Forecasting economic and financial time series with non-linear models

In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain.

Resources for improving journalists' understanding of the economic and financial parameters of Australia's agricultural and commodity producers

The research addresses how an understanding of the fundamentals of economics will better inform general journalists who report on issues or events affecting rural and regional Australia. The research draws on practice-based experience of the author, formal economics studies, interviews with news editors from Australian television news organisations, and interviews from leading economists. A guidebook has also been written to help journalists apply economic theories to their reporting. The guidebook enables reporters to think strategically and consider the 'big picture' when they inform society about policies, commodity trade, the environment, or any issues involving rural and regional Australia.