Giám sát quản lý kinh tế xã hội của vùng Nam Bộ ở Việt Nam: Tiếp cận phân cụm

Nội dung text: Giám sát quản lý kinh tế xã hội của vùng Nam Bộ ở Việt Nam: Tiếp cận phân cụm

1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 THE MONITOR OF SOCIO-ECONOMIC ADMINISTRATION OF SOUTHERN REGION IN VIETNAM: CLUSTER APPROACH GIÁM SÁT QUẢN LÝ KINH TẾ XÃ HỘI CỦA VÙNG NAM BỘ Ở VIỆT NAM: TIẾP CẬN PHÂN CỤM Huynh Ngoc Chuong, Bui Hong Ngoc VNUHCM-University of Economics and Law chuonghn@uel.edu.vn Abstract One of the targets of Vietnam in the national development strategy in the period 2011 - 2020 is growth and sustainable development with the equity and social enhancement. Vietnam yearns for reaching the economic efficiency but causing no harm to the environment and resources. The population of the Southern takes up more than 36% that of the country. Besides, the Southern contribute significantly to the the foundation of agriculture and industry for Vietnam. Thus, the analysis attempts to figure out the monitor of social economic administration of Southern region in Vietnam with the application of cluster approach in 2011, 2017 and period 2011 - 2017. The result shows different fluctuations in the clusters in different time considered. Keywords: Cluster analysis, socio-economic governance, Southern region. Tóm tắt Một trong các mục tiêu của Việt Nam trong chiến lược phát triển giai đoạn 2011 - 2020 là tăng trưởng và phát triển bền vững đi đôi với công bằng xã hội. Việt Nam đã đạt được một số hiệu quả kinh tế nhưng cũng tác động đến môi trường và các nguồn tài nguyên. Bên cạnh đó, vùng Nam bộ ở Việt Nam chiếm đến 36% dân số cả nước, là một nền tảng cốt lõi trong nông nghiệp và công nghiệp của Việt Nam. Do đó, nghiên cứu này cố gắng đưa ra một bức tranh về các chỉ báo quản trị kinh tế xã hội của các địa phương trong vùng với cách tiếp cận phân tích cụm ở các thời điểm 2011, 2017 và giai đoạn 2011 - 2017. Kết quả nghiên cứu cho thấy, các biến động khác nhau và các nhóm cụm thay đổi khác biệt qua thời gian. Từ khóa: Phân tích cụm, quản trị kinh tế xã hội, vùng Nam bộ. 1. Introduction In the national development strategy in the period 2011 - 2020, Vietnam set a target in which growth and sustainable development goes along with the equity and social improvement, and the economic efficiency is harvested without harming the environment and resources. Vietnam has to face various issues during the sustainable development process, for instance, the economic development is unsustainable and there is no linkage among provinces and cities. Besides, the problems about the East Sea disputes, employment, corruption, infrastructure quality, income, quality of education, national defense and security attract the concern of the citizens (UNDP, 2011; UNDP, 2015). At the local governance level, many socio-economic criteria that local governments can govern or control when decentralized (Anh, 2012) Whilst, the environmental issues often relate to the ability in cooperation among provinces, regions based on the natural characteristics, the valley, the problem of producing, and pollution. Hence, using the socio-economic criteria to analyze the ability of local governance is applicable. The Southern lies in the south of Vietnam, including two subregions: South East with the area and population is 23.564,4 km2 and 16,64 million people, respectively. There are 6 provinces and cities in this subregion: Ba Ria - Vung Tau Province, Dong Nai Province, Ho Chi Minh City, Binh Duong Province, Binh Phuoc Province, and Tay Ninh Province. The second subregion is South West, which has 13 414
2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 provinces and cities: Long An Province, Tien Giang Province, Dong Thap Province, Ben Tre Province, Vinh Long Province, Tra Vinh Province, Hau Giang Province, Soc Trang Province, An Giang Province, Kien Giang Province, Bac Lieu Province, Ca Mau Province, and Can Tho City. The area and population 2 of this subregion is 40.548,2 km and 17,3 million people, respectively. The Southern takes up more than 36% population of the country and contribute the foundation of agriculture and industry for Vietnam. The target of this research is to cluster the local based on the socio-economic criteria. This is also a way to categorize the governance quality in the social and economic development process at the provinces of Vietnam. 2. Literature review 2.1. Monitor of Local socio-economic indicators Indicator is one of the most crucial factors of empirical research. According to Innes (1990), indicators are “a set of rules for gathering and organizing data so they can be assigned meaning” (Hoernig & Seasons, 2004). Researchers suppose that social indicators should be established due to the advantages and disadvantages of the dependence on economic measures (Hoernig & Seasons, 2004). Three characteristics of social indicators: (1) relating to individual and household than other social aggregates; (2) relating to broader goals of society; (3) measuring outputs instead of inputs are the notion of Noll (2002). Analyzing the quality of social economic administration is one of the topics attracting the varied scholars. The approach of using cluster analysis is plausible in investigating the fluctuation of the social and economic improvement and public administration. In the research of Mlachila and others (2016), the authors investigate the quality growth index based on the various indicators. 2.2. Empirical Approach Our analysis does not figure out a general index to scrutinize the quality of social and economic administration. Instead, the variables considered in the study are divided into different clusters. From these clusters, it is plausible to evaluate the changes of the provinces/cities. The paper conducts the cluster of local’s social economic governance quality based on 7 socio- economic criteria: GRDP capita (cap_grdp), FDI capita (cap_fdi), PAPI (papi), household’s average income (income), inversed GINI (gini_inverse), the rate of adult literacy (literacy), the immunization rates for children (medi). The 5 indicators – GRDP capita, FDI capita, PAPI, household’s average income, inversed GINI are evidently close to sustainable economic development. However, the other two indicators – the rate of adult literacy (stand for education) and immunization rates for children (stand for health) also affect significantly growth pace, since they can influence the productivity of the economy. According to Mlachila et al. (2016), a country’s level of human capital - education and health - may influence the productivity of its economy, and hence its growth pace, and vice versa. The variable of import and export can be thought as good one. However, the appearance of these variables can force the results implausible, since not all the provinces/cities have the harbor where the trading activities can be taken place. Furthermore, the factory of a province/city can be allocated at another harbor-city; the trading activities will be counted for the harbor-city, not for the city owning the factory. The categorization of social economic governance quality is evaluated in terms of 2 aspects: point of time (the year 2011, and the year 2017) and period of time (2011 - 2017) based on the fluctuation of the indicators in the period. 3. Data and methodology 3.1. Data collection The data in the research are collected from Statistical Yearbook of southern provinces and cities in the in the time period 2011 - 2017. 415
3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 3.2. Methodology - Cluster Analysis The cluster analysis is used to investigate the quality of social economic administration of the southern region. There is a myriad of scholars applying cluster analysis to establish the indexes or evaluate, categorize the groups based on the observations. Cluster method attempts to determine the natural groupings (or clusters) of observations. The cluster analysis does not aim for verifying the hypothesis but likely the art in data mining in order to classiffy the observers in datasets (Everitt, Landau, Leese, & Stahl, 1980; Wilks, 2011). Mathematically, the K-mean can be represented by the general equation for a mixture of distributions: Where K is the number of clusters, is the probability of observing the kth cluster, and is the probability distribution function of that generates the data observed in the kth cluster. The technique of cluster analysis can support the analyst in checking and categorizing the clusters based on various criteria, sometimes the number of criteria can reach 30 (Milligan & Cooper, 1985). In this research, 3 indexes used are: the proportional reduction of error (PRE) coefficient (Makles, 2012), lower bound technique (LBT) (Steinley & Brusco, 2011) and Calinski-Harabasz pseudo-F index (Milligan & Cooper, 1985). The larger the value of PRE and Calinski, and the smaller the LBT, the better the results are. The steps analyzing cluster in the research: Step 1: Data collection from province’s statistic yearbook. Step 2: Standardize variables (variables in year 2011, 2017 and the changes in period 2011-2017). Step 3: Estimating K-mean Cluster the dataset with the range of the number of clusters: 2-10. Step 4: Choosing the optimal clusters through the post-estimation indexes. 4. Results 4.1. Variables Description Table 1 is the statistical description of the variables used in the study and it has three parts. The first part and the second part show the descriptive statistics of variable in 2011 and 2017, respectively. Regard to the economic index, average GRDP capita stands at more than 43 million per year. The gap among provinces/cities is high (std.dev more than mean). The maximum of GRDP capita is 250 million per capita; while this figure for the minimum province/city is only 19 million per capita. This happens similarly for other indexes. Concerning social index and public administration, there is no significant gap among the province/city, except the case of medical index. Table 1: Statistical Description in year 2011, 2017 Variable Obs Mean Std. Dev. Min Max cap_grdp2011 19 43.435 51.626 19.1084 249.4882 cap_fdi2011 19 2.615 5.387 0.0003 22.8401 gini2011 19 0.359 0.020 0.33 0.39 income2011 19 1.791 0.564 1.18 3.2 papi2011 19 35.812 2.125 31.93 39.95 literacy2011 19 93.484 3.255 85.8 97.5 416
4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 medi2011 19 91.821 9.333 64 99.4 cap_grdp2017 19 64.792 52.814 31.083 249.496 cap_fdi2017 19 3.964 5.982 0.017 19.067 gini2017 19 0.365 0.022 0.33 0.42 income2017 19 3.614 0.988 2.51 5.91 papi2017 19 36.883 1.547 33.49 39.52 literacy2017 19 94.347 2.626 88.5 98.5 medi2017 19 95.837 2.740 88.5 98.3 The last part displays the statistical description of variables in the period 2011 – 2017. The provinces/cities in the region show positive changes in terms of economics – income. The GRDP and FDI index all increase. However, this period also witnesses the classification among provinces/cities in growth and FDI attraction aspect (the std. dev. is high for all the variables investigated). Regarding social aspect, GINI index has a low average increase. Whereas, medical index rises markedly. This proves the improvement of medical system of the region. Concerning public administration, there is a great fluctuation in the process of enhancing public administration of province/city. Several provinces/cities possess greater improvement than the average of enhancement of the region. Table 2: Statistical Description in period 2011-2017 Variable Obs Mean Std. Dev. delta_cap_grdp 19 21.357 19.797 delta_cap_fdi 19 1.349 3.223 delta_papi 19 1.071 2.390 delta_income 19 1.823 0.506 delta_gini 19 0.005 0.011 delta_literacy 19 0.863 1.368 delta_medi 19 4.016 9.068 4.2. Cluster Estimation 4.2.1. The number of cluster estimation The research applies 3 criteria in the selection of the number of suitable clusters: PRE, LBT, Calinski. The result shows that 19 provinces are divided into 3 clusters in 2011. However, the result for the year 2017 is 6 clusters. In the period 2011 - 2017, the number of clusters is 5. Table 3: The result of cluster estimation k (cluster Year WSS log(WSS) eta-squared PRE lbt calinski number) Year 2011 3 54.611 4 0.567 0.468 0.433 10.458 Year 2017 6 21.939 3.088 0.826 0.402 0.174 12.333 Period 2011-2017 5 41.365 3.7224 0.6717 0.3596 0.3283 7.1612 Source: Authors’ estimation 417
5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Cluster classification to calibrate the fluctuation in the period 2011 – 2017 is more evident than that of the analysis in the point of time (2011 and 2017). Thus, despite the stability in the cluster classification, the criteria to select the number of clusters still remain significant difference. Figure 1: The selection of the number of clusters 4.2.2. Cluster analysis In 2011, the provinces and cities are divided into 3 clusters, in which Cluster 1 has only one province – Ba Ria Vung Tau, Cluster 3 has 3 provinces (Tra Vinh, Soc Trang, and An Giang), and Cluster 2 has 15 provinces. All the indexes of Ba Ria Vung Tau are high. The four highest indices are GDP per capita, FDI, public administration (papi), and inequality (highest GINI). The abovementioned indexes prove that Ba Ria Vung Tau is good at economic administration but having high inequality (while other indexes are ranked at position 3 and 4). 3 provinces – Tra Vinh, Soc Trang, and An Giang belong to Cluster 3. In 2011, these provinces possess the lowest social economic indexes among 19 provinces and cities in the Southern. Specifically, the indexes of Tra Vinh, for instance, GDP per capita, education (the rate of adult literacy), public administration stand at the lowest position; the medical and income index belong to the second lowest group. Whilst, GDP per capita and educational index of Soc Trang are ranked at the lowest and second lowest group, respectively. Concerning An Giang, the lowest position is medical index and others are also low. Hence, Cluster 3 is the low social economic index cluster. Cluster 2, which has 15 provinces and cities, the socio-economic indexes are varied. Ho Chi Minh City and Binh Duong stand at the top among the income and education indexes. Tien Giang and Hau Giang possess the highest medical index. Cau Mau and Tay Ninh belong to the lowest group about FDI. Almost all of the indexes are varied and the gap among the provinces and city is insignificant. 418
6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Table 4: The result of cluster analysis in 2011 Year 2011 Cluster 1 Cluster 2 Cluster 3 Binh Duong Ca Mau Ba Ria-Vung Tau Dong Nai Binh Phuoc Tra Vinh Ho Chi Minh City Tay Ninh Soc Trang Tien Giang Long An An Giang Dong Thap Ben Tre Kien Giang Vinh Long Hau Giang Can Tho Bac Lieu Good economic administration Average socio-economic administration Bad socio- but high inequality. Great trade- economic off between equity and administration economics. The result in Table 5 shows that in 2017, the provinces and cities are divided into 6 clusters, in which Cluster 1 and Cluster 4 has only one province – Binh Duong and Ba Ria – Vung Tau, respectively. Cluster 2 includes Dong Nai and Ho Chi Minh City; Cluster 5 includes Binh Phuoc and An Giang. Cluster 3 has 7 provinces, and Cluster 6 has 6 provinces. Table 5: The result of cluster analysis in 2017 Year 2017 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Ba Ria- Dong Nai Tien Giang Vung Tau Binh Phuoc Tay Ninh Binh Duong Ho Chi Minh City Tra Vinh An Giang Long An Dong Thap Ben Tre Kien Giang Vinh Long Hau Giang Can Tho Soc Trang Bac Lieu Ca Mau Good social Good social Low socio- Good Average economic Low average economic economic quality, economic economic quality and public economic quality quality, but equality, but quality, quality but administration, but but quite good at bad at public average public equality and high low social quality. social quality and administration. administration. public inequality public administration. administration. Regarding Binh Duong, though the indexes of economics and income are high and social index is good, public administration stands at the lowest position among the region (at 19th position). This is an important issue that the province has to consider in giving the adjustment to improve. 419
7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Concerning Ba Ria Vung Tau, all the indexes are high, the highest one is GDP. Other indexes, for example FDI and public administration (papi) are also high. Nevertheless, the inequality index of the province belongs to the lowest group. This shows that Ba Ria Vung Tau administrates economics well but the inequality remains at high level. Cluster 2 has Dong Nai and Ho Chi Minh City. This Cluster has highest indexes at economic aspect, social equality and education. However, the public administration index is at average. These results lead this cluster to be a good socio-economics and equality but average public administration. 7 provinces belong to Cluster 3 are Tien Giang, Tra Vinh, Dong Thap, Kien Giang, Hau Giang Soc Trang and Ca Mau. These provinces possess highest index of inequality and lowest index of income. Besides, the index of public administration is also low (except Dong Thap). Thus, these provinces are ranked to the group in which all the aspects socio-economics, social equality and public administration are low. Cluster 5 has two provinces – Binh Phuoc and An Giang. In 2017, these two provinces have the lowest social indexes, especially, the medical index. Others stand at average level. Therefore, Cluster 5 is listed as the cluster which has average economic quality and public administration and low social index. The provinces in Cluster 6 show a high social equality index but economic index is low. The social index is at average level and public administration is good. Thus, this Cluster is sorted as the cluster having low average economic quality but good at social and public administration. To analyze the fluctuation in economic, social aspect and public administration of the provinces and city in the time period 2011 – 2017, the research categorizes the cluster based on the indexes. The result shows that 5 clusters are sorted based on the fluctuation of indexes in these provinces and cities considered in the study as in Table 6. Table 6: The result of cluster analysis in period 2011 - 2017 Period 2011-2017 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Ba Ria-Vung Tau Binh Duong Tra Vinh Binh Phuoc Tay Ninh Long An An Giang Ben Tre Dong Nai Soc Trang Vinh Long TP. Ho Chi Minh Dong Thap Tien Giang Kien Giang Can Tho Bac Lieu Hau Giang Ca Mau Good improvement in Very good Very good improvement Stagnant Good income and education, improvement in in social issues, equality improvement improvement in but significantly economics and and public in economics, economics but increase in inequality income, bad at social administration, but income. stagnant and environmental stagnant improvement in improvement in criteria, decrease in economics. social issues. public administration Cluster 1 includes 3 provinces - Ba Ria-Vung Tau, Long An, Soc Trang. There is a significant decrease in social equality index in these provinces compared to others, though the income and education are enhanced. Hence, the characteristics of Cluster 1 are good improvement in income and education and the inequality increases markedly. 420
8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 With the specific characteristics, Binh Duong is separated to one cluster in the period 2011 – 2017. Namely, the indexes of very good improvement in economics and income belongs to the top. Whereas, social index and public administration of the province show decreases. Tra Vinh and An Giang are two member of Cluster 3. These provinces prove a marked enhancement in social index, social equality, and public administration. However, the index of economics and income is at average. Thus, good at social improvement, equality and public administration is the characteristic of Cluster 3. 7 provinces of Cluster 4 are Binh Phuoc, Ben Tre, Vinh Long, Dong Thap, Kien Giang, Bac Lieu, Ca Mau. These provinces have slow speed of economic and income enhancement. Cluster 5 and Cluster 6 include the rest of provinces. This Cluster has good improvement in economics but slow in social issue. 5. Discussion This research investigates the categorization of socio-economic quality based on the social and economic indexes and cluster analysis. The result shows that when considering the social and/or economic aspect at different point of time 2011 and 2017, the provinces and cities of south east, especially, Ba Ria Vung Tau, Binh Duong, Dong Nai. Ho Chi Minh City possess very good economic and income quality. During the development process in the period 2011 – 2017, each province/city shows different enhancement. Binh duong proves a very good economic improvement but social enhancement is still slow and public administration decreases. besides, various provinces show improvement in economics but slow enhancement in social aspect and vice versa. REFERENCES [1] Anh, V. T. T. (2012). Phân cấp kinh tế ở Việt Nam nhìn từ góc độ thể chế. Kỷ yếu Diễn đàn Kinh tế mùa Thu 2012 (pp. 226–249). [2] Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (1980). Cluster Analysis. Quality and Quantity, 14(1), 75–100. [3] Hoernig, H., & Seasons, M. (2004). Monitoring of indicators in local and regional planning practice: Concepts and issues. Planning Practice and Research, 19(1), 81–99. 0269745042000246595 [4] Makles, A. (2012). Stata tip 110: How to get the optimal k-means cluster solution. Stata Journal, 12(2), 347–351. [5] Milligan, G. W., & Cooper, M. C. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50(2), 159–179. [6] Noll, H. (2002). Social Indicators and Quality of Life Research: Background, Achievements and Current Trends. Advances in Sociological Knowledge over Half a , 1–36. Retrieved from /download?doi=10.1.1.199.5341&rep=rep1&type=pdf [7] Steinley, D., & Brusco, M. J. (2011). Choosing the Number of Clusters in K-Means Clustering. Psychological Methods, 16(3), 285–297. [8] Undp. (2011). Dịch vụ xã hội phục vụ phát triển con người. Báo cáo Quốc gia về Phát triển Con người năm 2011. [9] UNDP. (2015). Báo cáo Phát triển con người năm 2015: Việc làm vì phát triển con người. [10] Wilks, D. S. (2011). Cluster Analysis. International Geophysics (Vol. 100). 10.1016/B978-0-12-385022-5.00015-4 421