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The importance of supply and demand for oil prices : evidence from non-Gaussianity
Braun, Robin - In: Quantitative economics : QE ; journal of the … 14 (2023) 4, pp. 1163-1198
When quantifying the importance of supply and demand for oil price fluctuations, a wide range of estimates have been reported. Models identified via a sharp upper bound on the short-run price elasticity of supply find supply shocks to be minor drivers. In turn, when replacing the upper bound...
Persistent link: https://www.econbiz.de/10014496492
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Price dynamics in Tanzanian maize markets : insights from a semiparametric cointegration model
Ihle, Rico; Cramon-Taubadel, Stephan von - 2010
Maize is a major staple food in Sub-Saharan Africa. Monthly maize prices in Tanzania are analyzed since the country is an important maize producer and exporter in East Africa. We analyze price transmission between the five most important urban regions of Tanzania between 2000 and 2008 which...
Persistent link: https://www.econbiz.de/10010342910
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A non-parametric approach of heteroskedasticity robust estimation of Vector-Autoregressive (VAR) models
Grobys, Klaus - In: Journal of finance and investment analysis 1 (2012) 1, pp. 55-67
This contribution studies the application of heteroskedasticity robust estimation of Vector-Autoregressive (VAR) models. VAR models have become one of the most applied models for the analysis of multivariate time series. Econometric standard software usually provides parameter estimators that...
Persistent link: https://www.econbiz.de/10009511728
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Impulse response estimation via flexible local projections
Mumtaz, Haroon; Piffer, Michele - 2022
This paper introduces a exible local projection that generalises the model by Jordà (2005) to a non-parametric setting using Bayesian Additive Regression Trees. Monte Carlo experiments show that our BART-LP model is able to capture non-linearities in the impulse responses. Our first application...
Persistent link: https://www.econbiz.de/10013179339
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Robust inference for non-Gaussian SVAR models
Hoesch, Lukas; Lee, Adam; Mesters, Geert - 2022
All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...
Persistent link: https://www.econbiz.de/10013417421
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Locally robust inference for non-Gaussian SVAR models
Hoesch, Lukas; Lee, Adam; Mesters, Geert - In: Quantitative economics : QE ; journal of the … 15 (2024) 2, pp. 523-570
All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...
Persistent link: https://www.econbiz.de/10015053146
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A comparison of parametric, semi-nonparametric, adaptive, and nonparametric cointegration tests
Boswijk, Herman Peter; Lucas, André; Taylor, Nicholas - 1999
This paper provides an extensive Monte-Carlo comparison of severalcontemporary cointegration tests. Apart from the … estimation or semi-nonparametric density approximations. Thecomparison is completed with a fully nonparametric cointegration test …
Persistent link: https://www.econbiz.de/10011300549
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Semiparametric Estimation of Fractional Cointegration
Hualde, Javier - 2008
A semiparametric bivariate fractionally cointegrated system is considered, integration orders possibly being unknown and I (0) unobservable inputs having nonparametric spectral density. Two kinds of estimate of the cointegrating parameter amp;#957; are considered, one involving inverse spectral...
Persistent link: https://www.econbiz.de/10012770904
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Semi-Parametric Single-Index Predictive Regression Models with Cointegrated Regressors
Zhou, Weilun - 2020
This paper considers the estimation of a semi-parametric single-index regression model that allows for nonlinear predictive relationships. This model is useful for predicting financial asset returns, whose observed behavior is described by a stationary process, when the multiple non-stationary...
Persistent link: https://www.econbiz.de/10012822931
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Robust multivariate local whittle estimation and spurious fractional cointegration
Becker, Janis; Leschinski, Christian; Sibbertsen, Philipp - 2019
and the fractional cointegration vector robust to low frequency contaminations. This estimator as many other local Whittle … based procedures requires a priori knowledge of the cointegration rank. Since low frequency contaminations bias inference on … the cointegration rank, we also provide a robust estimator of the cointegration rank. As both estimators are based on the …
Persistent link: https://www.econbiz.de/10012105358