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Category: Agriculture

Published September 24, 2012

Mobile Phones: Does the Intrahousehold Allocation of Technology Matter?

There are good reasons to believe it does.

At least, that is the answer my coauthor Ken Lee and I come up with in a new article titled “Look Who’s Talking: The Impacts of the Intrahousehold Allocation of Mobile Phones on Agricultural Prices,” forthcoming in the Journal of Development Studies.

More specifically, in a sample of onion farmers in the Philippines, we look at whether there is a statistically significant relationship between whether anyone in a household owns a mobile phone and the price received by that household for its onions.

Failing to find any statistically significant association between the two, we then look at whether there is a statistically significant relationship between whether (i) the household head owns a mobile phone, (ii) the household head’s spouse owns a mobile phone, or (iii) any of the children in the household own a mobile phone and the price received by that household for its onions.

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Published September 20, 2012

Organic Food: Confirmation Bias or Ambiguity Aversion?

A reader writes:

This might be interesting for you: people are annoyed/unhappy with NPR’s coverage about a report out of Stanford that said organic food isn’t really any healthier than conventional food. Clear case in point showing when people are faced with data and facts that counter their beliefs, they will more often than not completely shut it out and continue with their original belief. It’s much easier to continue believing what you thought before than stretch your mind and possibly acknowledge that you’re wrong or at least don’t have the full story. And we wonder why things don’t get accomplished?

What the reader has in mind is confirmation bias, the cognitive bias that makes people give more weight to empirical evidence that support their beliefs and less weight to empirical evidence that contradicts their beliefs, and about which I have written before in the context of development policy.

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Published September 19, 2012

The Third Pillar of Microfinance: Insurance for the Poor in Developing Countries

Over the last few years, index insurance has been receiving an increasing amount of attention from researchers and policy makers.

Whereas regular insurance pays out when a verifiable loss is incurred (e.g., flood insurance pays out when there has been a flood), whether an index insurance pays out depends on whether some index crosses a certain threshold. So for example, a rainfall index insurance for the agricultural producers in a given region would pay out when growing conditions in that region are too dry, i.e., when rainfall falls below a specific, predetermined threshold.

The beauty of index insurance is that it greatly reduces the scope for moral hazard. Indeed, if I insure your crop, you might well decide to neglect your field, do nothing for the entire season, and wait for me to give you a payout. Not so with index insurance, since the index (e.g., rainfall, temperature, etc.) is typically very difficult to manipulate.

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