Estimating Flexible Income Processes from Subjective Expectations Data: Evidence from India and Colombia
We develop a methodology for modeling household income processes when subjective probabilistic assessments of future income are available. This allows us to flexibly estimate conditional cdfs directly using elicited individual subjective probabilities, and to obtain empirical measurements of subjective risk and persistence. We then use two longitudinal surveys collected in rural India and rural Colombia to explore the nature of income dynamics in those contexts. Our results suggest linear income processes are rejected in favor of more flexible versions in both cases; subjective income distributions feature heteroskedasticity, conditional skewness and nonlinear persistence.
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