Estimating demand for new products using a discrete price variable
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In this paper, the authors conduct a set of Monte Carlo sampling experiments to examine the use of discrete explanatory variables in market research for new products and compare three alternative estimators on the basis of mean square error.Abstract:
We conduct a set of Monte Carlo sampling experiments to examine the use of discrete explanatory variables in market research for new products. We compare three alternative estimators on the basis of mean square error. As part of the experimental design we vary the number of price points and the distribution of the error term. In addition, we consider demand functions that are linear, linear with structural breaks and nonlinear. In each case, our results show that using two discrete price points leads to the lowest estimation risk.read more
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Indirect estimation of (latent) linear models with ordinal regressors A Monte Carlo study and some empirical illustrations
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