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Journal of the Royal Statistical Society, Series B, 31 49 Butler, R W, and Huzurbazar, A V (1993) Prediction in stochastic networks In Bulletin of the International Statistical Institute, Proceedings of the 49th Session, Book 3, Topic 23 Butler, R W, and Huzurbazar, A V (1997) Stochastic network models for survival analysis Journal of the American Statistical Association, 92, 246 257 Butler, R W, and Huzurbazar, A V (2000) Bayesian prediction of waiting times in stochastic models The Canadian Journal of Statistics, 28, 311 325 Carlin, B, and Louis, T (1996) Bayes and Empirical Bayes Methods for Data Analysis New York: Chapman & Hall Casella, G, and Berger, R (2002) Statistical Inference, 2nd edition Paci c Grove, CA: Duxbury Casella, G, and George, E (1992) Explaining the Gibbs sampler American Statistician, 46, 167 174 Chatterjee, A, Strauss, M E, Smyth, K A.



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Because workers and businesses can find out about macroeconomics just as well as the politicians running the government, they realise that the only long-run effect of the upcoming stimulus will be for prices to rise from Po to P1 In addition, workers understand that real wages will remain unchanged in the long run, because both their nominal wages and their cost of living (given by the price level) will increase by equal amounts As a result, they know that in the long run, the stimulus isn t going to help them at all Indeed, their only hope for gains is based entirely upon the short run, when nominal wages should go up and the price level should stay the same In other words, they hope to benefit from the movement from A to B in Figure 7-2 But firms aren t stupid.





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, and Whitehouse, P J (1992) Personality changes in Alzheimer s disease Archives of Neurology, 49, 486 491 Chatterjee, S, Laudato, M, and Lynch, L (1996) Genetic algorithms and their statistical applications: an introduction Computational Statistics and Data Analysis, 22, 633 651 Chib, S, and Greenberg, E (1995) Understanding the Metropolis Hastings algorithm American Statistician, 49, 327 335 Collett, D (1994) Modelling Survival Data in Medical Research Boca Raton, FL: Chapman & Hall/CRC Press Commenges, D (1986) Semi-Markov and non-homogeneous Markov models in medicine In Semi-Markov Models: Theory and Applications, ed J Janssen New York: Plenum Press, pp 423 436 Commenges, D, Letenneur, L, Joly, P, Alioum, A, and Dartigues, J F, (1998) Modelling age-speci c risk: application to dementia Statistics in Medicine, 17, 1973 1988 Cox, D R (1955) A use of complex probabilities in the theory of stochastic processes.

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They don t want to have their profits reduced because wages are rising while prices are fixed So they simply anticipate everything Because prices eventually have to rise from Po to P1 and wages eventually have to rise by an equal amount, firms get ahead of the wage increases by raising prices as soon as they can Nothing prevents firms from raising prices because nothing in the economy is causing upward price stickiness So, if firms can see the stimulus coming ahead of time, they simply raise prices as soon as they can in order to make sure that prices and wages are going up at the same pace As a result, the price level jumps from Po to P1 Of course, at the same time, firms raise wages by an equal percentage in order to keep real wages the same.

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Proceedings of the Cambridge Philosophical Society, 51, 313 319..

They want to keep workers motivated to supply the labour necessary to produce Y* worth of output As you can see, if a government tries to stimulate the economy to produce beyond Y*, and if the stimulus is understood and anticipated by everyone in the economy, the policy may not work at all Prices and wages may simply.

and resulting change drives the whole industry and answers the demand from consumers for a constant stream of new ideas and offerings. Indeed it could be argued that without this constant generation and introduction of new ideas into the marketplace, the concept of fashion would not exist. Axiomatically, if consumers were not constantly engaged in the process of looking for new products or services to satisfy their emerging needs (and once having consumed them, allowing a set of new and different needs to emerge), the fashion process could not function. Thus the industry revolves around a time-based, i.e. seasonal, process in which new fashions are introduced into the marketplace and are adopted by enough consumers to warrant the description of fashion in its proper context in the rst place (as a current mode of consumption behaviour), only to wane eventually in terms of popularity, thus rendering them unfashionable . While some product offerings will remain popular over several or even many seasons, others will fade very quickly; these differences are discussed further in the chapter. The important point to stress here, however, is that this regenerative process is intrinsic to the fashion industry and is very necessary for its continued survival.

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