Causality, Uncertainty and Identification: Three Issues on the Spatial Econometrics Agenda

Author/s Jesùs Mur
Publishing Year 2013 Issue 2013/1
Language English Pages 23 P. 5-27 File size 993 KB
DOI 10.3280/SCRE2013-001001
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This paper offers a personal view on recent developments in the field of spatial econometrics. The approach is subjective and certainly biased. I focus on three issues that I consider of the utmost importance and which are at the basis of the discipline, namely spatial causality, the question of identification in spatial models, and the problem of selecting the (most appropriate) spatial weighting matrix. These three topics are receiving increasing attention in the spatial econometrics literature, although there are still many issues to be resolved. They will most likely be areas of intense activity in the near future.

Keywords: Spatial causality, weighting matrix, identification, spatial econometrics.

Jel codes: C21, C50, R15

  1. Aldstadt J., Getis A. (2006), Using AMOEBA to Create a Spatial Weight Matrix and Identify Spatial Clusters. Geographical Analysis, 38, 4: 327-343. DOI: 10.1111/j.1538-4632.2006.00689.x
  2. Anselin L. (1988), Spatial Econometrics: Methods and Models. Dordrecht: Kluwer Academic Publishers.
  3. Anselin L. (2010), Thirty Years of Spatial Econometrics. Papers in Regional Science, 89, 1: 3-25. DOI: 10.1111/j.1435-5957.2010.00279.x
  4. Anselin L., Florax R., Rey S. (eds.) (2004), Advances in Spatial Econometrics. Methodology, Tools and Applications. Berlin: Springer.
  5. Anselin L., Rey S. (eds.) (2010), Perspectives on Spatial Data Analysis. Berlin: Springer-Verlag. DOI: 10.1007/978-3-642-01976-0
  6. Arbia G. (2006), Spatial Econometrics: Statistical Foundations and Applications to Regional Convergence. Berlin: Springer-Verlag.
  7. Arbia G. (2011), A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007-2011). Spatial Economic Analysis, 6, 4: 377-395. DOI: 10.1080/17421772.2011.610901
  8. Arrow K. (1962), The Economic Implications of Learning by Doing. Review of Economic Studies, 29, 3: 155-173. DOI: 10.2307/2295952
  9. Autant-Bernard C., LeSage J. (2011), Quantifying Knowledge Spillovers Using Spatial Econometric Models. Journal of Regional Science, 51, 3: 471-496. DOI: 10.1111/j.1467-9787.2010.00705.x
  10. Basile R. (2008), Regional Economic Growth in Europe: A Semi Parametric Spatial Dependence Approach. Papers in Regional Science, 87, 4: 527-544. DOI: 10.1111/j.1435-5957.2008.00175.x
  11. Basile R. (2009), Productivity Polarization Across Regions in Europe: The Role of Nonlinearities and Spatial Dependence. International Regional Science Review, 32, 1: 92-115. DOI: 10.1177/0160017608326944
  12. Basile R., Capello R., Caragliu A. (2012), Technological Interdependence and Regional Growth in Europe. Papers in Regional Science, 91, 4: 697-722.
  13. Bavaud F. (1998), Models for Spatial Weights: A Systematic Look. Geographical Analysis, 30, 2: 153-171. DOI: 10.1111/j.1538-4632.1998.tb00394.x
  14. Beenstock M., Felsenstein D. (2012), Nonparametric Estimation of the Spatial Connectivity Matrix Using Spatial Panel Data. Geographical Analysis, 44, 4: 386-397. DOI: 10.1111/j.1538-4632.2012.00851.x
  15. Benjanuvatra S. (2012), Estimation of Spatial Weight Matrix for Mixed Regressive Spatial Autoregressive Model Using Quasi-maximum Likelihood. Paper presented in the VI World Conference of the Spatial Econometrics Association held at Salvador de Bahia: Brazil, July.
  16. Bhattacharjee A., Jensen-Butler C. (2005), Estimation of Spatial Weights Matrix in a Spatial Error Model, with an Application to Diffusion in Housing Demand. St. Andrews: University of St. Andrews, School of Economics and Finance, CRIEFF Discussion Paper n. 0519.
  17. Blommestein H., Nijkamp P. (1983), Causality Analysis in Soft Spatial Econometric Models. Papers of the Regional Science Association, 51, 1: 65-77. DOI: 10.1007/BF01940337
  18. Bodson P., Peeters D. (1975), Estimation of the Coefficients of a Linear Regression in the Presence of Spatial Autocorrelation: An Application to a Belgian Labour-demand Function. Environment and Planning, 7, 4: 455-472. DOI: 10.1068/a070455
  19. Bramoullé Y., Djebbari H., Fortin B. (2009), Identification of Peer Effects through Social Networks. Journal of Econometrics, 150, 1: 41-55. DOI: 10.1016/j.jeconom.2008.12.021
  20. Burridge P., Fingleton B. (2010), Bootstrap Inference in Spatial Econometrics: The J-test. Spatial Economic Analysis, 5, 1: 93-119. DOI: 10.1080/17421770903511346
  21. Cliff A., Ord K. (1981), Spatial Processes: Models & Applications. London: Pion.
  22. Corrado L., Fingleton B. (2012), Where is the Economics in Spatial Econometrics? Journal of Regional Science, 52, 2: 210-239. DOI: 10.1111/j.1467-9787.2011.00726.x
  23. Cressie N., Wikle C. (2011), Statistics for Spatio-Temporal Data. New York: John Wiley & Sons.
  24. Fernández E., Mayor M., Rodríguez J. (2009), Estimating Spatial Autoregressive Models by GME-GCE Techniques. International Regional Science Review, 32, 2: 148-172. DOI: 10.1177/0160017608326600
  25. Frenken K., Ponds R., van Oort F. (2010), The Citation Impact of Research Collaboration in Science-based Industries: A spatial-institutional Analysis. Papers in Regional Science, 89, 2: 351-371. DOI: 10.1111/j.1435-5957.2010.00309.x
  26. Getis A., Aldstadt J. (2004), Constructing the Spatial Weight Matrix Using a Local Statistic. Geographical Analysis, 36, 2: 90-104. DOI: 10.1111/j.1538-4632.2004.tb01127.x
  27. Getis A., Mur J., Zoller H. (eds.) (2003), Spatial Econometrics and Spatial Statistics. Basingstoke: Palgrave Macmillan. Gibbons S., Overman H. (2012), Mostly Pointless Spatial Econometrics? Journal of Regional Science, 52, 2: 172-191. DOI: 10.1111/j.1467-9787.2012.00760.x
  28. Granger C. (1980), Testing for Causality: A Personal Viewpoint. Journal of Economic Dynamics and Control, 2, 1: 329-352. DOI: 10.1016/0165-1889(80)90069-X
  29. Grassberger P., Procaccia I. (1983), Characterization of Strange Attractors. Physical Review Letters, 50, 5: 346-349. DOI: 10.1103/PhysRevLett.50.346
  30. Griffith A. (2003), Spatial Autocorrelation and Spatial Filtering: Gaining Understanding through Theory and Scientific Visualization. Berlin: Springer-Verlag. DOI: 10.1007/978-3-540-24806-4
  31. Griffith A., Paelinck J. (2011), Non-Standard Spatial Statistics and Spatial Econometrics. Berlin: Springer-Verlag. DOI: 10.1007/978-3-642-16043-1
  32. Haining R. (2003), Spatial Data Analysis: Theory and Practice. Cambridge: Cambridge University Press. DOI: 10.1017/CBO9780511754944
  33. Hansen B. (2007), Least Squares Model Averaging. Econometrica, 75, 4: 1175-1189. DOI: 10.1111/j.1468-0262.2007.00785.x
  34. Harris R., Moffat J., Kravtsova V. (2011), In Search of 'W'. Spatial Economic Analysis, 6, 3: 249-270. DOI: 10.1080/17421772.2011.586721
  35. Heckman J. (1999), Causal Parameters and Policy Analysis in Economics: A Twentieth Century Retrospective. New York: NBER, Working paper n. 7333.
  36. Herrera M. (2011), Causality. Contributions to Spatial Econometrics. Ph.D. Dissertation. Zaragoza: University of Zaragoza, Spain
  37. Herrera M., Mur J., Ruiz M. (2012), Selecting the Most Adequate Spatial Weighting Matrix: A Study on Criteria. Paper presented in the VI World Conference of the Spatial Econometrics Association held at Salvador de Bahia: Brazil, July.
  38. Hoover K. (2004), Lost causes. Journal of the History of Economic Thought, 26, 2: 149-164. DOI: 10.1080/1042771042000219000
  39. Kapoor M., Kelejian H., Prucha I. (2007), Panel Data Models with Spatially Correlated Error Components. Journal of Econometrics, 140, 2: 97-130. DOI: 10.1016/j.jeconom.2006.09.004
  40. Kelejian H. (2008), A Spatial J-test for Model Specification Against a Single or a Set of Non-nested Alternatives. Letters in Spatial and Resource Sciences, 1, 1: 3-11. DOI: 10.1007/s12076-008-0001-9
  41. Kelejian H., Prucha I. (1999), A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model. International Economic Review, 40, 2: 509-533. DOI: 10.1111/1468-2354.00027
  42. Kelejian H., Prucha I. (2007), HAC Estimation in a Spatial Framework. Journal of Econometrics 140, 1: 131-154. DOI: 10.1016/j.jeconom.2006.09.005
  43. Lee L. (2007), Identification and Estimation of Econometric Models with Group Interactions, Contextual Factors and Fixed Effects. Journal of Econometrics, 140, 2: 333-374. DOI: 10.1016/j.jeconom.2006.07.001
  44. Leenders R. (2002), Modeling Social Influence through Network Autocorrelation: Constructing the Weight Matrix. Social Networks, 24, 1: 21-47. DOI: 10.1016/S0378-8733(01)00049-1
  45. LeSage J., Pace K. (2009), Introduction to Spatial Econometrics. Boca Raton: Taylor & Francis. DOI: 10.1201/9781420064254
  46. Maggioni M., Nosvelli M., Uberti T. E. (2007), Space Versus Networks in the Geography of Innovation: A European Analysis. Papers in Regional Science, 86, 3: 471-493. DOI: 10.1111/j.1435-5957.2007.00130.x
  47. Manski C. (1993), Identification of Endogenous Social Effects: The Reflection Problem. The Review of Economic Studies, 60, 3: 531-542. DOI: 10.2307/2298123
  48. Marshall A. (1890), Principles of Economics, 8th ed. London: Macmillan.
  49. McMillen D. (2012), Perspectives on Spatial Econometrics: Linear Smoothing with Structured Models. Journal of Regional Science, 52, 2: 192-209. DOI: 10.1111/j.1467-9787.2011.00746.x
  50. Mora T., Moreno R. (2010), Specialisation Changes in European Regions: The Role Played by Externalities Across Regions. Journal of Geographical Systems, 12, 3: 311-334. DOI: 10.1007/s10109-009-0098-4
  51. Mur J., Paelinck J. (2011), Deriving the W-matrix via p-median Complete Correlation Analysis of Residuals. Annals of Regional Science, 47, 2: 253-267. DOI: 10.1007/s00168-010-0379-3
  52. Paelinck J., Klaassen L. (1979), Spatial Econometrics. Farnborough: Saxon House.
  53. Partridge M., Boarnet M., Brakman S., Ottaviano G. (2012), Introduction: Whither Spatial Econometrics. Journal of Regional Science, 52, 2: 167-171. DOI: 10.1111/j.1467-9787.2012.00767.x
  54. Pearl J. (2000), Causality: Models, Reasoning, and Inference. Cambridge: Cambridge University Press.
  55. Pinkse J., Slade M. (2010), The Future of Spatial Econometrics. Journal of Regional Science, 50, 103-117. DOI: 10.1111/j.1467-9787.2009.00645.x
  56. Pinkse J., Slade M., Brett C. (2002), Spatial Price Competition: A Semiparametric Approach. Econometrica, 70, 3: 1111-1153. DOI: 10.1111/1468-0262.00320
  57. Ponds R., van Oort F., Frenken K. (2007), The Geographical and Institutional Proximity of Research Collaboration. Papers in Regional Science, 86, 3: 423-443. DOI: 10.1111/j.1435-5957.2007.00126.x
  58. Robinson P. (2011), Asymptotic Theory for Nonparametric Regression with Spatial Data. Journal of Econometrics, 165, 1: 5-19. DOI: 10.1016/j.jeconom.2011.05.002
  59. Robinson P., Thawornkaiwong S. (2012), Statistical Inference on Regression with Spatial Dependence. Journal of Econometrics, 167, 2: 521-542. DOI: 10.1016/j.jeconom.2011.09.033
  60. Romer P. (1990), Endogenous Technological Change. Journal of Political Economy, 98, 5: 71-102. DOI: 10.1086/261725
  61. Sims C. (1980), Macroeconomics and Reality. Econometrica, 48, 1: 1-48. DOI: 10.2307/1912017
  62. Stakhovych S., Bijmolt T. H. A. (2008), Specification of Spatial Models: A Simulation Study on Weights Matrices. Papers in Regional Science, 88, 2: 389-408. DOI: 10.1111/j.1435-5957.2008.00213.x
  63. Tiefelsdorf M., Griffith D. (2007), Semiparametric Filtering of Spatial Autocorrelation: The Eigenvector Approach. Environment and Planning A, 39, 5: 1193-1221. DOI: 10.1068/a37378
  64. Tobler W. (1970), A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 2: 234-240. DOI: 10.2307/143141
  65. Wiener N. (1956), The theory of prediction. In: Beckenbach E. (ed.), Modern Mathematics for Engineers. New York: Mc GrawHill.

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Jesùs Mur, Causality, Uncertainty and Identification: Three Issues on the Spatial Econometrics Agenda in "SCIENZE REGIONALI " 1/2013, pp 5-27, DOI: 10.3280/SCRE2013-001001