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Essays on Measurement Error and Nonresponse
Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Economics.
2007 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Essay 1 deals with measurement errors. Matching survey data with administrative records provides unique opportunities to evaluate the statistical properties of respondents' answers. This paper focuses primarily on home ownership and wealth variables. For all analyzed variables we find that the classical assumption of no correlation between measurement error and true value is violated. In an empirical application explaining the housing tenure choice, LPM and Probit models are estimated using both survey and register data on gross financial wealth.

Essay 2 (with N. Anders Klevmarken) also analyzes measurement errors. Survey measures of wealth are error prone with a relatively large error variance. The errors are not uncorrelated with the true values but tend to have a negative correlation, which implies that wealthy people tend to under-report and less wealthy to over-report their responses. There is no general tendency of survey data to under-estimate mean wealth with the exception of the last percentile. The under-estimate of the wealth of the very rich is however not due to under-reporting but rather to selective nonresponse. Using simple models this paper discusses consequences of error prone wealth data.

Essay 3 (with N. Anders Klevmarken) studies the problem of nonresponse in survey data. Using rich register data to analyze response behavior in a survey on health and economic standard, a model to explain contact and participation probabilities is estimated. Previous attempts to build such models have been constrained by the very limited information available in the sampling frames. One main result is that both probabilities are lower among respondents out of the labor market, who are immigrants and on benefits.

Essay 4 analyzes different approaches to adjust for nonresponse bias. When a survey response mechanism depends on the variable of interest measured within the same survey and observed for only part of the sample, the situation is one of nonignorable nonresponse. If the nonresponse is ignored it will most likely generate significant bias in the estimates of the model parameters of interest. To solve this, one option is the joint modelling of the response mechanism and the variable of interest. Another option is to calibrate each observation with weights constructed from auxiliary data. In an application where earnings equations are estimated these approaches are all applied and compared with reference estimates. These reference estimates are based on a large data set without any nonresponse.

Place, publisher, year, edition, pages
Uppsala: Nationalekonomiska institutionen , 2007. , p. 130
Series
Economic studies, ISSN 0283-7668 ; 103
Keywords [en]
Economics
Keywords [sv]
Nationalekonomi
Identifiers
URN: urn:nbn:se:uu:diva-7920OAI: oai:DiVA.org:uu-7920DiVA, id: diva2:170376
Public defence
2007-05-22, Hörsal 2, Ekonomikum, Kyrkogårdsgatan 10, Uppsala, 10:15
Opponent
Supervisors
Available from: 2007-04-27 Created: 2007-04-27Bibliographically approved
List of papers
1. A Measurement Error Analysis of Survey Data – Using Administrative Data as a Validation Source
Open this publication in new window or tab >>A Measurement Error Analysis of Survey Data – Using Administrative Data as a Validation Source
(English)Manuscript (Other academic)
National Category
Economics
Identifiers
urn:nbn:se:uu:diva-95973 (URN)
Available from: 2007-04-27 Created: 2007-04-27 Last updated: 2012-01-03Bibliographically approved
2. Comparing Register and Survey Wealth Data
Open this publication in new window or tab >>Comparing Register and Survey Wealth Data
(English)Manuscript (Other academic)
Identifiers
urn:nbn:se:uu:diva-95974 (URN)
Available from: 2007-04-27 Created: 2007-04-27 Last updated: 2011-04-05Bibliographically approved
3. Explaining the Size and Nature of Response in a Survey on Health Status and Economic Standard
Open this publication in new window or tab >>Explaining the Size and Nature of Response in a Survey on Health Status and Economic Standard
2008 (English)In: Journal of Official Statistics, ISSN 0282-423X, E-ISSN 2001-7367, Vol. 24, no 3, p. 431-449Article in journal (Refereed) Published
Abstract [en]

Using rich register data to analyze response behavior in a survey on health and economic standard, a model to explain contact and participation probabilities is estimated. A main result is that both probabilities are lower among respondents who are less well-off, out of the labor market, on benefits or immigrants. We also find a significant time-cost effect on participation. Previous findings that the probability of contact is low in urban areas and among singles are confirmed.

Keywords
Nonresponse, response process, probit with selection, JEL-classification C34, C42. J14
National Category
Social Sciences
Research subject
Statistics
Identifiers
urn:nbn:se:uu:diva-95975 (URN)000268961400005 ()
Available from: 2007-04-27 Created: 2007-04-27 Last updated: 2017-12-14Bibliographically approved
4. How to Adjust for a Nonignorable Nonresponse Mechanism: Calibration, Heckit or FIML?
Open this publication in new window or tab >>How to Adjust for a Nonignorable Nonresponse Mechanism: Calibration, Heckit or FIML?
(English)Manuscript (Other academic)
National Category
Economics
Identifiers
urn:nbn:se:uu:diva-95976 (URN)
Available from: 2007-04-27 Created: 2007-04-27 Last updated: 2012-01-03Bibliographically approved

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