PPP Strikes Back: Aggregation and the Real Exchange Rate

Imbs, Jean; Mumtaz, Haroon; Ravn, Morton; Rey, Hélène

doi:10.3386/w9372

Cited by 151 publications

(216 citation statements)

References 47 publications

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“…Imbs et al (2005) examine a related problem and note that the relationship between the persistence of the aggregate and the persistence of the components depends on a complex function of the covariances of the time series. For series that are uncorrelated, so the covariances are zero, the persistence of the aggregate is always higher than the weighted average of the persistence of the components (computed using the same weights as those used in constructing the aggregate).…”

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confidence: 99%

Has the inflation process changed?

Cecchetti

Debelle

2006

Economic Policy

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"Inflation has been low in many countries for at least a decade. But have inflation processes changed in ways that would help make low inflation permanent? Using both aggregate and disaggregated inflation data, we find that the means of inflation processes have become smaller over the past two decades and that, allowing for these changes in the mean, their persistence has not declined much. Changes in monetary policy frameworks and recessions appear to have contributed to a reduction in the mean of inflation, but do not appear to have a meaningful impact on persistence, and there is some evidence that the shifts in inflation expectations are the proximate cause of the changes in the mean of inflation. These findings suggest that policy-makers should focus on maintaining credibility and carefully monitoring inflation expectations for any indication that they are rising." Copyright CEPR, CES, MSH, 2006.

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confidence: 99%

Has the inflation process changed?

Cecchetti

Debelle

2006

Economic Policy

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“…Let us now consider the clothing price data used in Imbs et al (). Note that since the sample period for the clothing price data is only one and a half decades long, we compute the deviation of the real exchange rate from PPP,

{true \overset{q}{true}}_{t}

, as the deviation of the real exchange rate from its mean, rather than from its linear time trend.…”

Section: Resultsmentioning

confidence: 99%

“…The second data set, which we downloaded from Hélène Rey's homepage, is the one that is used in Imbs et al (). This data set consists of data from Eurostat.…”

Section: Datamentioning

confidence: 99%

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Price level convergence and purchasing power divergence

Eleftheriou

Müller-Plantenberg

2017

International Finance

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We construct four large data sets of bilateral real exchange rates based on traded good prices (food and clothing, respectively) and broader price indices (consumer price index, CPI, and wholesale price index, WPI). On these data sets, we run non‐parametric regressions to examine how the real exchange rate, the price differential, and the nominal exchange rate react to an overvalued real exchange rate over time. In line with the theory we develop, our regressions show the following: First, real exchange rates are mean‐reverting. Second, prices converge. Third, price convergence implies purchasing power divergence and thus does not contribute to real exchange rate convergence. Indeed, when price adjustment is fast (as for our traded good price data sets), we even observe diverging nominal exchange rates. Our findings suggest that movements both away from and towards PPP may be less related to traded good price movements than is commonly thought.

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“…When dealing with multicountry data, the empirical literature has taken a number of short cuts and neglected some or all of these problems. For example, it is typical to assume that slope coefficients are common across (subsets of the) units (see, e.g., Fatas and Mihov, 2006), that there are no lagged interdependencies across units (see Dees et al, 2007), that the structural relationships are stable over arbitrary samples and that asymptotics in T apply (see Imbs et al, 2005), or a combination of all of these. None of these restrictions is appealing: Short time series are, in part, the result of new definitions and of the adaptation of international standards to data collection in developing countries; unit‐specific relationships may reflect differences in national regulations or policies; interdependencies result from world markets integration and time instabilities from evolving macroeconomic structures.…”

Section: Introductionmentioning

confidence: 99%

Estimating Multicountry Var Models*

Canova

Ciccarelli

2009

Int Economic Review

242

244

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4Non-technical summary 5 1. Introduction 7 2. The model 10 Inference 14 Model selection 185. Dynamic analysis 19 Recursive unconditional forecasts 195.2 Impulse responses 20 Conditional forecasts 236. The transmission of shocks in G-7 countries 24 Conclusions 29 References 31European Central Bank Working Paper Series 34 AbstractThis paper describes a methodology to estimate the coefficients, to test specification hypotheses and to conduct policy exercises in multi-country VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of MCMC routine. The transmission of certain shocks across G7 countries is analyzed. Non-technical SummaryWhen dealing with multi-country data, the empirical literature has taken a number of short cuts.For example, it is typical to assume that in the dynamic specification slope coefficients are common across (subsets of the) units; that there are no interdependencies across units or that they can be summarized with a simple time and unit invariant index; that the structural relationships are stable over time; that asymptotics in the time series dimension apply; or a combination of all of these.None of these restrictions is appealing: short time series are the result, in part, of new definitions and the adaptation of international standards to data collection in developing countries; unit specific relationships may reflect difference in national regulations or policies; interdependencies results from world markets integration and time instabilities from evolving macroeconomic structures. This paper shows how to conduct inference in multi-country VAR models featuring short time series and, potentially, unit specific dynamics, lagged interdependences and structural time variations. Since these last three features make the number of coefficients of the model large, no classical estimation method is feasible. We take a flexible Bayesian viewpoint and weakly restrict the coefficient vector to depend on a low dimensional vector of time varying factors. These factors capture, for example, variations in the coefficients which are common across units and variables (a "common" effect); variations which are specific to the unit (a "fixed" effect) , variations which are specific to a variable (a "variable" effect), etc. Factors relating to lags and time periods, or capturing the extent of lagged interdependencies across units, can also be included. We complete the specifications using a hierarchical structure which allows for exchangeability in the fixed effects, and time variations in the law of motion of the factors and in the variance of their innovations.The factor structure we employ effectively transfo...

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PPP Strikes Back: Aggregation and the Real Exchange Rate

Cited by 151 publications

References 47 publications

Has the inflation process changed?

Has the inflation process changed?

Price level convergence and purchasing power divergence

Estimating Multicountry Var Models*

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