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Category: Economics

Cool New Paper on the Transition from a Gift to a Market Economy

When I took his graduate class on the microeconomics of development, Chris Barrett mentioned that “Heterogeneity and the Three ‘Nons'” differentiate developing economies from industrialized economies:

  1. Heterogeneity: Heterogeneity of endowments, preferences, technologies, and abilities affect outcomes,
  2. Non-Separability: Households are both production and consumption units, and these two decision are not always separable,
  3. Non-Anonymity: Village life is not anonymous, and who one transacts with often affects the terms of exchange,
  4. Non-Market Institutions: High transactions costs often cause households not to participate in markets and to develop seemingly inefficient institutions.

In a post titled “The Transformation Process of Rural Societies,” Frankfurt-based Chilean economist Dany Jaimovich discusses a cool new paper of his which gets at #3 above, i.e., how one can move from non-anonymous to relatively more anonymous transactions:

In Which I Talk About Food Prices

While I was in Montreal for the McGill Conference on Global Food Security a few weeks ago, I was interviewed by CKUT — McGill’s student-run radio — for their Health on Earth program.

I spoke with CKUT’s Lorraine Wong about the difference between rising food prices and food price volatility and the social consequences thereof, and about various other food-policy-related topics. Though Lorraine aired the interview unedited, I managed to sound semi-coherent.

Fingerprints

Not the Katy Perry song, but actual fingerprints, which can be used to improve credit markets by lowering default rates.

A new article by Giné et al. in the American Economic Review:

We implemented a randomized field experiment in Malawi examining borrower responses to being fingerprinted when applying for loans. This intervention improved the lender’s ability to implement dynamic repayment incentives, allowing it to withhold future loans from past defaulters while rewarding good borrowers with better loan terms. As predicted by a simple model, fingerprinting led to substantially higher repayment rates for borrowers with the highest ex ante default risk, but had no effect for the rest of the borrowers. We provide unique evidence that this improvement in repayment rates is accompanied by behaviors consistent with less adverse selection and lower moral hazard.

In other words, fingerprinting does a ton of good to the credit market. Because they fear getting denied loans in the future, borrowers who have been fingerprinted repay at a higher rate, and fingerprinting also both (i) reduces the proportion of bad borrowers and (ii) the likelihood that borrowers will invest borrowed funds in risky projects.

The fact that fingerprinting borrowers reduces default rates might seem obvious, but note that it had never been shown convincingly before that improvements in how lenders identify borrowers led to improvements in credit markets.

Moreover, those improvements are important for policy because they can reduce the amount of credit rationing. As Stiglitz and Weiss (1981) have shown, because of adverse selection and moral hazard, lenders often have to maintain artificially low interest rates. This causes credit to be rationed in many economies, which means that many people are denied loans.