Forecasting the federal budget with time‐series models | CU Experts

AbstractThe stochastic properties of conventionally denned federal expenditures and revenues are examined, and cointegration is found. Alternative time‐series models‐univariate ARIMA models, vector autoregressions in levels and differences, and an error correction model‐are specified and estimated using quarterly data from 1955:1 through 1979:4. Updated forecasts for up to three years beyond the sample period are evaluated against actual expenditures, revenues and the deficit. The vector autoregression in levels shows evidence of nonstationarity, which leads to strong biases in the forecasts. The remaining models produce forecasts that are satisfactory by the mean squared error criterion, and the magnitudes of biases at the longer horizons are significantly smaller than those of the official forecasts.

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