The payoffs to agricultural biotechnology: an assessment of the evidence

Transgenic crops are relatively new technologies being adopted rapidly in the United States and in a few other countries. The economic impacts of these technologies have, thus far, been estimated in a piecemeal fashion. The purpose of this study was to collect and characterize the economic evidence available to date, organize it, and determine if any general implications can be drawn from it. The general classes of economic impacts at the farm level are discussed. The types of studies that generate estimates of these benefits are also characterized and categorized in terms of the implications for measuring economic impacts when the set of things held constant in the type of study does not correspond to those that economic theory suggests. The evidence is presented, along with some general implications drawn from the analysis. These implications are: (1) growing transgenic cotton is likely to result in reduced pesticide use in most years and is likely to be profitable in most years in most U.S. states in the Cotton Belt, 2) Bt corn will provide a small but significant yield increase in most years across the U.S. Corn Belt, and in some years and some places the increase will be substantial, and (3) although there is some evidence of a small yield loss in the Roundup Ready soybean varieties, in most years and locations savings in pesticide costs and, possibly, tillage costs will more than offset the lost revenue from the yield discrepancy. There is not yet enough evidence to generalize even these few conclusions to other countries. More farm- level studies in more years and across more locations are required before any additional implications can be drawn. Studies that measure the non-pecuniary benefits and costs of these technologies should be undertaken, as well.Transgenic plants., Technological innovations., Agricultural research Economic aspects., Rate of return., Impact assessment,

Research returns redux: a meta-analysis of the returns to agricultural R&D

A total of 289 studies of returns to agricultural R&D were compiled and these provide 1821 estimates of rates of return. After removing statistical outliers and incomplete observations, across the remaining 1128 observations the estimated annual rates of return averaged 65 per cent overall — 80 per cent for research only, 80 per cent for extension only, and 47 per cent for research and extension combined. These averages reveal little meaningful information from a large body of literature, which provides rate‐of‐return estimates that are often not directly comparable. This study was aimed at trying to account for the differences. Several features of the methods used by research evaluators matter, in particular assumptions about lag lengths and the nature of the research‐induced supply shift.Research and Development/Tech Change/Emerging Technologies,

CFD-3D and 1D modeling of fuel cell powertrain for a hydrogen vehicle

As it is known the transport sector represents a major contributor to climate change. In particular, private transport contributes to the degradation of the air quality inside the cities or the residential areas. To address this issue, a progressive reduction of the use of fossil fuels as a primary energy source for these vehicles and the promotion of cleaner powertrain alternatives is in order. This study focuses on designing a fuel cell powertrain for a hydrogen-powered passenger car using numerical modeling. To this purpose, we initially modeled a base fuel cell and optimized its performance by using various materials for the bipolar plates and adjusting the platinum loading between the anode and cathode. Then, a preliminary design of the new powertrain has been proposed in order to achieve a nominal power of 100 kW and it has been tested on a WLTP 3b homologation cycle. Finally, we have been able to numerically estimate the behavior of the three main feeding line: hydrogen line, air line and cooling line. In conclusion, the obtained results demonstrate how numerical modelling can be successfully used in the design of complex systems such as those related to alternative energy. This work also provides a solid basis for the future development of increasingly efficient and environmentally friendly hydrogen vehicles

Research returns redux: a meta-analysis of the returns to agricultural R&D

A total of 294 studies of returns to agricultural R&D (including extension) were compiled and these studies provide 1,858 separate estimates of rates of return. This includes some extreme values, which are implausible. When the highest and lowest 2.5 percent of the rates of return were set aside, the estimated annual rates of return averaged 73 percent overall–88 percent for research only, 45 percent for research and extension, and 79 percent for extension only. But these averages reveal little meaningful information from a large and diverse body of literature, which provides rate-of-return estimates that are often not directly comparable. The purpose of this study was to go behind the averages, and try to account for the sources of differences, in a meta-analysis of the studies of returns to agricultural R&D. The results conform with the theory and prior beliefs in many ways. Several features of the methods used by research evaluators matter, in particular assumptions about lag lengths and the nature of the research-induced supply shift.Rate of return., Agricultural research.,

Development of a grid-dispersion model in a large-eddy-simulation–generated planetary boundary layer

Numerical simulations of dispersion experiments within the planetary boundary layer are actually feasible making use of Large Eddy Simulations (LES). In Eulerian framework, a conservation equation for a passive scalar may be superimposed on LES wind/turbulence fields to get a realistic description of timevarying concentration field. Aim of this work is to present a numerical technique to solve the Eulerian conservation equation. The technique is based on Fractional Step/Locally One-Dimensional (LOD) methods. Advection terms are calculated with a semi-Lagrangian cubic-spline technique, while diffusive terms are calculated with Crank-Nicholson implicit scheme. To test the grid model, the dispersion of contaminants emitted from an elevated continuous point source in a convective boundary layer is simulated. Results show that the calculated concentration distributions agree quite well with numerical and experimental data found in the literature

A meta-analysis of rates of return to agricultural R & D: ex pede Herculem?

IFPRI has long argued that spending on agricultural research constitutes a sound investment in poverty reduction and agricultural and economic growth, through improvements in productivity. This argument is based partly on the reported evidence of high rates of return to agricultural research, typically believed to be in the range of 40–60 percent per year. Yet there continues to be controversy over whether these figures are to be believed, and over what they actually indicate. This study represents the first attempt to take a comprehensive look at all the available evidence on rates of return to investments in agricultural R&D since 1953, and the only attempt to do so in a formal statistical fashion. This report has compiled and documented the literature in ways that make it more accessible and more useful to other researchers and policymakers, as well as others interested in the evidence. The analysis reveals some systematic patterns and some sources of biases that make it easier to interpret the evidence and draw meaningful conclusions. (Excerpted from Summary by Per Pinstrup-Andersen)Development projects Evaluation., Agricultural research, Statistics., Agricultural economics and policies,

Regression spline bivariate probit models: A practical approach to testing for exogeneity

Bivariate probit models can deal with a problem usually known as endogeneity. This issue is likely to arise in observational studies when confounders are unobserved. We are concerned with testing the hypothesis of exogeneity (or absence of endogeneity) when using regression spline recursive and sample selection bivariate probit models. Likelihood ratio and gradient tests are discussed in this context and their empirical properties investigated and compared with those of the Lagrange multiplier and Wald tests through a Monte Carlo study. The tests are illustrated using two datasets in which the hypothesis of exogeneity needs to be tested