@techreport{NBERt0165,
 title = "Estimating Deterministic Trends in the Presence of Serially Correlated  Errors",
 author = "Eugene Canjels and Mark W. Watson",
 institution = "National Bureau of Economic Research",
 type = "Working Paper",
 series = "Technical Working Paper Series",
 number = "165",
 year = "1994",
 month = "September",
 URL = "http://www.nber.org/papers/t0165",
 abstract = {This paper studies the problems of estimation and inference in the linear trend model: yt=à+þt+ut, where ut follows an autoregressive process with largest root þ, and þ is the parameter of interest.  We contrast asymptotic results for the cases þþþ < 1 and þ=1, and argue that the most useful asymptotic approximations obtain from modeling þ as local-to-unity.  Asymptotic distributions are derived for the OLS, first-difference, infeasible GLS and three feasible GLS estimators. These distributions depend on the local-to-unity parameter and a parameter that governs the variance of the initial error term, þ.  The feasible Cochrane-Orcutt estimator has poor properties, and the feasible Prais-Winsten estimator is the preferred estimator unless the researcher has sharp a priori knowledge about þ and þ.  The paper develops methods for constructing confidence intervals for þ that account for uncertainty in þ and þ.  We use these results to estimate growth rates for real per capita GDP in 128 countries.},
}