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Capturing asymmetry in real exchange rate with quantile autoregression

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  • Mauro Ferreira

Abstract

Quantile Autoregression (QAR) is used to explore asymmetries in the adjustment process of pairwise Real Exchange Rate (RER) between the Italian lire, French franc, Deutsch mark and the British pound. Based on the best specification for each quantile we construct predicted conditional density functions, which guided us to identify two sources of asymmetry: (1) dispersion depends on the conditioned value of the RER, i.e. 'conditional' heteroskedasticity; (2) the probability of increases and falls also changes according to the conditioned value, i.e. there is higher probability for the RER to appreciate (depreciate) given the currency is depreciated (appreciated). We only verified strong heterokedasticity in relations among the lire, franc and mark, which was resolved by estimating quadratic autoregressive model for some quantiles. Relations involving the pound presented stable but higher dispersion indicating larger probability of wider oscillation.

Suggested Citation

  • Mauro Ferreira, 2011. "Capturing asymmetry in real exchange rate with quantile autoregression," Applied Economics, Taylor & Francis Journals, vol. 43(3), pages 327-340.
    • Handle: RePEc:taf:applec:v:43:y:2011:i:3:p:327-340
    DOI: 10.1080/00036840802584919
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    References listed on IDEAS

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    Cited by:

    1. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    2. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    3. Mohsen Bahmani-Oskooee & Omid Ranjbar, 2016. "Quantile unit root test and PPP: evidence from 23 OECD countries," Applied Economics, Taylor & Francis Journals, vol. 48(31), pages 2899-2911, July.

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