Bias-corrected cluster-robust standard errors for fixed effects PPML estimators of gravity panel models with autocorrelated disturbances
Michael Pfaffermayr
What the paper says
Panel gravity models with country-pair and time variation typically feature autocorrelated disturbances calling for country-pair clustered standard errors of the estimated structural parameters. Yet, Monte Carlo simulations reveal a pronounced downward bias of the country-pair clustered standard errors. With an estimated autocorrelation parameter of the disturbances at hand, it is straightforward to form a working variance that accounts for autocorrelation within country-pairs and to apply the Pustejovsky and Tipton (JBES 36:672–683, 2018)-bias correction. Monte Carlo simulations illustrate that this bias correction nearly eliminates the bias and yields correct coverage rates of the confidence intervals. Using the cluster-specific pairs bootstrap to form percentile confidence intervals also performs well and exhibits correct coverage rates.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.