Β k are the regression/slope coefficients.

X i are the variables representing observed product characteristics

P it is the price of the i th model in period t A basic regression formula for a hedonic model could take the form shown in equation 1. The regression may take different functional forms, but in each form the independent variables are “regressed” against the dependent variable yielding implicit prices (regression coefficients) for each of the independent variables. These product characteristics enter a regression as independent (explanatory) variables and the product’s selling price is entered as the dependent variable. For instance, a computer can be disaggregated into characteristics such as speed of processor, hard drive capacity, amount of memory, and many other defining features that influence the computer’s price. In other words, a product must first be disaggregated into its characteristics. At its most basic, hedonics can be described as a regression designed to isolate and measure the influence on price of economically meaningful product characteristics. 1 One of the most widely recognized pioneers in applied hedonic research was Griliches (1988) who stated that '.one might use regression techniques to relate the prices of different models or versions of a commodity to differences in their characteristics, and discover thereby the relative valuation of such qualities is reasonably obvious.” The terms hedonics or hedonic models are often used by economists when referring to a form of econometrics (Gujarati 1995). The Producer Price Index (PPI) program has developed and adopted several methodologies to respond to these quality measurement challenges, but the primary focus here will be on hedonic methods. Valuing changes in the quality of products or services is one of the oldest measurement challenges facing statistical agencies around the world. Bureau of Labor Statistics Producer Price Index Program June 2011

Hedonic Models in the Producer Price Index

Hedonic theory