Although linearly interpolated series are often used in economics, little has been done to examine the effects of interpolation on time-series properties and on statistical inference. We show that linear interpolation of a trend stationary series superimposes a ‘periodic’ structure on the moments of the series. Using conventional time-series methods to make inference about the interpolated series may therefore be invalid. Also, the interpolated series may exhibit more shock persistence than the original trend stationary series.
Linear Interpolation Trend-Stationary Series Shock Persistence Periodic Properties of Time Series