Development of an Alternative Municipal and City Level Competitiveness Index in the Philippines

Year: 2021       Vol.: 70       No.: 1      

Authors: Ramoncito G. Cambel and Zita VJ. Albacea

Abstract:

The Philippine Cities and Municipalities Competitiveness Index (CMCI) by the National Competitiveness Council (NCC) measures the local government unit’s competitiveness. This paper presents the results of a study that employed an alternative weighting method for the indicators through a statistical technique called principal component analysis and factor analysis. Moreover, the study utilized both national census data and administrative data from the government. Four factors were extracted from the available data. The four factors’ compositions are: “Housing and Household Characteristics, Financial Institutions and Capacity of Government for Health Services,” “Establishments for Tourists Accommodation,” Cost of Labor”, and “Capacity of Local Government to Deliver Services.” Unlike the distribution of the NCC’s 2016 competitiveness level of municipalities and cities which is symmetric, the distribution of the proposed alternative competitiveness index is positively skewed. This suggests that only a few municipalities and cities can be considered highly competitive. Moran’s I of 0.3457 proves that there exists positive spatial autocorrelation on the competitiveness level of Philippine municipalities and cities. Municipalities and cities in the Provinces of Bulacan, Pampanga, Cavite, Laguna, Rizal, and Cebu, and also in the National Capital Region are generally identified as those in the highhigh cluster in terms of the proposed alternative 2016 competitiveness level. In contrast, municipalities and cities in the Provinces of Mindoro, Romblon, and Surigao del Norte, and those in the Cordillera Autonomous Region, Ilocos Region, Cagayan Valley Region, and Eastern Visayas Region are generally considered as those in the low-low cluster in terms of the proposed alternative 2016 competitiveness level. Statistical properties of the index such as consistency, accuracy, and precision were then assessed using the bootstrap resampling technique. Results showed that the proposed alternative CMCI is said to be unbiased and mean square error consistent. This indicates the proposed CMCI could be used as an alternative Municipality and City Level Competitiveness Index for the Philippines. This index concentrated on four factors with 33 indicators. These factors are weighted in the index based on their importance in their contribution to the variability of the index.

Keywords: statistical index, spatial analysis, factor analysis

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