Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/193379 
Year of Publication: 
2019
Series/Report no.: 
IZA Discussion Papers No. 12085
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this paper, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably trans- parent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.
Subjects: 
partial identification
measurement error
mobility
transition matrices
poverty
JEL: 
C18
D31
I32
Document Type: 
Working Paper

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