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Title:Cluster sample inference using sensitivity analysis: The case with few groups PDF Logo
Authors:Vikström, Johan
Issue Date:2009
Series/Report no.:Working paper // IFAU - Institute for Labour Market Policy Evaluation 2009:15
Abstract:This paper re-examines inference for cluster samples. Sensitivity analysis is proposed as a new method to perform inference when the number of groups is small. Based on estimations using disaggregated data, the sensitivity of the standard errors with respect to the variance of the cluster effects can be examined in order to distinguish a causal effect from random shocks. The method even handles just-identified models. One important example of a just-identified model is the two groups and two time periods difference-indifferencessetting. The method allows for different types of correlation over time and between groups in the cluster effects.
Subjects:Cluster-correlation
Difference-in-Differences
Sensitivity analysis
JEL:C12
C21
C23
Document Type:Working Paper
Appears in Collections:Working Papers, IFAU - Institute for Evaluation of Labour Market and Education Policy

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