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July  2011, 7(3): 573-592. doi: 10.3934/jimo.2011.7.573

A three-stage DEA-SFA efficiency analysis of labour-owned and mercantile firms

1. 

Escuela de Administración y Contaduría Pública, Facultad de Ciencias Económicas, Universidad Nacional de Colombia, Carrera 30 No 45-03, Edificio 311 Oficina 305, Bogotá, Colombia

2. 

Emeritus Professor, University of New Brunswick, Canada

3. 

Departamento de Gestión de Empresas, Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona, Navarra, Spain

Received  November 2008 Revised  May 2011 Published  June 2011

This paper undertakes a three-stage DEA-SFA (Data Envelopment Analysis / Stochastic Frontier Analysis) efficiency analysis of labour-owned (LOF) and mercantile (PCF) firms to assess whether variations in the productive efficiency and in the total factor productivity of LOFs and PCFs are explainable by differences in their capital-ownership configuration. The model first purges, from each firm's performance, the impact of statistical noise and of environmental factors and yields increasing average efficiency estimates of the firms under study. Then, it tests the hypothesis that the average firm, be it LOF or PCF, is equally efficient and exhibits comparable levels of productivity growth. The evidence presented supports the proposition that differences in the capital-ownership configuration do not play a very significant role in their performance efficiency or in their productivity growth and whatever productivity growth occurs is attributable largely to innovation rather than to catching up to the efficient firms.
Citation: Zuray Melgarejo, Francisco J. Arcelus, Katrin Simon-Elorz. A three-stage DEA-SFA efficiency analysis of labour-owned and mercantile firms. Journal of Industrial and Management Optimization, 2011, 7 (3) : 573-592. doi: 10.3934/jimo.2011.7.573
References:
[1]

Z. J. Acs and J. E. Amorós, Entrepreneurship and competitiveness dynamics in Latin America, Small Business Economics, 31 (2008), 305-322. doi: 10.1007/s11187-008-9133-y.

[2]

G. Ahuja and S. K. Majumdar, An assessment of the performance of Indian state-owned enterprises, Journal of Productivity Analysis, 9 (1998), 113-132. doi: 10.1023/A:1018352415813.

[3]

J. M. Arauzo-Carod and A. Segarra-Blasco, The determinants of entry are not independent of start-up size: Some evidence from Spanish manufacturing, Review of Industrial Organization, 27 (2005), 147-165. doi: 10.1007/s11151-005-8321-z.

[4]

F. J. Arcelus and P. Arocena, Measuring sectoral productivity across time and across countries, European Journal of Operational Research, 119 (1999), 254-266. doi: 10.1016/S0377-2217(99)00129-0.

[5]

F. J. Arcelus and P. Arocena, Convergence and productive efficiency in OECD countries: A non parametric frontier approach, International Journal of Production Economics, 66 (2000), 105-117. doi: 10.1016/S0925-5273(99)00116-4.

[6]

J. M. Argilés and E. J. Slof, The use of financial accounting information and firm performance: An empirical quantification for farms, Accounting and Business Research, 33 (2003), 251-273.

[7]

N. K. Avkiran and T. Rowlands, How to better identify the true managerial performance: State of the art using DEA, Omega, 36 (2008), 317-324. doi: 10.1016/j.omega.2006.01.002.

[8]

R. D. Banker, A. Charnes and W. W. Cooper, Some models for estimating technical and scale inefficiency in data envelopment analysis, Management Science, 30 (1984), 1078-1092. doi: 10.1287/mnsc.30.9.1078.

[9]

R. D. Banker and R. Morey, Efficiency analysis for exogenously fixed inputs and outputs, Operations Research, 34 (1986), 513-521. doi: 10.1287/opre.34.4.513.

[10]

W. J. Baumol, Entrepreneurial enterprises, large established firms and other components of the free-market growth machine, Small Business Economics, 23 (2004), 9-21. doi: 10.1023/B:SBEJ.0000026057.47641.a6.

[11]

G. E. Batesse and T. J. Coelli, Frontier production function, technical efficiency and panel data: With application to paddy farmers in India, Journal of Productivity Analysis, 3 (1992), 153-169. doi: 10.1007/BF00158774.

[12]

J. L. T. Blank and V. Valdmanis, A modified three-stage data envelopment analysis, European Journal of Health Economics, 6 (2005), 65-72. doi: 10.1007/s10198-004-0260-3.

[13]

A. N. Bojanic, S. B. Caudill and J. M. Ford, Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroskedasticity, European Journal of Operational Research, 108 (1998), 140-147. doi: 10.1016/S0377-2217(97)00101-X.

[14]

M. Callejón and A. Segarra, Business dynamics and efficiency in industries and regions: The case of Spain, Small Business Economics, 1 (1999), 253-271.

[15]

J. L. Calvo, Testing Gibrat's law for small, young and innovating firms, Small Business Economics, 26 (2006), 117-123. doi: 10.1007/s11187-004-2135-5.

[16]

S. B. Caudill and J. M. Ford, Biases in frontier estimation due to heteroskedasticity, Economics Letters, 4 (1993), 17-20. doi: 10.1016/0165-1765(93)90104-K.

[17]

S. B. Caudill, J. M. Ford and D. Gropper, Frontier estimation and firm-specific inefficiency measures in the presence of heteroskedasticity, Journal of Business & Economic Statistics, 13 (1995), 105-111. doi: 10.2307/1392525.

[18]

Y. Chen, L. Liang and J. Zhou, Equivalence in two-stage DEA approaches, European Journal of Operational Research, 193 (2009), 600-604. doi: 10.1016/j.ejor.2007.11.040.

[19]

T. J. Coelli, "A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program,", CEPA WP8, (). 

[20]

T. J. Coelli, D. S. P. Rao, C. J. O'Donnell and G. E. Batesse, "An Introduction to Efficiency and Productivity Analysis," Springer-Verlag, New York, 2005.

[21]

J. M. Cordero-Ferrera, F. Pedraja-Chaparro and J. Salinas-Jiménez, Measuring efficiency in education: An analysis of different approaches for incorporating non-discretionary inputs, Applied Economics, 40 (2008), 1323-1339. doi: 10.1080/00036840600771346.

[22]

M. A. Díaz, R. Sánchez, Firm size and productivity in Spain: A stochastic frontier analysis, Small Business Economics, 30 (2008), 315-323. doi: 10.1007/s11187-007-9058-x.

[23]

C. Doucouliagos, The comparative efficiency and productivity of labor-managed and capital-managed firms, Review of Radical Political Economics, 29 (1997), 45-69. doi: 10.1177/048661349702900203.

[24]

G. Dow, "Governing the Firm: Worker's Control in Theory and in Practice," Cambridge University Press, Cambridge, 2003.

[25]

R. Färe, S. Grosskopf, B. Lindgren and P. Roos, Productivity developments in Swedish hospitals; A Malmquist output index approach, in "Data Envelopment Analysis: Theory, Methodology and Applications" (eds. A. Charnes, W. W. Cooper, A. Y. Lewin and L. M. Seiford), Kluwer Academic Publishers, Boston, 1994.

[26]

R. Färe, S. Grosskopf and C. A. K. Lovell, "Production Frontiers," Cambridge University Press, Cambridge, 1994.

[27]

M. J. Farrell, The measurement of productive efficiency, Journal of the Royal Statistical Society, Series A, General, 120 (1957), 253-282. doi: 10.2307/2343100.

[28]

M. Fritsch, U. Brixy and O. Falk, The effect of industry, region and time on new business survival - A multidimensional analysis, Review of Industrial Organization, 28 (2006), 285-306. doi: 10.1007/s11151-006-0018-4.

[29]

H. O. Fried, C. A. K. Lovell, S. Schmidt and S. Yaisawarng, Accounting for environmental effects and statistical noise in data envelopment analysis, Journal of Productivity Analysis, 17 (2002), 157-174. doi: 10.1023/A:1013548723393.

[30]

H. O. Fried, S. S. Schmidt and S. Yaisawarng, Incorporating the operating environment into a nonparametric measure of technical efficiency, Journal of Productivity Analysis, 17 (1999), 249-267. doi: 10.1023/A:1007800306752.

[31]

F. C. Fu, C. P. C. Vijverberg and Y. S. Chen, Productivity and efficiency of state-owned enterprises in China, Journal of Productivity Analysis, 29 (2008), 249-259. doi: 10.1007/s11123-007-0078-y.

[32]

T. García-Marco and M. D. Robles-Fernández, Risk-taking behavior and ownership in the banking industry: The Spanish evidence, Journal of Business and Economics, 60 (2008), 332-354. doi: 10.1016/j.jeconbus.2007.04.008.

[33]

W. H. Greene, Maximum likelihood estimation of econometric frontier functions, Journal of Econometric, 13 (1980), 26-57. doi: 10.1016/0304-4076(80)90041-X.

[34]

W. H. Greene, "Econometric Analysis," 6th edition, Prentice-Halle, New York, 2008.

[35]

W. H. Greene, "LIMDEP, Version 9.0 - Econometric Modeling Guide," Econometric Software, New York, 2007.

[36]

J. F. Hair, B. Black, B. Babin, R. E. Anderson and R. L. Tatham, "Multivariate Analysis," Prentice-Halle, New York, 2006.

[37]

J. A. Hausman, Specification tests in econometrics, Econometrica, 46 (1978), 1251-1271. doi: 10.2307/1913827.

[38]

J. Hekcman, Sample selection bias as a specification error, Econometrica, 47 (1979), 153-161. doi: 10.2307/1912352.

[39]

E. Huerta, La economía navarra: ¿por qué es importante la productividad? Diario de Noticias, 5 (2007), November 13.

[40]

S. Jansson, Swedish labour-owned industrial firms, Annals of Public and Cooperative Economics, 57 (1986), 103-116. doi: 10.1111/j.1467-8292.1986.tb01934.x.

[41]

J. Y. Lee, Application of the three-stage DEA in measuring efficiency - an empirical evidence, Applied Economics Letters, 15 (2008), 49-52. doi: 10.1080/13504850600675435.

[42]

C.-C. Liu, Evaluating the operational efficiency of major ports in the Asian-Pacific region using data envelopment analysis, Applied Economics, 40 (2008), 1737-1743. doi: 10.1080/00036840600905126.

[43]

F.-H. F. Liu and P.-H. Wang, DEA Malmquist productivity measure: Taiwanese semiconductor companies, International Journal of Production Economics, 112 (2008), 367-379. doi: 10.1016/j.ijpe.2007.03.015.

[44]

O. W. Maletta and V. Sena, Is competition really bad for cooperatives? Some empirical evidence for Italian producers' cooperatives, Journal of Productivity Analysis, 29 (2008), 221-233.

[45]

B. B. Margari, F. Erbetta, C. Petraglia and M. Piacenza, Regulatory and environmental effects on public transit efficiency: A mixed DEA-SFA approach, Journal of Regulatory Economics, 32 (2007), 131-151. doi: 10.1007/s11149-007-9025-0.

[46]

Z. Melgarejo, F. J. Arcelus and K. Simon, Type of ownership and the creation of new enterprises in Navarre, Spain: Differences in financial survival, International Journal of Technology, Policy and Management, 7 (2007), 225-244. doi: 10.1504/IJTPM.2007.015108.

[47]

M. Muñiz, Separating managerial inefficiency and external conditions in data, European Journal of Operational Research, 143 (2002), 625-643. doi: 10.1016/S0377-2217(01)00344-7.

[48]

W. Nasierowski and F. J. Arcelus, On the efficiency of national innovation systems, Socio-Economic Planning Sciences, 37 (2003), 215-234. doi: 10.1016/S0038-0121(02)00046-0.

[49]

W. K. Newey and K. D. West, A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica, 55 (1987), 703-708. doi: 10.2307/1913610.

[50]

S. J. Nickell, Competition and corporate performance, Journal of Political Economy, 104 (1996), 724-745. doi: 10.1086/262040.

[51]

M. Núñez-Nickel and J. Moyano-Fuentes, Ownership structure of cooperatives as an environmental buffer, Journal of Management Studies, 41 (2004), 1131-1152. doi: 10.1111/j.1467-6486.2004.00469.x.

[52]

R. Park, D. Kruse and J. Sesil, Does employment ownership enhance firm survival?, in "Employee Participation, Firm Performance and Survival" (eds. V. Pérotin and A. Robinson), 3, Advances in Economic Analysis of Participatory and Labor-Managed Firms, JAI Press, Greenwich, CT, 2004.

[53]

S. Rho and J. An, Evaluating the efficiency of a two-stage production process using data envelopment analysis, International Transactions in Operations Research, 14 (2007), 395-410. doi: 10.1111/j.1475-3995.2007.00597.x.

[54]

J. Ruggiero, Non-discretionary inputs in data envelopment analysis, European Journal of Operational Research, 111 (1998), 461-469. doi: 10.1016/S0377-2217(97)00306-8.

[55]

J. M. Sarriegui, El reto de la pequeña empresa, El País, 30 (2006), October 12.

[56]

J.-K. Shang, W.-T. Hung and F.-C. Wang, "Service Outsourcing and Hotel Performance: Three-Stage Dea Analysis," Applied Economics Letters, 2008. doi: 10.1080/13504850600993523.

[57]

J.-K. Shang, W.-T. Hung and F.-C. Wang, Ecommerce and hotel performance: Three-stage DEA analysis, The Service Industries Journal, 28 (2008), 529-540. doi: 10.1080/02642060801917679.

[58]

R. W. Shephard, "Theory of Cost and Production Functions," Princeton Studies in Mathematical Economics, 4, Princeton University Press, Princeton, 1970.

[59]

H. A. Simon and C. P. Bonini, The size distribution of business firms, American Economic Review, 58 (1958), 607-617.

[60]

J. Surroca, M. A. García-Cestona and L. L. Santamaría, Corporate governance and the Mondragón cooperatives, Management Research, 4 (2006), 99-112. doi: 10.2753/JMR1536-5433040202.

[61]

E. Taymaz, Are small firms really less productive?, Small Business Economics, 25 (2005), 429-445. doi: 10.1007/s11187-004-6492-x.

[62]

H. Tulkens and P. V. Vanden Eeckaut, Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects, European Journal of Operational Research, 80 (1995), 474-499. doi: 10.1016/0377-2217(94)00132-V.

[63]

H. White, A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity, Econometrica, 48 (1980), 817-838. doi: 10.2307/1912934.

[64]

R. Yaffee, "Primer for Panel Data Analysis,", Available from: \url{http://www.nyu.edu/its/statistics/Docs/pda.pdf}., 2005 (). 

show all references

References:
[1]

Z. J. Acs and J. E. Amorós, Entrepreneurship and competitiveness dynamics in Latin America, Small Business Economics, 31 (2008), 305-322. doi: 10.1007/s11187-008-9133-y.

[2]

G. Ahuja and S. K. Majumdar, An assessment of the performance of Indian state-owned enterprises, Journal of Productivity Analysis, 9 (1998), 113-132. doi: 10.1023/A:1018352415813.

[3]

J. M. Arauzo-Carod and A. Segarra-Blasco, The determinants of entry are not independent of start-up size: Some evidence from Spanish manufacturing, Review of Industrial Organization, 27 (2005), 147-165. doi: 10.1007/s11151-005-8321-z.

[4]

F. J. Arcelus and P. Arocena, Measuring sectoral productivity across time and across countries, European Journal of Operational Research, 119 (1999), 254-266. doi: 10.1016/S0377-2217(99)00129-0.

[5]

F. J. Arcelus and P. Arocena, Convergence and productive efficiency in OECD countries: A non parametric frontier approach, International Journal of Production Economics, 66 (2000), 105-117. doi: 10.1016/S0925-5273(99)00116-4.

[6]

J. M. Argilés and E. J. Slof, The use of financial accounting information and firm performance: An empirical quantification for farms, Accounting and Business Research, 33 (2003), 251-273.

[7]

N. K. Avkiran and T. Rowlands, How to better identify the true managerial performance: State of the art using DEA, Omega, 36 (2008), 317-324. doi: 10.1016/j.omega.2006.01.002.

[8]

R. D. Banker, A. Charnes and W. W. Cooper, Some models for estimating technical and scale inefficiency in data envelopment analysis, Management Science, 30 (1984), 1078-1092. doi: 10.1287/mnsc.30.9.1078.

[9]

R. D. Banker and R. Morey, Efficiency analysis for exogenously fixed inputs and outputs, Operations Research, 34 (1986), 513-521. doi: 10.1287/opre.34.4.513.

[10]

W. J. Baumol, Entrepreneurial enterprises, large established firms and other components of the free-market growth machine, Small Business Economics, 23 (2004), 9-21. doi: 10.1023/B:SBEJ.0000026057.47641.a6.

[11]

G. E. Batesse and T. J. Coelli, Frontier production function, technical efficiency and panel data: With application to paddy farmers in India, Journal of Productivity Analysis, 3 (1992), 153-169. doi: 10.1007/BF00158774.

[12]

J. L. T. Blank and V. Valdmanis, A modified three-stage data envelopment analysis, European Journal of Health Economics, 6 (2005), 65-72. doi: 10.1007/s10198-004-0260-3.

[13]

A. N. Bojanic, S. B. Caudill and J. M. Ford, Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroskedasticity, European Journal of Operational Research, 108 (1998), 140-147. doi: 10.1016/S0377-2217(97)00101-X.

[14]

M. Callejón and A. Segarra, Business dynamics and efficiency in industries and regions: The case of Spain, Small Business Economics, 1 (1999), 253-271.

[15]

J. L. Calvo, Testing Gibrat's law for small, young and innovating firms, Small Business Economics, 26 (2006), 117-123. doi: 10.1007/s11187-004-2135-5.

[16]

S. B. Caudill and J. M. Ford, Biases in frontier estimation due to heteroskedasticity, Economics Letters, 4 (1993), 17-20. doi: 10.1016/0165-1765(93)90104-K.

[17]

S. B. Caudill, J. M. Ford and D. Gropper, Frontier estimation and firm-specific inefficiency measures in the presence of heteroskedasticity, Journal of Business & Economic Statistics, 13 (1995), 105-111. doi: 10.2307/1392525.

[18]

Y. Chen, L. Liang and J. Zhou, Equivalence in two-stage DEA approaches, European Journal of Operational Research, 193 (2009), 600-604. doi: 10.1016/j.ejor.2007.11.040.

[19]

T. J. Coelli, "A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program,", CEPA WP8, (). 

[20]

T. J. Coelli, D. S. P. Rao, C. J. O'Donnell and G. E. Batesse, "An Introduction to Efficiency and Productivity Analysis," Springer-Verlag, New York, 2005.

[21]

J. M. Cordero-Ferrera, F. Pedraja-Chaparro and J. Salinas-Jiménez, Measuring efficiency in education: An analysis of different approaches for incorporating non-discretionary inputs, Applied Economics, 40 (2008), 1323-1339. doi: 10.1080/00036840600771346.

[22]

M. A. Díaz, R. Sánchez, Firm size and productivity in Spain: A stochastic frontier analysis, Small Business Economics, 30 (2008), 315-323. doi: 10.1007/s11187-007-9058-x.

[23]

C. Doucouliagos, The comparative efficiency and productivity of labor-managed and capital-managed firms, Review of Radical Political Economics, 29 (1997), 45-69. doi: 10.1177/048661349702900203.

[24]

G. Dow, "Governing the Firm: Worker's Control in Theory and in Practice," Cambridge University Press, Cambridge, 2003.

[25]

R. Färe, S. Grosskopf, B. Lindgren and P. Roos, Productivity developments in Swedish hospitals; A Malmquist output index approach, in "Data Envelopment Analysis: Theory, Methodology and Applications" (eds. A. Charnes, W. W. Cooper, A. Y. Lewin and L. M. Seiford), Kluwer Academic Publishers, Boston, 1994.

[26]

R. Färe, S. Grosskopf and C. A. K. Lovell, "Production Frontiers," Cambridge University Press, Cambridge, 1994.

[27]

M. J. Farrell, The measurement of productive efficiency, Journal of the Royal Statistical Society, Series A, General, 120 (1957), 253-282. doi: 10.2307/2343100.

[28]

M. Fritsch, U. Brixy and O. Falk, The effect of industry, region and time on new business survival - A multidimensional analysis, Review of Industrial Organization, 28 (2006), 285-306. doi: 10.1007/s11151-006-0018-4.

[29]

H. O. Fried, C. A. K. Lovell, S. Schmidt and S. Yaisawarng, Accounting for environmental effects and statistical noise in data envelopment analysis, Journal of Productivity Analysis, 17 (2002), 157-174. doi: 10.1023/A:1013548723393.

[30]

H. O. Fried, S. S. Schmidt and S. Yaisawarng, Incorporating the operating environment into a nonparametric measure of technical efficiency, Journal of Productivity Analysis, 17 (1999), 249-267. doi: 10.1023/A:1007800306752.

[31]

F. C. Fu, C. P. C. Vijverberg and Y. S. Chen, Productivity and efficiency of state-owned enterprises in China, Journal of Productivity Analysis, 29 (2008), 249-259. doi: 10.1007/s11123-007-0078-y.

[32]

T. García-Marco and M. D. Robles-Fernández, Risk-taking behavior and ownership in the banking industry: The Spanish evidence, Journal of Business and Economics, 60 (2008), 332-354. doi: 10.1016/j.jeconbus.2007.04.008.

[33]

W. H. Greene, Maximum likelihood estimation of econometric frontier functions, Journal of Econometric, 13 (1980), 26-57. doi: 10.1016/0304-4076(80)90041-X.

[34]

W. H. Greene, "Econometric Analysis," 6th edition, Prentice-Halle, New York, 2008.

[35]

W. H. Greene, "LIMDEP, Version 9.0 - Econometric Modeling Guide," Econometric Software, New York, 2007.

[36]

J. F. Hair, B. Black, B. Babin, R. E. Anderson and R. L. Tatham, "Multivariate Analysis," Prentice-Halle, New York, 2006.

[37]

J. A. Hausman, Specification tests in econometrics, Econometrica, 46 (1978), 1251-1271. doi: 10.2307/1913827.

[38]

J. Hekcman, Sample selection bias as a specification error, Econometrica, 47 (1979), 153-161. doi: 10.2307/1912352.

[39]

E. Huerta, La economía navarra: ¿por qué es importante la productividad? Diario de Noticias, 5 (2007), November 13.

[40]

S. Jansson, Swedish labour-owned industrial firms, Annals of Public and Cooperative Economics, 57 (1986), 103-116. doi: 10.1111/j.1467-8292.1986.tb01934.x.

[41]

J. Y. Lee, Application of the three-stage DEA in measuring efficiency - an empirical evidence, Applied Economics Letters, 15 (2008), 49-52. doi: 10.1080/13504850600675435.

[42]

C.-C. Liu, Evaluating the operational efficiency of major ports in the Asian-Pacific region using data envelopment analysis, Applied Economics, 40 (2008), 1737-1743. doi: 10.1080/00036840600905126.

[43]

F.-H. F. Liu and P.-H. Wang, DEA Malmquist productivity measure: Taiwanese semiconductor companies, International Journal of Production Economics, 112 (2008), 367-379. doi: 10.1016/j.ijpe.2007.03.015.

[44]

O. W. Maletta and V. Sena, Is competition really bad for cooperatives? Some empirical evidence for Italian producers' cooperatives, Journal of Productivity Analysis, 29 (2008), 221-233.

[45]

B. B. Margari, F. Erbetta, C. Petraglia and M. Piacenza, Regulatory and environmental effects on public transit efficiency: A mixed DEA-SFA approach, Journal of Regulatory Economics, 32 (2007), 131-151. doi: 10.1007/s11149-007-9025-0.

[46]

Z. Melgarejo, F. J. Arcelus and K. Simon, Type of ownership and the creation of new enterprises in Navarre, Spain: Differences in financial survival, International Journal of Technology, Policy and Management, 7 (2007), 225-244. doi: 10.1504/IJTPM.2007.015108.

[47]

M. Muñiz, Separating managerial inefficiency and external conditions in data, European Journal of Operational Research, 143 (2002), 625-643. doi: 10.1016/S0377-2217(01)00344-7.

[48]

W. Nasierowski and F. J. Arcelus, On the efficiency of national innovation systems, Socio-Economic Planning Sciences, 37 (2003), 215-234. doi: 10.1016/S0038-0121(02)00046-0.

[49]

W. K. Newey and K. D. West, A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica, 55 (1987), 703-708. doi: 10.2307/1913610.

[50]

S. J. Nickell, Competition and corporate performance, Journal of Political Economy, 104 (1996), 724-745. doi: 10.1086/262040.

[51]

M. Núñez-Nickel and J. Moyano-Fuentes, Ownership structure of cooperatives as an environmental buffer, Journal of Management Studies, 41 (2004), 1131-1152. doi: 10.1111/j.1467-6486.2004.00469.x.

[52]

R. Park, D. Kruse and J. Sesil, Does employment ownership enhance firm survival?, in "Employee Participation, Firm Performance and Survival" (eds. V. Pérotin and A. Robinson), 3, Advances in Economic Analysis of Participatory and Labor-Managed Firms, JAI Press, Greenwich, CT, 2004.

[53]

S. Rho and J. An, Evaluating the efficiency of a two-stage production process using data envelopment analysis, International Transactions in Operations Research, 14 (2007), 395-410. doi: 10.1111/j.1475-3995.2007.00597.x.

[54]

J. Ruggiero, Non-discretionary inputs in data envelopment analysis, European Journal of Operational Research, 111 (1998), 461-469. doi: 10.1016/S0377-2217(97)00306-8.

[55]

J. M. Sarriegui, El reto de la pequeña empresa, El País, 30 (2006), October 12.

[56]

J.-K. Shang, W.-T. Hung and F.-C. Wang, "Service Outsourcing and Hotel Performance: Three-Stage Dea Analysis," Applied Economics Letters, 2008. doi: 10.1080/13504850600993523.

[57]

J.-K. Shang, W.-T. Hung and F.-C. Wang, Ecommerce and hotel performance: Three-stage DEA analysis, The Service Industries Journal, 28 (2008), 529-540. doi: 10.1080/02642060801917679.

[58]

R. W. Shephard, "Theory of Cost and Production Functions," Princeton Studies in Mathematical Economics, 4, Princeton University Press, Princeton, 1970.

[59]

H. A. Simon and C. P. Bonini, The size distribution of business firms, American Economic Review, 58 (1958), 607-617.

[60]

J. Surroca, M. A. García-Cestona and L. L. Santamaría, Corporate governance and the Mondragón cooperatives, Management Research, 4 (2006), 99-112. doi: 10.2753/JMR1536-5433040202.

[61]

E. Taymaz, Are small firms really less productive?, Small Business Economics, 25 (2005), 429-445. doi: 10.1007/s11187-004-6492-x.

[62]

H. Tulkens and P. V. Vanden Eeckaut, Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects, European Journal of Operational Research, 80 (1995), 474-499. doi: 10.1016/0377-2217(94)00132-V.

[63]

H. White, A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity, Econometrica, 48 (1980), 817-838. doi: 10.2307/1912934.

[64]

R. Yaffee, "Primer for Panel Data Analysis,", Available from: \url{http://www.nyu.edu/its/statistics/Docs/pda.pdf}., 2005 (). 

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