Labeling Regulations and Segregation of First- and, Second-Generation Genetically Modified Products: Innovation Incentives and Welfare Effects, April 2005

We review some of the most significant issues and results on the economic effects of genetically modified (GM) product innovation, with emphasis on the question of GM labeling and the need for costly segregation and identity preservation activities. The analysis is organized around an explicit model that can accommodate the features of both first-generation and second-generation GM products. The model accounts for the proprietary nature of GM innovations and for the critical role of consumer preferences vis-à-vis GM products, as well as for the impacts of segregation and identity preservation and the effects of a mandatory GM labeling regulation. We also investigate briefly a novel question in this setting, the choice of “research direction”when both cost-reducing and quality-enhancing GM innovations are feasible.

An Evaluation of the Second Generation Consolidation Monitoring Device, HR-1013, 1984

The objective was to evaluate the usefulness, accuracy, precision, and reproducibility of the second generation CMD for PC concrete under production conditions.

Assessing High-Speed Internet Access in the State of Iowa: Second Assessment, February 2002

Report for Iowa Utilities Board

Quadrennial Need Study Report on Highways, Roads, and Streets for Study Years 2002-2021, Second Annual Update, January 2004

Study report on highways, roads and streets for future years by Iowa Department of Transportation

Quarterly Census of Employment and Wages, Preliminary County Data, Second Quarter, 2004

Second Quarterly County information for Census of Employment & Wage, County

Quarterly Census of Employment and Wages, Preliminary Statewide Data, Second Quarter, 2004

Second Quarterly County information for Census of Employment & Wage, Statewide

Iowa Workforce, Today and Tomorrow, 2004

Demographic and employment information are used by economic developers, market researchers, counselors and curriculum developers for educational institutions, academic researchers, government planners, and private businesses. Occupational information on employment and wages also provides guidance for students making their first career choices and older workers considering a change of profession. In the last decade, Iowans have grown older and more diverse. The median age (2000) stood at 36.6 years, with 38 counties recording a median age of 40 or above. In the last decade, Hispanics accounted for a third of Iowa’s population growth. The most highly educated Iowans were Asians, with 43 percent earning a minimum of a bachelor’s degree. The Iowa labor force has been growing erratically since 1980, but still reached a record 1,663,000 in 2002 before inching downward. In the next 25 years, the labor force will see dramatic changes with the impending retirement of the baby boom generation and the influx of new immigrants and younger college-educated workers. While Iowa nonfarm employment declined by 7,000 workers during 2003, it did show improvement in the second half of the year. In a prosperous year, the Iowa economy generates an average of 2,500 jobs per month. This number was negative during the recession and has been below average this year. National economic events will continue to have a strong impact on Iowa job growth. Occupations requiring higher education are among the higher-paying Iowa jobs. Computer software engineers, computer support specialists, and customer service representatives are expected to be among the faster-growing occupations. Also, the aging population will bring opportunities for workers in healthcare. Occupations requiring higher education are among the higher-paying Iowa

Worknet, Second Quarter, 2002

Newsletter for the Iowa Workforce Development

Worknet, Second Quarter, 2004

Newsletter for the Iowa Workforce Development

Worknet, Second Quarter, 2003

Newsletter for the Iowa Workforce Development

Generation of Simulated Daily Precipitation and Air and Soil Temperatures, January 2000

This paper describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Parameter estimates are reported for Brookings, SD, and Boone, IA, to illustrate the procedure. The use of this parametric model to generate stochastic time series of daily weather is then summarized. A soil temperature model is described that determines daily average, maximum, and minimum soil temperatures based on air temperatures and precipitation, following a lagged process due to soil heat storage and other factors.