SPATIAL AUTOCORRELATION ANALYSIS OF THE FISCAL IMPACTS OF THE COVID-19 PANDEMIC ON PHILIPPINE LOCAL GOVERNMENT UNITS: A STUDY OF LUZON ISLAND
DOI:
https://doi.org/10.21837/pm.v23i35.1689Keywords:
Community Resilience, Disaster Preparedness, Pandemic recovery, Spatial Analysis, Urban and Regional PlanningAbstract
The COVID-19 pandemic has disrupted economic activities across Philippine Local Government Units (LGUs), resulting in significant fiscal implications. This study applied spatial autocorrelation analysis to a dataset covering around 15,480 data points from 645 LGUs (cities and municipalities) spanning 2009-2021, focusing on Locally-sourced Revenue (LSR) and Internal Revenue Allotment (IRA) dependencies. It assessed the fiscal impact of the pandemic by comparing actual 2021 LSR and IRA dependencies with their predicted levels. Pre-pandemic analysis identified "high-high" and "low-low" areas, revealing pronounced clustering of local economic advantages and disadvantages. During the pandemic, the majority of LGUs experienced negligible (36%) or slightly negative (27%) impacts on LSR dependencies with no spatial pattern found (Global Moran's I=0.001). Conversely, severe positive (49%) and negative (46%) impacts occurred on IRA dependencies with clear spatial autocorrelation (Global Moran's I=0.319). To address these disparities, policymakers are urged to implement proactive measures, including (a) targeted resource allocation and investments, (b) incentives for marginalized districts, (c) establishment of growth poles in lagging regions, and (d) enhance economic interconnectivity among LGUs.
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