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by Ramoncito G. Cambel Institute of Statistics University of the Philippines Los Baños

CONSTRUCTION OF A STATISTICAL INDEX USING THE MILLENNIUM DEVELOPMENT GOAL INDICATORS AS A MEASURE OF A COUNTRY’S MULTIDIMENSIONAL DEVELOPMENT. by Ramoncito G. Cambel Institute of Statistics University of the Philippines Los Baños. Institute of Statistics

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by Ramoncito G. Cambel Institute of Statistics University of the Philippines Los Baños

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  1. CONSTRUCTION OF A STATISTICAL INDEX USING THE MILLENNIUM DEVELOPMENT GOAL INDICATORS AS A MEASURE OF A COUNTRY’S MULTIDIMENSIONAL DEVELOPMENT by Ramoncito G. Cambel Institute of Statistics University of the Philippines Los Baños Institute of Statistics University of the Philippines Los Baños

  2. I. INTRODUCTION Determination of economic growth is used as a basis for policies regarding the reduction of poverty, unemployment, and other social problems GDP Economic growth Different organizations formulated different indices that assess economic, government, and even human development issues. Institute of Statistics University of the Philippines Los Baños

  3. I. INTRODUCTION This study generally aims to construct a statistical index which could serve as a measure of a country’s multidimensional development. Specifically, it aims to: • compare the constructed statistical index with the existing measure(a) of economic growth and human development; and - evaluate the statistical properties of the constructed index. Institute of Statistics University of the Philippines Los Baños

  4. II. METHODOLOGY Data Source Indicators for monitoring progress of the eight Millennium Development Goals were used in the study (retrieved from the World Bank’s site). Index Construction The analysis of data considered only a specific year which has the most number of available indicators. Indicators were then subjected to Principal Component Analysis to reduce its dimensionality. The identified principal components with high loadings were used in the construction of the statistical index. Institute of Statistics University of the Philippines Los Baños

  5. II. METHODOLOGY Statistical Properties of Index The methodology used by Ynion in 2011 was employed. The population of the statistical indices across countries was considered as the ‘surrogate population’. The mean value of the constructed indices across countries was computed. Samples of size m were repeatedly drawn from the population of the constructed statistical indices across countries for different number of resamples. Based on the bootstrap samples, statistical properties of the index were checked. Institute of Statistics University of the Philippines Los Baños

  6. III. RESULTS AND DISCUSSION 3indicators 2 indicators 5indicators 2indicators 2indicators 2indicators 6indicators 5indicators Principal Component Analysis 1 2 Institute of Statistics University of the Philippines Los Baños

  7. III. RESULTS AND DISCUSSION Table 1. Factor loadings of the variables in the Multidimensional Development Index Institute of Statistics University of the Philippines Los Baños

  8. III. RESULTS AND DISCUSSION Lowest index value = -18.45922 Highest index value = 12.65043 Mean index = 0.2611 Median index = 1.5731 Standard deviation = 7.4304 Sweden tops the list with an index value of 12.6503, followed by Finland (12.0564), and Luxembourg (11.8064). On the other hand, Niger, Sierra Leone, and Chad are the countries with the lowest development. Fig. 1. Distribution of the Multidimensional Development Index Institute of Statistics University of the Philippines Los Baños

  9. III. RESULTS AND DISCUSSION Based on the Spearman rank correlation analysis, there is a very strong positive association (rs = 0.9608) between the ranking of countries using the proposed index and that of using HDI. Also, there exists a very strong positive association (rs = 0.9214) between the ranking of countries using the proposed index and that of using MPI. Bootstrap resampling technique was used to evaluate the statistical properties of MDI. Bootstrap resamples, B, of size 500, 750, 1000, 1500, and 2000 and different sample sizes of 5%, 10%, 15%, 20%, 25%, and 30% were considered. Institute of Statistics University of the Philippines Los Baños

  10. III. RESULTS AND DISCUSSION Fig. 2 Estimated mean MDI Fig. 3 Bias of the estimated mean MDI The bias of the estimated mean approaches zero as the sample size increases. Based on this, the proposed index is “consistent” as shown graphically. In addition, standard error tend to approach to 0 as the sample size increases. Fig. 4 Standard error of the estimated mean MDI Institute of Statistics University of the Philippines Los Baños

  11. IV. SUMMARY AND CONCLUSION Principal Component Analysis was used to determine the weights of the indicators included in the study. The proposed index, the Multidimensional Development Index (MDI), serves as an alternative measure of a country’s development by looking on aspects other than economic growth. It encompasses multidimensional development by looking at MDG targets: eradicating extreme poverty and hunger, reducing child mortality, improving maternal health, ensuring environmental sustainability, and developing a global partnership for development. The statistical index was found to possess desirable characteristics of an estimator. Institute of Statistics University of the Philippines Los Baños

  12. THANK YOU FOR LISTENING! For additional information, please contact: Author’s name Ramoncito G. Cambel Designation Instructor Affiliation Institute of Statistics, UPLB Address University of the Philippines, Los Baños, Laguna Tel. no. (049) 536-2381 Email address rgcambel2@up.edu.ph Institute of Statistics University of the Philippines Los Baños

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