Abstract
Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects.
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The datasets generated and/or analyzed during the current study are available in the World Bank database 2018 (https://databank.worldbank.org/data/source/world-development-indicators#). UNESCO Institute of Statistics (UNESCO Institute for Statistics. 2013. Data Centre. Accessed November, 2013 http://stats.uis.unesco.org).
Notes
Published by Social Progress Imperative can be retrieved from https://www.socialprogress.org/.
A comprehensive review of literature on construction of development index can be found in Basel et al. (2020).
Handbook on Constructing Composite Indicator—methodology and user guide, OECD (2008).
As per the UN reports on World Economic Situation and Prospects (WESP), 2019. Can be accessed from https://unctad.org/en/pages/publications/World-Economic-Situation-and-Prospects-(Series).aspx.
As per the Morgan Stanley Capital International Emerging Market Index 24 developing economies qualify as emerging markets, out of these 9 are present in C2 and remaining 9 are in C3, 6 are not included in this study.
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Appendix 1: Grey relational coefficient
Appendix 1: Grey relational coefficient
Country | Social | Sustainability | Economic | Institution |
|---|---|---|---|---|
Albania | 0.649 | 0.625 | 0.496 | 0.778 |
Algeria | 0.728 | 0.484 | 0.406 | 0.590 |
Argentina | 0.733 | 0.574 | 0.688 | 0.472 |
Armenia | 0.739 | 0.566 | 0.495 | 0.498 |
Australia | 0.424 | 0.691 | 0.668 | 0.515 |
Austria | 0.461 | 0.659 | 0.682 | 0.485 |
Azerbaijan | 0.646 | 0.454 | 0.397 | 0.520 |
Bahrain | 0.734 | 0.610 | 0.653 | 0.670 |
Bangladesh | 0.639 | 0.610 | 0.641 | 0.490 |
Belarus | 0.531 | 0.727 | 0.456 | 0.412 |
Belgium | 0.652 | 0.609 | 0.574 | 0.650 |
Benin | 0.590 | 0.573 | 0.521 | 0.536 |
Bolivia | 0.635 | 0.565 | 0.535 | 0.483 |
Botswana | 0.793 | 0.500 | 0.612 | 0.483 |
Brazil | 0.622 | 0.499 | 0.470 | 0.521 |
Bulgaria | 0.626 | 0.557 | 0.502 | 0.680 |
Cambodia | 0.639 | 0.518 | 0.543 | 0.602 |
Cameroon | 0.625 | 0.611 | 0.593 | 0.451 |
Canada | 0.545 | 0.662 | 0.821 | 0.495 |
Chile | 0.676 | 0.505 | 0.584 | 0.761 |
China | 0.664 | 0.544 | 0.475 | 0.432 |
Colombia | 0.661 | 0.482 | 0.625 | 0.539 |
Congo, Dem. Rep. | 0.598 | 0.596 | 0.519 | 0.477 |
Costa Rica | 0.598 | 0.605 | 0.502 | 0.698 |
Croatia | 0.733 | 0.711 | 0.542 | 0.974 |
Cyprus | 0.553 | 0.835 | 0.726 | 0.508 |
Czech Republic | 0.592 | 0.642 | 0.509 | 0.732 |
Denmark | 0.686 | 0.487 | 0.655 | 0.602 |
Dominican Republic | 0.629 | 0.725 | 0.483 | 0.620 |
Ecuador | 0.564 | 0.599 | 0.497 | 0.433 |
Egypt, Arab Rep. | 0.660 | 0.704 | 0.503 | 0.628 |
El Salvador | 0.684 | 0.862 | 0.567 | 0.600 |
Estonia | 0.729 | 0.496 | 0.544 | 0.740 |
Finland | 0.807 | 0.481 | 0.615 | 0.889 |
France | 0.686 | 0.687 | 0.724 | 0.743 |
Gabon | 0.642 | 0.462 | 0.548 | 0.481 |
Germany | 0.787 | 0.614 | 0.598 | 0.572 |
Ghana | 0.622 | 0.533 | 0.379 | 0.730 |
Greece | 0.668 | 0.708 | 0.787 | 0.517 |
Guatemala | 0.627 | 0.524 | 0.582 | 0.459 |
Haiti | 0.630 | 0.619 | 0.448 | 0.826 |
Honduras | 0.627 | 0.553 | 0.524 | 0.544 |
Hungary | 0.692 | 0.618 | 0.624 | 0.747 |
Iceland | 0.692 | 0.640 | 0.466 | 0.480 |
India | 0.618 | 0.570 | 0.494 | 0.425 |
Indonesia | 0.722 | 0.524 | 0.546 | 0.644 |
Iran, Islamic Rep. | 0.624 | 0.798 | 0.494 | 0.457 |
Ireland | 0.647 | 0.722 | 0.540 | 0.500 |
Israel | 0.676 | 0.641 | 0.440 | 0.469 |
Italy | 0.718 | 1.000 | 0.732 | 0.422 |
Jamaica | 0.699 | 0.636 | 0.506 | 0.576 |
Japan | 0.437 | 0.965 | 0.512 | 0.600 |
Jordan | 0.696 | 0.615 | 0.431 | 0.431 |
Kazakhstan | 0.718 | 0.458 | 0.439 | 0.363 |
Kenya | 0.632 | 0.708 | 0.472 | 0.477 |
Korea, Rep. | 0.554 | 0.566 | 0.467 | 0.574 |
Kuwait | 0.504 | 0.654 | 0.416 | 0.729 |
Kyrgyz Republic | 0.698 | 0.538 | 0.470 | 0.538 |
Malaysia | 0.640 | 0.713 | 0.517 | 0.390 |
Malta | 0.559 | 0.656 | 0.578 | 0.649 |
Mauritius | 0.540 | 0.588 | 0.561 | 0.551 |
Mexico | 0.651 | 0.703 | 0.520 | 0.725 |
Moldova | 0.606 | 0.441 | 0.447 | 0.581 |
Mongolia | 0.641 | 0.458 | 0.396 | 0.454 |
Morocco | 0.651 | 0.579 | 0.468 | 0.402 |
Mozambique | 0.581 | 0.461 | 0.348 | 0.478 |
Nepal | 0.530 | 0.455 | 0.617 | 0.538 |
Netherlands | 0.792 | 0.618 | 0.638 | 0.480 |
Nicaragua | 0.596 | 0.578 | 0.557 | 0.499 |
Norway | 1.000 | 0.542 | 0.635 | 0.861 |
Pakistan | 0.579 | 0.664 | 0.500 | 0.502 |
Panama | 0.697 | 0.580 | 0.525 | 0.692 |
Paraguay | 0.725 | 0.615 | 0.422 | 0.613 |
Peru | 0.607 | 0.557 | 0.511 | 0.691 |
Philippines | 0.539 | 0.454 | 0.611 | 0.429 |
Poland | 0.565 | 0.476 | 0.469 | 0.784 |
Portugal | 0.554 | 0.669 | 0.740 | 0.703 |
Romania | 0.656 | 0.456 | 0.462 | 0.455 |
Russian Federation | 0.588 | 0.530 | 0.533 | 0.488 |
Saudi Arabia | 0.838 | 0.574 | 0.419 | 0.472 |
Senegal | 0.517 | 0.525 | 0.616 | 0.691 |
Singapore | 0.873 | 0.677 | 0.486 | 0.759 |
Slovak Republic | 0.708 | 0.676 | 0.535 | 0.616 |
Slovenia | 0.853 | 0.768 | 0.682 | 0.620 |
South Africa | 0.575 | 0.635 | 0.562 | 0.467 |
Spain | 0.711 | 0.782 | 0.737 | 1.000 |
Sri Lanka | 0.774 | 0.589 | 0.474 | 0.697 |
Sudan | 0.529 | 0.726 | 0.412 | 0.487 |
Sweden | 0.764 | 0.524 | 0.632 | 0.765 |
Switzerland | 0.863 | 0.757 | 0.677 | 0.794 |
Tanzania | 0.476 | 0.581 | 0.475 | 0.714 |
Thailand | 0.992 | 0.660 | 0.500 | 0.545 |
Togo | 0.468 | 0.623 | 0.431 | 0.495 |
Tunisia | 0.699 | 0.669 | 0.752 | 0.472 |
Turkey | 0.643 | 0.627 | 0.594 | 0.671 |
Ukraine | 0.644 | 0.613 | 0.503 | 0.797 |
United Kingdom | 0.781 | 0.695 | 0.815 | 0.607 |
United States | 0.553 | 0.570 | 1.000 | 0.832 |
Uruguay | 0.705 | 0.533 | 0.537 | 0.568 |
Vietnam | 0.641 | 0.666 | 0.438 | 0.404 |
Yemen, Rep. | 0.552 | 0.659 | 0.768 | 0.504 |
Zimbabwe | 0.784 | 0.597 | 0.426 | 0.333 |
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Basel, S., Gopakumar, K.U. & Rao, R.P. Classification of countries based on development indices by using K-means and grey relational analysis. GeoJournal 87, 3915–3933 (2022). https://doi.org/10.1007/s10708-021-10479-2
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DOI: https://doi.org/10.1007/s10708-021-10479-2