After a prolonged period characterized by rapid real appreciation in house prices, there is now broad recognition of the severe correction in housing markets that followed as one of the causes of the 2008-09 global recession. We investigate the time series characteristics of three relevant price indicators of the housing market-real house prices, price-to-income, and price-to-rent ratios-for the U.S. and 21 other countries during the period 1975Q1-2013Q2 (see Mack and Martínez-García (2011)) for evidence of explosive behavior as a plausible explanation for the boom and bust. The empirical detection of explosive behavior in house prices provides a precise timeline as well as empirical content to the narrative connecting the evolution of housing markets to the global recession; our rich cross-country dataset o¤ers a novel international perspective. For testing and detection, we adopt a pair of novel techniques based on a right-tail variation of the standard Augmented Dickey-Fuller (ADF ) test-the supremum ADF (SADF ) ) and the generalized SADF (GSADF ) (Phillips et al. (2012) and Phillips et al. (2013))-where the alternative hypothesis is of a mildly explosive process (even periodically collapsing with the GSADF test) behavior within sample. Statistically signi…cant periods of exuberance are found in most countries, with our empirical estimates suggesting an unprecendented synchronization across countries preceeding the global recession. The boom in housing begins during the late 90s in the U.S. spreading to most countries by the early 2000s, until it bursts for most during 2007 08 as the impact on economic activity was being felt. In this regard, our …ndings corroborate the narrative of the 2008-09 global recession. In this paper, we also discuss more generally the use of these procedures to monitor international housing markets and as a warning signal.JEL Classi…cation: C22, G12, R30, R31

https://sites.google.com/view/emgeconomics/. This research was initiated while Adrienne Mack (Mutual of Omaha) was working at the Federal Reserve Bank of Dallas. Since the update of May 2015, Valerie Grossman has been responsible for maintaining and developing the database and became the main contacting author for this paper too. We acknowledge Christophe André for providing helpful feedback on the OECD's own international house price dataset and the assistance of many national statistical offices and/or central banks in collecting the house price data (especially the relevant historical series). This draft is still work-in-progress as we continue to extend and enhance the database itself. The views in this paper are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System.

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The global slack hypothesis (e.g., Martínez-García and Wynne (2010)) is central to the discussion of the trade-offs monetary policy faces in an increasingly more open world economy. Open-Economy (forward-looking) New Keynesian Phillips curves describe how expected future inflation and a measure of global output gap (global slack) affect the current inflation rate. This paper studies the (potential) weak identification of these relationships in the context of a fully-specified structural model using Bayesian estimation techniques. We trace the problems to sample size, rather than misspecification bias. We conclude that standard macroeconomic time series with a coverage of less than forty years are subject to potentially serious identification issues, and also to model selection errors. We recommend estimation with simulated data prior to bringing the model to the actual data as a way of detecting parameters that are susceptible to weak identification in short samples.

This Online Appendix reports detailed results on the inflation forecasting horserace conducted by Duncan and Martínez-García (2022). The tables of results found here complement the evidence and are explained/contextualized in that paper. The dataset that we use here is exactly the same covering a sample of 18 countries (

We model local inflation dynamics using global inflation and domestic slack motivated by a novel interpretation of the implications of the workhorse open-economy New Keynesian model. We evaluate the performance of inflation forecasts based on the single-equation forecasting specification implied by the model, exploiting the spatial pattern of international linkages underpinning global inflation. We find that incorporating crosscountry interactions yields significantly more accurate forecasts of local inflation for a diverse group of 14 advanced countries (including the U.S.) than either a simple autoregressive model or a standard closed-economy Phillips curve-based forecasting model. We argue that modelling the temporal dimension-but not the crosscountry spillovers-of inflation does limit a model's explanatory power in-sample and its (pseudo) out-of-sample forecasting performance. Moreover, we also show that global inflation (without domestic slack) often contributes the most to achieve the gains on forecasting accuracy observed during our sample period (1984:Q1-2015:Q1)-this observation, according to theory, is crucially related to the flattening of the Phillips curve during this time period of increased globalization.