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How sensitive are the U.S. inpayments and outpayments to real exchange rate changes: an asymmetry analysis

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Abstract

Previous studies that assessed the impact of exchange rate changes on a country’s inpayments and outpayments assumed that such effects are symmetric. The evidence from the literature reveals that import and export prices react to exchange rate changes in an asymmetric manner. This implies that export earnings and payments for imports should also react to exchange rate changes in an asymmetric manner. We demonstrate this by using Shin et al.’s (2014) nonlinear ARDL approach and inpayments and outpayments of the U.S. with her 15 trading partners. We find evidence of short-run as well as long-run asymmetric effects in more than half of the models, though the findings are found to be partner specific.

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Notes

  1. Partners considered in this paper are: Australia (with 0.96% trade share), Belgium (1.4%), Canada (15.4%), Hong Kong (1.2%), China (16.0%), France (2.1%), Germany (4.7%), Italy (1.6%), Japan (5.2%), Korea (3.1%), Mexico (14.2%), Netherlands (1.5%), Singapore (1.3%), Switzerland (1.4%), U.K. (3.1%). Trade shares belong to 2015 and are defined as sum of the U.S. exports to and imports from a partner as a percent of sum of the U.S. exports to and imports from the World.

  2. For a review article see Bahmani-Oskooee et al. (2013).

  3. See Haynes et al. (1986, p. 931).

  4. A stationary variable is usually denoted by I(0). Therefore, an I(1) variable is a variable that achieves stationarity after being differenced once.

  5. The same approach has also been followed by Bahmani-Oskooee and Goswami (2004) using data between Japan and her nine major partners and by Bahmani-Oskooee et al. (2005a, 2005b) between U.K. and her partners and between Canada and her partners.

  6. As the Appendix shows the data are quarterly. In the absence of quarterly GDP data for most U.S. partners, we use index of industrial production as a measure of income. Also note that income elasticity in both models could be negative if increase in income is due to an increase in production of import-substitute goods (Bahmani-Oskooee 1986).

  7. Another advantage of this approach is that it addresses simultaneity or feedback effects that may exist among the variables. The approach deals with the issue by assuming all lagged values to serve as instruments (Bahmani-Oskooee and Hajilee 2010, p. 650). Pesaran et al. (2001, p. 299) alert us to this issue by writing “our approach is quiet general in the sense that we can use a flexible choice for the dynamic lag structure in …..as well as allowing for short-run feedbacks.”

  8. For more on the application of these methods see Delatte and Lopez-Villavicencio (2012), Verheyen (2013), Bahmani-Oskooee and Fariditavana (2015), Bahmani-Oskooee and Saha (2015), Gogas and Pragidis (2015), Durmaz (2015), Baghestani and Kherfi (2015), Pal and Mitra (2016), Al-Shayeb and Hatemi-J (2016), Lima et al. (2016), Nusair (2017), Aftab et al. (2017), and Gregoriou (2017).

  9. The ECMt-1 test is an alternative test under which we use the normalized coefficients estimates and long-run model (1) to generate the error term, denoted by ECM. We then replace the lagged level variables in (3) by ECMt-1 and estimate the new specification after imposing the same optimum lag numbers from Panel A. A significantly negative coefficient estimate attached to ECMt-1 will support cointegration. Like the F test, Pesaran et al. (2001, p. 303) tabulate new critical values for the t test to be used in establishing significance of this estimate. For exact procedure see Bahmani-Oskooee and Ratha (2008).

  10. In some models we had to include additional lags of the dependent variable in order to reduce the RESET statistic to an insignificant level.

  11. As dollar appreciates against Australian dollar in real term, expensive U.S. goods does not hurt the U.S. export earnings due to an inelastic import demand by Australia.

  12. Other statistics from panel C reveal that the residuals are autocorrelation free in almost all models since the LM statistic is insignificant. The RESET test is also insignificant in most models supporting lack of misspecification. Furthermore, most estimates are stable.

  13. Other diagnostics are similar to those in Table 1.

  14. Note that since trade flows are usually much more concentrated on specific goods than consumer good baskets, using the CPIs for the computation of real exchange rates is problematic. A better index would be GDP deflator. However, in the absence of GDP deflator at quarterly frequency for all countries, we restrict ourselves to CPI and acknowledge the bias in the results.

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Authors and Affiliations

  1. The Center for Research on International Economics and The Department of Economics, The University of Wisconsin-Milwaukee, Milwaukee, WI, 53201, USA

    Mohsen Bahmani-Oskooee

  2. Department of Political Science, International Development and International Affairs, The University of Southern Mississippi, Hattiesburg, MS, 39402, USA

    Hadiseh Fariditavana

Authors
  1. Mohsen Bahmani-Oskooee
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  2. Hadiseh Fariditavana
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Correspondence to Mohsen Bahmani-Oskooee.

Appendix

Appendix

1.1 Data definition and sources

Quarterly data over the 1970Q1-2015Q4 period are used to carry out the empirical exercise. The exception is China for which the data were only available during 1993I-2015IV period.

The data come from the following sources:

  1. a.

    Direction of Trade Statistics of IMF

  2. b.

    Federal Reserve Bank of St. Louis.

1.2 Variables

VX i :

The U.S. inpayments (value of exports) from trading partner i. Export value data come from source a.

VM i :

The U.S. outpayments (value of imports) to trading partner i. The data comes from source a.

Y :

Measure of income in the United States. It is measured by the index of industrial production. This is the only measure of income that is available on quarterly basis for all countries. The data come from source b.

Y i :

Measure of income in trade partner i. It is measured by the index of industrial production. The data come from source b.

REX i :

The real bilateral exchange rate between the U.S. dollar and partner i’s currency. It is defined as REXi = (PUS. NEXi / Pi) where NEXi is the nominal exchange rate defined as number of i’s currency per dollar, PUS is the price level in the U.S. measured by CPI, and Pi is the price level in partner i, again measured by CPI. All nominal exchange rates and CPI data come from source b.

Thus, a decline in REX reflects a real depreciation of the United States dollar against i’s currency.Footnote 14

Table 2 Full-Information Estimates of Both Linear (L-ARDL) and Nonlinear (NL-ARDL) Inpayment Models
Full size table
Table 3 Full-Information Estimates of Both Linear L-ARDL) and Nonlinear (NL-ARDL) Outpayment Models
Full size table

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Bahmani-Oskooee, M., Fariditavana, H. How sensitive are the U.S. inpayments and outpayments to real exchange rate changes: an asymmetry analysis. Int Econ Econ Policy 16, 619–647 (2019). https://doi.org/10.1007/s10368-018-0411-0

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  • DOI: https://doi.org/10.1007/s10368-018-0411-0

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