Latent Class Analysis of Consumer Expenditure Reports
نویسندگان
چکیده
Previous research by Tucker et al. (2007), working with the Consumer Expenditure Interview Survey (CE), explores the efficacy of measurement error indicators such as: interview length, extent and type of records used, the monthly patterns of reporting, and income question missing in a latent construct. Later research by Tucker, Meekins, and Biemer (2008) extend this latent class model to include indicators of response behavior across multiple interviews in a panel. This research develops a number of plausible models which possess the qualities of reliability and validity, in that they appear to accurately capture measurement error, but prove unable to explain a large amount of the variance associated with expenditure reports. This work extends past research by including the relatively recently recorded indicators from the Contact History Instrument added to the CE since 2005. In addition, this work examines measurement error by mode of collection (also a recently collected item).
منابع مشابه
A Microlevel Latent Class Model for Measurement Error in the Consumer Expenditure Interview Survey
Previous research by Tucker et al. (2005) and Tucker et al. (2006) attempts to identify a latent construct that predicts the amount of measurement error in expenditure reports on the Consumer Expenditure Interview Survey (CEIS). While this work was successful in identifying a construct that predicts measurement error in expenditure reports, it is more sensitive to falsely negative reports of th...
متن کاملLongitudinal Assessment of Measurement Error on the Consumer Expenditure
Previous work by the author used Markov Latent Class Analysis (MLCA) to make aggregate estimates of the underreporting of household expenditure by category (e.g. clothes, furniture, and electricity) by exploiting the four interview, rotating panel design of the Consumer Expenditure Interview Survey (CE). This analysis collapsed a few years of the CE into a pooled single panel. Estimates from th...
متن کاملLatent Class Analysis of Measurement Error in the Consumer Expenditure Survey
Previous research by Tucker et al. (2010), working with the Consumer Expenditure Survey (CE), explores the factor structure of measurement error indicators such as: interview length, extent and type of records used, the monthly patterns of reporting, reporting of income, attempt history information, and response behavior across multiple interviews in a latent class model. Findings from this res...
متن کاملEstimating the Level of Underreporting of Expenditures among Expenditure Reporters: A Further Micro-Level Latent Class Analysis
This paper makes estimates of the level of underreporting of consumer expenditures. The paper examines reporting in particular commodity categories and attempts only to make estimates of underreporting among those that report at least one expenditure in the category. The measure of the level of underreporting in a category by a particular responding unit is based on latent class analysis using ...
متن کاملAn application of Measurement error evaluation using latent class analysis
Latent class analysis (LCA) is a method of evaluating non sampling errors, especially measurement error in categorical data. Biemer (2011) introduced four latent class modeling approaches: probability model parameterization, log linear model, modified path model, and graphical model using path diagrams. These models are interchangeable. Latent class probability models express l...
متن کامل