The effect of sampling error on the time series behavior of consumption data

Abstract

Much empirical economic research today involves estimation of tightly specified time series models that derive from theoretical optimization problems. Resulting conclusions about underlying theoretical parameters may be sensitive to imperfections in the data. We illustrate this fact by considering sampling error in data from the Census Bureau's Retail Trade Survey. We find that parameter estimates in seasonal time series models for retail sales are sensitive to whether a sampling error component is included in the model. We conclude that sampling error should be taken seriously in attempts to derive economic implications by modeling time series data from repeated surveys.