Papers Containing Keywords(s): 'public'
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Authors
John M. Abowd - 4
Ian M. Schmutte - 4
Viewing papers 11 through 16 of 16
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Working PaperPublic-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.View Full Paper PDF
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Working PaperIMPROVING THE SYNTHETIC LONGITUDINAL BUSINESS DATABASE
February 2014
Working Paper Number:
CES-14-12
In most countries, national statistical agencies do not release establishment-level business microdata, because doing so represents too large a risk to establishments' confidentiality. Agencies potentially can manage these risks by releasing synthetic microdata, i.e., individual establishment records simulated from statistical models de- signed to mimic the joint distribution of the underlying observed data. Previously, we used this approach to generate a public-use version'now available for public use'of the U. S. Census Bureau's Longitudinal Business Database (LBD), a longitudinal cen- sus of establishments dating back to 1976. While the synthetic LBD has proven to be a useful product, we now seek to improve and expand it by using new synthesis models and adding features. This article describes our efforts to create the second generation of the SynLBD, including synthesis procedures that we believe could be replicated in other contexts.View Full Paper PDF
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Working PaperEXPANDING THE ROLE OF SYNTHETIC DATA AT THE U.S. CENSUS BUREAU
February 2014
Working Paper Number:
CES-14-10
National Statistical offices (NSOs) create official statistics from data collected from survey respondents, government administrative records and other sources. The raw source data is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of users to extract as much information from the data as possible. Traditional disclosure protection techniques result in official data products that do not fully utilize the information content of the underlying microdata. Typically, these products take the form of simple aggregate tabulations. In a few cases anonymized public- use micro samples are made available, but these face a growing risk of re-identification by the increasing amounts of information about individuals and firms available in the public domain. One approach for overcoming these risks is to release products based on synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata. We discuss re- cent Census Bureau work to develop and deploy such products. We discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.View Full Paper PDF
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Working PaperSYNTHETIC DATA FOR SMALL AREA ESTIMATION IN THE AMERICAN COMMUNITY SURVEY
April 2013
Working Paper Number:
CES-13-19
Small area estimates provide a critical source of information used to study local populations. Statistical agencies regularly collect data from small areas but are prevented from releasing detailed geographical identifiers in public-use data sets due to disclosure concerns. Alternative data dissemination methods used in practice include releasing summary/aggregate tables, suppressing detailed geographic information in public-use data sets, and accessing restricted data via Research Data Centers. This research examines an alternative method for disseminating microdata that contains more geographical details than are currently being released in public-use data files. Specifically, the method replaces the observed survey values with imputed, or synthetic, values simulated from a hierarchical Bayesian model. Confidentiality protection is enhanced because no actual values are released. The method is demonstrated using restricted data from the 2005-2009 American Community Survey. The analytic validity of the synthetic data is assessed by comparing small area estimates obtained from the synthetic data with those obtained from the observed data.View Full Paper PDF
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Working PaperIPO Waves, Product Market Competition, and the Going Public Decision: Theory and Evidence
March 2012
Working Paper Number:
CES-12-07
We develop a new rationale for IPO waves based on product market considerations. Two firms, with differing productivity levels, compete in an industry with a significant probability of a positive productivity shock. Going public, though costly, not only allows a firm to raise external capital cheaply, but also enables it to grab market share from its private competitors. We solve for the decision of each firm to go public versus remain private, and the optimal timing of going public. In equilibrium, even firms with sufficient internal capital to fund their new investment may go public, driven by the possibility of their product market competitors going public. IPO waves may arise in equilibrium even in industries which do not experience a productivity shock. Our model predicts that firms going public during an IPO wave will have lower productivity and post-IPO profitability but larger cash holdings than those going public off the wave; it makes similar predictions for firms going public later versus earlier in an IPO wave. We empirically test and find support for these predictions.View Full Paper PDF
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Working PaperThe Going Public Decision and the Product Market
July 2008
Working Paper Number:
CES-08-20
At what point in a firm's life should it go public? How do a firm's ex ante product market characteristics relate to its going public decision? Further, what are the implications of a firm going public on its post-IPO operating and product market performance? In this paper, we answer the above questions by conducting the first large sample study of the going public decisions of U.S. firms in the literature. We use the Longitudinal Research Database (LRD) of the U.S. Census Bureau, which covers the entire universe of private and public U.S. manufacturing firms. Our findings can be summarized as follows. First, a private firm's product market characteristics (market share, competition, capital intensity, cash flow riskiness) significantly affect its likelihood of going public. Second, private firms facing less information asymmetry and those with projects that are cheaper for outsiders to evaluate are more likely to go public (consistent with Chemmanur and Fulghieri (1999)). Third, IPOs of firms occur at the peak of their productivity cycle (consistent with Clementi (2002)): the dynamics of total factor productivity (TFP) and sales growth exhibit an inverted U-shaped pattern. Finally, sales, capital expenditures, and other performance variables exhibit a consistently increasing pattern over the years before and after the IPO. The last two findings are consistent with the widely documented post-IPO operating underperformance of firms being due to the real investment effects of a firm going public, and inconsistent with underperformance being solely due to earnings management immediately prior to the IPO.View Full Paper PDF
