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Activity Number:
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167
- Data Mining and Econometrics
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Type:
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Contributed
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Date/Time:
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Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #318994
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Title:
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Identification and Estimation of Demand in Large Concentrated Markets
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Author(s):
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Saman Banafti* and Tae-Hwy Lee
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Companies:
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UC Riverside and University of California, Riverside
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Keywords:
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Interactive effects;
Factor error structure;
Simultaneity;
Power-law tails;
Asymptotic Herfindahl index;
Demand elasticity
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Abstract:
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Gabaix and Koijen (2020) introduces the Granular Instrumental Variables (GIV) methodology, which takes advantage of panel data to construct instruments to estimate structural time series regression models that involve endogenous regressors. The GIVs are constructed based on panel data models with factor structures, where the idiosyncratic error terms may have extraordinarily useful information. In this paper, we extend their GIV methodology by developing the GIV identification procedure to a large $N$ and large $T$ framework (current identification is for fixed $N$ and large $T$) by establishing and restricting the asymptotic behavior of the Herfindahl index for large $N$ markets as a function of the tail index of the size distribution of the cross-sectional units.
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Authors who are presenting talks have a * after their name.
