Abstract
There are several econometric advantages to the Poisson pseudo-maximum likelihood (PPML) approach to estimating relationships involving flows (Santos Silva and Tenreyro 2010). One is that the coefficients on logged explanatory variables (X) in the (exponential) relationship involving non-logged flow magnitudes as the dependent variable (y) can be interpreted as the elasticity of the conditional expectation of y i with respect to X i .
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Santos Silva and Tenreyro (2010) note there is strong evidence that disturbances from log-linear gravity models are heteroscedastic.
References
Alonso W (1973) National interregional demographic accounts: a prototype. Monograph 17, Institute of Urban and Regional Development, University of California, Berkeley
Alonso W (1978) A theory of movements. In: Hansen NM (ed) Human settlement systems: international perspectives on structure, change and public policy. Ballinger, Cambridge, MA, pp 197–211
Anderson JE, van Wincoop E (2003) Gravity with gravitas: a solution to the border puzzle. Am Econ Rev 93(1):170–192
Anselin L, Smirnov O (1996) Efficient algorithms for constructing proper higher order spatial lag operators. J Reg Sci 36(1):67–89
Arvis J-F, Shepherd B (2013) The Poisson quasi-maximum likelihood estimator: a solution to the ‘adding up’ problem in gravity models. Appl Econ Lett 20(6):515–519
de Vries JJ, Nijkamp P, Rietveld P (2001) Alonso’s theory of movements: developments in spatial interaction modeling. J Geogr Syst 3:233–256
Fally T (2012) Structural gravity and fixed effects. Working paper available at: spot.colorado.edu/f̃ally/Gravity_PPML.pdf
Feenstra R (2004) Advance international trade, Princeton University Press
Gourieroux C, Monfort A, Trognon A (1984) Pseudo maximum likelihood methods: applications to Poisson models. Econometrica 52:701–720
Griffith DA (2007). Spatial structure and spatial interaction: 25 years later. Rev Reg Stud 37(1):28–38
Griffith DA, Jones KG (1980) Explorations into the relationship between spatial structure and spatial interaction. Environ Plan A 12:187–201
LeSage JP, Pace RK (2008) Spatial econometric modeling of origin-destination flows. J Reg Sci 48(5):941–967
LeSage JP, Pace RK (2009) Introduction to spatial econometrics, CRC Press, Taylor & Francis Group, Boca Raton, FL
LeSage JP, Thomas-Agnan C (2015) Interpreting spatial econometric origin-destination flow models. J. Reg. Sci 55(2):188–208
Martinez-Zarzoso I (2013) The log of gravity revisited. Appl Econ 45:311–327
Martinez-Zarzoso I, Nowak-Lehmann D F, Vollmer S (2007) The log of gravity revisited, CeGE Discussion Papers 64, University of Goettingen. Available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=999908
Rathnun SL, Fei S (2006) A spatial zero-inflated Poisson regression model for oak regeneration. Environ Ecol Stat 13:409–426
Sen A, Smith TE (1995) Gravity models of spatial interaction behavior, Springer, Heidelberg
Smith TE (1975) A choice theory of spatial interaction. Reg Sci Urban Econ 5(2):137–176
Santos Silva JMC, Tenreyro S (2006) The log of gravity. Rev Econ Stat 88:641–658
Santos Silva JMC, Tenreyro S (2010) On the existence of the maximum likelihood estimates for Poisson regression. Econ Lett 107(2):310–312
Santos Silva JMC, Tenreyro S (2011) Further simulation evidence on the performance of the Poisson-PML estimator. Econ Lett 112(2):220–222
Shiller R (1973) A distributed lag estimator derived from smoothness priors. Econometrica 41(4):775–788
Thomas-Agnan C, LeSage JP (2014) Spatial econometric origin-destination flow models. In: Fischer MM, Peter Nijkamp (eds) Handbook of regional science. Springer, pp 1653–1673
Wakefield J (2007) Disease mapping and spatial regression with count data. Biostatistics 8(2):158–183
Wilson AG (1967) A statistical theory of spatial distribution models Transp Res 1:253–269
Wilson AG (1970) Entropy in urban and regional modelling. Pion, London
Wilson AG (1974) Urban and regional models in geography and planning. Wiley, Chichester
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
LeSage, J.P., Satici, E. (2016). A Bayesian Spatial Interaction Model Variant of the Poisson Pseudo-Maximum Likelihood Estimator. In: Patuelli, R., Arbia, G. (eds) Spatial Econometric Interaction Modelling. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-319-30196-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-30196-9_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30194-5
Online ISBN: 978-3-319-30196-9
eBook Packages: Economics and FinanceEconomics and Finance (R0)