TECHNICAL EFFICIENCY OF LAND AND BUILDING TAX COLLECTION IN THE BANGKOK METROPOLITAN ADMINISTRATION, 2020-2024: EVIDENCE FROM DATA ENVELOPMENT ANALYSIS

Abstract

This study examines the efficiency of land and building tax collection at the district office level in Bangkok for fiscal years 2020 to 2024, following initial implementation of the Land and Building Tax Act B.E.2562 (2019). Despite nationwide enforcement of the Act, empirical evidence on district-level tax collection efficiency in a large metropolitan context remains limited. Secondary data is gathered on tax revenue, operational input, and district-level contextual factors for all 50 district offices. Efficiency is evaluated by data envelopment analysis (DEA) with the Banker, Charnes, and Cooper (BCC) model with variable returns to scale (VRS) and an output-oriented approach to estimate pure technical efficiency (PTE) and scale efficiency (SE). Multiple linear regression (MLR) using ordinary least squares (OLS) is further employed to examine links between tax revenues and selected operational and contextual variables. Qualitative data from in-depth interviews with district revenue officers is incorporated to support interpretation of administrative constraints. Results indicate overall improvement in pure technical efficiency over time, although major differences persist between districts. Pure technical rather than scale inefficiency predominates, suggesting that internal management and resource use are suboptimal. Regression findings imply that several operational and contextual factors are statistically associated with tax revenue performance, but these relationships should not be interpreted as causal. This empirical evidence on local tax collection performance under urban structural constraints highlights the importance of improving internal processes with apt consideration of scale conditions across diverse districts.

Keywords: Land and Building Tax, Tax Collection Efficiency, Data Envelopment Analysis (DEA)