogram of earnings and the application of the Laplace mechanism to recover a differentially-private CDF of earnings. We demonstrate that our algorithm can release earnings distributions with low error, and our algorithm out-performs prior work based on the concept of smooth sensitivity from Nissim, Raskhodnikova and Smith (2007).
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The Employee Clientele of Corporate Leverage: Evidence from Personal Labor Income Diversification
January 2018
Working Paper Number:
CES-18-01
Using employee job-level data, we empirically test the equilibrium matching between a firm's debt usage and its employee job risk aversion ('clientele effect'), as predicted by the existing theories. We measure job risk aversion for a firm's employees using their labor income concentration in the firm, calculated as the fraction of the employees' total personal labor income or total household labor
income that is accounted for by their income from this particular firm. Using a sample of about 1,400 U.S. public firms from 1990-2008, we find a robust negative relation between leverage and employee job risk aversion, which is consistent with the clientele effect. Specifically, when a firm's existing employees have higher labor income concentration in it, the firm tends to have lower contemporaneous and future leverage. Moreover, in terms of new hires, firms with lower leverage are more likely to recruit employees with less alternative labor income. Our results continue to hold after we control for firm fixed effects, other employee characteristics such as wages, gender, age, race, and education, and managerial risk attitudes. Further, the matching between a firm's leverage and its workers' labor income concentration in it is more pronounced for firms with higher labor intensity and those in financial distress.
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Public-Use vs. Restricted-Use:
An Analysis Using the American Community Survey
January 2017
Working Paper Number:
CES-17-12
Statistical agencies frequently publish microdata that have been altered to protect confidentiality. Such data retain utility for many types of broad analyses but can yield biased or Insufficiently precise results in others. Research access to de-identified versions of the restricted-use data with little or no alteration is often possible, albeit costly and time-consuming. We investigate the the advantages and disadvantages of public-use and restricted-use data from the American Community
Survey (ACS) in constructing a wage index. The public-use data used were Public Use Microdata Samples, while the restricted-use data were accessed via a Federal Statistical Research Data Center. We discuss the advantages and disadvantages of each data source and compare estimated CWIs and standard errors at the state and labor market levels.
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Measuring Cross-Country Differences in Misallocation
January 2016
Working Paper Number:
CES-16-50R
We describe differences between the commonly used version of the U.S. Census of Manufactures available at the RDCs and what establishments themselves report. The originally reported data has substantially more dispersion in measured establishment productivity. Measured allocative efficiency is substantially higher in the cleaned data than the raw data: 4x higher in 2002, 20x in 2007, and 80x in 2012. Many of the important editing strategies at the Census, including industry analysts' manual edits and edits using tax records, are infeasible in non-U.S. datasets. We describe a new Bayesian approach for editing and imputation that can be used across contexts.
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Allocation of Company Research and Development Expenditures to Industries Using a Tobit Model
November 2015
Working Paper Number:
CES-15-42
This paper uses Census microdata and a regression-based approach to assign multi-division firms' pre-2008 Research and Development (R&D) expenditures to more than one industry. Since multi-division firms conduct R&D in more than one industry, assigning R&D to corresponding industries provides a more accurate representation of where R&D actually takes place and provides a consistent time-series with the National Science Foundation R&D by line of business information. Firm R&D is allocated to industries on the basis of observed industry payroll, as befits the historic importance of payroll in Census assignments of firms to industry. The results demonstrate that the method of assigning R&D to industries on the basis of payroll works well in earlier years, but becomes less effective over time as firms outsource their manufacturing function.
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Who Creates Jobs? Small vs. Large vs. Young
August 2010
Working Paper Number:
CES-10-17
There's been a long, sometimes heated, debate on the role of firm size in employment growth. Despite skepticism in the academic community, the notion that growth is negatively related to firm size remains appealing to policymakers and small business advocates. The widespread and repeated claim from this community is that most new jobs are created by small businesses. Using data from the Census Bureau Business Dynamics Statistics and Longitudinal Business Database, we explore the many issues regarding the role of firm size and growth that have been at the core of this ongoing debate (such as the role of regression to the mean). We find that the relationship between firm size and employment growth is sensitive to these issues. However, our main finding is that once we control for firm age there is no systematic relationship between firm size and growth. Our findings highlight the important role of business startups and young businesses in U.S. job creation. Business startups contribute substantially to both gross and net job creation. In addition, we find an 'up or out' dynamic of young firms. These findings imply that it is critical to control for and understand the role of firm age in explaining U.S. job creation.
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Downsizing and Productivity Growth: Myth or Reality?
April 1994
Working Paper Number:
CES-94-04
The conventional wisdom is that the rising productivity in the U.S. manufacturing sector in the 1980s has been driven by the apparently pervasive downsizing over this period. Aggregate evidence clearly shows falling employment accompanying the rise in productivity. In this paper, we examine the microeconomic evidence using the plant level data from the Longitudinal Research Database (LRD). In contrast to the conventional wisdom, we find that plants that increased employment as well as productivity contribute almost as much to overall productivity growth in the 1980s as the plants that increased productivity at the expense of employment. Further, there are striking differences by sector (defined by industry, size, region, wages, and ownership type) in the allocation of plants in terms of whether they upsize or downsize and whether they increase or decrease productivity. Nevertheless, in spite of the striking differences across sectors defined in a variety of ways, most of the variance of productivity and employment growth is accounted for by idiosyncratic factors.
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The Importance of Establishment Data in Economic Research
August 1993
Working Paper Number:
CES-93-10
The importance and usefulness of establishment microdata for economic research and policy analysis is outlined and contrasted with traditional products of statistical agencies -- aggregate cross-section tabulations. It is argued that statistical agencies must begin to seriously rethink the way they view establishment data products.
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