Bootstrapping autoregressions with conditional heteroskedasticity of unknown form
TLDR
The asymptotic validity of three easy-to-implement alternative bootstrap proposals for stationary autoregressive processes with m.i.s.d. errors is established, finding them to be more accurate in small samples than the conventional large-sample approximation based on robust standard errors.About:
This article is published in Journal of Econometrics.The article was published on 2004-11-01 and is currently open access. It has received 591 citations till now. The article focuses on the topics: Conditional probability distribution & Heteroscedasticity.read more
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Not All Oil Price Shocks are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market
Lutz Kilian,Lutz Kilian +1 more
TL;DR: In this paper, a structural decomposition of the real price of crude oil in four components is proposed: oil supply shocks driven by political events in OPEC countries; other oil supply shock; aggregate shocks to the demand for industrial commodities; and demand shocks that are specific to the crude oil market.
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Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market
TL;DR: In this article, a structural decomposition of the real price of crude oil is proposed, based on a newly developed measure of global real economic activity, and the authors estimate the dynamic effects of these shocks on the real prices of oil.
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The impact of oil price shocks on the u.s. stock market
Lutz Kilian,Cheolbeom Park +1 more
TL;DR: In this paper, the reaction of U.S. real stock returns to an oil price shock differs greatly depending on whether the change in the price of oil is driven by demand or supply shocks in the oil market.
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The Economic Effects of Energy Price Shocks
Lutz Kilian,Lutz Kilian +1 more
TL;DR: In this paper, a number of the key issues in this debate are addressed: What are energy price shocks and where do they come from? How responsive is energy demand to changes in energy prices? How do consumers' expenditure patterns evolve in response to energy price spikes? How does energy price changes affect real output, inflation, stock markets and the balance-of-payments? Why do energy price increases seem to cause recessions, but energy price decreases do not seem to lead to expansions?
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The Economic Effects of Energy Price Shocks
TL;DR: In this article, a number of the key issues in this debate are addressed: What are energy price shocks and where do they come from? How responsive is energy demand to changes in energy prices? How do consumers' expenditure patterns evolve in response to energy price spikes? How does energy price changes affect U.S. real output, inflation and stock prices? Why do energy price increases seem to cause recessions, but energy price decreases do not seem to lead to expansions?
References
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Journal ArticleDOI
A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
TL;DR: In this article, a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic is presented, which does not depend on a formal model of the structure of the heteroSkewedness.
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Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
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Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev,Tim Bollerslev +1 more
TL;DR: In this paper, a natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in 1982 to allow for past conditional variances in the current conditional variance equation is proposed.
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On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks
TL;DR: In this article, a modified GARCH-M model was used to find a negative relation between conditional expected monthly return and conditional variance of monthly return, using seasonal patterns in volatility and nominal interest rates to predict conditional variance.
Book
Time Series: Theory and Methods
TL;DR: In this article, the mean and autocovariance functions of ARIMA models are estimated for multivariate time series and state-space models, and the spectral representation of the spectrum of a Stationary Process is inferred.