Abstract
We estimate exchange rate pass-through (PT) into import, producer and consumer price indexes for nine OECD countries, using a method proposed by Uhlig (2005). In a Vector Autoregression (VAR) model, we identify the exchange rate shock by imposing restrictions on the signs of impulse responses for a small subset of variables. These restrictions are consistent with a large class of theoretical models and previous empirical findings. We find that exchange rate PT is less than one at both short and long horizons. Among three price indexes, exchange rate PT is greatest for import price index and smallest for consumer price index. In addition, greater exchange rate PT is found in an economy which has a smaller size, higher import share, more persistent exchange rate, more volatile monetary policy, higher inflation rate, and less volatile aggregate demand.
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Notes
According to Obstfeld (2002), two conditions are required for a strong expenditure-switching effect: high exchange rate PT to import prices, but low exchange rate PT to consumer prices.
The cost includes re-tagging goods, revising and reprinting catalogues, and advertising.
Exchange rate changes are usually perceived as cost shocks for an exporter (see Yang 1997).
Industrial production is used because GDP is not available at a monthly frequency.
The nominal effective exchange rate of country j is constructed as the trade-weighted average of bilateral exchange rates between country j and its trading partners:
$$ NE{R_j} = \Pi_{{i = 1}}^qER_{{i,j}}^{{{\omega_i}}}, $$Where ER i,j is the index of bilateral nominal exchange rate between country i and j, expressed as units of currency j per unit of currency i. The weight, ω i , is the average share of imports of country j from country i during our sample period. For each country, q largest trading partners are included such that at least 80% of that country’s imports are covered in our calculation. The foreign export price index is calculated similarly.
Detailed description of the methodology is available in Uhlig (2005).
The posterior distribution is derived under the assumption of a diffuse Jeffries prior over the parameters of the VAR.
Drawing from flat prior on the unit sphere will make the results independent of the chosen decomposition of ∑. Thus, reordering the variables and choosing different Choleski decompositions in order to parameterize the impulse vectors will not yield different results.
We set n 1 = n 2 = 500, so there are 250,000 draws in total.
The impulse responses of output gaps and interest rates are not presented in the paper, but available upon request.
Our results do not change qualitatively in the simple correlation coefficients. Results of the simple correlation coefficients are available upon request.
We follow McCarthy (2007) in measuring the exchange rate volatility and persistence.
We thank the referee for suggesting we add more countries into our sample to alleviate this problem.
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All views are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System. We thank Editor George Tavlas and an anonymous referee for many constructive comments and suggestions. We would also like to thank participants at various seminars and conferences for comments and Janet Koech for excellent research assistance.
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An, L., Wang, J. Exchange Rate Pass-Through: Evidence Based on Vector Autoregression with Sign Restrictions. Open Econ Rev 23, 359–380 (2012). https://doi.org/10.1007/s11079-010-9195-8
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DOI: https://doi.org/10.1007/s11079-010-9195-8