We hope to be able to provide answers to the following questions: 1) Has there been a structural break in postwar U.S. real GDP growth toward more stabilization? 2) If so, when would it have been? 3) What's the nature of the structural break? For this purpose, we employ a Bayesian approach to dealing with structural break at an unknown changepoint in a Markov-switching model of business cycle. Empirical results suggest that there has been a structural break in U.S. real GDP growth toward more stabilization, with the posterior mode of the break date around 1984:1. Furthermore, we #nd a narrowing gap between growth rates during recessions and booms is at least as important as a decline in the volatility of shocks. Key Words: Bayes Factor, Gibbs sampling, Marginal Likelihood, Markov-Switching, Stabilization, Structural Break. JEL Classi#cations: C11, C12, C22, E32. 1. Introduction In the literature, the issue of postwar stabilization of the U.S. economy relative to the prewar period has...

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We consider a deterministically trending dynamic time series model in which multiple structural changes in level, trend and error variance are modeled explicitly and the number but not the timing of the changes are known. Estimation of the model is made possible by the use of the Gibbs sampler. The determination of the number of structural breaks and the form of structural change is considered as a problem of model selection and we compare the use of marginal likelihoods, posterior odds ratios and Schwarz ' BIC model selection criterion to select the most appropriate model from the data. We evaluate the e cacy of the Bayesian approach using a small Monte Carlo experiment. As empirical examples, we investigate structural changes in the U.S. ex-post real interest rate and in a long time series of U.S. real GDP.

Many empirical studies find a negative correlation between the returns on the nominal spot exchange rate and the lagged forward discount. This forward discount anomaly implies that the current forward rate is a biased predictor of the future spot rate. A large number of studies in the existing literature try to explain this anomaly, and recent work has tried to explain the anomaly as a statistical artifact based on (1) the long memory behavior of the forward discount; or (2) the existence of structural breaks in the forward discount. In this paper, we evaluate the evidence for long memory and structural change in the forward discount. Our approach is as follows. First, we nonparametrically estimate the long memory parameter for a number of forward discount series without allowing for structural breaks. Second, we test for and estimate a multiple mean break model and then adjust for the structural breaks in the forward discount. Finally, we re-estimate the long memory parameter on the mean-break adjusted data. To check the robustness of our results, we use Monte Carlo simulations to evaluate our procedure to estimate structural breaks in the presence of long-memory. We show that allowing for structural breaks drastically reduces the persistence of the forward discount. However, after removing the breaks, we still find evidence of stationary long memory in all of the forward discount series. Our results have important implications for understanding the statistical properties of the forward discount, because we confirm not only the presence of long memory behavior in the forward discount but also the importance of structural breaks.

This paper-- a product of the Macroeconomics and Growth Division, Policy Research Department m is part of a larger effort in the department to understand the links of foreign shocks and macroeconomic policies. Copies of the paper are available free from the World Bank, 1818 H Street lqW, Washington, DC 20433. Please contact Raquel Luz, room N11-043, extension 31320 (24 pages). January 1995

We show how …nite sample bootstrapping methods can help to detect multiple breaks in systems of equations with long time series. The method of Banerjee and Urga (1995, 1996), where single breaks in the marginal models are imposed in the conditional model and then the conditional model estimated, is extended to cover the case of multiple (> 2) breaks in marginal and conditional models by using the technique of dominant break dating. An empirical investigation of a small monetary system for the United Kingdom establishes the viability of our method in developing congruent dynamic regression models.

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: We use a no-arbitrage, cost-of-carry pricing model to examine whether equity spot and futures markets are cointegrated. A stock index and its futures price should be cointegrated if the cost of carry is stationary. Otherwise, the appropriate cointegrating relationship is trivariate and includes the index, futures price, and cost of carry. We study the relationships among the Standard and Poor's 500 index, associated index futures price series, and interest rate for January 4, 1988, through June 30, 1995, and find that all three series are nonstationary. We further find that the index and futures price are not cointegrated unless the cost of carry is included in the cointegrating relationship. Our findings are consistent with the no-arbitrage pricing model and do not appear to be sensitive to the presence of structural breaks in the series. JEL classification: G10, G12 Key words: cointegration, cost-of-carry model Stochastic Trends and Cointegration in the Market for Equities I. I...

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In this paper we test for the existence of asset price bubbles in Latin America in the 19802001 period, focusing mainly on stock prices. Based on unit root and cointegration tests we cannot reject the hypothesis of bubbles. We arrive at the same conclusion using Froot and Obstfeld's intrinsic bubbles model. We identify periods of significant stock price overvaluation to examine empirical regularities of these bubble episodes in the region. We quantify the relative importance of different factors that determine the probability of bubble occurrence, focusing on the contrast between the country-specific variables and the common external factors. We included in the country-specific variables (a) both the level and the volatility of domestic credit growth, (b) the volatility of asset returns, (c) capital flows to each country, and (d) the terms of trade. As common external variables, we considered (a) the degree of asset overvaluation in the stock market and the real estate market in the U.S., and (b) the term spread of U.S. Treasury securities. To quantitatively assess the relative importance of each factor, we estimated a Logit model for a panel of five Latin American countries from 1985 to 2001. In general, we found that the marginal probabilities of both common and country-specific variables were roughly of the same order of magnitude. This contrasts with previous studies that found that real asset returns in Latin America were dominated by local factors. Finally we explore the main channels through which asset prices affect real economic activity, with the most important being the balance-sheet effect and its impact on bank lending. We show how the allocation of bank lending across different sectors responded sensitively to real estate prices during the boom years in co...