Local and Regional Economic Impacts of Biofuel Development
Expanded processing of agricultural products in rural areas has been widely pursued as a strategy for rural economic development. By adding value to farm products before they leave the area, new processing plants can create new employment opportunities and generate economic spinoffs in rural areas that have experienced economic stagnation or decline as a result of long term trends of farm consolidation. In addition, farmer owned processing facilities provide a way for producers to integrate forward and capture potential profits from processing and marketing their products. Consequently, the expansion of agricultural processing in rural areas usually receives broad-based support from commodity groups, rural development interests, and state political leaders. In recent years, the most prevalent type of new agricultural processing ventures in the Midwest and Great Plains states has been corn ethanol plants. Like other types of agricultural processing, these biofuel ventures have generally received widespread support, and numerous studies have addressed their contributions to local or regional economies. However, while the methods employed have seemingly been quite similar, the findings have varied widely with the impacts attributed to ethanol development differing as much as ten-fold. The purpose of this paper is to (1) examine reasons why estimates of local or regional economic impacts of biofuel development may vary and (2) compare the economic impacts of corn-based ethanol production with those expected to be associated with cellulosic ethanol production.
The Role of Information Technology in the Fuel Ethanol Industry
This USDA-sponsored study uses panels of ethanol industry experts and follow up interviews with plant owners and managers to examine how information technology has impacted the structure, organization, and operations of the fuel ethanol industry. The study examined the following questions regarding the future of the ethanol industry: (1) Does the present ethanol industry represent a stable structure or a transitional step toward an inevitable concentration of ownership into the hands of a few large processing firms? (2) Have contemporary information technologies fundamentally changed the information flows, scale of operations, access to markets, conditions of vertical and horizontal coordination, sources of finance, and the competitive landscape for the medium-sized, independent processing firm? (3) To what degree have cost savings associated with better access to information and financing offset the cost savings traditionally associated with horizontal and vertical integration in processing industries? (4) What steps do medium-sized ethanol production entities need to take to continue to survive in this new information-based market environment?
1.5 Million Missing Numbers: Overcoming Employment Suppression in County Business Patterns Data
Missing data frustrate research and limit our understanding of regional economies. County Business Patterns annually provides employment data for all U.S. counties and states at the most detailed industrial level, but two out of every three employment statistics are missing. In rural areas, this percentage is higher still. To protect the rights of employers to confidentiality, the U.S. Census Bureau has not disclosed the number of employees in 1.5 million cases in the 2002 data. Instead, it offers a suppression flag that represents an employment range. This article presents a two-stage method for replacing all the flags with employment estimates. Taking advantage of the hierarchical nature of the data both by industry and geography, the first stage identifies the smallest possible range for each suppressed number. Ensuring that employment adds up correctly up and down the industrial and geographical hierarchies, the second stage iteratively adjusts all the estimates until millions of constraints are met. The procedure simultaneously considers all industries in all counties, states, and the nation to produce a complete data set, which is available to the research community on the Internet.