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The purpose of this paper is to demonstrate how managerial estimates of long-term market price trends can be included into investment analysis of metal mining. The inclusion of subjective market information with a new cycle reverting price process is proposed.

Subjective managerial estimates are included into stochastic metal price modeling by defining separately the following parameters of each price cycle phase: approximated length, approximated long-term price level and volatility. An net present value-based investment analysis model is applied together with Monte Carlo simulation.

It is plausible to combine managerial estimates about metal price trends and cycles with stochastic modeling for shorter term and to include the information into investment analysis. The results show that the difference between the proposed process and the commonly used mean reverting process is remarkable in terms of decision-making implications.

The proposed method allows the inclusion of more relevant information into the metal price modeling used in mining investment analysis. Results suggest that the cyclical nature of metal prices affects project value of metal mining projects, and it should be considered when making irreversible investment decisions. The proposed method can be generalized for any cyclical processes.

The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.