Abstract
Policymakers are in growing need of metrics which will assist them in ranking and assessing entities on different topics. Composite indicators, aggregated individual indicators, have become a valuable metric to do so. One of the approaches used in the process of their creation is the benefit-of-the-doubt (BoD) model. To overcome the observed issue of full freedom of the BoD model, herein we propose the application of a novel unsupervised approach to imposing constraints: the bootstrap I-distance; a data-driven statistical method used to obtain weight intervals. The proposed variant of the BoD model is named Bootstrap I-distance benefit-of-the-doubt (B-ID-BoD). To verify the B-ID-BoD model, we employed it on the ease of doing business index (EDBI) issued by the World Bank. The obtained results indicate that the model can be solved, that all the imposed constraints have been adhered to, and that the official EDBI weighting scheme does not need alteration. The proposed approach can initiate further research on data-driven approaches to constraining the BoD model and further applications of the bootstrap I-distance.
Similar content being viewed by others
Data availability
The data is available on the request from the corresponding author.
References
Allen, M.M.C., Aldred, M.L.: Business regulation, inward foreign direct investment, and economic growth in the new European Union member states. Crit. Perspect. Int. Bus. 9, 301–321 (2013). https://doi.org/10.1108/17422041311330431
Amado, C.A.F., São-José, J.M.S., Santos, S.P.: Measuring active ageing: a data envelopment analysis approach. Eur. J. Oper. Res. 255, 207–223 (2016). https://doi.org/10.1016/j.ejor.2016.04.048
Arcones, M.A., Gine, E.: The bootstrap of the mean with arbitrary bootstrap sample size. Ann. l’I.H.P. Probab. Stat. 25, 457–481 (1989)
Babamoradi, H., van den Berg, F., Rinnan, Å.: Bootstrap based confidence limits in principal component analysis—a case study. Chemom. Intell. Lab. Syst.. Intell. Lab. Syst. 120, 97–105 (2013). https://doi.org/10.1016/j.chemolab.2012.10.007
Beran, R., Ducharme, G.: Asymptotic theory for bootstrap methods in statistics. Centre de Recherches Mathematiques (1991)
Berman, E.P., Hirschman, D.: The sociology of quantification: where are we now? Contemp. Sociol. A J. Rev. 47, 257–266 (2018). https://doi.org/10.1177/0094306118767649
Bickel, P.J., Sakov, A.: On the choice of m in the m out of n bootstrap and its application to confidence bounds for extreme percentiles. Stat. Sin. 18, 967–985 (2008)
Cavicchia, C., Sarnacchiaro, P., Vichi, M.: A composite indicator for the waste management in the EU via hierarchical disjoint non-negative factor analysis. Socioecon. Plann. Sci.. Plann. Sci. 73, 100832 (2021). https://doi.org/10.1016/j.seps.2020.100832
Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429–444 (1978). https://doi.org/10.1016/0377-2217(78)90138-8
Cherchye, L., Moesen, W., Rogge, N., Puyenbroeck, T.V.: An introduction to “benefit of the doubt” composite indicators. Soc. Indic. Res. 82, 111–145 (2007). https://doi.org/10.1007/s11205-006-9029-7
De Bin, R., Janitza, S., Sauerbrei, W., Boulesteix, A.L.: Subsampling versus bootstrapping in resampling-based model selection for multivariable regression. Biometrics 72, 272–280 (2016). https://doi.org/10.1111/biom.12381
Decancq, K., Lugo, M.A.: Weights in multidimensional indices of wellbeing: an overview. Econ. Rev. 32, 7–34 (2013). https://doi.org/10.1080/07474938.2012.690641
Dmitrovic, V., Dobrota, M., Knezevic, S.: A statistical approach to evaluating bank productivity. Manag. J. theory Pract. Manag. 20, 47–56 (2015). https://doi.org/10.7595/management.fon.2015.0010
Dobrota, M., Martic, M., Bulajic, M., Jeremic, V.: Two-phased composite I-distance indicator approach for evaluation of countries’ information development. Telecommun. Policy. 39, 406–420 (2015). https://doi.org/10.1016/j.telpol.2015.03.003
Dobrota, M., Savic, G., Bulajic, M.: A new approach to the evaluation of countries’ educational structure and development: the European study. Eur. Rev. 23, 553–565 (2015). https://doi.org/10.1017/S1062798715000277
Dobrota, M., Bulajic, M., Bornmann, L., Jeremic, V.: A new approach to the QS university ranking using the composite I-distance indicator: uncertainty and sensitivity analyses. J. Assoc. Inf. Sci. Technol. 67, 200–211 (2016). https://doi.org/10.1002/asi.23355
Doing Business.: Doing business country profile—Canada (2020)
Doing Business.: Doing business regional profile—Latin America and the Caribbean (2020)
Doing Business.: Doing business country profile—New Zealand (2020)
Doshi, R., Kelley, J.G., Simmons, B.A.: The power of ranking: the ease of doing business indicator and global regulatory behavior. Int. Organ. 73, 611–643 (2019). https://doi.org/10.1017/S0020818319000158
Economist.: The doing business report-pulling rank (2015). http://www.economist.com/news/finance-and-economics/21667925-shortcomings-world-banks-business-climate-index-pulling-rank
Efron, B.: Bootstrap methods: another look at the jacknife. Ann. Stat. 7, 1–26 (1979). https://doi.org/10.1214/aoms/1177692541
Efron, B., Tibshirani, R.: An Introduction to the Bootstrap. Chapman & Hall/CRC, London (1993)
Fang, Y., Wang, J.: Selection of the number of clusters via the bootstrap method. Comput. Stat. Data Anal. 56, 468–477 (2012). https://doi.org/10.1016/j.csda.2011.09.003
Fusco, E.: Enhancing non-compensatory composite indicators: a directional proposal. Eur. J. Oper. Res. 242, 620–630 (2015). https://doi.org/10.1016/j.ejor.2014.10.017
Fusco, E., Vidoli, F., Rogge, N.: Spatial directional robust Benefit of the Doubt approach in presence of undesirable output: an application to Italian waste sector. Omega 94, 102053 (2020). https://doi.org/10.1016/j.omega.2019.03.011
Giambona, F., Vassallo, E.: Composite indicator of financial development in a benefit-of-doubt approach. Econ. Notes 42, 171–202 (2013). https://doi.org/10.1111/j.1468-0300.2013.12005.x
Goethals, G.R.: Social comparison theory. Pers. Soc. Psychol. Bull. 12, 261–278 (1986). https://doi.org/10.1177/0146167286123001
Gonçalves, A.C., Almeida, R.M.V.R., Lins, M.P.E., Samanez, C.P.: Canonical correlation analysis in the definition of weight restrictions for data envelopment analysis. J. Appl. Stat. 40, 1032–1043 (2013). https://doi.org/10.1080/02664763.2013.772571
Greco, S., Ishizaka, A., Tasiou, M., Torrisi, G.: On the methodological framework of composite indices: a review of the issues of weighting, aggregation, and robustness. Soc. Indic. Res. 141, 61–94 (2018). https://doi.org/10.1007/s11205-017-1832-9
Grupp, H., Mogee, M.E.: Indicators for national science and technology policy: how robust are composite indicators? Res. Policy 33, 1373–1384 (2004). https://doi.org/10.1016/j.respol.2004.09.007
Guaita Martínez, J.M., Martín Martín, J.M., Ostos Rey, M.S., de Castro Pardo, M.: Constructing knowledge economy composite indicators using an MCA-DEA approach. Econ. Res. Istraživanja. 34, 331–351 (2021). https://doi.org/10.1080/1331677X.2020.1782765
Gulati, R., Kattumuri, R., Kumar, S.: A non-parametric index of corporate governance in the banking industry: an application to Indian data. Socioecon. Plan. Sci. 70, 100702 (2020). https://doi.org/10.1016/j.seps.2019.03.008
Hedges, S.: The number of replications needed for accurate estimation of the bootstrap P value in phylogenetic studies. Mol. Biol. Evol. 9, 366–369 (1992). https://doi.org/10.1093/oxfordjournals.molbev.a040725
Hellwig, Z.: On the problem of weighting in international comparisons. France, Paris (1969)
Høyland, B., Moene, K., Willumsen, F.: The tyranny of international index rankings. J. Dev. Econ. 97, 1–14 (2012). https://doi.org/10.1016/j.jdeveco.2011.01.007
Ivanovic, B.: Classification of underdeveloped areas according to level of economic development. East. Eur. Econ. 2, 46–61 (1963). https://doi.org/10.1080/00128775.1963.11647849
Ivanovic, B.: Teorija klasifikacije. Institut za ekonomiku industrije, Beograd (1977)
Jeremic, V., Bulajic, M., Martic, M., Radojicic, Z.: A fresh approach to evaluating the academic ranking of world universities. Scientometrics 87, 587–596 (2011). https://doi.org/10.1007/s11192-011-0361-6
Jeremic, V., Jovanovic Milenkovic, M., Radojicic, Z., Martic, M.: Excellence with leadership: the crown indicator of Scimago Institutions Rankings Iber report. El Prof. la Inf. 22, 474–480 (2013). https://doi.org/10.3145/epi.2013.sep.13
Jiang, W., Simon, R.: A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification. Stat. Med. 26, 5320–5334 (2007). https://doi.org/10.1002/sim.2968
Jovanovic, M., Jeremic, V., Savic, G., Bulajic, M., Martic, M.: How does the normalization of data affect the ARWU ranking? Scientometrics 93, 319–327 (2012). https://doi.org/10.1007/s11192-012-0674-0
Kleiner, A., Talwalkar, A., Sarkar, P., Jordan, M.I.: A scalable bootstrap for massive data. J. R. Stat. Soc. Ser. B Stat Methodol.Methodol. 76, 795–816 (2014). https://doi.org/10.1111/rssb.12050
Kline, R.B.: Principles and practice of structural equation modeling. (2005)
Kuc-Czarnecka, M., Lo Piano, S., Saltelli, A.: Quantitative storytelling in the making of a composite indicator. Soc. Indic. Res. 149, 775–802 (2020). https://doi.org/10.1007/s11205-020-02276-0
Lafuente, E., Araya, M., Leiva, J.C.: Assessment of local competitiveness: a composite indicator analysis of Costa Rican counties using the ‘benefit of the doubt’ model. Socioecon. Plann. Sci.. Plann. Sci. 81, 100864 (2022). https://doi.org/10.1016/j.seps.2020.100864
Mariano, E.B., Sobreiro, V.A., Rebelatto, D.A.N.: Human development and data envelopment analysis: a structured literature review. Omega 54, 33–49 (2015). https://doi.org/10.1016/j.omega.2015.01.002
Maricic, M., Bulajic, M., Radojicic, Z., Jeremic, V.: Multivariate approach to imposing additional constraints on the benefit-of-the-doubt model: the case of QS World University Rankings by Subject. Croat. Rev. Econ. Bus. Soc. Stat. 2, 1–14 (2016). https://doi.org/10.1515/crebss-2016-0005
Maricic, M., Kostic-Stankovic, M.: Towards an impartial responsible competitiveness index: a twofold multivariate I-distance approach. Qual. Quant. 50, 103–120 (2016). https://doi.org/10.1007/s11135-014-0139-z
Maricic, M., Bulajic, M., Radojicic, Z., Jeremic, V.: Shedding light on the doing business index: machine learning approach. Bus. Syst. Res. 10, 73–84 (2019). https://doi.org/10.2478/bsrj-2019-019
Maricic, M., Egea, J.A., Jeremic, V.: A hybrid enhanced scatter search—composite I-distance indicator (eSS-CIDI) optimization approach for determining weights within composite indicators. Soc. Indic. Res. 144, 497–537 (2019). https://doi.org/10.1007/s11205-018-02056-x
Marković, M., Zdravković, S., Mitrović, M., Radojičić, A.: An iterative multivariate post hoc I-distance approach in evaluating OECD better life index. Soc. Indic. Res. 126, 1–19 (2016). https://doi.org/10.1007/s11205-015-0879-8
Marozzi, M.: A composite indicator dimension reduction procedure with application to university student satisfaction. Stat. Neerl. 63, 258–268 (2009). https://doi.org/10.1111/j.1467-9574.2009.00422.x
Mecit, E.D., Alp, I.: A new proposed model of restricted data envelopment analysis by correlation coefficients. Appl. Math. Model. 37, 3407–3425 (2013). https://doi.org/10.1016/j.apm.2012.07.010
Melyn, W., Moesen, W.: Towards a synthetic indicator of macroeconomic performance: unequal weighting when limited information is available (1991)
Morris, R., Aziz, A.: Ease of doing business and FDI inflow to Sub-Saharan Africa and Asian countries. Cross Cult. Manag. An Int. J. 18, 400–411 (2011). https://doi.org/10.1108/13527601111179483
Munda, G., Nardo, M.: On the methodological foundations of composite indicators used for ranking countries, Ispra, Italy (2003)
Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., Giovannini, E.: Handbook on constructing composite indicators (2005)
OECD.: Glossary of statistical terms. https://stats.oecd.org/glossary/detail.asp?ID=6278
Pattengale, N.D., Alipour, M., Bininda-Emonds, O.R.P., Moret, B.M.E., Stamatakis, A.: How many bootstrap replicates are necessary? In: Lecture notes in Computer Science (including subseries lecture notes in Artificial Intelligence and lecture notes in Bioinformatics). pp. 184–200 (2009)
Peiró-Palomino, J., Picazo-Tadeo, A.J.: OECD: one or many? Ranking countries with a composite well-being indicator. Soc. Indic. Res. 139, 847–869 (2018). https://doi.org/10.1007/s11205-017-1747-5
Perišić, A.: Data-driven weights and restrictions in the construction of composite indicators. Croat. Oper. Res. Rev. 6, 29–42 (2015)
Pinheiro-Alves, R., Zambujal-Oliveira, J.: The ease of doing business index as a tool for investment location decisions. Econ. Lett. 117, 66–70 (2012). https://doi.org/10.1016/j.econlet.2012.04.026
Radojicic, M., Savic, G., Jeremic, V.: Measuring the efficiency of banks: the bootstrapped I-distance GAR DEA approach. Technol. Econ. Dev. Econ. 24, 1581–1605 (2018). https://doi.org/10.3846/tede.2018.3699
Reggi, L., Arduini, D., Biagetti, M., Zanfei, A.: How advanced are Italian regions in terms of public e-services? The construction of a composite indicator to analyze patterns of innovation diffusion in the public sector. Telecommun. Policy. 38, 514–529 (2014). https://doi.org/10.1016/j.telpol.2013.12.005
Rogge, N.: Composite indicators as generalized benefit-of-the-doubt weighted averages. Eur. J. Oper. Res. 267, 381–392 (2018). https://doi.org/10.1016/j.ejor.2017.11.048
Rogge, N.: On aggregating benefit of the doubt composite indicators. Eur. J. Oper. Res. 264, 364–369 (2018). https://doi.org/10.1016/j.ejor.2017.06.035
Rogge, N., Archer, G.: Measuring and analyzing country change in establishing ease of doing business using a revised version of World Bank’s ease of doing business index. Eur. J. Oper. Res. 290, 373–385 (2020). https://doi.org/10.1016/j.ejor.2020.07.065
Sahoo, B.K., Singh, R., Mishra, B., Sankaran, K.: Research productivity in management schools of India during 1968–2015: a directional benefit-of-doubt model analysis. Omega 66, 118–139 (2017). https://doi.org/10.1016/j.omega.2016.02.004
Saisana, M., Tarantola, S.: State-of-the-art report on current methodologies and practices for composite indicator development (2002)
Saisana, M., Saltelli, A.: Statistical Audit of the 2014 Global Innovation Index (2014)
Saisana, M., D’Hombres, B., Saltelli, A.: Rickety numbers: Volatility of university rankings and policy implications. Res. Policy 40, 165–177 (2011). https://doi.org/10.1016/j.respol.2010.09.003
Singh, G.: Relationship between doing business index and foreign direct investment. In: International Conference on Ease of Doing Business: Contemporary Issues, Challenges and Future Scope, pp. 13–21 (2015)
Singh, R.K., Murty, H.R., Gupta, S.K., Dikshit, A.K.: Development of composite sustainability performance index for steel industry. Ecol. Indic. 7, 565–588 (2007). https://doi.org/10.1016/j.ecolind.2006.06.004
Streukens, S., Leroi-Werelds, S.: Bootstrapping and PLS-SEM: a step-by-step guide to get more out of your bootstrap results. Eur. Manag. J. 34, 618–632 (2016). https://doi.org/10.1016/j.emj.2016.06.003
Talukder, B., Hipel, K., Van Loon, G.: Developing composite indicators for agricultural sustainability assessment: effect of normalization and aggregation techniques. Resources 6, 1–27 (2017). https://doi.org/10.3390/resources6040066
Tan, K.G., Gopalan, S., Nguyen, W.: Measuring ease of doing business in India’s sub-national economies: a novel index. South Asian J. Bus. Stud. 7, 242–264 (2018). https://doi.org/10.1108/SAJBS-02-2018-0010
Terzi, S., Otoiu, A., Grimaccia, E., Mazziotta, M., Pareto, A.: Open issues in composite indicators: a starting point and a reference on some state-of-the-art issues. Roma TrE-Press, Rome (2021)
Van Puyenbroeck, T., Rogge, N.: Geometric mean quantity index numbers with benefit-of-the-doubt weights. Eur. J. Oper. Res. 256, 1004–1014 (2017). https://doi.org/10.1016/j.ejor.2016.07.038
Verbunt, P., Rogge, N.: Geometric composite indicators with compromise benefit-of-the-doubt weights. Eur. J. Oper. Res. 264, 388–401 (2018). https://doi.org/10.1016/j.ejor.2017.06.061
Wehrens, R., Putter, H., Buydens, L.M.: The bootstrap: a tutorial. Chemom. Intell. Lab. Syst. 54, 35–52 (2000). https://doi.org/10.1016/S0169-7439(00)00102-7
World Bank.: Doing Business in OHADA (2017). https://archive.doingbusiness.org/en/reports/regional-reports/ohada
World Bank.: Doing Business 2019 (2019)
World Bank.: Doing Business 2020 (2020)
World Bank.: World Bank Group to Discontinue Doing Business Report. https://www.worldbank.org/en/news/statement/2021/09/16/world-bank-group-to-discontinue-doing-business-report
Zhang, Y., Xiao, Y., Wu, J., Lu, X.: Comprehensive world university ranking based on ranking aggregation. Comput. Stat. 36, 1139–1152 (2021). https://doi.org/10.1007/s00180-020-01033-8
Zhou, P., Ang, B.W., Poh, K.L.: Comparing aggregating methods for constructing the composite environmental index: an objective measure. Ecol. Econ. 59, 305–311 (2006). https://doi.org/10.1016/j.ecolecon.2005.10.018
Zhu, W.: Making bootstrap statistical inferences: a tutorial. Res. Q. Exerc. SportExerc. Sport 68, 44–55 (1997). https://doi.org/10.1080/02701367.1997.10608865
Zientek, L.R., Thompson, B.: Applying the bootstrap to the multivariate case: bootstrap component/factor analysis. Behav. Res. Methods 39, 318–325 (2007). https://doi.org/10.3758/BF03193163
Zornic, N., Bornmann, L., Maricic, M., Markovic, A., Martic, M., Jeremic, V.: Ranking institutions within a university based on their scientific performance: a percentile-based approach. El Prof. la Inf. 24, 551–566 (2015). https://doi.org/10.3145/epi.2015.sep.05
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
All authors declare not having conflicts of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix 1: B-ID-BoD model scores and ranks, alongside the ranks and values of the official EDBI, authors’ work
Economy | B-ID-BoD score | B-ID-BoD rank | EDBI score | EDBI rank | Economy | B-ID-BoD score | B-ID-BoD rank | EDBI score | EDBI rank |
---|---|---|---|---|---|---|---|---|---|
New Zealand | 87.197 | 1 | 86.59 | 1 | Spain | 79.048 | 28 | 77.68 | 30 |
Singapore | 86.087 | 2 | 85.24 | 2 | France | 79.026 | 29 | 77.29 | 32 |
Denmark | 85.792 | 3 | 84.64 | 3 | Kazakhstan | 78.885 | 30 | 77.89 | 28 |
Hong Kong SAR, China | 85.669 | 4 | 84.22 | 4 | Rwanda | 78.861 | 31 | 77.88 | 29 |
Korea, Rep | 85.363 | 5 | 84.14 | 5 | Russian Federation | 78.473 | 32 | 77.37 | 31 |
Norway | 84.392 | 6 | 82.95 | 7 | Portugal | 78.461 | 33 | 76.55 | 34 |
Georgia | 84.184 | 7 | 83.28 | 6 | Netherlands | 78.101 | 34 | 76.04 | 36 |
United Kingdom | 83.681 | 8 | 82.65 | 9 | Belarus | 77.832 | 35 | 75.77 | 37 |
United States | 83.306 | 9 | 82.75 | 8 | Slovenia | 77.726 | 36 | 75.61 | 40 |
Sweden | 83.108 | 10 | 81.27 | 12 | Poland | 77.725 | 37 | 76.95 | 33 |
United Arab Emirates | 83.031 | 11 | 81.28 | 11 | Czech Republic | 77.682 | 38 | 76.1 | 35 |
Taiwan, China | 82.402 | 12 | 80.9 | 13 | Switzerland | 77.570 | 39 | 75.69 | 38 |
Lithuania | 82.333 | 13 | 80.83 | 14 | Japan | 77.179 | 40 | 75.65 | 39 |
Northern Macedonia | 82.079 | 14 | 81.55 | 10 | Armenia | 76.961 | 41 | 75.37 | 41 |
Estonia | 82.002 | 15 | 80.5 | 16 | Slovak Republic | 76.773 | 42 | 75.17 | 42 |
Finland | 81.791 | 16 | 80.35 | 17 | Turkey | 75.241 | 43 | 74.33 | 43 |
Malaysia | 81.519 | 17 | 80.6 | 15 | China | 75.227 | 44 | 73.64 | 46 |
Iceland | 80.724 | 18 | 79.35 | 21 | Belgium | 75.200 | 45 | 73.95 | 45 |
Mauritius | 80.697 | 19 | 79.58 | 20 | Moldova | 75.104 | 46 | 73.54 | 47 |
Australia | 80.649 | 20 | 80.13 | 18 | Kosovo | 75.083 | 47 | 74.15 | 44 |
Latvia | 80.573 | 21 | 79.59 | 19 | Serbia | 74.678 | 48 | 73.49 | 48 |
Germany | 80.186 | 22 | 78.9 | 24 | Italy | 74.645 | 49 | 72.56 | 51 |
Ireland | 80.039 | 23 | 78.91 | 23 | Israel | 73.982 | 50 | 73.23 | 49 |
Austria | 80.029 | 24 | 78.57 | 26 | Hungary | 73.439 | 51 | 72.28 | 53 |
Canada | 79.934 | 25 | 79.26 | 22 | Romania | 73.368 | 52 | 72.3 | 52 |
Thailand | 79.475 | 26 | 78.45 | 27 | Montenegro | 73.356 | 53 | 72.73 | 50 |
Azerbaijan | 79.353 | 27 | 78.64 | 25 | Chile | 73.121 | 54 | 71.81 | 56 |
Cyprus | 73.070 | 55 | 71.71 | 57 | Panama | 67.528 | 83 | 66.12 | 79 |
Croatia | 73.034 | 56 | 71.4 | 58 | Tunisia | 67.396 | 84 | 66.11 | 80 |
Morocco | 72.896 | 57 | 71.02 | 60 | South Africa | 67.032 | 85 | 66.03 | 82 |
Brunei Darussalam | 72.869 | 58 | 72.03 | 55 | Botswana | 66.788 | 86 | 65.4 | 86 |
Mexico | 72.512 | 59 | 72.09 | 54 | El Salvador | 66.727 | 87 | 65.41 | 85 |
Bulgaria | 72.177 | 60 | 71.24 | 59 | Zambia | 66.073 | 88 | 65.08 | 87 |
Luxembourg | 72.122 | 61 | 69.01 | 66 | Saudi Arabia | 65.710 | 89 | 63.5 | 92 |
Bahrain | 71.854 | 62 | 69.85 | 62 | Samoa | 65.576 | 90 | 63.77 | 90 |
Kenya | 70.958 | 63 | 70.31 | 61 | St. Lucia | 65.435 | 91 | 63.02 | 93 |
Albania | 70.483 | 64 | 69.51 | 63 | Tonga | 64.708 | 92 | 63.59 | 91 |
Puerto Rico (U.S.) | 70.393 | 65 | 69.46 | 64 | Bosnia and Herzegovina | 64.546 | 93 | 63.82 | 89 |
Costa Rica | 69.972 | 66 | 68.89 | 67 | Seychelles | 64.269 | 94 | 62.41 | 96 |
Colombia | 69.854 | 67 | 69.24 | 65 | Kuwait | 64.263 | 95 | 62.2 | 97 |
Greece | 69.836 | 68 | 68.08 | 72 | Djibouti | 63.921 | 96 | 62.02 | 99 |
Peru | 69.548 | 69 | 68.83 | 68 | Vanuatu | 63.836 | 97 | 62.87 | 94 |
Oman | 69.548 | 70 | 67.19 | 78 | Guatemala | 63.693 | 98 | 62.17 | 98 |
Kyrgyz Republic | 69.519 | 71 | 68.33 | 70 | Uruguay | 63.688 | 99 | 62.6 | 95 |
Vietnam | 69.390 | 72 | 68.36 | 69 | Dominica | 63.417 | 100 | 61.07 | 103 |
Ukraine | 69.189 | 73 | 68.25 | 71 | Jordan | 63.221 | 101 | 60.98 | 104 |
Uzbekistan | 68.699 | 74 | 67.4 | 76 | Fiji | 63.174 | 102 | 61.15 | 101 |
Indonesia | 68.619 | 75 | 67.96 | 73 | Sri Lanka | 62.900 | 103 | 61.22 | 100 |
Mongolia | 68.559 | 76 | 67.74 | 74 | Dominican Republic | 62.674 | 104 | 61.12 | 102 |
Qatar | 68.548 | 77 | 65.89 | 83 | Lesotho | 61.971 | 105 | 60.6 | 106 |
Bhutan | 68.402 | 78 | 66.08 | 81 | Trinidad and Tobago | 61.851 | 106 | 60.81 | 105 |
India | 68.355 | 79 | 67.23 | 77 | Namibia | 61.640 | 107 | 60.53 | 107 |
Jamaica | 67.966 | 80 | 67.47 | 75 | Antigua and Barbuda | 61.565 | 108 | 59.48 | 112 |
San Marino | 67.708 | 81 | 64.74 | 88 | Brazil | 61.534 | 109 | 60.01 | 109 |
Malta | 67.564 | 82 | 65.43 | 84 | Papua New Guinea | 61.198 | 110 | 60.12 | 108 |
Bahamas, The | 60.889 | 111 | 58.9 | 118 | Senegal | 55.673 | 140 | 54.15 | 141 |
Solomon Islands | 60.843 | 112 | 59.17 | 115 | Lebanon | 55.537 | 141 | 54.04 | 142 |
Paraguay | 60.832 | 113 | 59.4 | 113 | Cambodia | 55.450 | 142 | 54.8 | 138 |
Nepal | 60.740 | 114 | 59.63 | 110 | Niger | 55.254 | 143 | 53.72 | 143 |
West Bank and Gaza | 60.671 | 115 | 59.11 | 116 | Mali | 55.035 | 144 | 53.5 | 145 |
Eswatini | 60.597 | 116 | 58.95 | 117 | Grenada | 54.819 | 145 | 52.71 | 147 |
Philippines | 60.438 | 117 | 57.68 | 124 | Tanzania | 54.761 | 146 | 53.63 | 144 |
Ghana | 60.345 | 118 | 59.22 | 114 | Mauritania | 53.927 | 147 | 51.99 | 148 |
Malawi | 60.202 | 119 | 59.59 | 111 | Nigeria | 53.853 | 148 | 52.89 | 146 |
Argentina | 59.785 | 120 | 58.8 | 119 | Marshall Islands | 53.812 | 149 | 51.62 | 150 |
Egypt, Arab Rep | 59.499 | 121 | 58.56 | 120 | Burkina Faso | 53.203 | 150 | 51.57 | 151 |
Belize | 59.415 | 122 | 57.13 | 125 | Benin | 53.102 | 151 | 51.42 | 153 |
Ecuador | 59.354 | 123 | 57.94 | 123 | Gambia, The | 52.989 | 152 | 51.72 | 149 |
Honduras | 58.951 | 124 | 58.22 | 121 | Guinea | 52.923 | 153 | 51.51 | 152 |
St. Vincent and the Grenadines | 58.910 | 125 | 56.35 | 130 | Lao PDR | 52.689 | 154 | 51.26 | 154 |
Barbados | 58.663 | 126 | 56.78 | 129 | Bolivia | 51.862 | 155 | 50.32 | 156 |
Côte d'Ivoire | 58.576 | 127 | 58 | 122 | Algeria | 51.806 | 156 | 49.65 | 157 |
Tajikistan | 58.463 | 128 | 57.11 | 126 | Kiribati | 51.334 | 157 | 49.07 | 158 |
Iran, Islamic Rep | 58.158 | 129 | 56.98 | 128 | Zimbabwe | 51.177 | 158 | 50.44 | 155 |
Cabo Verde | 58.091 | 130 | 55.95 | 131 | Ethiopia | 51.157 | 159 | 49.06 | 159 |
Uganda | 57.837 | 131 | 57.06 | 127 | Sudan | 50.934 | 160 | 48.84 | 162 |
Mozambique | 57.551 | 132 | 55.53 | 135 | Micronesia, Fed. Sts | 50.917 | 161 | 48.99 | 160 |
Palau | 57.329 | 133 | 55.59 | 133 | Sierra Leone | 50.797 | 162 | 48.74 | 163 |
Nicaragua | 57.056 | 134 | 55.64 | 132 | Suriname | 50.627 | 163 | 48.05 | 165 |
St. Kitts and Nevis | 56.986 | 135 | 54.36 | 140 | Comoros | 50.410 | 164 | 48.66 | 164 |
Togo | 56.892 | 136 | 55.2 | 137 | Madagascar | 50.270 | 165 | 48.89 | 161 |
Guyana | 56.481 | 137 | 55.57 | 134 | Burundi | 49.686 | 166 | 47.41 | 168 |
Pakistan | 56.415 | 138 | 55.31 | 136 | Afghanistan | 49.116 | 167 | 47.77 | 167 |
Maldives | 55.973 | 139 | 54.43 | 139 | Cameroon | 48.847 | 168 | 47.78 | 166 |
Economy | B-ID-BoD score | B-ID-BoD rank | EDBI score | EDBI rank |
---|---|---|---|---|
Iraq | 47.746 | 169 | 44.72 | 171 |
São Tomé and Príncipe | 47.654 | 170 | 45.14 | 170 |
Myanmar | 47.243 | 171 | 44.72 | 172 |
Angola | 46.759 | 172 | 43.86 | 173 |
Gabon | 46.401 | 173 | 45.58 | 169 |
Liberia | 44.887 | 174 | 43.51 | 174 |
Guinea-Bissau | 44.655 | 175 | 42.85 | 175 |
Timor-Leste | 44.471 | 176 | 41.6 | 178 |
Syrian Arab Republic | 44.461 | 177 | 41.57 | 179 |
Bangladesh | 43.670 | 178 | 41.97 | 176 |
Equatorial Guinea | 43.185 | 179 | 41.94 | 177 |
Haiti | 41.382 | 180 | 38.52 | 182 |
Congo, Rep | 40.629 | 181 | 39.83 | 180 |
Chad | 40.412 | 182 | 39.36 | 181 |
Congo, Dem. Rep | 38.527 | 183 | 36.85 | 184 |
South Sudan | 38.031 | 184 | 35.34 | 185 |
Central African Republic | 37.869 | 185 | 36.9 | 183 |
Libya | 37.199 | 186 | 33.44 | 186 |
Yemen, Rep | 36.045 | 187 | 32.41 | 187 |
Venezuela, RB | 31.906 | 188 | 30.61 | 188 |
Eritrea | 26.041 | 189 | 23.07 | 189 |
Somalia | 23.117 | 190 | 20.04 | 190 |
Appendix 2: B-ID-BoD weights assigned to EDBI countries, authors’ work
Economy | T1 | T2 | T3 | T4 | T5 | T6 | T7 | T8 | T9 | T10 |
---|---|---|---|---|---|---|---|---|---|---|
New Zealand | 0.108 | 0.094 | 0.099 | 0.121 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Singapore | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Denmark | 0.108 | 0.087 | 0.118 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Hong Kong SAR, China | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Korea, Rep | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Norway | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.097 |
Georgia | 0.108 | 0.087 | 0.099 | 0.121 | 0.077 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
United Kingdom | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
United States | 0.108 | 0.087 | 0.099 | 0.096 | 0.095 | 0.092 | 0.102 | 0.116 | 0.093 | 0.112 |
Sweden | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
United Arab Emirates | 0.108 | 0.098 | 0.118 | 0.121 | 0.072 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Taiwan, China | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.108 | 0.093 | 0.090 |
Lithuania | 0.108 | 0.087 | 0.104 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Northern Macedonia | 0.108 | 0.094 | 0.099 | 0.096 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Estonia | 0.108 | 0.087 | 0.104 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Finland | 0.108 | 0.087 | 0.107 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.112 |
Malaysia | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.105 | 0.096 | 0.116 | 0.093 | 0.090 |
Iceland | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
Mauritius | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.108 | 0.093 | 0.090 |
Australia | 0.108 | 0.106 | 0.112 | 0.096 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Latvia | 0.108 | 0.087 | 0.106 | 0.096 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Germany | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.106 | 0.116 | 0.093 | 0.112 |
Ireland | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
Austria | 0.108 | 0.087 | 0.118 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Canada | 0.108 | 0.087 | 0.099 | 0.096 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.097 |
Thailand | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
Azerbaijan | 0.108 | 0.087 | 0.099 | 0.121 | 0.076 | 0.118 | 0.117 | 0.091 | 0.093 | 0.090 |
Spain | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
France | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Kazakhstan | 0.108 | 0.087 | 0.099 | 0.121 | 0.072 | 0.118 | 0.098 | 0.091 | 0.116 | 0.090 |
Rwanda | 0.108 | 0.087 | 0.106 | 0.121 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Russian Federation | 0.108 | 0.087 | 0.118 | 0.121 | 0.095 | 0.092 | 0.105 | 0.091 | 0.093 | 0.090 |
Portugal | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
Netherlands | 0.108 | 0.087 | 0.107 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.112 |
Belarus | 0.108 | 0.094 | 0.118 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Slovenia | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.106 | 0.116 | 0.093 | 0.112 |
Poland | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
Czech Republic | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
Switzerland | 0.108 | 0.087 | 0.118 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Japan | 0.108 | 0.097 | 0.118 | 0.096 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.112 |
Armenia | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
Slovak Republic | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
Turkey | 0.108 | 0.087 | 0.118 | 0.121 | 0.079 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
China | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.100 | 0.090 |
Belgium | 0.108 | 0.095 | 0.099 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.112 |
Moldova | 0.108 | 0.087 | 0.104 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Kosovo | 0.108 | 0.087 | 0.099 | 0.103 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Serbia | 0.108 | 0.106 | 0.099 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Italy | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.097 |
Israel | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.105 | 0.096 | 0.116 | 0.093 | 0.090 |
Hungary | 0.108 | 0.087 | 0.099 | 0.121 | 0.095 | 0.092 | 0.099 | 0.116 | 0.093 | 0.090 |
Romania | 0.108 | 0.087 | 0.099 | 0.103 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Montenegro | 0.108 | 0.094 | 0.099 | 0.096 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Chile | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Cyprus | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.101 |
Croatia | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
Morocco | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Brunei Darussalam | 0.108 | 0.100 | 0.118 | 0.096 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Mexico | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.092 | 0.096 | 0.116 | 0.093 | 0.099 |
Bulgaria | 0.108 | 0.106 | 0.099 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Luxembourg | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Bahrain | 0.108 | 0.087 | 0.104 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Kenya | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.118 | 0.104 | 0.091 | 0.093 | 0.090 |
Albania | 0.108 | 0.087 | 0.099 | 0.096 | 0.095 | 0.118 | 0.096 | 0.116 | 0.093 | 0.092 |
Puerto Rico (U.S.) | 0.108 | 0.087 | 0.105 | 0.096 | 0.095 | 0.092 | 0.096 | 0.116 | 0.093 | 0.112 |
Costa Rica | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.092 | 0.105 | 0.116 | 0.093 | 0.090 |
Colombia | 0.108 | 0.087 | 0.118 | 0.104 | 0.095 | 0.118 | 0.096 | 0.091 | 0.093 | 0.090 |
Greece | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Peru | 0.108 | 0.096 | 0.118 | 0.121 | 0.095 | 0.092 | 0.096 | 0.091 | 0.093 | 0.090 |
Oman | 0.108 | 0.087 | 0.118 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Kyrgyz Republic | 0.108 | 0.106 | 0.099 | 0.121 | 0.079 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Vietnam | 0.108 | 0.106 | 0.118 | 0.111 | 0.095 | 0.092 | 0.096 | 0.091 | 0.093 | 0.090 |
Ukraine | 0.108 | 0.106 | 0.099 | 0.096 | 0.083 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Uzbekistan | 0.108 | 0.087 | 0.118 | 0.109 | 0.072 | 0.092 | 0.117 | 0.091 | 0.116 | 0.090 |
Indonesia | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.103 |
Mongolia | 0.108 | 0.106 | 0.099 | 0.109 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Qatar | 0.108 | 0.106 | 0.110 | 0.121 | 0.072 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Bhutan | 0.108 | 0.087 | 0.118 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
India | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.118 | 0.096 | 0.099 | 0.093 | 0.090 |
Jamaica | 0.108 | 0.106 | 0.111 | 0.096 | 0.095 | 0.092 | 0.096 | 0.091 | 0.093 | 0.112 |
San Marino | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Malta | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Panama | 0.108 | 0.096 | 0.118 | 0.096 | 0.095 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Tunisia | 0.108 | 0.106 | 0.118 | 0.109 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
South Africa | 0.108 | 0.097 | 0.118 | 0.096 | 0.072 | 0.118 | 0.117 | 0.091 | 0.093 | 0.090 |
Botswana | 0.108 | 0.106 | 0.099 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
El Salvador | 0.108 | 0.087 | 0.106 | 0.096 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Zambia | 0.108 | 0.106 | 0.112 | 0.096 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Saudi Arabia | 0.108 | 0.093 | 0.118 | 0.121 | 0.072 | 0.118 | 0.096 | 0.091 | 0.093 | 0.090 |
Samoa | 0.108 | 0.098 | 0.118 | 0.121 | 0.072 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
St. Lucia | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.108 | 0.093 | 0.090 |
Tonga | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Bosnia and Herzegovina | 0.087 | 0.087 | 0.099 | 0.121 | 0.095 | 0.092 | 0.098 | 0.116 | 0.093 | 0.112 |
Seychelles | 0.108 | 0.092 | 0.099 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Kuwait | 0.108 | 0.098 | 0.118 | 0.121 | 0.072 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Djibouti | 0.108 | 0.106 | 0.109 | 0.096 | 0.072 | 0.118 | 0.117 | 0.091 | 0.093 | 0.090 |
Vanuatu | 0.108 | 0.087 | 0.118 | 0.109 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Guatemala | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.092 | 0.105 | 0.116 | 0.093 | 0.090 |
Uruguay | 0.108 | 0.087 | 0.118 | 0.109 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Dominica | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Jordan | 0.108 | 0.087 | 0.118 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Fiji | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
Sri Lanka | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.105 | 0.096 | 0.116 | 0.093 | 0.090 |
Dominican Republic | 0.108 | 0.106 | 0.106 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Lesotho | 0.108 | 0.087 | 0.099 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.098 | 0.090 |
Trinidad and Tobago | 0.108 | 0.106 | 0.118 | 0.096 | 0.095 | 0.092 | 0.096 | 0.106 | 0.093 | 0.090 |
Namibia | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.091 | 0.110 | 0.090 |
Antigua and Barbuda | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.096 | 0.116 | 0.106 | 0.090 |
Brazil | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.101 | 0.096 | 0.116 | 0.116 | 0.090 |
Papua New Guinea | 0.108 | 0.100 | 0.118 | 0.096 | 0.095 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Bahamas, The | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.091 | 0.110 | 0.090 |
Solomon Islands | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.108 | 0.093 | 0.090 |
Paraguay | 0.108 | 0.106 | 0.118 | 0.121 | 0.072 | 0.092 | 0.096 | 0.104 | 0.093 | 0.090 |
Nepal | 0.108 | 0.087 | 0.099 | 0.121 | 0.072 | 0.118 | 0.096 | 0.116 | 0.093 | 0.090 |
West Bank and Gaza | 0.108 | 0.087 | 0.118 | 0.096 | 0.095 | 0.092 | 0.105 | 0.116 | 0.093 | 0.090 |
Eswatini | 0.108 | 0.106 | 0.099 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Philippines | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Ghana | 0.108 | 0.106 | 0.118 | 0.096 | 0.089 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Malawi | 0.108 | 0.087 | 0.099 | 0.121 | 0.095 | 0.092 | 0.099 | 0.116 | 0.093 | 0.090 |
Argentina | 0.108 | 0.087 | 0.118 | 0.102 | 0.072 | 0.118 | 0.096 | 0.116 | 0.093 | 0.090 |
Egypt, Arab Rep | 0.108 | 0.106 | 0.118 | 0.096 | 0.095 | 0.107 | 0.096 | 0.091 | 0.093 | 0.090 |
Belize | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Ecuador | 0.108 | 0.106 | 0.118 | 0.109 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Honduras | 0.108 | 0.106 | 0.099 | 0.105 | 0.095 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
St. Vincent and the Grenadines | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Barbados | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.105 | 0.093 | 0.112 |
Côte d'Ivoire | 0.108 | 0.106 | 0.108 | 0.121 | 0.095 | 0.092 | 0.096 | 0.091 | 0.093 | 0.090 |
Tajikistan | 0.108 | 0.087 | 0.099 | 0.121 | 0.072 | 0.118 | 0.098 | 0.091 | 0.116 | 0.090 |
Iran, Islamic Rep | 0.108 | 0.106 | 0.118 | 0.109 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Cabo Verde | 0.108 | 0.106 | 0.099 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.104 | 0.090 |
Uganda | 0.108 | 0.087 | 0.099 | 0.096 | 0.079 | 0.092 | 0.117 | 0.116 | 0.116 | 0.090 |
Mozambique | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Palau | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.092 | 0.117 | 0.102 | 0.093 | 0.090 |
Nicaragua | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.105 | 0.116 | 0.116 | 0.090 |
St. Kitts and Nevis | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.096 | 0.116 | 0.106 | 0.090 |
Togo | 0.108 | 0.106 | 0.118 | 0.109 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Guyana | 0.108 | 0.087 | 0.099 | 0.103 | 0.072 | 0.092 | 0.117 | 0.116 | 0.116 | 0.090 |
Pakistan | 0.108 | 0.090 | 0.099 | 0.096 | 0.072 | 0.118 | 0.096 | 0.116 | 0.093 | 0.112 |
Maldives | 0.108 | 0.106 | 0.110 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Senegal | 0.108 | 0.106 | 0.118 | 0.109 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Lebanon | 0.108 | 0.087 | 0.118 | 0.121 | 0.072 | 0.092 | 0.117 | 0.102 | 0.093 | 0.090 |
Cambodia | 0.087 | 0.087 | 0.118 | 0.105 | 0.095 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Niger | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.100 | 0.090 |
Mali | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Grenada | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Tanzania | 0.108 | 0.098 | 0.118 | 0.096 | 0.095 | 0.092 | 0.096 | 0.091 | 0.116 | 0.090 |
Mauritania | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.092 | 0.096 | 0.100 | 0.116 | 0.090 |
Nigeria | 0.108 | 0.091 | 0.099 | 0.096 | 0.095 | 0.118 | 0.096 | 0.091 | 0.116 | 0.090 |
Marshall Islands | 0.108 | 0.106 | 0.110 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Burkina Faso | 0.108 | 0.106 | 0.099 | 0.107 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Benin | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.092 | 0.103 | 0.116 | 0.093 | 0.090 |
The Gambia | 0.108 | 0.106 | 0.099 | 0.105 | 0.072 | 0.092 | 0.096 | 0.116 | 0.116 | 0.090 |
Guinea | 0.108 | 0.106 | 0.118 | 0.111 | 0.072 | 0.092 | 0.096 | 0.091 | 0.116 | 0.090 |
Lao PDR | 0.108 | 0.106 | 0.099 | 0.121 | 0.079 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Bolivia | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.096 | 0.116 | 0.106 | 0.090 |
Algeria | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.111 | 0.091 | 0.116 | 0.090 |
Kiribati | 0.108 | 0.106 | 0.099 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.104 | 0.090 |
Zimbabwe | 0.108 | 0.087 | 0.099 | 0.121 | 0.095 | 0.092 | 0.117 | 0.098 | 0.093 | 0.090 |
Ethiopia | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.104 | 0.116 | 0.090 |
Sudan | 0.108 | 0.106 | 0.118 | 0.121 | 0.072 | 0.092 | 0.109 | 0.091 | 0.093 | 0.090 |
Micronesia, Fed. Sts | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Sierra Leone | 0.108 | 0.087 | 0.099 | 0.096 | 0.072 | 0.118 | 0.117 | 0.097 | 0.116 | 0.090 |
Suriname | 0.108 | 0.106 | 0.110 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Comoros | 0.108 | 0.106 | 0.118 | 0.109 | 0.072 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Madagascar | 0.108 | 0.087 | 0.099 | 0.096 | 0.072 | 0.118 | 0.117 | 0.116 | 0.097 | 0.090 |
Burundi | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.092 | 0.117 | 0.102 | 0.093 | 0.090 |
Afghanistan | 0.108 | 0.087 | 0.104 | 0.096 | 0.095 | 0.118 | 0.096 | 0.091 | 0.093 | 0.112 |
Cameroon | 0.108 | 0.106 | 0.118 | 0.096 | 0.095 | 0.107 | 0.096 | 0.091 | 0.093 | 0.090 |
Iraq | 0.108 | 0.106 | 0.118 | 0.113 | 0.072 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
São Tomé and Príncipe | 0.108 | 0.106 | 0.118 | 0.096 | 0.072 | 0.092 | 0.109 | 0.116 | 0.093 | 0.090 |
Myanmar | 0.108 | 0.106 | 0.118 | 0.113 | 0.072 | 0.092 | 0.117 | 0.091 | 0.093 | 0.090 |
Angola | 0.108 | 0.106 | 0.109 | 0.096 | 0.072 | 0.118 | 0.117 | 0.091 | 0.093 | 0.090 |
Gabon | 0.108 | 0.106 | 0.118 | 0.096 | 0.085 | 0.092 | 0.096 | 0.116 | 0.093 | 0.090 |
Liberia | 0.108 | 0.087 | 0.099 | 0.096 | 0.095 | 0.092 | 0.117 | 0.091 | 0.103 | 0.112 |
Guinea-Bissau | 0.108 | 0.092 | 0.099 | 0.121 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Timor-Leste | 0.108 | 0.098 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.093 | 0.090 |
Syrian Arab Republic | 0.108 | 0.087 | 0.118 | 0.106 | 0.072 | 0.118 | 0.117 | 0.091 | 0.093 | 0.090 |
Bangladesh | 0.108 | 0.106 | 0.099 | 0.096 | 0.072 | 0.118 | 0.117 | 0.101 | 0.093 | 0.090 |
Equatorial Guinea | 0.108 | 0.106 | 0.118 | 0.111 | 0.072 | 0.092 | 0.096 | 0.091 | 0.116 | 0.090 |
Haiti | 0.087 | 0.096 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.116 | 0.090 |
Congo, Rep | 0.108 | 0.106 | 0.099 | 0.104 | 0.072 | 0.118 | 0.096 | 0.091 | 0.116 | 0.090 |
Chad | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.092 | 0.096 | 0.100 | 0.116 | 0.090 |
Congo, Dem. Rep | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.103 | 0.117 | 0.091 | 0.093 | 0.090 |
South Sudan | 0.108 | 0.106 | 0.099 | 0.109 | 0.072 | 0.092 | 0.117 | 0.091 | 0.116 | 0.090 |
Central African Republic | 0.108 | 0.106 | 0.099 | 0.121 | 0.072 | 0.099 | 0.096 | 0.116 | 0.093 | 0.090 |
Libya | 0.108 | 0.087 | 0.118 | 0.096 | 0.072 | 0.092 | 0.117 | 0.116 | 0.104 | 0.090 |
Yemen, Rep | 0.108 | 0.087 | 0.099 | 0.121 | 0.072 | 0.099 | 0.117 | 0.091 | 0.116 | 0.090 |
Venezuela, RB | 0.087 | 0.106 | 0.099 | 0.121 | 0.095 | 0.099 | 0.096 | 0.091 | 0.116 | 0.090 |
Eritrea | 0.108 | 0.087 | 0.099 | 0.121 | 0.072 | 0.099 | 0.117 | 0.091 | 0.116 | 0.090 |
Somalia | 0.108 | 0.087 | 0.102 | 0.121 | 0.072 | 0.092 | 0.096 | 0.116 | 0.116 | 0.090 |
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Maricic, M., Jeremic, V. Imposing unsupervised constraints to the Benefit-of-the-Doubt (BoD) model. METRON 81, 259–296 (2023). https://doi.org/10.1007/s40300-023-00254-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40300-023-00254-3