Testing for residual autocorrelation in growth curve models

摘要

Growth curve models are frequently used for technological forecasting. Despite the practical importance of these models, the time series properties of the residuals in these models are often overlooked. Neglected serial correlation in the residuals leads to suboptimal statistical inference and inaccurate out-of-sample forecasts. This paper gives a general diagnostic test for residual autocorrelation, which is based on the Lagrange multiplier principle. The test is illustrated for the logistic curve and the Gompertz curve.