Moreover, you might recall from your reading of the paper that I use worldwide data. This means that the identification strategy goes something like (i) natural disaster in country A, (ii) shock to the supply and/or demand of food propagated through world food markets, and (iii) social unrest in country B as a consequence of an exogenous change in the price of food. Rarely (if ever) in the data will you have a natural disaster in country A followed by social unrest in country A. So the short time scale and the geographical dispersion of the causal chain aids the identification. Thanks, however, for highlighting that I need to do a better job of explaining that.

On the second, we’ll have to agree to disagree. A Typhoon, Tsunami, or Earthquake often impact social cohesion quickly… not just months. Try applying your assumption to Haiti for example. Did the earthquake only impact social cohesion in Haiti through food prices? Not sure you can ignore the massive loss of life? etc, etc, etc.

I also wonder about the sensitivity of using the FAO food price index for a measure of volatility generally. Most traders and farmers make decisions by following individual commodities daily (or hourly, or less), while the FAO index aggregates a basket of commodities for monthly data. In my experience volatility is a problem day to day, not month to month, so wouldn’t the FAO index hide a lot of the actual volatility?

I would be interested to see the outcome of your research using the daily closing prices of major grains. Have you tried that? (curious, not trying to make more work!)

Your point about the exclusion restriction is well taken and on a long enough time scale, I completely agree with you. That is why I use monthly data — in such a short period of time, it becomes less likely that those other channels affect social unrest, whereas markets respond relatively quickly.

I understand the broader point you are making about causality – but I’m not sure our colleague in DC who used the metaphor of the mold and hurricane would agree with the way you’ve represented his argument. I thought that rather than saying it was “impossible to talk of causality” he was actually just being more nuanced about the causality itself. His work convincingly showed (and predicted) that food prices had created the conditions for conflict (mold) but noted that for conflict to occur there also needed to be a “trigger” (the hurricane).

Going in a completely different direction – I personally would not agree with the notion that natural disasters only affect social unrest through food prices. You also need to account for the other impacts that disasters frequently have on populations – beyond loss of life there is often a deterioration of social cohesion due to a breakdown of community ties, disruption of order, family structure, loss of housing, opportunity, education, etc. Look at the components of ‘social cohesion’ and almost every one is likely to be adversely impacted by a natural disaster.

Not sure what that means for your research but let me know next time you’re up in DC if you want to chat!

For example, with the hurricane and mold story, and assuming that somehow we found that both mold and hurricanes seem to have a causal relationship with house collapse, how important is it if hurricanes (or mold for all I know) explain house collapses better than some other factor?