We examine the forecast quality of Chicago Board Options Exchange (CBOE) implied volatility indexes based on the Nasdaq 100 and Standard and Poor’s 100 and 500 stock indexes. We find that the forecast quality of CBOE implied volatilities for the S&P 100 (VXO) and S&P 500 (VIX) has improved since 1995. Implied volatilities for the Nasdaq 100 (VXN) appear to provide even higher quality forecasts ...

Econometric Causality This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and...

This paper examines the forward pricing efficiency of the local crude palm oil (CPO) futures market. In an efficient market, the relevant signal to be used by -the producers, traders and processors is simply the futures price. The forward pricing efficiency is measured in terms of the forecasting ability of Malaysian crude palm oil futures price on physical price. The relative predictive power ...

This paper evaluates different strategies to forecast Spanish inflation using information of price series for 57 products and 18 regions in Spain. We consider vector equilibrium correction (VeqC) models that include cointegration relationships between Spanish prices and prices in the regions of Valencia, Andalusia, Madrid, Catalonia and the Basque Country. This approach is consistent with econo...

What is the impact of surprise and anticipated policy changes when agents form expectations using adaptive learning rather than rational expectations? We examine this issue using the standard stochastic real business cycle model with lump-sum taxes. Agents combine knowledge about future policy with econometric forecasts of future wages and interest rates. Dynamics under learning can have large ...

Weather forecasting is a complex process that involves numerous specialized fields of expertise. The output from computationally intensive numerical weather prediction (NWP) models forms the starting point of the forecasting process. Expert forecasters have both a general knowledge of large-scale weather systems and specific knowledge about the idiosyncratic behavior of local scale weather phen...

We present a structural econometric framework of supply chain information flows. The framework analyzes supply chain black boxes by measuring how input demand signals transform into output order signals. It characterizes inventory policies with impulse response functions (IRFs). We develop an algorithm to estimate these IRFs, and the structural parameters underlying them, with single firm sales...

Financial Econometrics is simply the application of econometric tools to financial data. For many years, least squares techniques provided satisfactory tools. Stock market forecasts, efficient market tests, and even tests of portfolio models such as the CAPM and APT were essentially implemented with least squares on cleverly manipulated data sets. More recently, however, the field has developed...

Cointegration analysis has led to equilibrium-correction econometric systems being ubiquitous. But in a non-stationary world subject to structural breaks, where model and mechanism differ, equilibrium-correction models are a risky device from which to forecast. Equilibrium shifts entail systematic forecast failure, as forecasts will tend to move in the opposite direction to data. We explain the...

The bootstrap, like the jackknife, is a technique for estimating standard errors. The idea is to usc Monte Carlo simulation, based on a non-parametric estimate of the underlying error distribution. The bootstrap will be applied to an econometric model describing the demand for capital, labor, energy, and materials. The model is fitted by three-stage least squares. In sharp contrast with previou...