Agricultural and Applied Economics—Without Apology
From a similarly titled post by Dave Giles:
- Always, but always, plot your data.
- Remember that data quality is at least as important as data quantity.
- Always ask yourself, “Do these results make economic/common sense”?
- Check whether your “statistically significant” results are also “numerically/economically significant”.
- Be sure that you know exactly what assumptions are used/needed to obtain the results relating to the properties of any estimator or test that you use.
My department is hosting this academic year’s edition of the MIEDC conference:
In the spring of 2014, the Department of Applied Economics at the University of Minnesota will host the 11th Midwest International Economic Development Conference on Friday, May 2 and Saturday, May 3 2014 at the McNamara Alumni Center on the University of Minnesota East Bank Campus in Minneapolis, Minnesota.
The guest speaker will be Tim Besley, Professor of Economics and Political Science at the London School of Economics, University of London.
We invite you, and any other interested faculty and graduate students in your department or elsewhere, to submit a paper to present at the conference. Papers on any topic related to international economic development are welcome. Submissions for an entire session (of 3 papers) are also welcome.
Deadline for submissions is January 6, 2014. Papers will be reviewed by a committee from the University of Minnesota and the University of Wisconsin–Madison. You will be notified by January 31, 2014 whether your paper has been accepted.
Information about topics, papers and presenters at last year’s conference is available at:
http://www.aae.wisc.edu/
mwiedc/schedule.asp Additional information about this year’s conference is available at:
http://faculty.apec.umn.edu/
pglewwe/Minnconf/index.html Questions about submissions, contact: Paul Glewwe
Submit papers to: Frank Trnka
A new working paper (ungated copy here) by Mark Rosenzweig and Chris Udry:
We use newly-available Indian panel data to estimate how the returns to planting-stage investments vary by rainfall realizations. We show that the forecasts significantly affect farmer investment decisions and that these responses account for a substantial fraction of the inter-annual variability in planting-stage investments, that the skill of the forecasts varies across areas of India, and that farmers respond more strongly to the forecast where there is more forecast skill and not at all when there is no skill. We show, using an IV strategy in which the Indian government forecast of monsoon rainfall serves as the main instrument, that the return to agricultural investment depends substantially on the conditions under which it is estimated. Using the full rainfall distribution and our profit function estimates, we find that Indian farmers on average under-invest, by a factor of three, when we compare actual levels of investments to the optimal investment level that maximizes expected profits. Farmers who use skilled forecasts have increased average profit levels but also have more variable profits compared with farmers without access to forecasts. Even modest improvements in forecast skill would substantially increase average profits.
The intuition for some of the main results is as follows, from a (very) quick read of the paper: Risk-averse farmers will hedge against the considerable uncertainty surrounding rainfall by underinvesting, and thus underproducing.
In some cases, rainfall forecasts allow reducing some of that uncertainty, which brings investment decisions closer to the optimum, which in turn increases output. The more precise the forecast, the more a forecast of good rainfall will improve investment.
This is interesting and important work. One of the key distinctions of development economics relative to other fields of economics is that it takes into account heterogeneity and recognizes it as a cause of underdevelopment. Here, there are a few sources of heterogeneity: first, whether a rainfall forecast is available at all and second, whether that forecast is good.