Microbased Time Series Analysis: Estimating the autocorrelation function using survey samples
Analysts using data from official statistical authorities often neglect the fact that data frequently is collected using sample surveys. We study the impact of sampling error on the estimation of the autocorrelation function for a population total under a microbased superpopulation time series model. We show that uncritical use of data published by statistical agencies may result in biased estimators. The bias is caused by the sampling error and is different from aggregation bias, Theil (1954). A simulation study shows that the bias can be considerable.
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