A spatial productivity index in the presence of efficiency spillovers: Evidence for U.S. banks, 1992-2015

We present the methodology for a new spatial decomposition of total factor productivity (TFP) growth. The relevant literature is underdeveloped as there is just one short study which proposes a partial spatial TFP growth decomposition. We develop this literature in four respects. The first two developments are methodological to go from a partial decomposition to a complete one. First, we augment the partial decomposition with a cost efficiency spillover growth component. Second, we introduce own and spillover allocative efficiency growth components. Third, we provide a more detailed coverage of the spatial decomposition of TFP growth. Fourth, in contrast to the traditional application to geographical areas (e.g., countries) in the relevant literature, we apply our decomposition using firm level data, which suggests that there can be an important role for spatial productivity analysis in OR. Our application is to large U.S. banks over the period 1992–2015. Among other things, we find for the average large U.S. bank that TFP growth since the financial crisis has become much more dependent on the bank itself and less so on spatial spillovers.

[1]  Giorgio Vittadini,et al.  Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency , 2014 .

[2]  G. Battese,et al.  Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data , 1988 .

[3]  Christopher J. O'Donnell,et al.  Using information about technologies, markets and firm behaviour to decompose a proper productivity index , 2016 .

[4]  S. Miller,et al.  Productivity growth in large US commercial banks: The initial post-deregulation experience , 2001 .

[5]  D. Jorgenson,et al.  TRANSCENDENTAL LOGARITHMIC PRODUCTION FRONTIERS , 1973 .

[6]  A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in Norway , 2018, The Energy Journal.

[7]  C. W. Sealey,et al.  Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions , 1977 .

[8]  C. Gouriéroux,et al.  Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression Parameters , 1982 .

[9]  William H. Greene,et al.  Persistent and transient productive inefficiency: a maximum simulated likelihood approach , 2014 .

[10]  Luis Orea,et al.  Parametric Decomposition of a Generalized Malmquist Productivity Index , 2002 .

[11]  Subal C. Kumbhakar,et al.  Technical efficiency in competing panel data models: a study of Norwegian grain farming , 2014 .

[12]  Alfons Oude Lansink,et al.  Primal and dual dynamic Luenberger productivity indicators , 2015, Eur. J. Oper. Res..

[13]  T. Coelli,et al.  Accounting for Environmental Influences in Stochastic Frontier Models: With Application to International Airlines , 1999 .

[14]  Subal C. Kumbhakar,et al.  FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY: A GENERALIZED TRUE RANDOM-EFFECTS model , 2014 .

[15]  Harry H. Kelejian,et al.  A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model , 1999 .

[16]  Subal C. Kumbhakar,et al.  Productivity and efficiency estimation: A semiparametric stochastic cost frontier approach , 2015, Eur. J. Oper. Res..

[17]  William C. Horrace,et al.  Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming , 2004 .

[18]  Oleg Badunenko,et al.  Economies of scale, technical change and persistent and time-varying cost efficiency in Indian banking: Do ownership, regulation and heterogeneity matter? , 2017, Eur. J. Oper. Res..

[19]  Luis Orea,et al.  Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model , 2018, Journal of Productivity Analysis.

[20]  P. Schmidt,et al.  Production Frontiers and Panel Data , 1984 .

[21]  Allen N. Berger,et al.  How Does Capital Affect Bank Performance During Financial Crises? , 2012 .

[22]  James R. Barth,et al.  Policy Watch The Repeal of Glass-Steagall and the Advent of Broad Banking , 2000 .

[23]  Kevin J. Fox,et al.  Decomposing productivity indexes into explanatory factors , 2017, Eur. J. Oper. Res..

[24]  Karligash Glass,et al.  Productivity Growth Decomposition Using a Spatial Autoregressive Frontier Model , 2013 .

[25]  William H. Greene,et al.  Reconsidering heterogeneity in panel data estimators of the stochastic frontier model , 2005 .

[26]  W. Greene Distinguishing between Heterogeneity and Inefficiency: Stochastic Frontier Analysis of the World Health Organization S Panel Data on National Health Care Systems , 2003, Health economics.

[27]  M. Tsionas,et al.  A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions , 2016 .

[28]  Paul W. Bauer,et al.  Decomposing TFP growth in the presence of cost inefficiency, nonconstant returns to scale, and technological progress , 1990 .

[29]  Raluca A. Roman,et al.  Did Saving Wall Street Really Save Main Street? The Real Effects of TARP on Local Economic Conditions , 2015, Journal of Financial and Quantitative Analysis.

[30]  P. Schmidt,et al.  Production frontiers with cross-sectional and time-series variation in efficiency levels , 1990 .

[31]  J. W. B. Bos,et al.  Effects of heterogeneity on bank efficiency scores , 2009, Eur. J. Oper. Res..

[32]  Robin C. Sickles,et al.  A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers , 2015 .

[33]  J. Jaumandreu,et al.  Modelling price competition across many markets (An application to the Spanish loans market) , 2002 .

[34]  Luc Anselin,et al.  Spatial Externalities, Spatial Multipliers, And Spatial Econometrics , 2003 .

[35]  Subal C. Kumbhakar,et al.  When, where and how to estimate persistent and transient efficiency in stochastic frontier panel data models , 2016, Eur. J. Oper. Res..

[36]  B. Baltagi,et al.  Firm-Level Productivity Spillovers in China's Chemical Industry: A Spatial Hausman-Taylor Approach , 2014, SSRN Electronic Journal.

[37]  Xi Qu,et al.  Estimating a spatial autoregressive model with an endogenous spatial weight matrix , 2015 .

[38]  Anthony J. Glass,et al.  Returns to scale and curvature in the presence of spillovers: evidence from European countries , 2016 .