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GTAP Resource #6240

"Incorporating additional information for the estimation of interregional trade flows"
by Fernandez Vazquez, Esteban and Bartlomiej Rokicki

One frequent problem when studying interregional trade flows is the lack of sufficiently detailed data based on surveys. Interregional trade flows are not usually registered in surveys by statistical agencies and some indirect estimation method is applied. There are several alternatives when dealing with this problem in the input-output context. One of the most frequently applied solutions is to use a gravity approach (e.g. Miller and Blair, 2009), first suggested by Leontief and Strout (1963). Alternatively, an estimation procedure based on entropy maximization -or information minimization - can be applied with the same purpose.
In this paper we explore the performance of alternative entropy formulations proposed by Golan et al. (1994), that rely not on these aggregates but in the cross-moments between the interregional trade flows and some additional covariates that are not considered in simple gravity-type equations.
We apply entropy-based estimation procedure and compare its performance with double-constraint gravity model. We analyze two different entropy specifications - the data-constrained Generalized Cross Entropy (GCE) estimator and the moment-constrained GCE estimator. The performance of each estimator is evaluated by means of numerical simulations. We find that entropy-based estimators provide more accurate results than the gravity model once the possibility of potential errors in row or column totals is included. The bigger the potential error and the higher the number of regions the greater difference in accuracy between the gravity model and GCE estimators. Also, the moment-constrained GCE estimator tends to be more accurate than the data-constrained GCE estimator.

Resource Details (Export Citation) GTAP Keywords
Category: 2021 Conference Paper
Status: Not published
By/In: Presented during the 24th Annual Conference on Global Economic Analysis (Virtual Conference)
Date: 2021
Version: 1
Created: Rokicki, B. (4/12/2021)
Updated: Rokicki, B. (4/12/2021)
Visits: 497
- Calibration and parameter estimation
- Other data bases and data issues

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