The accurate forecast of public expenditure is crucial for the success of the new public
financial management approach developed in Turkey since the financial crisis of 2001. The public
institutions are now obliged to align their expenditure with the framework shaped by the Public
Financial Management and Control Law (No: 5018), the Middle-Term Programme of 2010-2012, and
recently the Fiscal Rule envisaged to apply in the next budgetary period. This necessitates a better
forecasting method than the traditional way of budget forecasting, which is typically based on the
expenditures of previous years adjusted by inflation. Particularly focusing on the expenditure side of the
budget, this chapter applies various artificial neural networks models to the expenditures of 1973-2008
of two Turkish public institutions, namely, the State Planning Organization and the Court of Accounts
to achieve accurate forecast levels. The artificial neural networks approach is rarely applied for the
forecasting of public expenditures, and as far as we know this is the first of such attempts involving
Turkish data. The artificial neural networks application provided very accurate public expenditure
forecasts for these public institutions, suggesting that the artificial neural networks is a very useful
method for the public expenditure forecasting, as well.
Keywords: Artificial neural networks, Budget forecasting, Public expenditure, Time series
