The study discusses the use and limitations of time series models as additional instruments for monitoring and forecasting total budget revenues. Following an analysis of the properties and estimation of time series models, the paper presents the data set to be used for the estimation exercise, as well as analyse the data’s stationarity and the correlogram of the stationary series to be modelled. The data sample includes the quarterly evolution of total budget revenues in Moldova from the first quarter of 2016 to the first quarter of 2023. The paper includes the econometric estimates of the preferred time series model, as well as out-of-sample forecasts of the quarterly evolution of budget revenues from the second quarter of 2023 to the fourth quarter of 2024. The preferred model’s annual forecast of budget revenues for 2023 is slightly more optimistic than the Ministry of Finance’s estimate for 2023 contained in the recently approved Medium Term Budget Framework document and is very close to the projection of the International Monetary Fund contained in its latest country report for Moldova. The paper concludes by summarising the uses and limitations of time series models for monitoring and forecasting the evolution of budget revenues and suggesting areas for further work.