Hermeneutics of the DEA analysis methodology: A case of comparative effectiveness assessment of the consolidated budget performance by the constituent entities of the Russian Federation in the area of preschool education
Porunov A.N. Samara State Technical University, Samara, Russian Federation firstname.lastname@example.org
Subject This article discusses the key points of the methodology for relative efficiency assessment of financial management based on Data Envelopment Analysis (DEA analysis). I used the DEA analysis for the comparative effectiveness assessment, in a comprehensive manner, of the consolidated budget performance by the Russian Federation entities and territorial public non-budgetary funds for preschool education, as a result of 2015. Objectives The article aims to address key issues in the practice of DEA analysis, identify the RF entities showing the most productive practice in the implementation of the consolidated budget in preschool education, and rate them on the basis of an aggregate assessment of comparative efficiency. Methods For the study, I used the methods of systems analysis, mathematical, economic, and statistical analyses, decomposition, and aggregation. The factual basis of the study is the Federal Treasury's data on the consolidated budgets of the constituent entities of the Russian Federation and the budgets of the territorial public non-budgetary funds in 2015, and the Rosstat operative statistical records on organizations that carry out educational activities in preschool education programs and childcare for 2015. Results The article presents aggregate estimates of the comparative efficiency of the implementation of consolidated budgets in preschool education. As well, the article presents a rating of the RF entities, depending on the effectiveness of their implementation of the consolidated budget in the area of preschool education. Conclusions Most regions (94 percent) have a very low relative effectiveness of their budget performance with respect to best practices. The best practice (absolutely effective) of budget execution at the time of the study was observed in the Chukotka Autonomous Okrug.
Keywords: pre-primary education, consolidated budget, comparative economic efficiency, DEA analysis
Cook W.D., Harrison J., Imanirad R., Rouse P., Zhu J. Data Envelopment Analysis with Nonhomogeneous DMUs. Operations Research, 2013, vol. 61, iss. 3, pp. 666–676. doi: 10.1287/opre.2013.1173
Cook W.D., Zhu J. Multiple Variable Proportionality in DEA. Operations Research, 2011, vol. 59, iss. 4, pp. 1024–1032. doi: 10.1287/opre.1110.0937
Hammerschmidt M., Bauer H.H. Messung der Werbeeffizienz – Ein zweistufiger DEA-Ansatz. Marketing Review St. Gallen, 2008, vol. 25, iss. 2, pp. 34–39. doi: 10.1007/s11621-008-0023-0
Stewart T.J. Goal Directed Benchmarking for Organizational Efficiency. International Journal of Management Science, 2010, vol. 38, рр. 534–539. doi: 10.1016/j.omega.2010.01.004
Clark J.B. Raspredelenie bogatstva [The Distribution of Wealth]. Moscow, Gelios ARV Publ., 2000, 367 p.
Bowlin W.F. Measuring Performance: An Introduction to Data Envelopment Analysis (DEA). Journal of Cost Analysis, 1998, vol. 15, iss. 2, pp. 3–27. doi: 10.1080/08823871.1998.10462318
Podinovski V.V., Athanassopoulos A. Assessing the Relative Efficiency of Decision Making Units in DEA Models with Weight Restrictions. Journal of the Operational Research Society, 1998, vol. 49, iss. 5, pp. 500–508. doi: 10.1057/palgrave.jors.2600543
Dyson R.G., Allen R., Camanho A.S., Podinovski V.V., Sarrico C.S., Shale E.A. Pitfalls and Protocols in DEA. European Journal of Operational Research, 2001, vol. 132, iss. 2, pp. 245–259. doi: 10.1016/S0377-2217(00)00149-1
Hadi Shirouyehzad, Farhad Hosseinzadeh Lotfi, Reza Dabestani. Aggregating the Results of Ranking Models in Data Envelopment Analysis by Shannon's Entropy: A case study in hotel industry. International Journal of Modelling in Operations Management, 2013, vol. 3, no. 2, pp. 149–163. doi: 10.1504/IJMOM.2013.055970
Bian Y., Yang F. Resource and Environment Efficiency Analysis of Provinces in China: A DEA approach based on Shannon's entropy. Energy Policy, 2010, vol. 38, iss. 4, pp. 1909–1917. doi: 10.1016/j.enpol.2009.11.071
Xie Q., Dai Q., Li Y., Jiang A. Increasing the Discriminatory Power of DEA Using Shannon's Entropy. Entropy, 2014, vol. 16, iss. 3, pp. 1571–1585. doi: 10.3390/e16031571
Soleimani-Damaneh M., Zarepisheh M.Shannon's Entropy for Combining the Efficiency Results of Different DEA Models: Method and Application. Expert Systems with Applications: An International Journal, 2009, vol. 36, pp. 5146–5150. doi: 10.1016/j.eswa.2008.06.031
Wu J., Sun J., Liang L. DEA Cross-Efficiency Aggregation Method Based upon Shannon Entropy. International Journal of Production Research, 2012, vol. 50, iss. 23, pp. 6726–6736. doi: 10.1080/00207543.2011.618150
Wilken R. Dynamisches Benchmarking. Ein Verfahren auf Basis der Data Envelopment Analysis. Deutscher Universitätsverlag, Wiesbaden, 2007, 226 p. doi: 10.1007/978-3-8350-9569-4
Keenye R.L., Raiffa H. Prinyatie reshenii pri mnogikh kriteriyakh: predpochteniya i zameshcheniya [Decisions with Multiple Objectives: Preferences and Value Tradeoffs]. Moscow, Radio i svyaz' Publ., 1981, 560 p.
Podinovskii V.V., Gavrilov V.M. Optimizatsiya po posledovatel'no primenyaemym kriteriyam [Optimization by successive criteria]. Moscow, Sovetskoe radio Publ., 1975, 192 p.
Shvetsov A.V. [A statistical analysis of the budgetary security of the constituent entities of the Russian Federation]. Rossiiskoe predprinimatel'stvo = Russian Journal of Entrepreneurship, 2010, no. 7-1, pp. 138–142. (In Russ.)