Abstract
This paper studies the predictive power of external imbalances for exchange rate returns. We focus on Switzerland, a very open economy where exchange rate movements have a strong effect on external imbalances through valuation effects and trade flows. Using a simple modification of the Gourinchas and Rey (J Polit Econ 115(4):665–703, 2007) approach to make their approximation applicable to Switzerland, we find that measures of deviations from trends in Swiss net foreign assets and net exports help to forecast Swiss franc nominal effective exchange rate movements, both in and out of sample.
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Notes
We follow the timing convention of GR and measure assets and liabilities at the beginning of the period.
The approximation proposed in Whelan (2008) for the household budget constraint works only if net saving is negative, as is the case for US data. But in an internet appendix Whelan (2008) shows that with an adjustment very similar to the one used here his approximation works also in the general case. While Whelan (2008) approximates the household budget constraint in levels, we approximate countries’ external budget constraints around the trends in external positions and trade flows.
Evans (2012) rewrites the accumulation identity as \(A_{t+1}-L_{t+1} = R_{t+1} \left (A_{t}-L_{t} + X^{\ast }_{t}-M^{\ast }_{t}\right )\), where \(X^{\ast }_{t} \equiv X_{t} + \tau _{t}\) and \(M^{\ast }_{t} \equiv M_{t} + \tau _{t}\).
When solving (17) forward, we use a period t approximation around \(\epsilon _{t+1}^{a}=\epsilon _{t+1}^{l}=0\) and a period t+1 approximation around \(\epsilon _{t+1}^{a\ast }=\epsilon _{t+1}^{l\ast }=0\). The two are compatible since we compute trends so that \(\bar {A}_{t}^{\ast }=\bar {A}_{t}+\bar {\tau }^{a}_{t}\). This ensures that \({\epsilon _{t}^{a}}=0\) if and only if \(\epsilon _{t}^{a\ast }=0\). Following GR, we use an HP-filter for detrending. The trend of \(\hat {A}_{t}^{\ast }\) is then computed as
$$\bar{A}_{t}^{\ast }=\bar{A}_{t}+\bar{\tau}^{a}=e^{HP\left( \ln \hat{A}_{t}\right) }+e^{HP\left( \ln \tau^{a}\right) } $$where \(HP(\ln \hat {A}_{t})\) denotes the HP-filtered series \(\ln \hat {A}_{t}\).
We thank Philip Lane for providing us with an updated version of this dataset.
In the GR dataset, US dollar one-quarter depreciation rates computed with trade weights and FDI weights exhibit a correlation coefficient of 0.86 over the 1973-2004 sample.
The increase in Switzerland’s net foreign assets has been smaller than what is implied by the size of current account surpluses. This is because of valuation changes, as discussed in Stoffels and Tille (2007). Note also that the economically relevant size of the current account surplus is smaller than its measured size. See Jordan (2013) and IMF (2012, annex I) on this point.
We follow GR and detrend all variables (in logs) using an HP filter with λ = 2400000, filtering out only long-term trends.
The original GR measure nxa turns out to be highly correlated with nxa ∗, although its absolute approximation error is larger, and its predictive power for exchange rate returns is weaker.
We find that in practice it makes little difference how the adjustment is distributed over τ a and τ l. See Section 5.3 below.
To compute the approximation error we need data on the ex-post portfolio return R t . Rather than constructing this from data on portfolio shares and returns on individual assets and liabilities, we compute R t as implied by the accumulation identity (1), given data on net foreign assets and net exports.
In constructing nxa ∗ we use extrapolation at the end of the rolling sample when computing quarterly series for external assets and liabilities from annual data. Also, we recompute \(\tau =\max (\hat {NX}_{t}) + 0.01\) for each rolling window to make sure that we use only information contained in the in-sample.
Unlike Meese and Rogoff (1983) we test ex-ante forecasting power.
As Clark and West (2006) show, under the null of no predictability, β 1 = 0 in regression (24), the MPSE of the unrestricted model, MSPE nxa , is expected to be larger than that of the random walk. This is the case because in the unrestricted model parameters are estimated which under the null have no predictive power.
We thank an anonymous referee for suggesting this explanation.
The results are weaker for the longer 1973-2014 sample, especially for Japan. Perhaps this is the case due to the large exchange rate adjustments in the aftermath of the Bretton Woods system.
Other popular risk measures, such as the VIX or VXO index of option-implied US stock market volatility, are only available from 1986.
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We thank Katrin Assenmacher, Sylvia Kaufmann, Pinar Yeşin, anonymous referees of this journal and of the SNB working paper series, and participants at the SNB brown bag seminar, the 2013 annual meeting of the Swiss Society of Economics and Statistics (Neuchâtel), the 4th conference on recent developments in macroeconomics (ZEW Mannheim), and the 7th International Workshop “Methods in International Finance Network” (Namur) for helpful comments and suggestions. The views expressed are those of the authors and do not necessarily reflect the position of the Swiss National Bank.
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Grisse, C., Nitschka, T. Exchange Rate Returns and External Adjustment: Evidence from Switzerland. Open Econ Rev 27, 317–339 (2016). https://doi.org/10.1007/s11079-015-9376-6
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DOI: https://doi.org/10.1007/s11079-015-9376-6