1,145
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A meta-regression analysis on judicial efficiency literature: the role of methodological and courts diversity

ORCID Icon, ORCID Icon & ORCID Icon
Article: 2284010 | Received 25 Aug 2022, Accepted 09 Nov 2023, Published online: 21 Dec 2023

References

  • Aiello, F., & Bonanno, G. (2016). Efficiency in banking: A meta-regression analysis. International Review of Applied Economics, 30(1), 112–24. https://doi.org/10.1080/02692171.2015.1070131
  • Aiello, F., & Bonanno, G. (2018). On the sources of heterogeneity in banking efficiency literature. Journal of Economic Surveys, 32(1), 194–225. https://doi.org/10.1111/joes.12193
  • Aiello, F., & Bonanno, G. (2019). Explaining differences in efficiency: A meta-study on local government literature. Journal of Economic Surveys, 33(3), 999–1027. https://doi.org/10.1111/joes.12310
  • Antonucci, L., Crocetta, C., & d’Ovidio, F. D. (2014). Evaluation of Italian judicial system. Procedia Economics and Finance, 17, 121–130. https://doi.org/10.1016/S2212-5671(14)00886-7
  • Assaf, A. G., & Josiassen, A. (2016). Frontier analysis: A state-of-the-art review and meta-analysis. Journal of Travel Research, 55(5), 612–627. https://doi.org/10.1177/0047287515569776
  • Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
  • Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98(2), 175–212. https://doi.org/10.1016/S0377-2217(96)00342-6
  • Bonanno, G., De Giovanni, D., & Domma, F. (2017). The ‘wrong skewness’ problem: A re-specification of stochastic frontiers. Journal of Productivity Analysis, 47(1), 49–64. https://doi.org/10.1007/s11123-017-0492-8
  • Bravo-Ureta, B. E., Solís, D., Moreira López, V. H., Maripani, J. F., Thiam, A., & Rivas, T. (2007). Technical efficiency in farming: A meta-regression analysis. Journal of Productivity Analysis, 27(1), 57–72. https://doi.org/10.1007/s11123-006-0025-3
  • Brons, M., Nijkamp, P., Pels, E., & Rietveld, P. (2005). Efficiency of urban public transit: A meta-analysis. Transportation, 32(1), 1–21. https://doi.org/10.1007/s11116-004-0939-4
  • Castro, A. S. (2009). Court performance in Brazil: Evidence from judicature-level data. (No. ID 2612941). Social Science Research Network.
  • Chaffai, M. E. (2022). New evidence on Islamic and conventional bank efficiency: A meta-regression analysis. Bulletin of Economic Research, 74(1), 221–246. https://doi.org/10.1111/boer.12291
  • Coelli, T. J. (1995). Recent developments in frontier modelling and efficiency measurement. Australian Journal of Agricultural Economics, 39(3), 219–245. https://doi.org/10.1111/j.1467-8489.1995.tb00552.x
  • Coelli, T., & Perelman, S. (1999). A comparison of parametric and non-parametric distance functions: With application to European railways. European Journal of Operational Research, 117(2), 326–339. https://doi.org/10.1016/S0377-2217(98)00271-9
  • Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1–4. https://doi.org/10.1016/j.omega.2013.09.004
  • Djokoto, J. G., & Gidiglo, K. F. (2016). Technical efficiency in agribusiness: A meta-analysis on Ghana. Agribusiness, 32(3), 397–415. https://doi.org/10.1002/agr.21457
  • Elbialy, N., & García-Rubio, M. A. (2011). Assessing judicial efficiency of Egyptian first instance courts: A DEA analysis. MAGKS Papers on Economics (No. 201119). Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Espasa, M., & Esteller-Moré, A. (2015). Analyzing judicial courts’ performance: Inefficiency vs. Congestion. Revista De Economia Aplicada, 23, 61–82.
  • European Commission. (2017). European semester: Thematic factsheet – effective justice systems. European Commission. https://commission.europa.eu/system/files/2018-06/european-semester_thematic-factsheet_effective-justice-systems_en_0.pdf
  • Falavigna, G., Ippoliti, R., Manello, A., & Ramello, G. B. (2015). Judicial productivity, delay and efficiency: A directional distance function (DDF) approach. European Journal of Operational Research, 240(2), 592–601. https://doi.org/10.1016/j.ejor.2014.07.014
  • Falavigna, G., Ippoliti, R., & Ramello, G. B. (2018). DEA-based Malmquist productivity indexes for understanding courts reform. Socio-Economic Planning Sciences, 62, 31–43. https://doi.org/10.1016/j.seps.2017.07.001
  • Fall, F., Akim, A.-M., & Wassongma, H. (2018). DEA and SFA research on the efficiency of microfinance institutions: A meta-analysis. World Development, 107, 176–188. https://doi.org/10.1016/j.worlddev.2018.02.032
  • Fan, Y., Wang, C., & Nan, Z. (2018). Determining water use efficiency of wheat and cotton: A meta-regression analysis. Agricultural Water Management, 199, 48–60. https://doi.org/10.1016/j.agwat.2017.12.006
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120(3), 253–281. https://doi.org/10.2307/2343100
  • Fauvrelle, T. A., & Almeida, A. T. C. (2018). Determinants of judicial efficiency change: Evidence from Brazil. Review of Law and Economics, 14(1), 14. https://doi.org/10.1515/rle-2017-0004
  • Ferrandino, J. (2012). The impact of revision 7 on the technical efficiency of florida’s circuit courts. Justice System Journal, 33(1), 22–46. https://doi.org/10.1080/0098261X.2012.10768000
  • Ferro, G., Romero, C. A., & Romero-Gómez, E. (2018). Efficient courts? A frontier performance assessment. Benchmarking: An International Journal, 25(9), 3443–3458. https://doi.org/10.1108/BIJ-09-2017-0244
  • Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research, 204(2), 189–198. https://doi.org/10.1016/j.ejor.2009.08.003
  • Finocchiaro Castro, M., & Guccio, C. (2014). Searching for the source of technical inefficiency in Italian judicial districts: An empirical investigation. European Journal of Law and Economics, 38(3), 369–391. https://doi.org/10.1007/s10657-012-9329-0
  • Finocchiaro Castro, M., & Guccio, C. (2018). Measuring potential efficiency gains from mergers of Italian first instance courts through nonparametric Model. Public Finance Review, 46(1), 83–116. https://doi.org/10.1177/1091142116652723
  • Fusco, E., Laurenzi, M., & Maggi, B. (2018). A data envelopment analysis of the Italian judicial efficiency. DSS Empirical Economics and Econometrics Working Papers Series (No. 2018/2). Centre for Empirical Economics and Econometrics, Department of Statistics, University of Rome.
  • Gallet, C. A., & Doucouliagos, H. (2014). The income elasticity of air travel: A meta-analysis. Annals of Tourism Research, 49, 141–155. https://doi.org/10.1016/j.annals.2014.09.006
  • Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8. https://doi.org/10.2307/1174772
  • Glass, G. V., McGaw, B., & Smith, M. L. (1981). Meta-analysis in Social Research. Sage Publications, Beverly Hills.
  • Gorman, M. F., & Ruggiero, J. (2009). Evaluating U.S. judicial district prosecutor performance using DEA: Are disadvantaged counties more inefficient? European Journal of Law and Economics, 27(3), 275–283. https://doi.org/10.1007/s10657-008-9093-3
  • Guzowska, M., & Strak, T. (2010). An examination of the efficiency of Polish public sector entities based on public prosecutor offices. Operations Research and Decisions, 2, 41–57. https://ord.pwr.edu.pl/assets/papers_archive/161%20-%20published.pdf.
  • Harbord, R. M., & Higgins, J. P. T. (2008). Meta-regression in Stata. Stata Journal, 8(4), 493–519. https://doi.org/10.1177/1536867X0800800403
  • Havranek, T., Irsova, Z., & Janda, K. (2012). Demand for gasoline is more price-inelastic than commonly thought. Energy Economics, 34(1), 201–207. https://doi.org/10.1016/j.eneco.2011.09.003
  • Havránek, T., Stanley, T. D., Doucouliagos, H., Bom, P., Geyer‐Klingeberg, J., Iwasaki, I., Reed, W. R., Rost, K., & Van Aert, R. C. M. (2020). Reporting guidelines for meta‐analysis in economics. Journal of Economic Surveys, 34(3), 469–475. https://doi.org/10.1111/joes.12363
  • Iliyasu, A., Mohamed, Z. A., Ismail, M. M., & Abdullah, A. M. (2014). A meta-analysis of technical efficiency in aquaculture. Journal of Applied Aquaculture, 26(4), 329–339. https://doi.org/10.1080/10454438.2014.959829
  • Ippoliti, R., Melcarne, A., & Ramello, G. B. (2015a). The impact of judicial efficiency on entrepreneurial action: A European perspective. Economic Notes, 44(1), 57–74. https://doi.org/10.1111/ecno.12030
  • Ippoliti, R., Melcarne, A., & Ramello, G. B. (2015b). Judicial efficiency and entrepreneurs’ expectations on the reliability of European legal systems. European Journal of Law and Economics, 40(1), 75–94. https://doi.org/10.1007/s10657-014-9456-x
  • Ippoliti, R., & Ramello, G. B. (2018). Governance of tax courts. Economics of Governance, 19(4), 317–338. https://doi.org/10.1007/s10101-018-0212-5
  • Ivanova, N. B. (2014). Judicial reform and its effect on the economy: The case of Bulgaria [ Master Thesis]. Erasmus University Rotterdam,
  • Kao, C., & Hung, H. T. (2008). Data envelopment analysis with common weights: The compromise solution approach. Journal of the Operational Research Society, 59(7), 893–903.
  • Kiadaliri, A. A., Jafari, M., & Gerdtham, U.-G. (2013). Frontier-based techniques in measuring hospital efficiency in Iran: A systematic review and meta-regression analysis. BMC Health Services Research, 13(1). https://doi.org/10.1186/1472-6963-13-312
  • Kittelsen, S. A. C., & Førsund, F. R. (1992). Efficiency analysis of Norwegian district courts. Journal of Productivity Analysis, 3(3), 277–306. https://doi.org/10.1007/BF00158357
  • Lovell, C. A. K. (2002). Performance Assessment in the Public Sector. In: Fox, K.J. (eds). Performance assessment in the public sector. Efficiency in the Public Sector, Studies in the Productivity and Efficiency Series (pp. 11–35). Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3592-5_2
  • Major, W. (2015). Data envelopment analysis as an instrument for measuring the efficiency of courts. Operations Research and Decisions, 25(4), 19–34. https://doi.org/10.5277/ord150402
  • Marciano, A., Melcarne, A., & Ramello, G. B. (2019). The economic importance of judicial institutions, their performance and the proper way to measure them. Journal of Institutional Economics, 15(1), 81–98. https://doi.org/10.1017/S1744137418000292
  • Mattsson, P., & Tidanå, C. (2019). Potential efficiency effects of merging the Swedish district courts. Socio-Economic Planning Sciences, 67, 58–68. https://doi.org/10.1016/j.seps.2018.09.002
  • Melcarne, A., & Ramello, G. (2015). Judicial independence, judges’ incentives and efficiency. Review of Law and Economics, 11(2), 149–169. https://doi.org/10.1515/rle-2015-0024
  • Merkel, A., & Holmgren, J. (2017). Dredging the depths of knowledge: Efficiency analysis in the maritime port sector. Transport Policy, 60, 63–74. https://doi.org/10.1016/j.tranpol.2017.08.010
  • Nguyen, K. H., & Coelli, T. (2009). Quantifying the effects of modelling choices on hospital efficiency measures: A meta-regression analysis. Centre for Efficiency and Productivity Analysis. (No. WP072009). School of Economics, University of Queensland, Australia.
  • Nissi, E., Giacalone, M., & Cusatelli, C. (2019). The efficiency of the Italian judicial system: A two stage data envelopment analysis approach. Social Indicators Research, 146(1–2), 395–407. https://doi.org/10.1007/s11205-018-1892-5
  • Nissi, E., & Rapposelli, A. (2010). A data envelopment analysis of Italian courts efficiency. Statistica Applicata Italian Journal of Applied Statistics, 22(2), 199–210.
  • Odeck, J., & Bråthen, S. (2012). A meta-analysis of DEA and SFA studies of the technical efficiency of seaports: A comparison of fixed and random-effects regression models. Transportation Research Part A: Policy and Practice, 46(10), 1574–1585. https://doi.org/10.1016/j.tra.2012.08.006
  • Odhiambo, O. J. (2014). Technical Efficiency of the Kenyan Judiciary: A case of the magistrates‘ courts [ Master Thesis].
  • Ogundari, K. (2014). The paradigm of agricultural efficiency and its implication on food security in Africa: What does meta-analysis reveal? World Development, 64, 690–702. https://doi.org/10.1016/j.worlddev.2014.07.005
  • Ogundari, K., & Brümmer, B. (2011). Technical Efficiency of Nigerian agriculture: a meta-regression analysis. Outlook on Agriculture, 40(2), 171–180 https://doi.org/10.5367/oa.2011.0038.
  • Park, S. Y., & Zhu, J. (2011). An exact algorithm for the DEA problem with a large number of outputs. European Journal of Operational Research, 210(1), 69–76.
  • Pedraja-Chaparro, F., & Salinas-Jimenez, J. (2010). An assessment of the efficiency of Spanish courts using DEA. Applied Economics, 28(11), 1391–1403. https://doi.org/10.1080/000368496327651
  • Peyrache, A., & Zago, A. (2016). Large courts, small justice! The inefficiency and the optimal structure of the Italian justice sector. Omega, 64, 42–56. https://doi.org/10.1016/j.omega.2015.11.002
  • Ramello, G. B, and Voigt S. (2012). The economics of efficiency and the judicial system. International Review of Law and Economics, 32(1), 1–2. https://doi.org/10.1016/j.irle.2011.12.003
  • Rushid, A. R. (2018). Technical efficiency of Swedish district courts [ Master Thesis].
  • Santos, S. P., & Amado, C. A. F. (2014). On the need for reform of the Portuguese judicial system – does data envelopment analysis assessment support it? Omega, 47, 1–16. https://doi.org/10.1016/j.omega.2014.02.007
  • Schneider, M. R. (2005). Judicial Career Incentives and court performance: An empirical study of the German Labour courts of appeal. European Journal of Law and Economics, 20(2), 127–144. https://doi.org/10.1007/s10657-005-1733-2
  • Seiford, L. M., & Thrall, R. M. (1990). Recent developments in DEA: The mathematical programming approach to frontier analysis. Journal of Econometrics, 46(1–2), 7–38. https://doi.org/10.1016/0304-4076(90)90045-U
  • Silva, M. C. A. (2018). Output-specific inputs in DEA: An application to courts of justice in Portugal. Omega, 79, 43–53. https://doi.org/10.1016/j.omega.2017.07.006
  • Simões, P., & Marques, R. C. (2012). Influence of regulation on the productivity of waste utilities. What can we learn with the Portuguese experience? Waste Management, 32(6), 1266–1275. https://doi.org/10.1016/j.wasman.2012.02.004
  • Sousa, M. D. M., Guimaraes, T. A., Guimaraes, T. A., & Sousa, M. D. M. (2018). Resources, innovation and performance in labor courts in Brazil. Revista de Administração Pública, 52(3), 486–506. https://doi.org/10.1590/0034-761220170045
  • Stanley, T. D. (2001). Wheat from chaff: Meta-analysis as quantitative literature review. Journal of Economic Perspectives, 15(3), 131–150. https://doi.org/10.1257/jep.15.3.131
  • Thiam, A., Bravo-Ureta, B. E., & Rivas, T. E. (2001). Technical efficiency in developing country agriculture: A meta-analysis. Agricultural Economics, 25(2–3), 235–243. https://doi.org/10.1111/j.1574-0862.2001.tb00204.x
  • Tian, X., & Yu, X. (2012). The enigmas of TFP in China: A meta-analysis. China Economic Review, 23(2), 396–414. https://doi.org/10.1016/j.chieco.2012.02.007
  • Trong Ho, P., Burton, M., Ma, C., & Hailu, A. (2022). Quantifying heterogeneity, heteroscedasticity and publication bias effects on technical efficiency estimates of rice farming: A meta-regression analysis. Journal of Agricultural Economics, 73(2), 580–597. https://doi.org/10.1111/1477-9552.12468
  • Tsai, C., & Tsai, J. (2010). Performance evaluation of the judicial system in Taiwan using data envelopment analysis and decision trees. 2010 Second International Conference on Computer Engineering and Applications, 2, 290–294. Bali, Indonesia.
  • Voigt, S. (2016). Determinants of judicial efficiency: A survey. European Journal of Law and Economics, 42(2), 183–208. https://doi.org/10.1007/s10657-016-9531-6
  • Xu, T., Dong, J., & Qiao, D. (2023). China’s marine economic efficiency: A meta-analysis. Ocean & Coastal Management, 239, 106633. https://doi.org/10.1016/j.ocecoaman.2023.106633
  • Yeung, L. (2014). Measuring efficiency of courts: An assessment of Brazilian courts Productivity. In A. Emrouznejad & E. Cabanda (Eds.), Managing service productivity: Using frontier efficiency methodologies and multicriteria decision making for improving service performance (pp. 155–165). Springer.
  • Yeung, L. L., & Azevedo, P. F. (2011). Measuring efficiency of Brazilian courts with data envelopment analysis (DEA). IMA Journal of Management Mathematics, 22(4), 343–356. https://doi.org/10.1093/imaman/dpr002
  • Yeung, L., & Azevedo, P. (2011). Measuring the Efficiency of Brazilian Courts from 2006 to 2008: What Do the Numbers Tell Us?. Insper Working Paper.