ABSTRACT
This article follows the nonlinear Autoregressive Distributed Lag (ARDL) error-correction methodology to explore nonlinearity in the relationship between the trade balances and the real exchange rates for China and its 21 partners. We find evidence for short-run asymmetric effects of exchange rate in cases of 18 partners, short-run adjustment asymmetry in cases of 11 partners, short-run cumulative asymmetry in cases of seven partners, and a significant long-run asymmetric effect cases of five partners. We find support for the “J-curve” that is only due to appreciation or depreciation of the Yuan in cases of five partners, including the U.S.
Notes
1. Please refer to Bahmani-Oskooee and Ratha (Citation2004) and Bahmani-Oskooee and Hegerty (Citation2010) for a detailed review of the literature.
3. This section closely follows Bahmani-Oskooee and Fariditavana (Citation2016) who used such methods to estimate bilateral trade balance models between the U.S. and six of her major trading partners.
4. For the precise normalization procedure, see Bahmani-Oskooee and Fariditavana (Citation2015).
5. Note that since critical values do account for integrating properties of variables, there is no need to perform unit-root tests and variables could be combination of I(0) and I(1) which is the case for almost all macro variables.
6. See Shin, Yu, and Greenwood-Nimmo (Citation2014, 291) for details.
7. For some other application of these methods see Apergis and Miller (Citation2006), Verheyen (Citation2013), and McFarlane et al. (Citation2014), Gregoriou, Healy, and Savvides (Citation2014), Durmaz (Citation2015), Gogas and Pragidis (Citation2015), Baghestani and Kherfi (Citation2015), Nusair (Citation2017), Al-Shayeb and Hatemi-J. (Citation2016), Lima et al. (Citation2016), and Aftab et al. (Citation2017).
8. Note that since in the ARDL approach of Pesaran, Shin, and Smith (Citation2001, 303), variables are a combination of I(0) and I(1), they also tabulate an upper bound and a lower bound critical values for this t test. However, since their values are only for large samples, whereas Banerjee, Dolado, and Mestre’s (Citation1998, 276) values are for small as well as large samples, we use values from this later source.
9. The results from the linear ARDL model are more or less consistent with Bahmani-Oskooee and Wang (Citation2006) who tested the J-curve between China and each of her 13 partners.
10. A few other studies have considered bilateral trade balance of China with its partners. Wang, Lin, and Yang (Citation2012) using a panel framework have focused on post-2005 period and used monthly data over the period, August 2005-September 2009, across 19 partners to show that a real appreciation of Yuan had adverse effects on China’s trade balance. As indicated in the text, an approach such as this is prone to the aggregation bias as the general conclusion may hold for one partner, but may not hold with the other. Indeed, this seems to be the case when Yang, Zhang, and Tokgoz (Citation2013) assessed the impact of Yuan appreciation on different regions and found that appreciation improves China’s trade balances with the EU, Australia and New Zealand, ASEAN, Japan and Korea, but not with the U.S. In contrast, using the Chinese-U.S. trade flows over the period 1994–2012, Cheung, Chinn, and Qian (Citation2016) suggest that “the value of China’s exports to the US responds negatively to real renminbi (RMB) appreciation, while imports respond positively”. None of these studies, however, allows for asymmetric effects which is the main focus of this article.
11. In the linear as well as in the nonlinear models with Hong Kong, the real Yuan-Hong Kong dollar does not seem to play a significant role. We suspect that this is due the lack of variation in the exchange rate between two regions. It is also worth pointing out that some portion of the Chinese export goes through Hong Kong. In these cases, the relatively stable exchange rate between Yuan and Hong Kong Dollar does not mask the variation and the importance of the exchange rate of Yuan with other currencies.
Bahmani-Oskooee, M., and A. Ratha. 2004. The J-Curve: A literature review. Applied Economics 36 (13):1377–98. doi:10.1080/0003684042000201794. Bahmani-Oskooee, M., and S. W. Hegerty. 2010. The J- and S-Curves: A survey of the recent literature. Journal of Economic Studies 37:580–96. doi:10.1108/01443581011086639. Brada, J. C., A. Kutan, and S. Zhou. 1993. China’s exchange rate and the balance of trade. Economics of Planning 26:229–42. doi:10.1007/BF01265668. Zhang, Z. 1998. Does devaluation of the renminbi improve China’s balance of trade? Economia Internazionale 51 (3):437–45. Zhang, Z. 1999. China’s exchange rate reform and its impact on the balance of trade and domestic inflation. Asia Pacific Journal of Economics and Business 3 (2):4–22. Weixian, W. 1999. An empirical study of the foreign trade balance in China. Applied Economics Letters 6:485–90. doi:10.1080/135048599352781. Zhang, Z. 1999. China’s exchange rate reform and its impact on the balance of trade and domestic inflation. Asia Pacific Journal of Economics and Business 3 (2):4–22. Bahmani-Oskooee, M., and H. Fariditavana. 2016. Nonlinear ARDL approach and the J-Curve phenomenon. Open Economies Review 27:51–70. doi:10.1007/s11079-015-9369-5. Bahmani-Oskooee, M., and H. Fariditavana. 2015. Nonlinear ARDL approach, asymmetric effects and the J-Curve. Journal of Economic Studies 42:519–30. doi:10.1108/JES-03-2015-0042. Shin, Y., B. C. Yu, and M. Greenwood-Nimmo. 2014. Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in honor of peter schmidt: econometric methods and applications, eds R. Sickels, and W. Horrace, 281–314. New York, NY: Springer. https://doi.org/10.1007/978-1-4899-8008-3_9 Apergis, N., and S. Miller. 2006. Consumption asymmetry and the stock market: Empirical evidence. Economics Letters 93:337–42. doi:10.1016/j.econlet.2006.06.002. Verheyen, F. 2013. Interest rate pass-through in the EMU: New evidence using nonlinear ARDL framework. Economics Bulletin 33 (1):729–39. McFarlane, A., A. Das, and M. Chowdhury. 2014. Non-linear dynamics of employment, output and real wages in Canada: Recent time series evidence. Journal of Economic Studies 41:554–68. doi:10.1108/JES-02-2013-0022. Gregoriou, A., J. Healy, and N. Savvides. 2014. Market efficiency and the basis in the European Union Emissions Trading Scheme: New evidence from non linear mean reverting unit root tests. Journal of Economic Studies 41:615–28. doi:10.1108/JES-08-2012-0120. Durmaz, N. 2015. Industry level J-Curve in Turkey. Journal of Economic Studies 42-4:689–706. doi:10.1108/JES-08-2013-0122. Gogas, P., and I. Pragidis. 2015. Are there asymmetries in fiscal policy shocks? Journal of Economic Studies 42:303–21. doi:10.1108/JES-04-2013-0059. Baghestani, H., and S. Kherfi. 2015. An error-correction modeling of US consumer spending: Are there asymmetries? Journal of Economic Studies 42:1078–94. doi:10.1108/JES-04-2014-0065. Nusair, S. A. 2017. The J-Curve phenomenon in European transition economies: A nonlinear ARDL approach. International Review of Applied Economics 31 (1):1–27. doi: 10.1080/02692171.2016.1214109. Al-Shayeb, A., and A. Hatemi-J. 2016. Trade openness and economic development in the UAE: An asymmetric approach. Journal of Economic Studies 43:587–97. doi:10.1108/JES-06-2015-0094. Lima, L., C. Foffano Vasconcelos, J. Simão, and H. De Mendonça. 2016. The quantitative easing effect on the stock market of the USA, the UK and Japan: An ARDL approach for the crisis period. Journal of Economic Studies 43:1006–21. doi:10.1108/JES-05-2015-0081. Aftab, M., R. Ahmad, I. Ismail, and M. Ahmed. 2017. Exchange rate volatility and Malaysian-Thai bilateral industry trade flows. Journal of Economic Studies 44:99–114. doi:10.1108/JES-05-2015-0091. Pesaran, M. H., Y. Shin, and R. J. Smith. 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16 (3):289–326. doi:10.1002/(ISSN)1099-1255. Banerjee, A., J. Dolado, and R. Mestre. 1998. Error-correction mechanism tests in a singleequation framework. Journal of Time Series Analysis 19:267–85. doi:10.1111/1467-9892.00091. Bahmani-Oskooee, M., and Y. Wang. 2006. The J-Curve: China versus her trading partners. Bulletin of Economic Research 58 (2006):323–43. doi:10.1111/j.1467-8586.2006.00247.x. Wang, C.-H., C.-H. A. Lin, and C.-H. Yang. 2012. Short-run and long-run effects of exchange rate change on trade balance: evidence from China and its trading partners. Japan and the World Economy 24:266–73. doi:10.1016/j.japwor.2012.07.001. Yang, J., W. Zhang, and S. Tokgoz. 2013. Macroeconomic impacts of Chinese currency appreciation on China and the Rest of world: A global cge analysis. Journal of Policy Modeling 35:1029–42. doi:10.1016/j.jpolmod.2013.07.003. Cheung, Y.-W., M. D. Chinn, and X. Qian. 2016. China-US trade flow behavior; The implications of alternative exchange rate measures and trade classifications. Review of World Economy 152:43–67. doi:10.1007/s10290-015-0232-y. Additional information
Funding
This work was supported by the Shanghai Education Development Foundation and Shanghai Municipal Education Commission [Shanghai Pujiang Program and the “Shuguang Program”].