Breaks, trends, and unit roots in spot prices for crude oil and petroleum products

Sun, Jingwei; Shi, Wendong

doi:10.1016/j.eneco.2015.05.001

Cited by 19 publications

(14 citation statements)

References 32 publications

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“…If too many breaks for a typically finite sample are allowed, it may introduce low power and/or size distortion. Also as pointed out by Sun and Shi (2015), the one break date detected by PY test is the most significant one for the whole series, whilst the second one detected by for instance the Kejriwal and Perron (2010) test is less important. Following the above suggestions, and taking into account the size of our sample, we employ PY test allowing for one break and the results are reported in Tables 3.…”

Section: 2structural Break and Convergence Test Resultsmentioning

confidence: 80%

Segmenting global tourism markets: A panel club convergence approach

Lin

You

Lau

et al. 2019

Annals of Tourism Research

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This study adopts an advanced panel club convergence approach to analyzing global tourism market segmentation. We empirically examine the convergence process of Turkish global tourism source markets over the period of 2001-2015, covering 81 markets. We further employ a recently developed procedure to test for structural breaks in our data. Three groups of breakpoint-homogenous countries are identified. We then examine within-group club formation and reveal a number of convergence clubs (or segments). The results show the importance of Asian source markets in the post-break periods. This study illustrates the application of structural break and club convergence analysis for segmenting global tourism markets, and generates important implications for tourism organizations to develop global marketing strategies.

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Section: 2structural Break and Convergence Test Resultsmentioning

confidence: 80%

Segmenting global tourism markets: A panel club convergence approach

Lin

You

Lau

et al. 2019

Annals of Tourism Research

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“…An extant literature exists that have found commodity prices to be plagued by structural breaks. Some of the studies include Zivot and Andrews (1992); Zanias (2005); Kellard and Wohar (2006); Harvey, Leybourne, and Taylor (2010); Ghoshray (2011); Ghoshray, Kejriwal, and Wohar (2014); Sun and Shi (2015). We test for structural break in commodity prices used in this study and find that all commodity prices are found to contain two structural breaks.…”

Section: Data and Empirical Resultsmentioning

confidence: 95%

“…Thus, while the GVAR model has advantages in incorporating a large number of variables to be analyzed together, there remain limitations particularly relating to the nonlinearity of commodity prices that arise due to the presence of structural breaks in commodity prices (see Zanias 2005;Kellard and Wohar 2006;Ghoshray 2011;Ghoshray, Kejriwal, and Wohar 2014;Sun and Shi 2015). Taking account of the recent studies in the area, the VAR model approach remains popular.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of a People's Republic of China Slowdown on Commodity Prices and Detecting the Asymmetric Responses of Economic Activity in Asian Countries to Commodity Price Shocks

Ghoshray

Pundit

2016

SSRN Journal

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Cataloging-In-Publication Data Asian Development Bank. The Impact of a People's Republic of China slowdown on commodity prices and detecting the asymmetric responses of economic activity in Asian countries to commodity price shocks. Mandaluyong City, Philippines: Asian Development Bank, 2016. 1. Commodity prices. 2. Economic growth. 3. Flexible fourier form. 4. Impulse response analysis. 5. PRC slowdown. I. Asian Development Bank. The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned. By making any designation of or reference to a particular territory or geographic area, or by using the term "country" in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

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“…To understand the different relationships of supply and demand over the time horizon, it is worth noting that the fundamental characteristics of crude oil price series are the result of different types of interconnections in different time windows [12]. Most of current studies obtain the fluctuation mechanism of oil prices by investigating the structural break effect, which could hide the diversity and evolution characteristics of oil price fluctuations [13,14]. It is also obvious that we could obtain detailed information regarding the oil price volatility by exploring the heterogeneous interconnection, which is important to understand crude oil markets.…”

Section: Introductionmentioning

confidence: 99%

The Heterogeneous Interconnections between Supply or Demand Side and Oil Risks

Liao

et al. 2019

Energies

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Due to the crucial implication of oil risks for economic growth and policy making, the aim of this paper is to explore the heterogeneous interconnections of supply or demand in oil risks over time horizons and different countries. Specifically, we first examine the correlation of supply or demand in oil return risks and show the relationships in different countries based on wavelet coherence. Furthermore, we explore the time-varying interconnections between supply- or demand-side and oil return risks, as well as oil producers and demand countries. The empirical results show that the correlation between supply and oil return risks is relatively stable, whereas the linkage between demand and oil return risks shows greater volatility due to the impact of specific events. Further study indicates that there are heterogeneous interconnections between supply- or demand-side and oil return risks over sample periods. Specifically, the sign of response could be divided into four phases, i.e., 1997–2002, 2002–2010, 2010–2013 and 2014–2018. In addition, the interconnections of the demand side could be divided into three phases due to the sign of it. What is more, the dynamic interconnections of oil producers’ or countries’ demands behave quite heterogeneously in different countries. Thus policymakers should focus on the coordination level and space capacity in the global crude oil market.

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Breaks, trends, and unit roots in spot prices for crude oil and petroleum products

Cited by 19 publications

References 32 publications

Segmenting global tourism markets: A panel club convergence approach

Segmenting global tourism markets: A panel club convergence approach

The Impact of a People's Republic of China Slowdown on Commodity Prices and Detecting the Asymmetric Responses of Economic Activity in Asian Countries to Commodity Price Shocks

The Heterogeneous Interconnections between Supply or Demand Side and Oil Risks

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