Improving the Efficiency of Local Government Decision-Making through Econometric Modeling and Forecasting - Rakhmonjonovich, Akhmedov Farkhod (Academia Open, 2026)
General Background: Effective decision-making in local government is essential for sustainable socio-economic development and optimal resource allocation. Specific Background: This study analyzes socio-economic indicators in the Namangan region from 2018–2025, including adopted decisions, poverty, unemployment, employment generation, and infrastructure access. Knowledge Gap: Despite increasing use of quantitative methods, integrated econometric modeling linking these indicators to decision-making efficiency remains insufficiently explored. Aims: The study aims to develop econometric models, estimate their parameters, and generate forecasts for 2026–2030 to support scientifically grounded decision-making. Results: Regression and polynomial models estimated using the least squares method demonstrate strong explanatory power, with key indicators such as unemployment rate, job creation, and access to drinking water showing significant relationships with poverty and governance outcomes; the multivariate model explains up to 94% of variation. Forecast results indicate declining poverty and unemployment alongside improvements in infrastructure and decision volume. Novelty: The study integrates multiple socio-economic variables into a unified econometric framework for modeling and forecasting local governance efficiency. Implications: The findings support evidence-based policymaking, improved resource allocation, and systematic monitoring of socio-economic development at the regional level. Highlights:• Multivariate regression explains major variation in poverty dynamics• Forecast projections indicate consistent socio-economic improvement trends• Infrastructure and employment variables show strong statistical relationships Keywords: Local Government, Decision-Making, Econometric Model, Forecasting, Socio-Economic Indicators