TAILIEUCHUNG - Handbook of Economic Forecasting part 103

Handbook of Economic Forecasting part 103. Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting. The handbook covers developments in how forecasts are constructed based on multivariate time-series models, dynamic factor models, nonlinear models and combination methods. The handbook also includes chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on survey forecasts and volatility forecasts. Areas of applications of forecasts covered in the handbook include economics, finance and marketing | 994 PH. Franses where ak 0 for k p and fik 0 for k m. These partial derivatives can be used to compute the decay factor dSt _ 3St k p k 4 US dA Due to the very nature of the data this decay factor can only be computed for discrete values of k. Obviously this decay factor is a function of the model parameters. Through interpolation one can decide on the value of k for which the decay factor is equal to some value of p which is typically set equal to or . This estimated k is then called the p -percent duration interval. Next to its point estimate one would also want to estimate the confidence bounds of this duration interval taking aboard that the decay factors are based on non-linear functions of the parameters. The problem when determining the expected value of p k is that the expectation of this non-linear function of parameters is not equal to the function applied to the expectation of the parameters that is E f 0 f E 0 . So the values of p k need to be simulated. With the proper assumptions for the general ADL model it holds that the OLS estimator is asymptotically normal distributed. Franses and Vroomen 2003 suggest to use a large number of simulated parameter vectors from this multivariate normal distribution and calculate the values of p k . This simulation exercise also gives the relevant confidence bounds. The Koyck model Although the general ADL model seems to gain popularity in advertising-sales modeling see Tellis Chandy and Thaivanich 2000 and Chandy et al. 2001 a commonly used model still is the so-called Koyck model. Indeed matters become much more easy for the ADL model if it is assumed that m is rc all a parameters are zero and additionally that Pj p0Tj_1 where T is assumed to be inbetween 0 and 1. As this model involves an infinite number of lagged variables one often considers the so-called Koyck transformation Koyck 1954 . In many studies the resultant model is called the Koyck The Koyck transformation amounts to multiplying both

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