This paper illustrates the flexibility of the ESTAR model to encompass a number of different char... more This paper illustrates the flexibility of the ESTAR model to encompass a number of different characteristics found in economic and financial series, such as multiple equilibria, complex dynamics, chaotic-like behavior, and spurious trends. We then reassess the power of the Kapetanios et al. (2003), Enders and Granger (1998), and Augmented Dickey Fuller unit root tests in the presence of nuisance parameters for parameter values typically encountered in the empirical literature. Our results show the lack of dominance of any particular test and that the power is not independent to priors about the nuisance parameters. Finally, we examine several asset price deviations from fundamentals and one hyper-inflation series and find contradictory results between the nonlinear fitted models and unit root tests. The findings highlight that new testing procedures with higher power are desirable.
Recent empirical work has reported results in which the behavior of many macroeconomic and financ... more Recent empirical work has reported results in which the behavior of many macroeconomic and financial time series is parsimoniously captured by nonlinear models (see e.g., Taylor et al., 2001; Bec et al., 2000; Taylor, van Dijk and Franses, 2000; Monoyios and Sarno, 2002). However, the fact that a series may exhibit both nonlinearity and heteroskedasticity in the mean suggests that caution should be taken in hypothesis testing (e.g. Bera and Higgins, 1997). This paper investigates the performance of a series of linearity tests. Namely, the unit root tests of Kapetanios et al. (2003), the GLS detrended test of Kapetanios and Shin (2002), and the more general test for linearity by Escribano and Jorda (2001). We examine the size and power of those tests when heteroskedasticity of different forms is present in the data (ARCH/GARCH, unknown form, Markov switching). Monte Carlo simulations indicate that the effect of the heteroskedasticity on the hypothesis testing can be severe. Asymptoti...
In this paper, we examine changes in the time series properties of standard housing market indica... more In this paper, we examine changes in the time series properties of standard housing market indicators (real house prices, price-to-income ratios, and price-to-rent ratios) for a large set of countries to detect episodes of explosive dynamics. Dating exuberance in housing markets provides a timeline as well as empirical content to the narrative connecting housing exuberance to the global 2008―09 recession. For our investigation, we employ two recursive univariate unit root tests developed by Phillips et al. (2011) and Phillips et al. (2015). We also propose a novel extension of the Phillips et al. (2015) test to a panel setting in order to exploit the large cross-sectional dimension of our international dataset. Statistically significant periods of exuberance are found in most countries. Moreover, there is also strong evidence of an unprecedented period of exuberance in the early 2000s that eventually collapsed around 2006―07, preceding the 2008―09 global recession. We find that long-term interest rates, credit growth and global economic conditions help to predict (in-sample) episodes of housing exuberance. We conclude that global macro and financial factors explain (partly) the synchronization of exuberance episodes that we detect in the data in the 2000s.
ABSTRACT The detection of explosive behavior in house prices and the implementation of early warn... more ABSTRACT The detection of explosive behavior in house prices and the implementation of early warning diagnosis tests are of great importance for policy-making. This paper applies the GSADF test developed by Phillips et al. (2012) and Phillips et al. (2013), a novel procedure for testing, detection and date-stamping of explosive behavior, to the data from the Dallas Fed International House Price Database documented in Mack and Martínez-García (2011). We discuss the use of the GSADF test to monitor international housing markets. We assess the international boom and bust cycle experienced during the past 15 years through this lens — with special attention to the United States, the United Kingdom, and Spain. Our empirical results suggest that these three countries experienced a period of exuberance in housing prices during the late 90s and the first half of the 2000s that cannot be attributed solely to the behavior of fundamentals. Looking at all 22 countries covered in the International House Price Database, we detect a pattern of synchronized explosive behavior during the last international house boom-bust episode not seen before.
This paper deals with the nonlinear modeling and forecasting of the dollar-sterling real exchange... more This paper deals with the nonlinear modeling and forecasting of the dollar-sterling real exchange rate using a long span of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in-sample statistical tests. Second, we investigate the small sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post-Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The winner turns out to be the nonlinear model, against the odds. 1 Despite the overwhelming evidence supporting the presence of nonlinearites in real exchange rates (e.g., Taylor et al., 2001; Pavlidis et al., 2009a), the empirical literature on the out-of-sample performance of Smooth Transition Autoregressive (STAR) models is scarce, and a bet that a nonlinear model beats a linear one would be against the odds. One of the few studies on nonlinear real exchange rate forecasting is that of Sarantis (1999). By employing monthly real effective exchange rates for the G-10 countries from 1980 to 1996, the author provides evidence in favor of the presence of significant smooth-transition nonlinear dynamics for the majority of the processes. Moreover, the estimated STAR models provide more accurate forecasts, in terms of the root mean square error criterion, against the Random Walk (RW) and the Markov Switching model but not the linear autoregressive (AR) model. A recent study that utilizes more sophisticated forecast evaluation techniques and a longer data set for the post-Bretton Wood era is provided by Rapach and Wohar (2006). The authors replicate the results of Obstfeld and Taylor (1997) and Taylor et al. (2001) by fitting Threshold Autoregressive (TAR) and Exponential STAR (ESTAR) models to four monthly U.S. dollar real exchange rates. On the basis of point, interval and density forecasts comparisons Rapach and Wohar (2006, p. 341) conclude: "any nonlinearities in monthly real exchange rate data from the post-Bretton Woods period are quite "subtle" for Band-TAR and exponential smooth autoregressive model specifications". These discouraging findings may but do not necessarily imply that the nonlinearity documented in the literature is a spurious artifact. Inoue and Kilian (2005) illustrate that for linear models in-sample tests tend to have, and in many cases substantially, higher Berka, Martin, "General Equilibrium Model of Arbitrage Trade and Real Exchange Rate Persistence," MPRA Paper 234, University Library of Munich, Germany 2005. Boero, Gianna and Emanuela Marrocu, "The performance of SETAR models: a regime conditional evaluation of point, interval and density forecasts,
This paper illustrates the flexibility of the ESTAR model to encompass a number of different char... more This paper illustrates the flexibility of the ESTAR model to encompass a number of different characteristics found in economic and financial series, such as multiple equilibria, complex dynamics, chaotic-like behavior, and spurious trends. We then reassess the power of the Kapetanios et al. (2003), Enders and Granger (1998), and Augmented Dickey Fuller unit root tests in the presence of nuisance parameters for parameter values typically encountered in the empirical literature. Our results show the lack of dominance of any particular test and that the power is not independent to priors about the nuisance parameters. Finally, we examine several asset price deviations from fundamentals and one hyper-inflation series and find contradictory results between the nonlinear fitted models and unit root tests. The findings highlight that new testing procedures with higher power are desirable.
Recent empirical work has reported results in which the behavior of many macroeconomic and financ... more Recent empirical work has reported results in which the behavior of many macroeconomic and financial time series is parsimoniously captured by nonlinear models (see e.g., Taylor et al., 2001; Bec et al., 2000; Taylor, van Dijk and Franses, 2000; Monoyios and Sarno, 2002). However, the fact that a series may exhibit both nonlinearity and heteroskedasticity in the mean suggests that caution should be taken in hypothesis testing (e.g. Bera and Higgins, 1997). This paper investigates the performance of a series of linearity tests. Namely, the unit root tests of Kapetanios et al. (2003), the GLS detrended test of Kapetanios and Shin (2002), and the more general test for linearity by Escribano and Jorda (2001). We examine the size and power of those tests when heteroskedasticity of different forms is present in the data (ARCH/GARCH, unknown form, Markov switching). Monte Carlo simulations indicate that the effect of the heteroskedasticity on the hypothesis testing can be severe. Asymptoti...
In this paper, we examine changes in the time series properties of standard housing market indica... more In this paper, we examine changes in the time series properties of standard housing market indicators (real house prices, price-to-income ratios, and price-to-rent ratios) for a large set of countries to detect episodes of explosive dynamics. Dating exuberance in housing markets provides a timeline as well as empirical content to the narrative connecting housing exuberance to the global 2008―09 recession. For our investigation, we employ two recursive univariate unit root tests developed by Phillips et al. (2011) and Phillips et al. (2015). We also propose a novel extension of the Phillips et al. (2015) test to a panel setting in order to exploit the large cross-sectional dimension of our international dataset. Statistically significant periods of exuberance are found in most countries. Moreover, there is also strong evidence of an unprecedented period of exuberance in the early 2000s that eventually collapsed around 2006―07, preceding the 2008―09 global recession. We find that long-term interest rates, credit growth and global economic conditions help to predict (in-sample) episodes of housing exuberance. We conclude that global macro and financial factors explain (partly) the synchronization of exuberance episodes that we detect in the data in the 2000s.
ABSTRACT The detection of explosive behavior in house prices and the implementation of early warn... more ABSTRACT The detection of explosive behavior in house prices and the implementation of early warning diagnosis tests are of great importance for policy-making. This paper applies the GSADF test developed by Phillips et al. (2012) and Phillips et al. (2013), a novel procedure for testing, detection and date-stamping of explosive behavior, to the data from the Dallas Fed International House Price Database documented in Mack and Martínez-García (2011). We discuss the use of the GSADF test to monitor international housing markets. We assess the international boom and bust cycle experienced during the past 15 years through this lens — with special attention to the United States, the United Kingdom, and Spain. Our empirical results suggest that these three countries experienced a period of exuberance in housing prices during the late 90s and the first half of the 2000s that cannot be attributed solely to the behavior of fundamentals. Looking at all 22 countries covered in the International House Price Database, we detect a pattern of synchronized explosive behavior during the last international house boom-bust episode not seen before.
This paper deals with the nonlinear modeling and forecasting of the dollar-sterling real exchange... more This paper deals with the nonlinear modeling and forecasting of the dollar-sterling real exchange rate using a long span of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in-sample statistical tests. Second, we investigate the small sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post-Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The winner turns out to be the nonlinear model, against the odds. 1 Despite the overwhelming evidence supporting the presence of nonlinearites in real exchange rates (e.g., Taylor et al., 2001; Pavlidis et al., 2009a), the empirical literature on the out-of-sample performance of Smooth Transition Autoregressive (STAR) models is scarce, and a bet that a nonlinear model beats a linear one would be against the odds. One of the few studies on nonlinear real exchange rate forecasting is that of Sarantis (1999). By employing monthly real effective exchange rates for the G-10 countries from 1980 to 1996, the author provides evidence in favor of the presence of significant smooth-transition nonlinear dynamics for the majority of the processes. Moreover, the estimated STAR models provide more accurate forecasts, in terms of the root mean square error criterion, against the Random Walk (RW) and the Markov Switching model but not the linear autoregressive (AR) model. A recent study that utilizes more sophisticated forecast evaluation techniques and a longer data set for the post-Bretton Wood era is provided by Rapach and Wohar (2006). The authors replicate the results of Obstfeld and Taylor (1997) and Taylor et al. (2001) by fitting Threshold Autoregressive (TAR) and Exponential STAR (ESTAR) models to four monthly U.S. dollar real exchange rates. On the basis of point, interval and density forecasts comparisons Rapach and Wohar (2006, p. 341) conclude: "any nonlinearities in monthly real exchange rate data from the post-Bretton Woods period are quite "subtle" for Band-TAR and exponential smooth autoregressive model specifications". These discouraging findings may but do not necessarily imply that the nonlinearity documented in the literature is a spurious artifact. Inoue and Kilian (2005) illustrate that for linear models in-sample tests tend to have, and in many cases substantially, higher Berka, Martin, "General Equilibrium Model of Arbitrage Trade and Real Exchange Rate Persistence," MPRA Paper 234, University Library of Munich, Germany 2005. Boero, Gianna and Emanuela Marrocu, "The performance of SETAR models: a regime conditional evaluation of point, interval and density forecasts,
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