Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v286y2020i1p389-399.html
   My bibliography  Save this article

A spatial stochastic frontier model with endogenous frontier and environmental variables

Author

Listed:
  • Kutlu, Levent
  • Tran, Kien C.
  • Tsionas, Mike G.
Abstract
We propose a spatial autoregressive stochastic frontier model, which allows for the endogeneity in both the frontier and environmental variables (i.e., endogeneity due to correlation of inefficiency term and two-sided error term). The model parameters are estimated using a single-stage control function approach. Monte Carlo simulations show that our proposed model and approach perform well in finite samples. We employed our methodology to the Chinese chemicals firm data and found evidence for both spatial effects and endogeneity.

Suggested Citation

  • Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2020. "A spatial stochastic frontier model with endogenous frontier and environmental variables," European Journal of Operational Research, Elsevier, vol. 286(1), pages 389-399.
    • Handle: RePEc:eee:ejores:v:286:y:2020:i:1:p:389-399
    DOI: 10.1016/j.ejor.2020.03.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720302344
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2020.03.020?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. 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.
    2. Jith Jayaratne & Philip E. Strahan, 1996. "The Finance-Growth Nexus: Evidence from Bank Branch Deregulation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(3), pages 639-670.
    3. Luis Orea & Jevgenijs Steinbuks, 2018. "Estimating Market Power In Homogenous Product Markets Using A Composed Error Model: Application To The California Electricity Market," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1296-1321, April.
    4. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2016. "Firm‐Level Productivity Spillovers in China's Chemical Industry: A Spatial Hausman‐Taylor Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 214-248, January.
    5. Levent Kutlu & Usha Nair-Reichert, 2019. "Agglomeration effects and spatial spillovers in efficiency analysis: a distribution-free methodology," Regional Studies, Taylor & Francis Journals, vol. 53(11), pages 1565-1574, November.
    6. Wolfgang Keller & Stephen R. Yeaple, 2009. "Multinational Enterprises, International Trade, and Productivity Growth: Firm-Level Evidence from the United States," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 821-831, November.
    7. Perloff,Jeffrey M. & Karp,Larry S. & Golan,Amos, 2007. "Estimating Market Power and Strategies," Cambridge Books, Cambridge University Press, number 9780521011143, September.
    8. Griffiths, William E. & Hajargasht, Gholamreza, 2016. "Some models for stochastic frontiers with endogeneity," Journal of Econometrics, Elsevier, vol. 190(2), pages 341-348.
    9. 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.
    10. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2017. "Endogenous environmental variables in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 199(2), pages 131-140.
    11. Randall S. Kroszner & Philip E. Strahan, 1999. "What Drives Deregulation? Economics and Politics of the Relaxation of Bank Branching Restrictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(4), pages 1437-1467.
    12. Mester, Loretta J., 1997. "Measuring efficiency at U.S. banks: Accounting for heterogeneity is important," European Journal of Operational Research, Elsevier, vol. 98(2), pages 230-242, April.
    13. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    14. 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.
    15. Tecles, Patricia Langsch & Tabak, Benjamin M., 2010. "Determinants of bank efficiency: The case of Brazil," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1587-1598, December.
    16. Mustafa U. Karakaplan & Levent Kutlu, 2017. "Handling Endogeneity in Stochastic Frontier Analysis," Economics Bulletin, AccessEcon, vol. 37(2), pages 889-901.
    17. Kutlu, Levent, 2018. "Estimating efficiency in a spatial autoregressive stochastic frontier model," Economics Letters, Elsevier, vol. 163(C), pages 155-157.
    18. 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.
    19. Mustafa U. Karakaplan & Levent Kutlu, 2019. "Estimating market power using a composed error model," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(4), pages 489-510, September.
    20. Kutlu, Levent & Sickles, Robin C., 2012. "Estimation of market power in the presence of firm level inefficiencies," Journal of Econometrics, Elsevier, vol. 168(1), pages 141-155.
    21. Allen N. Berger & Timothy H. Hannan, 1998. "The Efficiency Cost Of Market Power In The Banking Industry: A Test Of The "Quiet Life" And Related Hypotheses," The Review of Economics and Statistics, MIT Press, vol. 80(3), pages 454-465, August.
    22. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    23. Mustafa U. Karakaplan & Levent Kutlu, 2017. "Endogeneity in panel stochastic frontier models: an application to the Japanese cotton spinning industry," Applied Economics, Taylor & Francis Journals, vol. 49(59), pages 5935-5939, December.
    24. Brissimis, Sophocles N. & Delis, Manthos D. & Tsionas, Efthymios G., 2010. "Technical and allocative efficiency in European banking," European Journal of Operational Research, Elsevier, vol. 204(1), pages 153-163, July.
    25. Bos, J.W.B. & Koetter, M. & Kolari, J.W. & Kool, C.J.M., 2009. "Effects of heterogeneity on bank efficiency scores," European Journal of Operational Research, Elsevier, vol. 195(1), pages 251-261, May.
    26. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    27. Ryan Mutter & William Greene & William Spector & Michael Rosko & Dana Mukamel, 2013. "Investigating the impact of endogeneity on inefficiency estimates in the application of stochastic frontier analysis to nursing homes," Journal of Productivity Analysis, Springer, vol. 39(2), pages 101-110, April.
    28. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.
    29. Wolfgang Keller, 2004. "International Technology Diffusion," Journal of Economic Literature, American Economic Association, vol. 42(3), pages 752-782, September.
    30. Tran, Kien C. & Tsionas, Efthymios G., 2013. "GMM estimation of stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 118(1), pages 233-236.
    31. Bresnahan, Timothy F., 1989. "Empirical studies of industries with market power," Handbook of Industrial Organization, in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 2, chapter 17, pages 1011-1057, Elsevier.
    32. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    33. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    34. William H. Greene & Lynda Khalaf & Robin Sickles & Michael Veall & Marcel-Cristian Voia (ed.), 2016. "Productivity and Efficiency Analysis," Springer Proceedings in Business and Economics, Springer, edition 1, number 978-3-319-23228-7, June.
    35. Jaepil Han & Deockhyun Ryu & Robin C. Sickles, 2016. "Spillover Effects of Public Capital Stock Using Spatial Frontier Analyses: A First Look at the Data," Springer Proceedings in Business and Economics, in: William H. Greene & Lynda Khalaf & Robin Sickles & Michael Veall & Marcel-Cristian Voia (ed.), Productivity and Efficiency Analysis, edition 1, chapter 0, pages 83-97, Springer.
    36. 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.
    37. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.
    38. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2019. "A time-varying true individual effects model with endogenous regressors," Journal of Econometrics, Elsevier, vol. 211(2), pages 539-559.
    39. 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.
    40. Tran, Kien C. & Tsionas, Efthymios G., 2015. "Endogeneity in stochastic frontier models: Copula approach without external instruments," Economics Letters, Elsevier, vol. 133(C), pages 85-88.
    41. Michael Koetter & James W. Kolari & Laura Spierdijk, 2012. "Enjoying the Quiet Life under Deregulation? Evidence from Adjusted Lerner Indices for U.S. Banks," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 462-480, May.
    42. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    43. Glass, Anthony J. & Kenjegalieva, Karligash, 2019. "A spatial productivity index in the presence of efficiency spillovers: Evidence for U.S. banks, 1992–2015," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1165-1179.
    44. Kutlu, Levent, 2018. "A distribution-free stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 163(C), pages 152-154.
    45. Albert G. Z. Hu & Gary H. Jefferson & Qian Jinchang, 2005. "R&D and Technology Transfer: Firm-Level Evidence from Chinese Industry," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 780-786, November.
    46. Kutlu, Levent, 2012. "US banking efficiency, 1984–1995," Economics Letters, Elsevier, vol. 117(1), pages 53-56.
    47. Kutlu, Levent, 2010. "Battese-coelli estimator with endogenous regressors," Economics Letters, Elsevier, vol. 109(2), pages 79-81, November.
    48. 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.
    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. Levent Kutlu, 2022. "Spatial stochastic frontier model with endogenous weighting matrix," Empirical Economics, Springer, vol. 63(4), pages 1947-1968, October.
    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. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    4. Hou, Zhezhi & Zhao, Shunan & Kumbhakar, Subal C., 2023. "The GMM estimation of semiparametric spatial stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1450-1464.
    5. M.V. Leonov, 2021. "Review of Modern Approaches for Assessing the Effectiveness of Banking," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 294-326.
    6. Lamees Al-Durgham & Mohammad Adeinat, 2020. "Efficiency of Listed Manufacturing Firms in Jordan: A Stochastic Frontier Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 5-9.
    7. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    8. Anthony J. Glass & Karligash Kenjegalieva, 2023. "Dynamic returns to scale and geography in U.S. banking," Papers in Regional Science, Wiley Blackwell, vol. 102(1), pages 53-85, February.
    9. Tran, Kien C. & Tsionas, Mike G. & Prokhorov, Artem B., 2023. "Semiparametric estimation of spatial autoregressive smooth-coefficient panel stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1189-1199.
    10. Mustafa U. Karakaplan & Levent Kutlu & Mike G. Tsionas, 2020. "A solution to log of dependent variables with negative observations," Journal of Productivity Analysis, Springer, vol. 54(2), pages 107-119, December.
    11. Wang, Luojia & Du, Kerui & Shao, Shuai, 2024. "Transportation infrastructure and carbon emissions: New evidence with spatial spillover and endogeneity," Energy, Elsevier, vol. 297(C).
    12. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
    13. 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".
    14. Kutlu, Levent, 2023. "Calculating efficiency for spatial autoregressive stochastic frontier model," Economics Letters, Elsevier, vol. 225(C).
    15. Hung-pin Lai & Kien C. Tran, 2022. "Persistent and transient inefficiency in a spatial autoregressive panel stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 58(1), pages 1-13, August.
    16. Li, Mingyang & Jin, Man & Kumbhakar, Subal C., 2022. "Do subsidies increase firm productivity? Evidence from Chinese manufacturing enterprises," European Journal of Operational Research, Elsevier, vol. 303(1), pages 388-400.
    17. E. Fusco & R. Benedetti & F. Vidoli, 2023. "Stochastic frontier estimation through parametric modelling of quantile regression coefficients," Empirical Economics, Springer, vol. 64(2), pages 869-896, February.
    18. Vidoli, Francesco & Auteri, Monica & Marinuzzi, Giorgia & Tortorella, Walter, 2023. "Spatial interdependence in cost efficiency and local government optimal size: The case of Italian municipalities," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    19. Hou, Zheng & Roseta-Palma, Catarina & Ramalho, Joaquim J.S., 2024. "Can operational efficiency in the Portuguese electricity sector be improved? Yes, but..," Energy Policy, Elsevier, vol. 190(C).
    20. Carmelo Algeri & Luc Anselin & Antonio Fabio Forgione & Carlo Migliardo, 2022. "Spatial dependence in the technical efficiency of local banks," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 685-716, June.
    21. D’Inverno, Giovanna & Vidoli, Francesco & De Witte, Kristof, 2023. "Sustainable budgeting and financial balance: Which lever will you pull?," European Journal of Operational Research, Elsevier, vol. 309(2), pages 857-871.
    22. Kerui Du & Luis Orea & Inmaculada C. Álvarez, 2024. "Fitting spatial stochastic frontier models in Stata," Stata Journal, StataCorp LP, vol. 24(3), pages 402-426, September.
    23. Emir Malikov & Jingfang Zhang & Shunan Zhao & Subal C. Kumbhakar, 2023. "Accounting for Cross-Location Technological Heterogeneity in the Measurement of Operations Efficiency and Productivity," Papers 2302.13430, arXiv.org.

    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. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2019. "A time-varying true individual effects model with endogenous regressors," Journal of Econometrics, Elsevier, vol. 211(2), pages 539-559.
    2. Levent Kutlu, 2022. "Spatial stochastic frontier model with endogenous weighting matrix," Empirical Economics, Springer, vol. 63(4), pages 1947-1968, October.
    3. Mustafa U. Karakaplan & Levent Kutlu, 2019. "Estimating market power using a composed error model," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(4), pages 489-510, September.
    4. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
    5. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.
    6. 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.
    7. Kutlu, Levent & Nair-Reichert, Usha, 2022. "Executive compensation and the potential for additional efficiency gains: Evidence from the Indian manufacturing sector," Economic Modelling, Elsevier, vol. 114(C).
    8. Tran, Kien C. & Tsionas, Mike G. & Prokhorov, Artem B., 2023. "Semiparametric estimation of spatial autoregressive smooth-coefficient panel stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1189-1199.
    9. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    10. Dibyendu Maiti & Chiranjib Neogi, 2024. "Endogeneity-corrected stochastic frontier with market imperfections," Empirical Economics, Springer, vol. 67(3), pages 1149-1183, September.
    11. Mustafa U. Karakaplan & Levent Kutlu & Mike G. Tsionas, 2020. "A solution to log of dependent variables with negative observations," Journal of Productivity Analysis, Springer, vol. 54(2), pages 107-119, December.
    12. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    13. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    14. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2020. "Socio-institutional determinants of educational resource efficiency according to the capability approach: An endogenous stochastic frontier analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    15. 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.
    16. Kutlu, Levent, 2018. "A distribution-free stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 163(C), pages 152-154.
    17. Levent Kutlu & Kien C. Tran & Mike G. Tsionas, 2020. "Unknown latent structure and inefficiency in panel stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 54(1), pages 75-86, August.
    18. Kutlu, Levent, 2018. "Estimating efficiency in a spatial autoregressive stochastic frontier model," Economics Letters, Elsevier, vol. 163(C), pages 155-157.
    19. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    20. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.

    More about this item

    Keywords

    Productivity and competitiveness; Chinese chemical firms; Endogeneity; Spatial autoregressive spillover; Stochastic frontier;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    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:ejores:v:286:y:2020:i:1:p:389-399. 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/eor .

    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.