research institute for compassionate economics

Working to eat, eating to work

Written by Diane Coffey on March 9th, 2011

For this post, I’d like to share a paper that I just read by Anil Deolalikar, published in 1988 in the Review of Economics and Statistics entitled “Nutrition and Labor Productivity in Agriculture: Estimates for Rural South India.”

Deolalikar’s article is written in response to a body of research produced in the 1970s and 1980s about the efficiency wage hypothesis. This grew out of the idea that where workers are very poorly nourished we might see wages fail to respond to an increase in the labor supply. Ordinarily, when more people want to work than jobs are available, we think that the wage will go down. However, employers might instead simply higher fewer people and pay them more. This is because in order for workers to be productive they must have enough to eat. We can think of the efficiency wage as a biologically determined minimum wage.

In order to test whether we actually find efficiency wages in poor places, Deolalikar looked at panel data—data collected on the same individuals over time—from South India. He found that changes in workers’ calorie intake from one period to the next were not related to changes in their wages. On average, however, workers of the same heights who lost weight from one period to the next were more likely to see declines in their wages. Deolalikar took this as evidence that short term changes in consumption do not impact productivity, but long term changes probably do.

I’m not sure that Deolalikar’s explanation is complete, though. I’d like to offer two other plausible explanations. One is that changes in calories are hard to measure—in order to measure changes in calorie consumption you first have to ask people what they ate and then convert it to calories—and so the amount of noise in the data might be preventing us from seeing the signal. Thus, change in weight is a more reliable measure of changes in how much people ate, and that’s where we see the effect.

Another, though certainly not the only, possible explanation is that changes in calorie intake were measured correctly, but that they do not predict wages because food intake, in and of itself, doesn’t really determine productivity. It could be that some people lost weight not by eating less, but because they were sick (perhaps with diarrhea, which is common in India and can lead to weight loss despite no change in calorie consumption). Therefore, it could be disease that is determining productivity.

Although a lot of research has been done in this area since 1988, the puzzle is by no means solved.