There is a lack of evidence on regulatory effectiveness available to support policy makers with the selection of appropriate instruments to deliver better environmental regulation. We identify the types of evidence required to enable regulatory reform, characterize evidence gaps, and explore how these may be filled through future research. A typology of regulatory instruments is presented, and evidence of what has worked when and why is examined, drawing on international experience and recent cases from the United Kingdom (UK). Evidence of the capabilities of good environmental regulators for regulatory effectiveness is lacking, and it is proposed that ethnographic research that captures the nuances of regulatory practice will prove necessary to address this. This paper is of value to policy makers and regulators around the world considering the selection and deployment of the full range of environmental regulatory instruments to respond to environmental risks and in support of economic growth. It can inform the selection of suitable approaches and the design of institutions capable of delivering them. Copyright © 2012 John Wiley & Sons, Ltd and ERP Environment.

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Metal price forecasts support estimates of future profits from metal exploration and mining and inform purchasing, selling and other day-today activities in the metals industry. Past research has shown that cyclical behaviour is a dominant characteristic of metal prices. Wavelet analysis enables to capture this cyclicality by decomposing a time series into its frequency and time domain. This study assesses the usefulness of an improved combined wavelet-autoregressive integrated moving average (ARIMA) approach for forecasting monthly prices of aluminium, copper, lead and zinc. The performance of ARIMA models in forecasting metal prices is demonstrated to be increased substantially through a wavelet-based multiresolution analysis (MRA) prior to ARIMA model fitting. The approach demonstrated in this paper is novel because it identifies the optimal combination of the wavelet transform type, wavelet function and the number of decomposition levels used in the MRA and thereby increases the forecast accuracy significantly. The results showed that, on average, the proposed

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