Spatial Analysis of Urban Competitiveness in Metro Manila and Its Periphery: Identifying Leading and Lagging Clusters through CMCI Indices (2015-2023)
Keywords: Urban Competitiveness, CMCI, Spatial Autocorrelation, Core-Periphery, Moran’s I
Abstract. Local competitiveness has become a critical policy concern in the Philippines, as cities within and around Metro Manila experience uneven growth trajectories. The Cities and Municipalities Competitiveness Index (CMCI) of the Department of Trade and Industry provides a systematic benchmarking framework, yet the spatial dynamics of competitiveness across Metro Manila and its contiguous local government units (LGUs) remain underexplored. This study examined whether competitiveness is randomly distributed or spatially clustered within the National Capital Region (NCR) and its first- and second-degree neighboring LGUs, using CMCI data from 2015, 2020, and 2023. A two-stage methodological framework was applied: (1) exploratory visualization through GIS-based choropleth mapping, and (2) inferential spatial statistics using Global Moran’s I and Local Indicators of Spatial Association (LISA), complemented by standardized z-scores for identifying leading and lagging LGUs. Results revealed shifting spatial dynamics: significant clustering in 2015, largely random patterns in 2020, and renewed clustering in 2023, particularly in Economic Dynamism and Innovation. A high-performing “hot spot” cluster was observed in the core LGU of Makati City, while a spatial outlier was observed in Pasay City, being a high scorer surrounded with lower scores. Sub-pillar analysis highlighted common drivers of competitiveness, notably infrastructure, governance efficiency, business registration, investment inflows, and health service capacity. Findings underscore the polycentric nature of Metro Manila’s competitiveness and its uneven spillovers into adjacent LGUs, with implications for metropolitan-scale cooperation, regional planning, and policies that promote balanced growth across localities.
