Forecasting spatially dependent origin and destination commodity flows

James LeSage and Carlos Llano-Verduras
Authors registered in the RePEc Author Service: Carlos Llano Verduras

Empirical Economics, 2014, vol. 47, issue 4, 1543-1562

Abstract: We explore origin–destination forecasting of commodity flows between 15 Spanish regions, using data covering the period from 1995 to 2004. The 1-year-ahead forecasts are based on a recently introduced spatial autoregressive variant of the traditional gravity model. Gravity (or spatial interaction models) attempt to explain variation in $$N=n^2$$ N = n 2 flows between $$n$$ n origin and destination regions that reflect a vector arising from an $$n$$ n by $$n$$ n flow matrix. The spatial autoregressive variant of the gravity model used here takes into account spatial dependence between flows from regions neighboring both the origin and destinations during estimation and forecasting. One-year-ahead forecast accuracy of non-spatial and spatial models are compared. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Gravity models; Bayesian spatial autoregressive regression model; Spatial connectivity of origin–destination flows; C11; C23; O47; O52 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s00181-013-0786-2

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