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Expert has developed and tested numerous forecasting methods to pick the best forecasting models for his clients. He has used some of the most advanced statistical models to significantly improve forecast accuracy. A significant part of his research has involved the detection of market trends. The class of forecasting models considered are ARIMA (Autoregressive Integrated Moving Average), ESM (Exponential Smoothing Models: triple exponential models), and SLR (Seasonal Regression Models).

He has used his extensive and advanced econometric/statistical training to develop forecasting models that have brought his clients significant accuracy in their estimation of program impacts and forecast capabilities. He has over twenty years of quantitative research and consulting experience in this area. Some of his cutting edge research results have been published in prestigious economic/industry journals such as Review of Economics and Statistics or Resource and Energy Economics Journal.

Expert has conducted extensive market segmentation based on analysis of survey responses. His market segmentation work has been based on developing cluster analysis and discriminant analysis methodology to determine the factors associated with customers’ preferences.

Expert has used his advanced applied statistics training to help his clients in the CPG, financial, and energy industries. He has over 20 years of experience in statistical modeling, time series forecasting, survival, and demand analysis. He has successfully demonstrated his ability to identify problems, analyze needs, and develop strategies to solve problems. Additional experience includes award-winning instruction of econometrics, and statistics courses at the University of Wisconsin – Madison. Some of his cutting edge research results have been published in prestigious quantitative/industry journals such as Review of Economics and Statistics or Resource and Energy Economics Journal.

Customer Response to Marginal Cost Based Hourly Prices. Conducted first-of-its-kind econometric analysis to compare customer behavior under real-time pricing with that of a pre-selected control group. Client: Niagara Mohawk Power Corporation Incorporation of Real Time Price Customer Response into System Operations and Day-Ahead Price Forecasting. Developed the methodology, simulated multiple price scenarios, and determined the optimal price for the following day. Client: Georgia PowerTime-Of-Use Study. Designed numerous voluntary TOU programs. Estimated load impacts and designed and implemented customer surveys to explore potential differences between participants and non-participants. Analysis of results led to approval of new rate programs by the regulatory commissions. Supervised up to 10 colleagues for different stages of these projects. Client: Midwest Power CorporationMarket Segmentation Based on Analysis of Survey Responses. Developed cluster analysis and discriminant analysis methodology to determine the factors associated with customers’ preferences for certain consumer products.Sample Design and Statistical Analysis for Various Studies. Developed experimental designs and significantly improved existing sampling methodologies that increase efficiencies and cut sampling costs while improving precision and reliability of results. Analyzed the survey responses using the collected survey data. Client: USPS