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It has been a while since I blogged, so I thought it would be a good idea to share this new working paper of mine.

A few years ago I was asked to pitch ideas to the editors of the Annual Review of Resource Economics (ARRE)–in case you are not familiar with the Annual Reviews, they have done a fine job of competing with the Elsevier Handbooks, especially since they feature new articles every year.

One of the ideas that I pitched, and which the editors liked enough to ask me to submit to them, was for a review of the literature on price risk–that is, unexpected departures of a price from its expected level, also known as price volatility or price uncertainty.

This is something I have done a bunch of work on, from estimating the welfare impacts of price risk in a sample of agricultural households, to looking at whether food price volatility caused food riots, to discussing the potential of experimental and behavioral economics to study price risk, to estimating the response of producers to output price risk in the lab and in the field, and to looking at whether participation in agricultural value chains can help producers insure against price risk.

Given that, and given that I think there is still a lot of work to be done on the topic, I thought it was time for a perspective of the literature, and so I teamed up with my PhD student Chris Boyd Leon, who is writing her dissertation on issues related to price risk.

Here is the paper we submitted to the ARRE, and here is its abstract:

Much of neoclassical economics is concerned with prices—more specifically with relative prices. Similarly, economists have studied behavior in the face of risk and uncertainty for at least a century, and risk and uncertainty are without a doubt a feature of economic life. It is thus puzzling that price risk—that is, price volatility, or unexpected departures from a mean price level—has received so little attention. In this review, we discuss the microeconomics of price risk. We begin by reviewing the theoretical literature, a great deal of which is concerned with the effects of unstable agricultural prices on the welfare of producers, consumers, and agricultural households. We then discuss the empirical literature on the effects of price risk on economic agents. We emphasize policy responses to agricultural price risk throughout, discussing price stabilization policies from both a theoretical as well as an empirical perspective. Perhaps most importantly, we provide several suggestions for future research in the area of price risk given increasing risk on world agricultural markets due to both policy uncertainty and climate change.

In January 2013, I wrote a post titled Quinoa Nonsense, of Why the World Still Needs Agricultural Economists. That was the second one of my posts to go viral.*

And did that post ever take me places–both figuratively and literally.

It figuratively took me places, because after I wrote that post, Seth Gitter got in touch with me to mention he’d been meaning to look at the effects of the quinoa price spike, and to ask whether I’d be interested in collaborating on that. Because of the same post, The Economist ran an article in their Leaders section last year titled “In praise of quinoa,” in which they were talking about the wonders of international trade, and in which they name-checked me. (In the same article, they also name-checked Saddam Hussein and Donald Trump, so make of that what you will.)

And it literally took me places, because Seth and I were soon thereafter flying to Peru to consult for the International Trade Center on the welfare impacts of the quinoa price spike. That was the first of several trips to Peru, a country where I am planning on doing more work as early as next summer.

In my January 2013 post, I ranted against journalists who present uninformed, sloppy thoughts as gospel. My foremost example then was this excerpt from an article in the Guardian:

A few months ago, I wrote a post titled “What to Do Instead of ln(x+1),” in which I discussed the inverse hyperbolic sine transformation (IHS, or more specifically arcsinh), which is frequently used in lieu of the logarithmic transformation in order to transform a variable that has a substantial number of zero-valued observations.

The day the post appeared, I received an email from Casey Wichman, from Resources for the Future,* who wrote:

Jonathan Eyer and I used the IHS transformation in our JEEM paper on water scarcity and electricity generation, and I’ve actually been thinking about your final point since then. That is, how to account for elasticities when using the IHS transformation. I would be interested to do a bit more digging to see if anyone has written anything on it. If not (and I can’t remember finding anything when I was looking), I think there would be value in writing a short note … Any interest?