Forecasting Market Shares of Alternative Home-Heating Units by Markov Process using Transition Probabilities Estimated from Aggregate Time Series Data

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Abstract
The purpose of this study is to forecast the market shares of alternative home-heating units: oil-burners, gas-burners and electric-heating units for the United States. The forecasting method used is The Markov Process with estimated transition probability matrices. The transition probabilities represent whether households will continue to use the same heating unit which they have used in the recent past or switch to another type unit. Maximum likelihood and Bayesian estimation techniques have been used to estimate these transition probabilities from aggregate historical market shares of alternative home-heating units.