939
Views
6
CrossRef citations to date
0
Altmetric
Articles

Dynamics of the total factor productivity in Lithuanian family farms with a statistical inference: the bootstrapped Malmquist indices and Multiple Correspondence Analysis

&
Pages 643-664 | Received 05 Nov 2013, Accepted 04 Feb 2016, Published online: 30 Jun 2016

References

  • Abdi, H. & Valentin, D. (2007). Multiple correspondence analysis. In N. Salkind (Ed.), Encyclopedia of Measurement and Statistics (pp. 651–657). Thousand Oaks: Sage.
  • Arjomandi, A., Valadkhani, A., & Harvie, C. (2011). Analysing productivity changes using the bootstrapped Malmquist approach: The case of the Iranian banking industry. Australasian Accounting Business and Finance Journal, 5, 35–56.
  • Balcombe, K., Davidova, S., & Latruffe, L. (2008). The use of bootstrapped Malmquist indices to reassess productivity change findings: An application to a sample of Polish farms. Applied Economics, 40, 2055–2061.10.1080/00036840600949264
  • Baležentis, T., Kriščiukaitienė, I., & Baležentis, A. (2014). A nonparametric analysis of the determinants of family farm efficiency dynamics in Lithuania. Agricultural Economics, 45, 589–599.10.1111/agec.2014.45.issue-5
  • Bogetoft, P., & Otto, L. (2011). Benchmarking with DEA, SFA, and R. Heidelberg: Springer.10.1007/978-1-4419-7961-2
  • Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50, 1393–1414.10.2307/1913388
  • Coelli, T. J., Rao, D. S. P., O’Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis. New York, NY: Springer.
  • Essid, H., Ouellette, P., & Vigeant, S. (2014). Productivity, efficiency, and technical change of Tunisian schools: A bootstrapped Malmquist approach with quasi-fixed inputs. Omega, 42, 88–97.10.1016/j.omega.2013.04.001
  • Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity changes in Swedish pharamacies 1980–1989: A non-parametric Malmquist approach. Journal of Productivity Analysis, 3, 85–101.10.1007/BF00158770
  • Färe, R., Grosskopf, S., & Margaritis, D. (2008). Efficiency and productivity: Malmquist and more. In Harold O. Fried (Ed.), The Measurement of Productive Efficiency and Productivity Change (pp. 522–622). Oxford: Oxford University Press.10.1093/acprof:oso/9780195183528.001.0001
  • Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 84, 66–83.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series A (General), 120, 253–290.10.2307/2343100
  • Fried, H. O., Lovell, C. A. K., & Schmidt, S. S. (2008). Efficiency and productivity. In: The Measurement of Productive Efficiency and Productivity Change (pp. 3–91). Oxford: Oxford University Press.10.1093/acprof:oso/9780195183528.001.0001
  • Gorton, M., & Davidova, S. (2004). Farm productivity and efficiency in the CEE applicant countries: A synthesis of results. Agricultural Economics, 30(1), 1–16.10.1111/agec.2004.30.issue-1
  • Hoff, A. (2006). Bootstrapping Malmquist indices for Danish seiners in the North Sea and Skagerrak. Journal of Applied Statistics, 33, 891–907.10.1080/02664760600742151
  • Horta, I. M., Camanho, A. S., Johnes, J., & Johnes, G. (2013). Performance trends in the construction industry worldwide: An overview of the turn of the century. Journal of Productivity Analysis, 39, 89–99.10.1007/s11123-012-0276-0
  • Husson, F., Lê, S., & Pages, J. (2010). Exploratory multivariate analysis by example using R. Computer sciences and data analysis. Boca Raton: Chapman & Hall/CRC.
  • Jaraitė, J., & Di Maria, C. (2012). Efficiency, productivity and environmental policy: A case study of power generation in the EU. Energy Economics, 34, 1557–1568.10.1016/j.eneco.2011.11.017
  • Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de Estadistica, 4, 209–242.10.1007/BF03006863
  • Odeck, J. (2009). Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers. Omega, 37, 1007–1017.10.1016/j.omega.2008.11.003
  • Parteka, A., & Wolszczak-Derlacz, J. (2013). Dynamics of productivity in higher education: Cross-European evidence based on bootstrapped Malmquist indices. Journal of Productivity Analysis, 40, 67–82.10.1007/s11123-012-0320-0
  • Perelman, S., & Serebrisky, T. (2012). Measuring the technical efficiency of airports in Latin America. Utilities Policy, 22, 1–7.10.1016/j.jup.2012.02.001
  • Ramanathan, R. (2003). An introduction to data envelopment analysis: A tool for performance measurement. Thousand Oaks: Sage Publications.
  • Ray, S. C., & Desli, E. (1997). Productivity growth, technical progress, and efficiency change in industrialized countries: Comment. The American Economic Review, 87, 1033–1039.
  • Rezitis, A., Tsiboukas, K., & Tsoukalas, S. (2009). Effects of the European Union farm credit programs on efficiency and productivity of the Greek livestock sector: A stochastic DEA application. Paper presented at the 8th Annual EEFS Conference ‘Current Challenges in the Global Economy: Prospects and Policy Reforms’, University of Warsaw, Faculty of Economic and Science.
  • Shepard, R. W. (1953). Cost and production functions. Princeton, NJ: Princeton University Press.
  • Simar, L., & Wilson, P. W. (1998a). Productivity Growth in Industrialized Countries. CORE Discussion Paper 1998036. Leuven: Université Catholique de Louvain.
  • Simar, L., & Wilson, P. W. (1998b). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44, 49–61.10.1287/mnsc.44.1.49
  • Simar, L., & Wilson, P. W. (1999). Estimating and bootstrapping Malmquist indices. European Journal of Operational Research, 115, 459–471.10.1016/S0377-2217(97)00450-5
  • Simar, L., & Wilson, P. W. (2000). A general methodology for bootstrapping in non-parametric frontier models. Journal of Applied Statistics, 27, 779–802.10.1080/02664760050081951
  • Titko, J., Stankevičienė, J., & Lāce, N. (2014). Measuring bank efficiency: DEA application. Technological and Economic Development of Economy, 20, 739–757.10.3846/20294913.2014.984255
  • Wheelock, D. C., & Wilson, P. W. (1999). Technical progress, inefficiency, and productivity change in US banking, 1984-1993. Journal of Money, Credit, and Banking, 31, 212–234.10.2307/2601230
  • Wilson, P. (2008). FEAR: A software package for frontier efficiency analysis with R. Socio-Economic Planning Sciences, 42, 247–254.10.1016/j.seps.2007.02.001
  • Zhou, P., Ang, B. W., & Han, J. Y. (2010). Total factor carbon emission performance: A Malmquist index analysis. Energy Economics, 32, 194–201.10.1016/j.eneco.2009.10.003