Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/regeco/v61y2016icp153-164.html
   My bibliography  Save this article

Spatial nonstationarity in the stochastic frontier model: An application to the Italian wine industry

Author

Listed:
  • Vidoli, Francesco
  • Cardillo, Concetta
  • Fusco, Elisa
  • Canello, Jacopo
Abstract
This research estimates the efficiency of a representative sample of Italian wine producers from the Italian FADN survey following a recent spatial stochastic frontier framework that allows to isolate the spatial dependence among units and to evaluate the role of intangible local factors in influencing the economic performance of firms. The empirical exercise shows that the specific territorial patterns in the data cannot be merely explained using a standard set of contextual factors. This intangible component can be interpreted as the role of the local business climate: in most localities, the presence of an embedded community stimulates a process of local learning that generates the diffusion of tacit knowledge through continuous interaction among the local actors. This effect is found to be different across firm size, with a larger impact on small firms.

Suggested Citation

  • Vidoli, Francesco & Cardillo, Concetta & Fusco, Elisa & Canello, Jacopo, 2016. "Spatial nonstationarity in the stochastic frontier model: An application to the Italian wine industry," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 153-164.
    • Handle: RePEc:eee:regeco:v:61:y:2016:i:c:p:153-164
    DOI: 10.1016/j.regsciurbeco.2016.10.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0166046216302630
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.regsciurbeco.2016.10.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Viliam Druska & William C. Horrace, 2004. "Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 185-198.
    3. Glass, Anthony & Kenjegalieva, Karligash & Sickles, Robin C., 2014. "Estimating efficiency spillovers with state level evidence for manufacturing in the US," Economics Letters, Elsevier, vol. 123(2), pages 154-159.
    4. Ernest Reig‐Martínez & José A. Gómez‐Limón & Andrés J. Picazo‐Tadeo, 2011. "Ranking farms with a composite indicator of sustainability," Agricultural Economics, International Association of Agricultural Economists, vol. 42(5), pages 561-575, September.
    5. Michael E. Porter, 2000. "Location, Competition, and Economic Development: Local Clusters in a Global Economy," Economic Development Quarterly, , vol. 14(1), pages 15-34, February.
    6. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    7. Craig Beebe & Farshid Haque & Chelsea Jarvis & Martin Kenney & Donald Patton, 2013. "Identity creation and cluster construction: the case of the Paso Robles wine region," Journal of Economic Geography, Oxford University Press, vol. 13(5), pages 711-740, September.
    8. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.
    9. Hughes, Neal & Lawson, Kenton & Davidson, Alistair & Jackson, Tom & Sheng, Yu, 2011. "Productivity pathways: climate-adjusted production frontiers for the Australian broadacre cropping industry," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100563, Australian Agricultural and Resource Economics Society.
    10. Edward Oczkowski & Hristos Doucouliagos, 2015. "Wine Prices and Quality Ratings: A Meta-regression Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 103-121.
    11. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    12. Giuliani, Elisa & Morrison, Andrea & Pietrobelli, Carlo & Rabellotti, Roberta, 2010. "Who are the researchers that are collaborating with industry? An analysis of the wine sectors in Chile, South Africa and Italy," Research Policy, Elsevier, vol. 39(6), pages 748-761, July.
    13. Hani, Fritz & Braga, Francesco S. & Stampfli, Andreas & Keller, Thomas & Fischer, Matthew & Porsche, Hans, 2003. "RISE, a Tool for Holistic Sustainability Assessment at the Farm Level," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 6(4), pages 1-13.
    14. Francisco José Areal & Kelvin Balcombe & Richard Tiffin, 2012. "Integrating spatial dependence into Stochastic Frontier Analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(4), pages 521-541, October.
    15. Giuliani, Elisa & Bell, Martin, 2005. "The micro-determinants of meso-level learning and innovation: evidence from a Chilean wine cluster," Research Policy, Elsevier, vol. 34(1), pages 47-68, February.
    16. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    17. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    18. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    19. Elisa Giuliani, 2007. "The selective nature of knowledge networks in clusters: evidence from the wine industry," Journal of Economic Geography, Oxford University Press, vol. 7(2), pages 139-168, March.
    20. LeSage, James P., 1997. "Regression Analysis of Spatial Data," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 27(2), pages 1-12.
    21. Glass, Anthony & Kenjegalieva, Karligash & Paez-Farrell, Juan, 2013. "Productivity growth decomposition using a spatial autoregressive frontier model," Economics Letters, Elsevier, vol. 119(3), pages 291-295.
    22. Vidoli, Francesco & Canello, Jacopo, 2016. "Controlling for spatial heterogeneity in nonparametric efficiency models: An empirical proposal," European Journal of Operational Research, Elsevier, vol. 249(2), pages 771-783.
    23. Pavlyuk, Dmitry, 2012. "Maximum Likelihood Estimator for Spatial Stochastic Frontier Models," MPRA Paper 43390, University Library of Munich, Germany.
    24. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    25. Fabio Sforzi, 2009. "The Empirical Evidence of Industrial Districts in Italy," Chapters, in: Giacomo Becattini & Marco Bellandi & Lisa De Propis (ed.), A Handbook of Industrial Districts, chapter 25, Edward Elgar Publishing.
    26. Erniel B. Barrios & Rouselle F. Lavado, 2010. "Spatial Stochastic Frontier Models," Microeconomics Working Papers 23091, East Asian Bureau of Economic Research.
    27. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    28. Vahidin Jeleskovic & Benjamin Schwanebeck, 2012. "Assessment of a spatial panel model for the efficiency analysis of the heterogonous healthcare systems in the world," MAGKS Papers on Economics 201248, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    29. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    30. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    31. Simon Turner, 2010. "Networks of learning within the English wine industry," Journal of Economic Geography, Oxford University Press, vol. 10(5), pages 685-715, September.
    32. Efthymios G. Tsionas & Panayotis G. Michaelides, 2016. "A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(3), pages 243-257, July.
    33. Morakinyo Adetutu & Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2015. "The effects of efficiency and TFP growth on pollution in Europe: a multistage spatial analysis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 307-326, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2021. "The spatial dimension of competition among airports at the worldwide level: a spatial stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 295(1), pages 118-130.
    2. Sadick Mohammed & Awudu Abdulai, 2022. "Do Egocentric information networks influence technical efficiency of farmers? Empirical evidence from Ghana," Journal of Productivity Analysis, Springer, vol. 58(2), pages 109-128, December.
    3. Samuel Faria & Sofia Gouveia & Alexandre Guedes & João Rebelo, 2021. "Transient and Persistent Efficiency and Spatial Spillovers: Evidence from the Portuguese Wine Industry," Economies, MDPI, vol. 9(3), pages 1-20, August.
    4. Jacopo Canello & Francesco Vidoli, 2020. "Investigating space‐time patterns of regional industrial resilience through a micro‐level approach: An application to the Italian wine industry," Journal of Regional Science, Wiley Blackwell, vol. 60(4), pages 653-676, September.
    5. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    6. Fei Jin & Lung-fei Lee, 2020. "Asymptotic properties of a spatial autoregressive stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-40, December.
    7. Laureti, Tiziana & Benedetti, Ilaria & Branca, Giacomo, 2021. "Water use efficiency and public goods conservation: A spatial stochastic frontier model applied to irrigation in Southern Italy," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    8. Fusco, Elisa & Allegrini, Veronica, 2020. "The role of spatial interdependence in local government cost efficiency: An application to waste Italian sector," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    9. Bernini, Cristina & Galli, Federica, 2024. "Economic and Environmental Efficiency, Subsidies and Spatio-Temporal Effects in Agriculture," Ecological Economics, Elsevier, vol. 218(C).
    10. Theodoros Skevas & Jasper Grashuis, 2020. "Technical efficiency and spatial spillovers: Evidence from grain marketing cooperatives in the US Midwest," Agribusiness, John Wiley & Sons, Ltd., vol. 36(1), pages 111-126, January.
    11. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    12. Thomas Graaff, 2020. "On the estimation of spatial stochastic frontier models: an alternative skew-normal approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 267-285, April.
    13. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    14. Christoph Pross & Christoph Strumann & Alexander Geissler & Helmut Herwartz & Nadja Klein, 2018. "Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-30, September.
    15. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2020. "Spatial competition and efficiency: an investigation in the airport sector," The Warwick Economics Research Paper Series (TWERPS) 1287, University of Warwick, Department of Economics.
    16. A. G. Billé & C. Salvioni & R. Benedetti, 2018. "Modelling spatial regimes in farms technologies," Journal of Productivity Analysis, Springer, vol. 49(2), pages 173-185, June.
    17. Fusco, Elisa & Vidoli, Francesco & Rogge, Nicky, 2020. "Spatial directional robust Benefit of the Doubt approach in presence of undesirable output: An application to Italian waste sector," Omega, Elsevier, vol. 94(C).
    18. Fusco, Elisa & Vidoli, Francesco & Sahoo, Biresh K., 2018. "Spatial heterogeneity in composite indicator: A methodological proposal," Omega, Elsevier, vol. 77(C), pages 1-14.
    19. Cavalieri, Marina & Di Caro, Paolo & Guccio, Calogero & Lisi, Domenico, 2020. "Does neighbours' grass matter? Testing spatial dependent heterogeneity in technical efficiency of Italian hospitals," Social Science & Medicine, Elsevier, vol. 265(C).
    20. Yiorgos Gadanakis & Francisco José Areal, 2020. "Accounting for rainfall and the length of growing season in technical efficiency analysis," Operational Research, Springer, vol. 20(4), pages 2583-2608, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    2. Fusco, Elisa & Allegrini, Veronica, 2020. "The role of spatial interdependence in local government cost efficiency: An application to waste Italian sector," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    3. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    4. Jacopo Canello & Francesco Vidoli, 2020. "Investigating space‐time patterns of regional industrial resilience through a micro‐level approach: An application to the Italian wine industry," Journal of Regional Science, Wiley Blackwell, vol. 60(4), pages 653-676, September.
    5. Bao Hoang Nguyen & Zhichao Wang & Valentin Zelenyuk, 2023. "Efficiency of Queensland Public Hospitals via Spatial Panel Stochastic Frontier Models," CEPA Working Papers Series WP102023, School of Economics, University of Queensland, Australia.
    6. Adjin, K. Christophe & Henning, Christian H. C. A., 2020. "Climate variability and farm inefficiency: A spatial stochastic frontier analysis of Senegalese agriculture," Working Papers of Agricultural Policy WP2020-09, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    7. Yiorgos Gadanakis & Francisco José Areal, 2020. "Accounting for rainfall and the length of growing season in technical efficiency analysis," Operational Research, Springer, vol. 20(4), pages 2583-2608, December.
    8. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2020. "Spatial competition and efficiency: an investigation in the airport sector," The Warwick Economics Research Paper Series (TWERPS) 1287, University of Warwick, Department of Economics.
    9. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2021. "The spatial dimension of competition among airports at the worldwide level: a spatial stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 295(1), pages 118-130.
    10. Mustafa U. Karakaplan & Levent Kutlu, 2019. "School district consolidation policies: endogenous cost inefficiency and saving reversals," Empirical Economics, Springer, vol. 56(5), pages 1729-1768, May.
    11. Fei Jin & Lung-fei Lee, 2020. "Asymptotic properties of a spatial autoregressive stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-40, December.
    12. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    13. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    14. Elisa Fusco & Giuseppe Arbia & Francesco Vidoli & Vincenzo Nardelli, 2024. "On Spatio-Temporal Stochastic Frontier Models," Econometrics Working Papers Archive 2024_09, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    15. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C. & Weyman-Jones, Thomas, 2018. "The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model," Working Papers 18-003, Rice University, Department of Economics.
    16. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    17. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.
    18. Valerien O. Pede & Francisco J. Areal & Alphonse Singbo & Justin McKinley & Kei Kajisa, 2018. "Spatial dependency and technical efficiency: an application of a Bayesian stochastic frontier model to irrigated and rainfed rice farmers in Bohol, Philippines," Agricultural Economics, International Association of Agricultural Economists, vol. 49(3), pages 301-312, May.
    19. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    20. Kutlu, Levent, 2018. "Estimating efficiency in a spatial autoregressive stochastic frontier model," Economics Letters, Elsevier, vol. 163(C), pages 155-157.

    More about this item

    Keywords

    Spatial nonstationarity; Spatial stochastic frontier model; Wine; Efficiency;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:regeco:v:61:y:2016:i:c:p:153-164. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/regec .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.