What question did this study set out to answer?

This research aims to analyze the predictability of public expenditures in Türkiye using machine learning methods.

May 1, 2026Open Access

Predictability of Government Expenditures: A Machine Learning Application

TATekin AkdemirAnkara Yıldırım Beyazıt University SKSavaş KAPTANAnkara Yıldırım Beyazıt University

Key Points

This research aims to analyze the predictability of public expenditures in Türkiye using machine learning methods.
Analyzed public expenditures using LSTM and ARIMA models
Focused on historical expenditure values for prediction
Evaluated the impact of macroeconomic and financial variables on predictions
LSTM model showed greater predictive capability than ARIMA model
Public expenditures largely predictable from past values
Contribution of macroeconomic variables to predictions found to be minimal

Abstract

Budget predictions are important for public financial management officials, as one of their primary responsibilities is to control expenditures and revenues in line with the government's macroeconomic goals. In this respect, we empirically analysed the predictability of Türkiye's public expenditures. The results from both the LSTM and ARIMA models showed that public expenditures can be largely predicted from their past values. The LSTM model demonstrated greater predictive capability for public expenditures than the ARIMA model. The contribution of macroeconomic and financial variables to predicting public expenditures was found to be infinitesimal.

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