Estimating Average Economic Growth in Time Series Data with Persistency

This paper studies estimation of deterministic trends in time series models with persistency. In particular, a joint estimation of the trend coefficient and the autoregressive parametere is proposed and asympototic analysis on the nonlinear estimator is provided. The joint estimator is compared with several conventional trend estimators. Monte Carlo experiments indicate that the proposed estimators have good finite sample performance. We use these procedures to estimate growth rates for real GNP and consumer price index in 40 countries.