Question

Why we should not worry about omitted variable bias in forecasting using time-series analysis?

Answer 1

The omitted-variable bias (OVB) in statistics arises if the statistical model omits out one or more relevant variables. The values in are time-series data are generated with the stochastic process wherein the assumptions can be made that move forward the process through time. In a time series regression the most common source of omitted variable bias is time. It will be true even if there would be no substantive relationship among the two variables. Therefore the omitted variable bias will be irrelevant for forecasting using time-series analysis.