Inference With Dyadic Data
Asymptotic Behavior of the Dyadic-Robust t -Statistic
Bibliographic Data
| ID | 19418007 |
|---|---|
| Authors | Max Tabord-Meehan (Northwestern University), Max Tabord‐Meehan (Northwestern University, corresponding author) |
| Year | 2019 |
| Volume | 37 |
| Issue | 4 |
| Pages | 671-680 |
| Publication date | 2019-10-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2017.1409630 |
| OpenAlex | W2963133024 |
| Language | EN |
| Citations received | 7 |
| References cited | 33 |
This article is concerned with inference in the linear model with dyadic data. Dyadic data are indexed by pairs of “units;” for example, trade data between pairs of countries. Because of the potential for observations with a unit in common to be correlated, standard inference procedures may not perform as expected. We establish a range of conditions under which a t-statistic with the dyadic-robust variance estimator of Fafchamps and Gubert is asymptotically normal. Using our theoretical results as a guide, we perform a simulation exercise to study the validity of the normal approximation, as well as the performance of a novel finite-sample correction. We conclude with guidelines for applied researchers wishing to use the dyadic-robust estimator for inference
Bayesian inference · Delta method · Econometrics · Estimator · Fiducial inference · Frequentist inference · Inference · Standard error · Statistic · Statistical inference · Statistics · Advanced Statistical Methods and Models · Computer Science · Global trade and economics · Mathematics · Statistical Methods and Inference · Applied Mathematics · Artificial Intelligence
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| Citations per year | 1.4 |
|---|---|
| Citation span | 2021 - 2026 (6) |
| Highly cited | No |