Addressing Pre-Commitment Bias with a Generalized EASI Model: An Application to Food Demand in Russia
Vardges Hovhannisyan, Aleksan Shanoyan, Hovhannisyan, Vardges, Shanoyan, Aleksan
Abstract
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Vardges Hovhannisyan, Aleksan Shanoyan, Hovhannisyan, Vardges, Shanoyan, Aleksan
Abstract
Open-access reader
The Exact Affine Stone Index (EASI) demand model offers distinct advantages over its predecessors. However, it does not account for pre-committed demand. This can bias elasticity estimates when such pre-commitments are present. We derive a generalized EASI model that allows for pre-committed demand. We illustrate the advantage of this model in an empirical analysis of food demand in Russia using provincial-level panel data. The results provide strong empirical evidence for the presence of pre-committed demand for key food commodities. The findings extend the literature on food demand in Russia by estimating elasticities that account for pre-commitments and unobserved regional heterogeneity.
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The Exact Affine Stone Index (EASI) demand model offers distinct advantages over its predecessors. However, it does not account for pre-committed demand. This can bias elasticity estimates when such pre-commitments are present. We derive a generalized EASI model that allows for pre-committed demand. We illustrate the advantage of this model in an empirical analysis of food demand in Russia using provincial-level panel data. The results provide strong empirical evidence for the presence of pre-committed demand for key food commodities. The findings extend the literature on food demand in Russia by estimating elasticities that account for pre-commitments and unobserved regional heterogeneity.
Key concepts: Business, Economics, Psychology, Computer science