In this paper, we disentangle tax revenue forecast errors into influences stemming from wrong macroeconomic assumptions and false predictions of the elasticities linking the tax base to its corresponding tax type. Across six tax types and the overall tax sum for Germany, we find a heterogeneous...

We forecast New York state tax revenues with a mixed-frequency model using a number of machine learning techniques. We found boosting with two dynamic factors extracted from a select list of New York and U.S. leading indicators did best in terms of correctly updating revenues for the fiscal year...

Time series analysis is a crucial tool for predicting how reinsurance revenues will be used. Reinsurance businesses must be aware of the estimated future values of claims in order to minimise the substantial losses brought on by predicted future claims. The potential values of anticipated claims...

We investigate the disciplining role of analysts’ revenue forecasts on firms’ discretionary revenues. We analyze quarterly data and three-year window around the initiation of analysts’ revenue forecasts reported in IBES. Our study shows a decrease in the magnitude of discretionary revenues...

Robust forecasting of mining sector revenues is key to effective budgeting (and broader fiscal management) in many resource-rich countries. However, this is challenging in practice, given commodity market volatility, the extended lags (and often opaque processes) between resource discoveries and...