Structural transformation and the oil price

Stefanski, Radoslaw

doi:10.1016/j.red.2013.09.006

Cited by 32 publications

(15 citation statements)

References 29 publications

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“…On the other hand, his model allows for non-zero trade deficits and includes more than two countries. 6 Other quantitative open economy models of structural change include Coleman (2007), Galor and Mountford (2008), Reyes-Heroles (2012), Stefanski (2012), Swiecki (2012), Ungor (2012). Coleman (2007) uses a multi-country Heckscher-Ohlin-Ricardo framework to study the effect of a large emerging market The paper is organized as follows.…”

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confidence: 99%

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Structural change in an open economy

Zhang

2013

Journal of Monetary Economics

199

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We study the importance of international trade in structural change. Our framework has both productivity and trade cost shocks, and allows for non-unitary income and substitution elasticities. We calibrate our model to investigate South Korea's structural change between 1971 and 2005. We find that the shock processes, propagated through the model's two main transmission mechanisms, non-homothetic preferences and the open economy, explain virtually all of the evolution of agriculture and services labor shares, and the rising part of the hump-shape in manufacturing. Counterfactual exercises show that the role of the open economy is quantitatively important for explaining South Korea's structural change. JEL: F20, F40, O13, O41

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confidence: 99%

“…For both the open and closed models, the subsequent TFP levels and trade costs are constructed the same way as in the benchmark calibration. 36 In the closed economy, illustrated by the gray dashed line, there is almost no structural change. This result can be understood via Equation (9).…”

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confidence: 99%

Structural change in an open economy

Zhang

2013

Journal of Monetary Economics

199

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“…Indeed, there are many studies suggesting that the determinants of oil price might vary in time, for example, due to the structural breaks [58][59][60][61]. For example, Fan and Xu [62] have stressed that the structure of the oil market changed significantly since 2000.…”

Section: Modelsmentioning

confidence: 99%

Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework

Drachal

2018

Energies

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This article presents results from modelling spot oil prices by Dynamic Model Averaging (DMA). First, based on a literature review and availability of data, the following oil price drivers have been selected: stock prices indices, stock prices volatility index, exchange rates, global economic activity, interest rates, supply and demand indicators and inventories level. Next, they have been included as explanatory variables in various DMA models with different initial parameters. Monthly data between January 1986 and December 2015 has been analyzed. Several variations of DMA models have been constructed, because DMA requires the initial setting of certain parameters. Interestingly, DMA has occurred to be robust to setting different values to these parameters. It has also occurred that the quality of prediction is the highest for the model with the drivers solely connected with the stock markets behavior. Drivers connected with macroeconomic fundamental indicators have not been found so important. This observation can serve as an argument favoring the hypothesis of the increasing financialization of the oil market, at least in the short-term period. The predictions from other, slightly different modelling variations based on DMA methodology, have happened to be consistent with each other in general. Many constructed models have outperformed alternative forecasting methods. It has also been found that normalization of the initial data, although not necessary for DMA from the theoretical point of view, significantly improves the quality of prediction.

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“…Moreover, the likelihood of resource wars would not only be driven by the price elasticity of demand (as in Acemoglu et al, 2012b), but also by the elasticity of demand with regard to output. Stefanski (2014) introduces non-homothetic preferences in a growth model with crude oil. However, in this model non-homothetic preferences only drive the inter-sectoral change in demand but not changes in intra-sectoral demand.…”

Section: Introductionmentioning

confidence: 99%

Industrialization and the demand for mineral commodities

Stuermer

2017

Journal of International Money and Finance

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Bonn Graduate School of Economics (BGSE)is gratefully acknowledged.Deutsche Post World Net is a sponsor of the BGSE. Industrialization and the demand for mineral commoditiesMartin Stuermer * November 15th, 2013Abstract What drives the long-term demand for mineral commodities? This paper provides empirical evidence on the long-run demand for mineral commodities since 1840. I extend the partial adjustment model to account for country-specific structures and technological change. I find that a one percent increase in manufacturing output leads to a 1.5 percent increase in the demand for aluminum and a one percent increase in the demand for copper. The estimated manufacturing output elasticities of demand for lead, tin, and zinc are far below one. The estimated price elasticities of demand are highly inelastic for all mineral commodities in the long run. My results suggest that industrialization in China, for example, will cause the consumption of aluminum and copper to increase at a considerably higher rate than the one of lead, tin, and zinc. All variables adjust slowly to equilibrium, which helps to explain the extended fluctuation in these markets.JEL classification: O13, Q31, N50

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Structural transformation and the oil price

Abstract: as well as members of the Minnesota International Trade and Development Workshop for helpful comments and suggestions. I thank Hossein Samiei and Kevin Cheng for initial discussion. I have also benefited from comments of seminar participants at the Sum

Cited by 32 publications

References 29 publications

Structural change in an open economy

Structural change in an open economy

Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework

Industrialization and the demand for mineral commodities

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