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Steve Miller - Michigan State University. East Lansing, MI, US

Steve Miller Steve Miller

Director of the Center for Economic Analysis and Assistant Professor, Agricultural, Food, and Resource Economics | Michigan State University


An expert in applied economic forecasting, modeling, and impact analysis.





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Fixed-term assistant professor Dr. Steven R. Miller specializes in applied economic methods for forecasting and impact analysis. As a graduate, Steven maintained and programmed the Oklahoma State University Econometric Forecasting model and served as investigator on several Oklahoma Department of Human Resources studies of TANF funding, and child support studies for impact and needs assessments.

He has produced numerous impact assessments of Wichita, Kansas area businesses seeking state and local sponsored incentives, produced papers on aviation demand across competing regional airports, and papers on alternative estimation methods of systems modeling. He is currently working on: Development of Profitable Michigan-Based Meat and Livestock Value Chains.

Industry Expertise (3)

Writing and Editing Education/Learning Food and Beverages

Areas of Expertise (3)

Michigan film industry economic impacts Climate and energy policy economic impacts Gas Prices

Education (2)

Oklahoma State University: Ph.D.

Oklahoma State University: B.A.

Journal Articles (2)

Waste biomass inventory to support renewable energy development American Society of Agricultural and Biological Engineers

Jason M Schneemann, Steve Andrew Miller, Yan “Susie” Liu, Steven I Safferman


Anaerobic digestion, gasification, direct combustion, ethanol production, biodiesel production, and other such technologies convert waste biomass to a renewable energy source as well as protect human health and the environment. High capital costs require optimized biomass-based fuels that are often developed by blending wastes. Transportation distances to move the biomass, however, must be minimized or a negative energy balance may result. Many states have compiled an inventory to assist in locating sources of biomass waste and non-productive crop land, including California, Ohio, Wyoming, Washington, and New Jersey. Several of these tools include a calculator to estimate energy availability from waste biomass. Michigan is developing a unique tool that also flags factors that may impact a site’s suitability for a centralized facility.

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Screening co‐digestion of food waste water with manure for biogas production Bio FPR

Yan Liu, Steve A. Miller, Steven I. Safferman


Anaerobic digestion, an environmental protection technology for treating organic compounds in waste water, produces biogas, resulting in a renewable energy source. A protocol including waste analysis, waste blending, energy potential and energy balance calculations was developed to determine the energy production from blending food and animal wastes. Fruit and vegetable waste water produced from crop commodity processing was characterized in terms of quantity and 5‐day biochemical oxygen demand (BOD). Often these wastes have high levels of degradable carbon but lack buffering capacity and adequate nitrogen and other nutrients to meet the minimal C/N ratio needed for optimal digestion. Blending food‐processing waste water with high nutrient manure can enhance the biogas production by optimizing nutrient levels and providing buffering capacity. The protocol shows the procedure to determine the optimal blend and theoretical biogas production from the anaerobic digestion of that blend. An energy balance technique that determines the lowest COD concentration required to close the energy balance in the digester during different seasons is illustrated. A case study was conducted to determine the potential energy production from anaerobically digesting blended waste water from the top 14 fruit and vegetable commodities in Michigan. The resulting biogas production supports a substantial amount of the energy consumption needed for the treatment process. This case study in Michigan can be extended to national level since the calculations were based on the mean value of their typical range.

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