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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect MatchingChristopher R. Bollinger Barry T. Hirsch D I S C U S S I O N P A P E R S E R I E S ABSTRACT Match Bias from Earnings Imputation in the CurrentPopulation Survey: The Case of Imperfect Matching * This paper examines alternative forms of match bias arising from earnings imputation. Wage equation parameters are estimated based on mixed samples of workers who do and do not report earnings, the latter group being assigned earnings of donors who share some but not all the attributes of the recipients. Regressions that include attributes not used as imputation match criteria (e.g., union status) are severely biased. Related forms of match bias arise with respect to attributes used as match criteria, but matched imperfectly. For example, an imperfect match on schooling creates bias that flattens estimated earnings profiles within low, middle, and high education groups, while creating large jumps in returns across groups. The same pattern arises in wage-age profiles. The paper provides a general analytic expression to correct match bias in regression coefficients under the assumption of conditional mean missing at random. The full sample correction approach is compared to the alternative of omitting imputed earners from the sample, with and without reweighting. Additional problems considered are bias in longitudinal analysis and the presence of dated donors.JEL Classification: J31, C81, C10

"This article utilizes an exact match file between the 1978 March [U.S.] Current Population Survey and administrative records from the Social Security Administration to analyze errors in the reporting of annual income using nonparametric methodology.... Three new findings are of interest: there is higher measurement error in cross-sectional samples than in panels. The negative relationship between measurement error and earnings is driven largely by overreporting among low earners. Median response errors are not related to earnings."

Su m m ary. H edonic of® ce ren t m odels are estim ated using data for Atlan ta that span th e years 1990± 96. Controllin g for typ ical build ing ch aracteri stics and lease term s, we ® nd that variab les m easu ring location al differen ces in w age rates, tran sport rates and proxim ity to con centration s of supp ort services an d of® ce work ers play an im portan t role in exp lain ing spatial variatio n in of® ce rents. N o evid ence is found in support of the hypothesis that tech n ological advan ces in telecom m unication s have dim in ish ed the role played b y face-to -face agglom eration econ om ies in determ ining the in tra-m etrop olitan location of of® ce ® rm s.

Abstract:We offer new evidence on earnings volatility of men and women in the United States over the past four decades by using matched data from the March Current Population Survey.We construct a measure of total volatility that encompasses both permanent and transitory instability, and that admits employment transitions and losses from self employment. We also present a detailed decomposition of earnings volatility to account for changing shares in employment probabilities, conditional variances of continuous workers, and conditional mean variances from labor-force entry and exit. Our results show that earnings volatility among men increased by 15 percent from the early 1970s to mid 1980s, while women's volatility fell, and each stabilized thereafter. However, this pooled series masks important heterogeneity in volatility levels and trends across education groups and marital status. We find that men's earnings volatility is increasingly accounted for by employment transitions, especially exits, while the share of women's volatility accounted for by continuous workers rose, each of which highlights the importance of allowing for periods of non-work in volatility studies. 1Whether and to what extent the volatility of earnings and income have increased in the United States in recent decades has been the subject of much research and debate Moffitt 1994, 2009;Dynarski and Gruber 1997;Haider 2001; Kniesner and Ziliak 2002a,b;Gundersen and Ziliak 2003;Dahl, DeLeire, and Schwabish 2008;Dynan, Elmendorf, and Sichel 2008;Hacker and Jacobs 2008; Jensen and Shore 2008; Keys 2008;Shin and Solon 2008;Winship 2009). Starting with Gottschalk and Moffitt (1994), the focus on volatility trends centered on identifying whether rising cross-sectional income inequality stemmed in part from transitory instability, while in more recent years interest in volatility expanded to concerns raised by Hacker and Jacobs (2008), among others, that there have been fundamental changes in the labor market that shifted more idiosyncratic and business cycle risk onto individuals. Whereas the preponderance of evidence on inequality in the United States is based on cross-section data from the Current Population Survey (CPS), with few exceptions the evidence on earnings and income volatility comes almost exclusively from longitudinal data in the Panel Study of Income Dynamics (Gittleman and Joyce 1996;Cameron and Tracy 1998;Dahl, et al. 2008;Celik, et al. 2009; Juhn and McCue 2010;Winship 2011). In this paper we offer new evidence on earnings volatility over the past four decades by exploiting the longitudinal dimension of the CPS to match individuals across surveys.The use of the PSID for estimates of volatility owes in part to the literature's early emphasis on decomposing volatility into its permanent and transitory components (Gottschalk and Moffitt 1994). This decomposition is illustrative because it permits identification of temporary deviations of earnings from long-term trends, as well as identification of structural changes in long-term tre...

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