Econometric Analysis and Forecasting of Financial Performance Indicators for Budget Management in Higher Education
DOI:
https://doi.org/10.31150/ajebm.v8i7.3796Keywords:
Finance in Higher Education, Budgetary Management, Econometric Assessment, Financial Performance Metrics, Predictive Models, Panel Data Analysis, Resource Distribution, Financial ViabilityAbstract
Effective financial management is critical for ensuring sustainability and strategic development in higher education institutions (HEIs), particularly under increasing global demands and financial constraints. Uzbekistan's HEIs face challenges in modernizing financial planning practices to align with changing economic conditions and limited government funding structures. There is insufficient integration of advanced econometric forecasting models, such as ARIMA, into HEI budget management processes to improve accuracy and long-term decision-making. This study aims to apply ARIMA modelling to forecast financial performance indicators, specifically total revenue growth rates, to support strategic budget management at Tashkent State University of Economics. The ARIMA (1,1,0) model was developed and tested, demonstrating strong predictive accuracy for total revenue growth rates from 2023 to 2027. Forecasts predict annual growth rates between 121.34% and 138.50%, highlighting income volatility and emphasizing the importance of diversified revenue strategies. This research integrates ARIMA-based econometric forecasting with HEI financial management in Uzbekistan, offering a quantitative tool for improving budget planning precision. Incorporating ARIMA forecasts into HEI financial systems can strengthen transparency, risk mitigation, and strategic resource allocation. The findings provide actionable recommendations for university administrators and policymakers to modernize financial management frameworks, enhancing institutional resilience and long-term sustainability.
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