Assessing cohort aggregation to minimise bias in pseudo-panels

Arbeitspapier

Pseudo-panels allow estimation of panel models when only repeated cross-sections are available. This involves grouping individuals into cohorts and using the cohort means as if they are observations in a genuine panel. Their practical use is constrained by a lack of consensus on how the pseudo-panels should be formed, particularly to address potential sampling error bias. We show that grouping can also create substantial aggregation bias, calling into question how well pseudo-panels can mimic panel estimates. We create two metrics for assessing the grouping process, one for each potential source of bias. If both metrics are above certain recommended values, the biases from aggregation and sampling error are minimised, meaning results can be interpreted as if they were from genuine panels.

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• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CREDIT Research Paper ; No. 18/01

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access ; Household Behavior: General ; Microeconomic Analyses of Economic Development
• Subject: Pseudo-panel ; Estimation bias ; Sampling error ; Aggregation bias ; Repeated Cross-Section ; Household Surveys

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Khan, Rumman
• Event: Veröffentlichung
• (who): The University of Nottingham, Centre for Research in Economic Development and International Trade (CREDIT)
• (where): Nottingham
• (when): 2018

Further information

• Handle: http://hdl.handle.net/10419/210839