68 research outputs found
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Being Surveyed Can Change Later Behavior and Related Parameter Estimates
Does completing a household survey change the later behavior of those surveyed? In three field studies of health and two of microlending, we randomly assigned subjects to be surveyed about health and/or household finances and then measured subsequent use of a related product with data that does not rely on subjects' self-reports. In the three health experiments, we find that being surveyed increases use of water treatment products and take-up of medical insurance. Frequent surveys on reported diarrhea also led to biased estimates of the impact of improved source water quality. In two microlending studies, we do not find an effect of being surveyed on borrowing behavior. The results suggest that limited attention could play an important but context-dependent role in consumer choice, with the implication that researchers should reconsider whether, how, and how much to survey their subjectsEconomic
The prognostic impact of minimal residual disease in patients with chronic lymphocytic leukemia requiring first-line therapy
Business training for women entrepreneurs in the Kyrgyz Republic: evidence from a randomised controlled trial
Choice between Microfinance Systems Operating on the Basis of Individual Liability Loan Contract or through Joint Liability Loan Contract
Estimation of semiparametric models when the criterion function is not smooth
We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some nonparametric estimators that can themselves depend on the parameters to be estimated. Our results extend existing theories like those of Pakes and Pollard (1989), Andrews (1994a) and Newey (1994). We also show that bootstrap provides asymptotically correct confidence regions for the finite dimensional parameters. We apply our results to two examples: a 'hit rate' and a partially linear median regression with some endogenous regressors
Moderate deviations for a test of symmetry based on deconvolution kernel density estimators
Estimation of infinite dilution activity coefficients of organic compounds in water with neural classifiers
Science-based insurance
Climate change with its potential to alter seasons, rainfall variability and temperature regimes1 poses a growing threat to the development agenda. Small-scale farmers in developing countries, who have few modern technologies or improved crop varieties at their disposal, are among those most vulnerable to changing patterns of rainfall and temperature.
In developed countries, crop insurance is a commonly employed mechanism by which farmers and ranchers can guard against the reduction or destruction of yields by extreme weather events. However, traditional crop insurance is largely absent in less-developed countries, because costs of implementation are high and there are not enough effective financial institutions to broker insurances. Furthermore, insurance policies perversely provide an incentive for farmers to neglect their fields, a problem that is usually countered with expensive site visits by insurance claim adjusters2, which would not be financially feasible in the developing world.
So-called index insurances, where an insurance indemnity payout depends on the exceedance of a threshold variable such as water level (for floods) or consecutive days without rain (for droughts), could fill that gap. Many insurance companies and non-profit development organizations are working to develop index insurance for small farmers. In principle, index insurance can serve several purposes. Apart from reducing the risk for small farmers, it can facilitate the availability of credit: banks are more likely to lend to a farmer who is insured against loss of harvest.
However, designing and pricing effective index insurance programs has proved to be extremely difficult, even in places where adequate crop and weather data are available. In the developing world, weather stations are few, records are discontinuous and historical weather data difficult to access3. To make the concept viable in these more challenging circumstances, a high degree of participation and engagement from the geoscience community is key, in particular to provide access to satellite remote sensing and high-resolution climate simulations
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