The Measurement of Quality-Adjusted Price Changes
The Measurement of Quality-Adjusted Price Changes
This chapter explores the alternative approaches to using scanner data for adjusting prices for quality change. It also compares the results of the three methods of measuring quality-adjusted price changes using scanner data: time dummy variable approach, exact (and superlative) hedonic indexes, and matching procedure. The superlative matched index effectively adjusts for changes in the quality mix of purchases being based on computational matching as opposed to statistical models. The use of hedonic adjustment methods offers an explicit basis for the quality adjustments. Different hedonic adjustment techniques present similar results, although the old and new predicted to actual appear to work best as a geometric mean. Scanner data provide a proxy variable on the extent to which each variety is sold in different outlets, and use of this is being considered to develop the experiment.
Keywords: scanner data, price changes, quality, time dummy variable approach, superlative matched index, computational matching, hedonic adjustment
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