Expert forecasts of quantitative variables in the form of continuous subjective probability distributions are more useful to decision makers than are point estimates or confidence intervals. We present 2 experiments using participants recruited via the Internet aimed at (a) developing methods for estimating and modeling continuous subjective distributions from small numbers of judgments, and (b...

Energy forecasting plays a dominant role in the sustainable development economic optimization, resource planning and secure operation of electric power systems. The variation in energy demand is a major source of uncertainty in planning for future capacity enhancement, resource needs and operation of existing generation resources. Electric utilities need monthly peak and yearly demand forecasti...

Recently developed structural models of the global crude oil market imply that the surge in the real price of oil between mid 2003 and mid 2008 was driven by repeated positive shocks to the demand for all industrial commodities, reflecting unexpectedly high growth mainly in emerging Asia. We evaluate this proposition using an alternative data source and a different econometric methodology. Rath...

F ollowing World War II, the quantity and quality of macroeconomic data expanded dramatically. The most important factor was the regular publication of the National Income and Product Accounts, which contained hundreds of consistently defined and measured statistics that summarized overall economic activity. As the data supply expanded, entrepreneurs realized that a market existed for applying ...

Timber price forecasts are important components of timberland investment analysis. Two techniques are widely used in forecasting. Econometric models use one or more independent variables to predict a dependent variable. Time series analysis or autoregression techniques use the prior observations of a variable, and only those prior observations, to make predictions of that variable. Either techn...

This paper compares model-based and reduced-form forecasts of financial volatility when high-frequency return data are available. We derived exact formulas for the forecast errors and analyzed the contribution of the “wrong” data modeling and errors in forecast inputs. The comparison is made for “feasible” forecasts, i.e. we assumed that the true data generating process, latent states and param...