Discussion Paper

No. 2018-55 | July 11, 2018
What drives food price volatility? Evidence based on a generalized VAR approach applied to the food, financial and energy markets

Abstract

The aim of this study is to investigate sources of food prices volatility. The analysis uses daily series for volatility of corn, soybean, wheat, rice, US dollar, crude oil, and SP500 futures spanning the period January 4, 2000 to April 1, 2017. The authors employ the generalized vector autoregressive framework in rolling sample approach in order to capture the time-varying nature of volatility spillovers. The results reveal that: volatility spillovers measures change over time; most of the volatility spillovers are observed within the two groups of markets: food markets and “non-food” markets; corn market is net volatility transmitter.

Data Set

JEL Classification:

Q17, G15, C58

Assessment

  • Downloads: 355

Links

Cite As

Sławomir Śmiech, Monika Papież, Marek A. Dąbrowski, and Kamil Fijorek (2018). What drives food price volatility? Evidence based on a generalized VAR approach applied to the food, financial and energy markets. Economics Discussion Papers, No 2018-55, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2018-55


Comments and Questions


Anonymous - Invited Reader Comment
July 31, 2018 - 09:47

1. The article analyses the volatility of food prices from 2000 to 2017. I think it’s important to consider that this includes the so-called 2000’s commodity boom from 2004 to 2014, approximately. I don’t know if the boom affected the volatility as well as the level. Can their results be ...[more]

... extended to regular times? At least, more on this should be clarified. Or robustness checks can be obtained adding periods of normal food prices.

2. What is the variable US dollar? Is it the exchange rate vis a vis the euro?

3. The authors present four results but they only provide a plausible explanation for one of them: i.e, the corn as source of volatility because of biofuels. I think it will be interesting to provide plausible explanations for the rest of the evidence as well.

4. In equation 1, the authors give their proxy for volatility which is the log-diff of the logs of max and min values. Why not just the log-diff of the original max and min values?

5. In the results presented in Table 2, wouldn’t it be relevant to show standard deviations of the spillovers?

6. In Figure 7, the authors present volatility spillovers within the food markets. Does this mean that the rest of variables are excluded from the GFEVD estimation? If yes, isn’t there any danger of omitted variable bias?

7. I find kind of hard to follow the results presented in Figure 9. Why not just plot the IRFs as usual?

8. The authors claim in their conclusion that financial and energy markets have a limited role in food prices volatility, and that the volatility comes mostly from the corn market, a food commodity itself. While this result might have an statistic relevance, I believe that there is not much of an economic contribution here. I think that a more important finding would be to know where does the volatility come from, besides the food market itself. E.g, is it from demand or supply driven shocks? But maybe this is beyond the scope of the article.


Sławomir Śmiech - responses to the comment
August 07, 2018 - 17:19

the attached pdf file contains detailed responses to all eight commentaries


Anonymous - Referee Report 1
August 08, 2018 - 08:31

see attached file


Sławomir Śmiech - reply to referee 1 report
September 10, 2018 - 11:09

see attached file