Professor Bernard Fingleton is a distinguished academic known for his expertise in the field of regional economics and spatial econometrics. His qualifications include a PhD in economic geography from Aberystwyth University, a Masters in Land Economy and a PhD in economics from the faculty of economics at Cambridge University. Apart from many years teaching and researching at the department of Land Economy, he was a Professor of economics at the University of Strathclyde, a senior lecturer at Anglia Ruskin University, and an economic consultant at Cambridge Econometrics.  He has given research papers at numerous Universities, with over 130 conference presentations, and was a Jean Monnet Fellow at the Department of Economics, European University Institute, Florence, and for several years  a Visiting Professor at Université Pantheon-Assas, Paris II. He has authored or edited 6 books, 15 book length consultancy reports, well over 100 papers in refereed Journals. He has advised Cambridge Econometrics, the World Bank, UK Department for Transport, HM Treasury, Public and Corporate Economic Consultants, National Science Foundation, USA, the ESRC, the Italian Ministry for Education, University and Research, the Austrian Science Fund, the Irish Research Council and the London School of Economics.

His research interests focus mainly on two areas. One is in developing new methods of data analysis, specifically relating to spatiotemporal panel data. The second strand is applying econometric methods, most specifically spatial econometrics, to study the dynamics of regional economies, the determinants of regional productivity and economic growth. His research as been recognised by winning the European Investment Bank-ERSA prize in Regional Science, receiving a British and Irish Regional Science Association Lifetime Contribution award, and gaining a fellowship of the Regional Science Association International. Also, he was the inaugural Moss Madden Memorial Medal winner, was awarded the Martin Beckmann RSAI Award for the best paper in Papers in Regional Science in 2006 and he won a Journal of Property Research Award for Best Paper in Real Estate Economics in 2011.

One of his most notable achievements has been as founding Editor-in-Chief of the journal Spatial Economic Analysis (2005-2015).

Much of his work is at the interface between geography and economics, what is loosely called regional science which can be thought of as maybe a dimension of Land Economy. It has both a technical and policy angle. Consider first a cross-section of data. Invariably with spatially distributed data, such as a policy impact indicator (y) across EU NUTS 2 regions, there is a non-random distribution with clusters of similar values of y in regions that are near to each other. The clustering could be partly because of similarly located fund allocations (x), but there may also be a direct across border effect simply involving y.  If for example output (y ) was boosted by policy instruments in a particular region, its effect could leak out to other regions, for example higher output in region A could lead to more demand for goods and services, and hence higher output  in ‘nearby’ region B. Moreover, there is also the possibility of copycat effects, so a local authority in one region may take account of actions by neighbours in setting local tax rates or in the provision of local government services, perhaps causing a convergence of policy impact indicators. Failure to take account of such spatial interactions leads to omitted variable bias. Bernard Fingleton’s research typically attempts to avoid such biases by careful and appropriate econometric modelling, and was a topic considered in his very early books (Upton and Fingleton, 1985,1989) which has turned into a lifetime’s work. Spatial dependence naturally extends to spatial panel data, best exemplified from a methodological perspective in his joint paper with Baltagi and Pirotte(2019) and in Fingleton(2023). A recent suite of papers applying recent panel-data methodology focuses on applications to estimate the local employment impacts of immigration (Fingleton. Olner and Pryce, 2020) and causes of UK regional variation in productivity (Gardiner et al, 2020, 2021), the impact of Brexit on employment (Fingleton, 2020, 2022) and on regional productivity in the UK (Fingleton, Gardiner, Martin and Barbieri, 2023).  

PUBLICATIONS

Authored Books

1. Models of Category Counts  (Cambridge University Press, 1984) 

                        Reprinted in paperback 2008

2. Spatial Data Analysis by Example, Volume 1 with Upton, G.J.G, (Wiley, 1985) 

            Revised 1988

Reprinted October 1990, October 1992, July 1994, Sept 1995

3. Spatial Data Analysis by Example, Volume 2 with Upton, G.J.G, (Wiley, 1989) 

                  Reprinted September 1995

Edited Books

1. European Regional Growth, Fingleton B (ed.),  (Springer 2003)

2. Regional Economic Growth, SMEs and the Wider Europe, Fingleton B, Paci R., Eraydin A. (eds.),  (Ashgate, 2003)

3. New Directions in Economic Geography, Fingleton  B (ed.)  (Edward Elgar, 2007)
4.  

Papers in refereed Journals and Chapters in edited volumes (published)

1. Fingleton, B. (1975) 'A factorial approach to the nearest centre hypothesis' Transactions of the Institute of British Geographers 65 131-139
2. Fingleton, B. (1976) 'Alternative approaches to modelling varied spatial behaviour' Geographical Analysis 8 95-101
3. Fingleton, B. (1978) 'Factors affecting optimum locations' Area 10 96-101
4. Upton, G.J.G. and Fingleton, B. (1979) 'Loglinear models in geography' Transactions of the Institute of British Geographers 4 103-115
5. Fingleton, B. (1980) 'Loglinear models, mostellerising and forecasting' Area 13 123-129
6. Fingleton, B. (1981) 'Loglinear modelling of geographical contingency tables' Environment and Planning Series A 13 1539-1551
7. Fingleton, B. (1983) 'Independence, stationarity, categorical spatial data and the chi-squared test' Environment and Planning Series A 15 483-499
8. Fingleton, B. (1983) 'Loglinear models with dependent spatial data' Environment and Planning Series A 15 801-813
9. Fingleton, B. (1984) 'Using GENSTAT to fit complex association models to contingency tables' GENSTAT newsletter 14 27-32
10. Fingleton, B. and B.T. Porteous (1985) 'Comment on the paper by Bennett and Haining' Journal of the Royal Statistical Society A 31-32

11. Fingleton, B. (1986) 'Analyzing cross-classified data with inherent spatial dependence' Geographical Analysis 18 48-61
12. Fingleton, B. (1988) 'Categorical data with inherent spatial dependence : the case of cluster sampling' Transactions of the Institute of British Geographers 13 497-503
13. Fingleton, B. (1989) 'Evaluating British Government regional policy : a cost oriented approach'  Transactions of the Institute of British Geographers 14 446-460
14. Fingleton, B. and P. Tyler (1990) 'A cost based approach to the modelling of industrial movement in Great Britain' Regional Studies, 5 433-445
15. Fingleton, B. (1991) 'Industrial location and policy : a spatial statistical analysis'  Papers in Regional Science 70 3 267-285
16. Fingleton, B. (1991)  'Regional development : positive and negative feedback' Geography Review, 5(2) 22-26
17. Fingleton, B. (1992)  'Some observations on the location of employment in high technology manufacturing in Great Britain' Urban Studies , 29 8 1265‑1276
18. Fingleton, B. (1994) 'The location of high‑technology manufacturing in Great Britain : changes in the late 1980s' Urban Studies,31 1 47-57
19. McCann P, Fingleton B (1996) 'The regional agglomeration impact of just in time input linkages : evidence from the Scottish economy'  Scottish Journal of Political Economy, vol 43, 493-518
20. Pinelli, D, Giacometti, R, Lewney, R, and Fingleton, B (1996) ‘Growth and real convergence effects’ , Chapter 7 (pp 173-208)  in European Economy, 4, 1996
21. Fingleton B (1997) 'Specification and Testing of Markov Chain Models: an Application to Convergence in the European Union' Oxford Bulletin of Economics and Statistics ,vol 59, no. 3, 385-403.
22. Fingleton B and McCombie J (1998) 'Increasing returns and economic growth : some evidence for manufacturing from the European Union regions' Oxford Economic Papers, vol. 50, 89-105
23. Fingleton B (1999) 'Spurious spatial regression: some Monte-Carlo results with a spatial unit root and spatial cointegration'  Journal of Regional Science, 39, 1-19
24. Fingleton B (1999)  ‘Estimates of time to economic convergence : an analysis of regions of the European Union’ International Regional Science Review, 22, 5-35
25. Fingleton B (1999) 'Generalised linear models, loglinear models and regional dynamics'  Chapter 17 in The Current State of Economic Science, vol 1 (ed S B Dahiya) Spellbound Publications, Rhotak, pp 285-307
26. Fingleton B (2000) ‘Convergence : international comparisons based on a simultaneous equation model with regional effects’  International Review of Applied Economics, 14, 285-305
27. Fingleton B (2000) ‘Spatial econometrics, economic geography, dynamics and equilibrium : a third way?’ Environment & Planning A,  32 1481-1498
28. Fingleton B (2001) ‘Equilibrium and economic growth : spatial econometric models and simulations’  Journal of Regional Science,  41 117-148
29. Fingleton B (2001) ‘Theoretical economic geography and spatial econometrics : dynamic perspectives'  Journal of Economic Geography, 1 201-225
30. Fingleton B (2001) , with TS Barker, K Homenidou and R Lewney 'The regional Cambridge multisectoral dynamic model of the UK economy' Chapter 5 in  Regional Science in Business (eds. G Clarke, M Madden) Springer-Verlag Heidelberg, pp. 79-96
31. Fingleton B (2003) ‘Externalities, Economic Geography and Spatial Econometrics : Conceptual And Modeling Developments’, International Regional Science Review, 26, 2 197-207 
32. Fingleton B (2003) ‘Introduction’ to European Regional Growth (Ed. B. Fingleton) Springer-Verlag,  pp. 1 - 10
33. Fingleton B (2003) ‘Models and simulations of GDP per inhabitant across Europe's regions : a preliminary view’  Chapter 1  in European Regional Growth (Ed. B. Fingleton) Springer-Verlag,  pp. 11-54
34. Fingleton B, Igliori D C and Moore B (2003) ‘Employment growth of small computing services firms and the role of horizontal clusters : evidence from Great Britain 1991-2000’  Chapter 9  in European Regional Growth (Ed. B. Fingleton) Springer-Verlag, pp. 267 - 292
35. B Fingleton, E Lopez-Bazo (2003) Explaining the distribution of manufacturing productivity in the EU regions’  Chapter 13 in European Regional Growth (Ed. B. Fingleton) Springer-Verlag,  pp. 375 – 410
36. Fingleton B, A Eraydin and R. Paci (2003) ‘Introduction’, Chapter 1 in  Regional Economic Growth, SMEs and the Wider Europe, (Eds Fingleton, Eradin, Paci) Ashgate,  pp. 1-10
37. Fingleton B (2003) ‘Non-orthodox approaches to European regional growth modeling : a review’ Chapter 2 in  Regional Economic Growth, SMEs and the Wider Europe, (Eds Fingleton, Eradin, Paci) Ashgate, pp. 14- 52
38. Fingleton B. (2003) 'Increasing returns: evidence from local wage rates in Great Britain',  Oxford Economic Papers, 55, 716-739
39. Fingleton B, Igliori D C and Moore B (2004) 'Employment Growth of Small High-technology Firms and the Role of Horizontal Clusters: Evidence from Computing Services and R&D in Great Britain 1991-2000' Urban Studies 41(4), 773-799
40. Fingleton B (2004) 'Some alternative geo-economics for Europe's regions'  Journal of Economic Geography 4  389-420
41. Fingleton B (2004) ‘Theoretical economic geography and spatial econometrics : bridging the gap between theory and reality’ pp. 8-27 in Arthur Getis, Jesus Mur and Henry Zoller (Eds) Spatial Econometrics and Spatial Statistics  (Palgrave)
42. Fingleton B (2004)  'Regional economic growth and convergence : insights from a spatial econometric perspective'  pp 397-432 in  Advances in  Spatial Econometrics (eds L Anselin, R Florax, S Rey), Springer
43. Fingleton B (2005) ‘The new economic geography versus urban economics : an evaluation using local wage rates in Great Britain’, chapter 2 in Contributions to Spatial Econometrics (eds. F. Javier Trívez et al.)
44. Fingleton, B (2005) ‘Contrastes Espaço-Temporais do Crescimento da Produtividade Industrial Européia: Implicações para a Teoria e o Desenvolvimento (Regional Space-time contrasts in European manufacturing productivity growth : implications for theory and development)’ chapter 16 pp 449-484 in Economia e Espaço (Economy and Space) (eds Clélio Campolina Diniz and Mauro Borges Lemos ) published by EDITORA UFMG of the Universidade Federal de Minas Gerais – UFMG (the Federal University of Minas Gerais)
45. Fingleton B, Igliori D C and Moore B (2005) ' Cluster Dynamics: New Evidence and Projections for Computing Services in Great Britain ',  Journal of Regional Science 45 283-311
46. Fingleton B (2005) 'Towards applied geographical economics: modelling relative wage rates, incomes and prices for the regions of Great Britain' Applied Economics 37 2417-2428
47. Fingleton B (2005) ‘Beyond neoclassical orthodoxy : a view based on the new economic geography and UK regional wage data’,  Papers in Regional Science 84 351-375
48. Fingleton B (2006) ‘The new economic geography versus urban economics : an evaluation using local wage rates in Great Britain’,  Oxford Economic Papers 58  501-530
49. Fingleton B, Eraydin A (2006) Networks relations and local economic development:  some causes of differentiated network structures and intensities among Turkish industrial firms,  Environment and Planning A 38 1171 – 1186
50. Fingleton B, Lopez-Bazo E (2006) ‘Empirical Growth Models with Spatial Effects’  Papers  in Regional Science 85   177-198
51. Fingleton B  (2006) ‘A cross-sectional analysis of residential property prices:  the effects of income, commuting, schooling, the housing stock and spatial interaction in the English regions'  Papers  in Regional Science 85  339-361
52. Fingleton B(2007) ‘A multi-equation spatial econometric model, with application to EU manufacturing productivity growth’ Journal of Geographical Systems  9 119-144 
53. Fingleton B, J Le Gallo (2007) ‘Finite Sample Properties of Estimators of Spatial Models with Autoregressive, or Moving Average, Disturbances and System Feedback’  Annales d’Économie et de Statistique no. 87-88 Juillet/Decembre 39-62
54. Fingleton B, Igliori D C, Moore B, Odedra R (2007) ' Employment growth an cluster dynamics of creative industries in Great Britain ',   Chapter 4  in  The Economic Geography of Innovation (Ed. Karen Polenske), Cambridge University Press
55. Fingleton B (2007) ‘New economic geography : some preliminaries’, Chapter 1 pp 11-52 in New Directions in Economic Geography (Ed B Fingleton)
56. Fingleton B(2007) ‘Testing the “new economic geography” : a comparative analysis based on EU regional data’, Chapter 3 pp 70-97  in  New Directions in Economic Geography (Ed B Fingleton)
57. Fingleton B, McCann P(2007) ‘Sinking the iceberg? On the treatment of transport costs in new economic geography’,  Chapter 6 pp 168-203 in  New Directions in Economic Geography (Ed B Fingleton)
58. Fingleton B, E Lopez-Bazo (2007) ‘Increasing returns and the distribution of manufacturing productivity in the EU regions’, Chapter 11 pp 151-177 in Understanding Economic Growth: New Directions in Theory and Policy, edited by Philip Arestis, Michelle Baddeley, John S. L. McCombie
59. B Fingleton (2007) ‘Modeling Globalization: a Spatial Econometric Analysis’  Chapter 16, p 393-416 in Globalization and Regional Economic Modeling edited by Russel J. Cooper, Kieran P. Donaghy, and Geoffrey J.D. Hewings
60. Fingleton B (2008)  ‘A Generalized Method of Moments estimator for a spatial model with Moving Average errors, with application to real estate prices’  Empirical Economics 34 35-57
61. Fingleton B (2008) ‘A Generalized Method of Moments estimator for a spatial panel model with an endogenous spatial lag and spatial moving average errors’  Spatial Economic Analysis, 3 27-44
62. Fingleton B (2008) ‘Competing models of global dynamics : evidence from panel models with spatially correlated error components’   Economic Modelling  25 542-558
63. Fingleton B (2008) ‘Housing supply, housing demand, and affordability’ Urban Studies  45 1545-1563
64. Fingleton B, J Le Gallo (2008) "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties"  Papers  in Regional Science 87 319-339
65. Arbia, G, Fingleton B G(2008) ‘New spatial econometric techniques and applications in regional science’, Papers in Regional Science Volume 87, Issue 3,  Pages: 311-317
66. Fingleton B, Igliori D C, Moore B (2008) R&D Clustering and Growth;  Chapter 5 in Handbook of Research on Clusters: Theories, Policies and Case Studies,  Edited by Charlie Karlsson, E Elgar
67. B Fingleton (2008) ‘Spatial Econometrics: Methods And Applications’, chapter 3 in ‘Spatial Econometrics: Methods And Applications’ eds Giuseppe Arbia, Badi H. Baltagi, Physica-verlag Heidelberg
68. Fingleton B (2009) ‘Prediction  using panel data regression with  spatial random effects’,  International Regional Science Review,  32 195-220
69. Fingleton B (2009) Spatial Autoregression  Geographical_Analysis 41 385-391
70. Fingleton B (2009) ‘Testing the NEG model : further evidence from panel data’ Région & Développement 30  141-158
71. Burridge P & Fingleton B (2010) Bootstrap inference in spatial econometrics : the J test Spatial Economic Analysis 5(1) 93-119
72. Fingleton B, Fischer M (2010) Neoclassical Theory versus New Economic Geography. Competing explanations of cross-regional variation in economic development,  Annals of Regional Science,  44  467-491
73. Fingleton B, J Le Gallo (2010)  ‘Endogeneity in a spatial context : properties of estimators’  pp 59-73 in Páez A, Le Gallo J, Buliung R, Dall’Erba S, Progress in Spatial Analysis: Theory and Computation, and Thematic Applications, Advances in Spatial Science, Springer
74. Fingleton B (2010) A multi-equation spatial econometric model, with application to EU manufacturing productivity growth, Chapter E3 pp 629-649 in Handbook of Applied Spatial Analysis (Springer, Edited by Manfred M.            Fischer and Arthur Getis)
75. Fingleton, B (2011)  The empirical performance of the NEG with reference to small areas  Journal of Economic Geography,  11 267-279
76. Fingleton B & Baddeley M (2011) ‘Globalisation And  Wage Differentials: A Spatial Analysis’  The Manchester School 79 1018-1034
77. Le Gallo J, Fingleton B (2012) ‘Measurement errors in a spatial context’   Regional Science and Urban Economics 42 114-125
78. Fingleton B, J Le Gallo (2012) ‘Endogeneité et autocorrélation spatiale : quelle utilité pour le modèle de Durbin ?’   Revue d’Economie Régionale et Urbaine  February  3-17
79. Fingleton B, Garretsen H,  Martin RL (2012) ‘Recessionary Shocks and Regional Employment: Evidence on the Resilience of U.K. Regions’ ,  Journal of Regional Science 52 109-133
80. Corrado L. & Fingleton B.  (2012)  Where is the economics in spatial econometrics?   Journal of Regional Science 52 210-239
81. Gómez-Antonio, Miguel, Fingleton B (2012),   Analysing the impact of public capital stock using the NEG wage equation : a panel data approach. Journal of Regional Science,  52 486–502
82. Gómez-Antonio, M, B Fingleton (2012) ‘Regional productivity variation and the impact of public capital stock: an analysis with spatial interaction, with reference to Spain’,  Applied Economics, Volume 44, Issue 28, October 2012, pages 3665-3677
83. Mark Roberts, Uwe Deichmann, Bernard Fingleton and Tuo Shi (2012) ‘Evaluating China’s Road to Prosperity: A New Economic Geography Approach’ Regional Science and Urban Economics 42 580-594
84. Chen, Y., Fingleton, B., Pryce, G., Chen, A. & Djordjević, S. (2013) ‘Implications of rising flood risk for employment location: A GMM spatial model with agglomeration and endogenous house price effects’ , Journal of Property Research, Volume 30, Issue 4 pages 298-323
85. Fingleton B,  Longhi S (2013)  ‘The effects of agglomeration on wages: evidence from the micro-level’  Journal of Regional Science 53 443-46
86. Fingleton B, Palombi S (2013) ‘Spatial panel data estimation, counterfactual predictions, and local economic resilience among  British towns in the Victorian era’  Regional Science and Urban Economics 43  649–662
87.  J Le Gallo, B Fingleton (2013) ‘Regional growth and convergence empirics’  Chapter 16, pp. 291-315  in  Handbook of Regional Science, Volume 1, Manfred Fischer and Peter Nijkamp (Eds.)
88. Fingleton B, Palombi S (2013) The wage curve reconsidered : is it truly an 'empirical law of economics'?   Région & Développement no. 38 49-92
89. Doran J, Fingleton B (2014) "Economic Shocks and Growth: Spatio-temporal Perspectives on Europe’s Economies in a Time of Crisis”  Papers in Regional Science 93, issue S1, pp S137-S165 Article first published online: 24 JUN 2013 | DOI: 10.1111/pirs.12048
90. Baltagi BH, Fingleton B and A Pirotte (2014) ‘Estimating and Forecasting with a  Dynamic Spatial Panel Model’  Oxford Bulletin of Economics and Statistics Volume 76, Issue 1, February 2014, Pages: 112–138
91. Baltagi B, Fingleton B,  Pirotte A (2014) ‘Spatial Lag Models     with Nested Random Effects: an IV procedure with application to English house prices’  Journal of Urban Economics 80 76-86 
92. Fingleton B  (2014) ‘Forecasting with dynamic spatial panel data : practical implementation methods’’ in Special Issue on "Advances in Regional Forecasting” , Economics and Business Letters  Vol 3, No 4 194-207
93. Baltagi B, Fingleton B,  Pirotte A (2014) ‘Multilevel and Spillover Effects estimated for Spatial Panel Data, with  application to English House Prices’ ?   Région & Développement vol 40 25-36
94. Fingleton B, Garretsen H,  Martin RL (2015)  ‘Shocking Aspects of Monetary Union: The Vulnerability of Regions in Euroland’  Journal of Economic Geography  15: 907-934
95.  Doran J, Fingleton B (2015) ‘Resilience from the micro-perspective’  Cambridge Journal of Regions, Economy and Society 8 (2): 205-223
96. Fingleton B, Palombi S (2016) ‘Bootstrap J Test for Panel Models with Spatially Dependent Error Components, a Spatial Lag and Additional Endogenous Variables’  Spatial Economic Analysis 11 7-26
97. Doran J and Fingleton (2016) ‘Employment resilience in Europe and the 2008 economic crisis: insights from micro level data'  Regional Studies, 50(4), 644-656
98. Fingleton B (2016) ‘Regional Science in a time of uncertainty’ REGION Volume 3, Number 2, 2016, 61-69
99. Fingleton B,  (2017) ‘Dynamic Spatial econometric models: a critical review’  Scienze Regionali (Italian Journal of Regional Science) 16(1), 9-30
100. Fingleton B ,  Pirotte A (2017) ‘'Dynamic spatial panel modelling : estimation and forecasting with application to English house prices' (in Spanish) Papeles de Economia Española 152 92-103
101. Fingleton B ,  Pirotte A (2017)’Contemporary developments in spatial econometrics modelling : the 14^th International Workshop on Spatial Econometrics and Statistics, Paris 2015, Spatial Economic Analysis 12 129-137
102. Fingleton B , Le Gallo J, , Pirotte A (2018) ‘Panel Data Models with Spatially Dependent Nested Random Effects’ Journal of Regional Science, VOL. 58, NO. 1, 2018, pp. 63–80
103.  Doran J, Fingleton B (2018)  ‘US Metropolitan Area Resilience: Insights from Dynamic Spatial Panel Estimation'   Environment & Planning A 50 111-132
104. Fingleton B , Le Gallo J,  Pirotte A (2018) ‘A multi-dimensional Spatial Lag Panel Data Model with spatial moving average nested random effects errors’

 Empirical Economics, 55(1), 113-146

105. J Le Gallo, B Fingleton (2018) ‘Regional growth and convergence empirics’  revised Chapter in  Handbook of Regional Science, 2^nd Edition, Manfred Fischer and Peter Nijkamp (Eds.)
106. Baltagi B, Fingleton B,  Pirotte A (2019) ‘A Time-Space Dynamic Panel Data Model  with Spatial Moving Average Errors’  Regional Science and Urban Economics 76 13-31
107. Fingleton B, Nikodem Szumilo(2019) ‘Simulating the impact of transport infrastructure investment on wages: a dynamic spatial panel model approach’, Regional Science and Urban Economics 75  148-164
108. Bernard Fingleton, Franz Fuerst and Nikodem Szumilo (2018) "Housing affordability: is new local supply the key?" E&P A Volume: 51 issue: 1, page(s): 25-50
109. Fingleton B(2020) ‘ Italexit, is it another Brexit?’ Journal of Geographical Systems.  22:77–104
110. Fingleton B(2020) ‘Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions’ Annals of Regional Science 64:455–491 https://doi.org/10.1007/s00168-019-00913-2
111. Le Gallo J., Fingleton B. (2019) Endogeneity in Spatial Models. In: Fischer M., Nijkamp P. (eds) Handbook of Regional Science. Springer, Berlin, Heidelberg DOI https://doi.org/10.1007/978-3-642-36203-3_122-1
112. Fingleton B, Olner D, Pryce G (2020) ‘Estimating the local employment impacts of immigration: A dynamic spatial panel model’, Urban Studies, Vol. 57, pp. 2646–2662 https://doi.org/10.1177/0042098019887916
113. Gardiner B, Fingleton, B,  and Martin R (2020) ‘Regional Disparities in Productivity and the Role of Capital Stock’ National Institute Economic Review, Volume 253, pp. R29-R43
114. Gardiner B, Fingleton, B,  Martin R and Barbieri L. (2021) ‘UK regional capital shocks and productivity, an updated analysis’ report for the Productivity Insights Network, funded by the Economic and Social Research Council
115. Fingleton B (2022) ‘Exploring Brexit Implications: The Impact Of Longer Journey Times’  International Journal of Computational Economics and Econometrics, Vol. 12, Nos. 1/2, pp. 174-196
116. Fingleton, Bernard, Gardiner, Ben, Martin, Ron and Barbieri, Luca. "The impact of brexit on regional productivity in the UK" ZFW – Advances in Economic Geography, vol. 67, no. 2-3, 2023, pp. 142-160. https://doi.org/10.1515/zfw-2021-0061
117. Fingleton, B. Modifying the linear two-step Windmeijer correction for the presence of spatial error dependence. J Spat Econometrics 3, 10 (2022). https://doi.org/10.1007/s43071-022-00029-4
118. Fingleton B (2023) ‘Estimating dynamic spatial panel data models with endogenous regressors using synthetic instruments’ Journal of Geographical Systems 25(1) pp 121-152  https://doi.org/10.1007/s10109-022-00397-3

(Professor) Justin Doran ‘regional resilience and vulnerability’ 2011

Urban and rural economy

Cambridge Centre for Economics and Public Policy (CCEP)