The purpose of this paper is to call attention to the important role that the statistical model and the data source play in the determination of a numerical estimate of price response. Price "elasticities" are estimated from both time-series and cross-sectional viewpoints using the same data base and essentially the same method of estimation, ordinary least squares regression (OLS). In each case the data are organized in a slightly different manner. The results obtained are reasonable from a statistical point of view, and yet each set suggests vastly different policy implications.