<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Non-Linear Price Transmission between Biofuels, Fuels and Food Commodities

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type , Research , Preprint 01 Jan 2013Publisher:Elsevier BVJournal:SSRN Electronic Journal (eissn: 1556-5068,

Authors: Ladislav Kristoufek; Karel Janda; David Zilberman;

doi: 10.2139/ssrn.2257390

Non-Linear Price Transmission between Biofuels, Fuels and Food Commodities

- Summary
- Subjects
- Metrics

Abstract

For the biofuel markets and related commodities, we study their price transmission, which is in fact equivalent to studying price cross-elasticities. Importantly, we focus on the price dependence of the price transmission mechanism. Several methodological caveats are discussed. Specifically, we combine the memory robust feasible generalized least squares estimation with two-stage least squares to control for endogeneity bias and inconsistency. We find that both ethanol and biodiesel prices are responsive to their production factors (ethanol to corn, and biodiesel to German diesel). The strength of transmission between both significant pairs increased remarkably during the food crisis of 2007/2008. Causality tests further show that price changes in production factors lead the changes in biofuels even after controlling for price effects.

Related Organizations

Charles University
Czech Republic
University of California, Berkeley
United States

Keywords

Q42, Q16, biofuels; price transmission; price cross-elasticity; causality;, non-linearity, biofuels, biofuels; price transmission; non-linearity, price transmission, C22, jel: jel:C22, jel: jel:Q42, jel: jel:Q16, ddc: ddc:330

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average