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Title: Empirical Comparison of Parametric and Nonparametric Trade Gravity Models
Accession Number: 01373855
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: A systematic comparison is made of parametric (i.e., ordinary least-squares regressions and related generalizations) and nonparametric (i.e., kernel regressions and regression trees) log-linear gravity models for reproducing international trade. Experiments were conducted to estimate a log-linear gravity model reproducing import and export trade flows in quantity between Italy and 13 world economic zones, based on a panel estimation data set. The best parametric regression model was estimated to define a baseline reference model. Some specifications of nonparametric models, belonging to the categories of kernel regressions and regression trees, were also estimated. The performance of parametric and nonparametric models is contrasted through a comparison of goodness-of-fit measures (R², mean absolute percentage error) both in estimation and in hold-out sample validation. To assess the differences in model elasticity and forecasts, both parametric and nonparametric models are applied to future scenarios and the corresponding results compared.
Supplemental Notes: This paper was sponsored by TRB committee AT015(4) Paper reviews -- Logistics
Monograph Title: Monograph Accession #: 01384365
Report/Paper Numbers: 12-0335
Language: English
Authors: Gallo, MarianoMarzano, VittorioSimonelli, FulvioPagination: pp 29-41
Publication Date: 2012
ISBN: 9780309223102
Media Type: Print
Features: References; Tables
TRT Terms: Geographic Terms: Subject Areas: Freight Transportation; Planning and Forecasting; I72: Traffic and Transport Planning
Files: TRIS, TRB, ATRI
Created Date: Feb 8 2012 4:54PM
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