Estimating the effectiveness of extension information systems using farm trials and subjective probabilities

A method of combining survey data and Dairy Herd Improvement Association (DHIA) records to achieve low cost farm trials is presented. Farm trials and surveys of current practices and production responses are useful to identify yield gaps between expectations predicted from experimental findings and actual field results. Different management schemes can be ranked using subjective probabilities and stochastic dominance to enhance successful implementation of research findings and to increase the feedback between researchers, extension workers, and producers. A survey of current masitis control practices and expected milk yield response is the example. Combining survey results with DHIA records allowed estimating the relationship between somatic cell counts (SCC) and milk yield. Eliciting beliefs about the relationship between SCC and milk yield showed that producers agreed with predictions from the statistical model. Subjective probabilities about SCC and mastitis control practices showed that our sample of experts and producers consistently ranked the different practices but extension agents had no consensus about the the most or least effective ones.     

Environmental Regulation and Innovation Offsets in the Bluegrass Seed Industry

Burning bluegrass seed stubble is an important production practice that, among other benefits, increases production and stand life of this perennial crop. Despite economic forecasts that higher production costs from the 1996 state ban on seed stubble burning would reduce Washington production by up to 30%, output in the years 1998–2005 was nearly two-thirds higher than in any previous eight-year period. This study seeks to explain why that paradoxical behavior occurred. This study puts forward and systematically tests several hypotheses. The only hypothesis with any support, innovation offsets, is examined by an assessment of contemporaneous innovations and by corroborative statistical evidence.     

Expected Option Returns

This paper examines expected option returns in the context of mainstream asset-pricing theory. Under mild assumptions, expected call returns exceed those of the underlying security and increase with the strike price. Likewise, expected put returns are below the risk-free rate and increase with the strike price. S&P index option returns consistently exhibit these characteristics. Under stronger assumptions, expected option returns vary linearly with option betas. However, zero-beta, at-the-money straddle positions produce average losses of approximately three percent per week. This suggests that some additional factor, such as systematic stochastic volatility, is priced in option returns.     

Numeraire choice in normalized quadratic functional forms

A semi-nested test procedure is developed for choosing the numeraire for a normalized quadratic profit function when too few observations exist for nested hypothesis testing and when too many alternatives exis for conventional non-nested testing. Sensitivity of empirical results to choice of numeraire price is examined using agricultural data for the US and ten multistate regions. Few test conclusions vary by numeraire but own price input demand elasticities differ greatly.     

The Delisting Bias in CRSP's Nasdaq Data and Its Implications for the Size Effect

We investigate the bias in CRSP's Nasdaq data due to missing returns for delisted stocks. We find that the missing returns are large and negative on average, and that delisted stocks experience a substantial decrease in liquidity. We estimate that using a corrected return of −55 percent for missing performance-related delisting returns corrects the bias. We revisit previous work which finds a size effect among Nasdaq stocks. After correcting for the delisting bias, there is no evidence that there ever was a size effect on Nasdaq. Our results are inconsistent with most risk-based explanations of the size effect.     

PRODUCTION INTERRELATIONSHIPS IN SRI LANKAN PEASANT AGRICULTURE

Technical change and the extent to which commodity supplies and input demands are interrelated in Sri Lankan peasant agriculture are explored in this paper. Using a multiple-product dual model, a seemingly unrelated system of product supply and input demand equations is estimated for four crops and four variable inputs. Restrictions based on competitive behaviour and a twice continuously-differentiable production function are maintained in the non-linear least squares estimation. A number of important interrelationships in individual product supplies and input demands are identified, further documenting the need to account for intercommodity production relationships in econometric and simulation studies and in policy formulation. Non-joint production and Hicksneutral technical change are both rejected.     

Measuring the effectiveness of non-price export promotion using a supply-side approach

In this paper we assess the effectiveness of the Market Promotion Program (MPP) in increasing U.S. exports and benefitting U.S. agricultural producers and food processors. Export shipments are linked to producer welfare using Kohli's (1978) profit maximization (GNP function) approach to modeling international trade. Using estimated profit functions in conjunction with a synthetic export demand function for processed agricultural products, we compute changes in farm and food processing sector profits that result from alternative own-price and advertising elasticities of export demand with and without the MPP subsidy. This approach allows us to investigate aggregate welfare effects of nonprice promotion without requiring the difficult task of estimating the export demand effects of market promotion activities for numerous commodities and importing countries. First version received: April 1999/Final version received: June 2000     

Induced Innovation in U.S. Agriculture: Time-series, Direct Econometric, and Nonparametric Tests

The hypothesis of induced innovation is tested for U.S. agriculture using a high-quality state-level panel data set and three disparate testing techniques—time series, direct econometric, and nonparametric. We find little support for the hypothesis. That conclusion is robust across testing techniques. However, as with all empirical tests of this hypothesis conducted to date, ours focus only on the demand side of the hypothesis. The hypothesis could have been rejected simply because the marginal cost of developing and implementing input-saving technologies for the relatively expensive inputs is greater than for the relatively cheap inputs.     

Enterprise diversification in US dairy: impact of risk preferences on scale and scope economies

Enterprise diversification has recently become a prominent feature of US dairy farms. Scope economies and risk aversion are two forces that simultaneously determine diversification. We jointly estimate scope economies and determine risk preferences under price uncertainty. We reject risk neutrality in favour of Increasing Absolute Risk Aversion (IARA) and Increasing Relative Risk Aversion (IRRA). Scope economies are significant, but diminish with farm size. Increasing returns to scale exist in the production of multiple enterprises and diminish with size. Large farms operate under decreasing returns to scale. Ignoring risk preferences, a common practice in empirical work, results in an underestimate of the effect of scope economies for large farms.     

Induced innovation and marginal cost of new technology

Lacking data on development and implementation costs for input-saving technologies, we develop a nonparametric procedure to estimate relative differences in marginal technology costs for technical change to be consistent with the induced innovation hypothesis. We apply it to U.S. agriculture.