Robert Vigfusson

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Staff Working Papers

Forecasting the Price of Oil

Staff Working Paper 2011-15 Ron Alquist, Lutz Kilian, Robert Vigfusson
We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications?

Avoiding the Pitfalls: Can Regime-Switching Tests Detect Bubbles?

Staff Working Paper 1996-11 Simon van Norden, Robert Vigfusson
Work on testing for bubbles has caused much debate, much of which has focussed on methodology. Monte Carlo simulations reported in Evans (1991) showed that standard tests for unit roots and cointegration frequently reject the presence of bubbles even when such bubbles are present by construction. Evans referred to this problem as the pitfall of testing for bubbles.
Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods JEL Code(s): C, C2, C22, C5, C52

Switching Between Chartists and Fundamentalists: A Markov Regime-Switching Approach

Staff Working Paper 1996-1 Robert Vigfusson
Since the early 1980s, models based on economic fundamentals have been poor at explaining the movements in the exchange rate (Messe 1990). In response to this problem, Frankel and Froot (1988) developed a model that uses two approaches to forecast the exchange rate: the fundamentalist approach, which bases the forecast on economic fundamentals, and the chartist approach, which bases the forecast on the past behaviour of the exchange rate.
Content Type(s): Staff Research, Staff Working Papers Topic(s): Financial markets JEL Code(s): C, C4, C40, G, G1, G12

Analytical Derivatives for Markov Switching Models

Staff Working Paper 1995-7 Jeff Gable, Simon van Norden, Robert Vigfusson
This paper derives analytical gradients for a broad class of regime-switching models with Markovian state-transition probabilities. Such models are usually estimated by maximum likelihood methods, which require the derivatives of the likelihood function with respect to the parameter vector. These gradients are usually calculated by means of numerical techniques. The paper shows that analytical gradients […]

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Technical Reports

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