Skip to content

Marc F. Bellemare Posts

Announcing the Online Agricultural and Resource Economics Seminar

Everyone is now stuck at home (with varying degrees of household responsibilities, to be sure, but stuck at home nevertheless), so my PhD student Jeff Bloem and I thought it would be a good idea to launch the Online Agricultural and Resource Economics Seminar (OARES).

The seminar will be held on Wednesdays at 11 am Central US time. Though this makes it difficult for our colleagues in Asia and Oceania to join in, that time slot allows colleagues from the West Coast to join in a little after breakfast, and colleagues in Europe to join in just before dinner time.

Our first seminar will be held on May 6, 2020. Leah Bevis, from Ohio State, will be presenting her paper with Digvijay Singh Negi titled “Long-Term Nutrition Impacts of the Green Revolution in India.” Here is their abstract:

We examine the impact of the Green Revolution on nutritional status for the first time, as far as we know, in India — the poster-child for the Green Revolution. We additionally piece together multiple nationally representative datasets to examine the impacts of the Green Revolution on cropping patterns, crop prices, and consumption patterns. We find that the Green Revolution improved women’s height, though the benefit accrued largely to urban women. In rural areas, the Green Revolution increased acreage to rice and wheat, usurping acreage to coarse cereals and pulses. It also (marginally) increased rural prices of coarse cereals and pulses relative to rice and wheat, and (marginally) decreased rural consumption of coarse cereals and pulses relative to rice and wheat. While the Green Revolution positively impacted women’s health, a Green Revolution that had included high-yielding pulse varieties would have likely been even more beneficial, particularly in rural areas.

If you would like to register, see the OARES website here, and make sure to sign up with your institutional address. The OARES website includes a schedule of forthcoming talks as well.

How COVID-19 May Disrupt Food Supply Chains in Developing Countries

I had been meaning to post about this earlier but did not get a chance to do so until today given the decreased productivity those of us with younger children are currently experiencing.

At the request of IFPRI’s new director general Jo Swinnen, Tom Reardon, David Zilberman, and I wrote for a post for the IFPRI blog on the prospective effects of COVID-19 on food supply chains in developing countries. Here are the opening paragraphs:

COVID-19 is spreading through the developing world. Many low- and middle-income countries are now reporting growing numbers of cases and imposing rigorous lockdown regulations in response, which impact all aspects of the economy. How will COVID-19 affect food-supply chains (FSCs) in developing countries?

The evidence suggests that the impacts will be felt widely, but unevenly. Farm operations may be spared the worst, while small and medium-sized enterprises (SMEs) in urban areas will face significant problems. Governments will have to develop policies to respond to these varied impacts to avoid supply chain disruptions, higher food prices, and severe economic fallout for millions of employees.

You can find the rest of the post (with translations in French and in Spanish) here.

‘Metrics Monday: Peter Kennedy, Judea Pearl, or Both?

Steve writes:

Marc,

I have followed your blog silently for a while now and always appreciate your approach to applied econometrics. I have a question for you if you will indulge me. I am a fan of Peter Kennedy ever since his “Sinning in the Basement” article and its inclusion in his Guide to Econometrics. Peter’s chapter on applied economics has shaped my econometric and data science teaching daily ever since. Last week I discovered Judea Pearl’s Book of Why. So I set out to see what I had been missing. I discovered Pearl wrote a paper on Haavelmo who I read at Ohio State over 40 years ago. I discovered exchanges between Pearl and Guido Imbens … I began to search for Peter Kennedy and Judea Pearl. Your blog entry … is one of the few google hits that came up for that search.

As you mention you are a fan of both Kennedy and Pearl, here are the questions that are on my mind: Are there links between Kennedy’s guidance on how to do applied economics and Pearl’s how to do causality? Do the two together make one a better applied econometrician? Do the two together constitute something business cares about?

I wrote a piece on what Kennedy’s rules mean from an ethical point of view. It is going to be published by O’Reilly Media in a collection: 97 Things About Ethics Everyone In Data Science Should Know, edited by Bill Franks. You can find my entry at https://econdatascience.com/ethics-rules-in-applied-econometrics-and-data-science/

My answers:

Are there links between Kennedy’s guidance on how to do applied economics and Pearl’s how to do causality? 

A little bit, but not that many. Kennedy was largely concerned with ethics (nowadays, he’d write about replicability, transparency, pre-analysis plans, and so on) and he was writing pre-Credibility Revolution (so before causality was “a thing”), whereas Pearl is largely concerned with making explicit the assumptions that can lead to causal inference, and he is clearly a major actor of the Credibility Revolution–if not in economics, at least clearly outside of it. I think the link is mainly this: Kennedy would say that you need to be clear about the limitations of your work; Pearl would say that you need to be clear about your assumptions, and about stating explicitly the causal model you have in mind. I see limitations as related to those assumptions.

Do the two together make one a better applied econometrician? 

Yes, no doubt. Kennedy is all about observational data and about providing clear, intuitive, math- and jargon-free (as much as possible) guidance about how to do good empirical work, but ignoring causality. Pearl is all about causality. As an economist, I’d recommend Kennedy as well Angrist and Pischke more than I’d recommend Kennedy and Pearl, or I’d substitute Morgan and Winship for Pearl, since their book is more easily accessible to economists. (Note: This is not a knock on Judea Pearl, whose contribution to our understanding has been nothing short of colossal. I just find that his Causality book is overkill for most economists.)

Do the two together constitute something business cares about?

It depends on what allows maximizing profit—prediction or inference. If it’s prediction, then no: they should be all about machine learning methods. If it’s about causal inference, then yes, because the Kennedy and Pearl together will make you a better user of data and econometric methods, and a sharper thinker on identification and (structural) assumptions. You might think “Does business really do causal inference?” I know economists who work for Amazon, and it turns out the answer is “Yes,” at least for Amazon, which apparently has a number of people working on causal inference. (Though from a microeconomic-theoretic perspective, I imagine the ability to invest in that type of research is facilitated by extra-normal profits, as with any old R&D activity!)