✦ LIBER ✦

Forecasting the federal budget with time-series models

✍ Scribed by Hamid Baghestani; Robert McNown

Publisher: John Wiley and Sons
Year: 1992
Tongue: English
Weight: 768 KB
Volume: 11
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.3980110204

No coin nor oath required. For personal study only.

✦ Synopsis

The stochastic properties of conventionally defined federal expenditures and revenues are examined, and cointegration is found. Alternative timeseries 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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