Agricultural production estimates have often differentiated and estimated different technologies within a sample of farms. The common approach is to use observable farm characteristics to split the sample into groups and subsequently estimate different functions for each group. Alternatively, unique technologies can be determined by econometric procedures such as latent class models. This paper compares the results of a latent class model with the use of a priori information to split the sample using dairy farm data. Latent class separation appears to be a superior method of separating heterogeneous technologies and suggests that technology differences are multifaceted.

This paper examines Chinese pesticide firms’ use and perceptions of various means of intellectual property (IP) protection in protecting their innovations, using a unique dataset from 97 pesticide firms surveyed in 2008. These firms rate Chinese patents as quite effective in protecting their IP from infringement, although 70 percent of them state that improved enforcement is needed. Those firms that have been granted patents and those that claim their patents have been infringed upon both give lower ratings to the perceived effectiveness of patents. Trademarks are rated as less effective than patents, but firms that have had experience with patenting and infringement of patents tend to rate trademarks as more effective than those firms that do not have direct experience with the patent system. General government policies to encourage increased privatization, more private R&D, and higher education are associated with more faith in IP, but policies to strengthen IP by promoting mandatory IP training and the development of specialized IP divisions in the firms do not influence perceptions of IP effectiveness. We conclude that if the Chinese government wants to encourage innovation using IP protection, it must focus on improving the enforcement of patents.

We use nonparametric production function methods to decompose farm-level labor productivity growth into components attributable to efficiency change, technical change, and factor intensity. The estimation is accomplished using balanced panel data drawn from the Kansas Farm Management Association for the period 1993 to 2007. We find that labor productivity growth is primarily driven by factor intensity and technical change. Efficiency change is declining with increasing productivity growth, and technical change is not Hicks-neutral and occurs at high levels of factor intensity, suggesting that innovation is embodied in factor intensity.

The forest owner's decision regarding when to harvest, based on forest's current worth, is analyzed using the real options approach for a representative Pacific Northwest Douglas-fir stand when the carbon price is stochastic and there is a fire risk. The problem is framed as a linear complementarity problem and solved using the fully implicit finite difference method combined with a penalty method. The fire risk results in lower option values and earlier critical harvesting times, whereas a wider carbon price range ($0–$100 versus $0–$10) produces contrary results and more responsiveness to the parameter changes.

A 2007 food-borne illness incident involving peanut butter is linked with structural change in consumer demand. Compensated and uncompensated own- and cross-price elasticities and expenditure elasticities were calculated for leading brands before and after the product recall using the Barten synthetic model and weekly time-series data from 2006 through 2008. Statistically significant differences in price elasticities for the affected brand, Peter Pan, were absent. After a period of 27 weeks, this brand essentially recovered from the food safety crisis. Significant differences in price elasticities were evident among non-affected brands. Hence, spillover effects and heightened competition are associated with the recall.

This study tests the causal direction between captive supply and cash market price in the U.S. cattle procurement market. Finding the correct causality should provide useful information to the decades-long debate on packers’ anti-competitive behavior in the U.S. cattle procurement market. It should also help researchers find better econometric specifications for the cash price-captive supply relationship. Two causality tests—the Granger test and the Modified Wald test—were conducted. Overall test results indicate that captive supply causes cash market price, and it favors the price-dependent model.

This paper examines the adaptation of dasymetric mapping methodologies to agricultural data, including their testing and transposition, in order to recover the underlying statistical surface (i.e., an approximation of the real distribution of data). A methodology based on the ideas of Gallego and Peedell (2001) and on the binary method is proposed. It has several steps: (i) the exclusion of target zones for which no observations exist (binary method), (ii) the application of an iterative process to define the most precise densities for data distribution, and (iii) the stratification/definition of sub-units with homogenous characteristics if the results of the previous step are not satisfactory, and the subsequent application of step two.

The methodology was applied in the Alentejo region of Portugal, using data from the 1999 Agricultural Census. Several counties are used as source zones. The aim was to generate a distribution of agro-forestry occupations as close as possible to reality. Two lines of analysis were followed: (i) application of the methodology simultaneously to all counties (definition of regional densities), and (ii) application of the methodology separately to the different subareas with similar characteristics (definition of sub-regional densities). For an easy application of the methodology, a computer tool was created, which allowed the easy optimization, validation, and exportation of the data into a Geographic Information System (GIS).

The results were validated using several error indicators at the county level, as well as in a sample of parishes. We show that the second variant of the methodology yielded more precise results, and is superior for the types of data available. This method yielded maps in which the distribution of the most relevant agro-forestry occupations is closest to reality.

Actual Production History (APH) yields play a critical role in determining the coverage offered to producers by the Risk Management Agency's yield-based crop insurance products. Using both county and individual insured unit data, we examine the impact of APH yield trends for Texas cotton and Illinois com. Our findings indicate that biases due to using simple average APH yields when yields are trending upward reduce the expected indemnity and actuarially fair premium rate. The estimated welfare effect also varies significantly with different commonly used detrending approaches. This study demonstrates that producer welfare can be enhanced through proper treatment of yield trends in crop insurance programs.

This study examines the impact of adopting Bt corn on farm profits, yields, and insecticide use. The study employs an econometric model that corrects for self-selection and simultaneity. The model is estimated using nationwide farm-level survey data for 2005. Regression analysis confirms that Bt adoption is associated with increased variable profits, yields, and seed demand. However, the results of this analysis suggest that Bt adoption is not significantly related to insecticide use. This result may be due to the fact that insect infestation levels were lower in 2005 than they were in previous years.