Towards Sustainable Financing Through Local Tax Revenue Forecasting Using Time Series

Abstract

AbstractTalking about the sustainable development of cities and the advent of the smart cities concept goes through the realization of several projects to serve citizen. However, planning these projects, and even their success, is dependent on financing availability. Good revenue forecasting therefore plays a key role for local authorities as it helps in budgeting, planning and financing projects. For this reason, various types of revenue must be forecast for a specific year, using predictive models with a small margin of error. This work aims to use time series processing models, such as auto-regression (AR), auto-regressive moving average (ARIMA) and seasonal ARIMA (SARIMA), for tax revenue prediction of a local authority in Morocco. Data collected concerns monthly tax receipts for the period from January 2000 to December 2020. Conclusions of this study can help experts in the process of preparing local authorities budgets to get more accuracy.KeywordsFinancial sustainabilityLocal authoritiesPredictionForecastingTax revenueAuto-RegressionARIMASARIMAMorocco