On the identification of joint distributions using marginals and aggregates

Marie-Helene Felt

Economics Letters, 2020, vol. 194, issue C

Abstract: A data combination approach is proposed to identify variables’ joint distribution when only their marginals and the distribution of their sum are known. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure. A variation of the well-known Lemma of Kotlarski (Kotlarski,1967) is established. Potential applications are proposed where aggregated data help identify within-household or longitudinal distributions in the absence of intra-household or panel data, respectively.

Keywords: Data combination; Aggregated data; Nonparametric identification; Kotlarski’s identity (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:194:y:2020:i:c:s016517652030269x

DOI: 10.1016/j.econlet.2020.109431

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