Abstract
This research paper investigates the effect of macroeconomic variables on the exchange rate USD/CYN using yearly time series data for China economy from 1980 to 2017. ARDL bounds test approach for cointegration is applied to test the long-run relation between the dependent and the independent variables. The results of long-run ARDL indicate that gross domestic product growth and trade openness have a positive effect on the exchange rate USD/CNY while interest and inflation rates have a negative effect on the exchange rate. Based on the results of this study, it is recommended that the policymakers of the Chinese government should implement vital monetary and fiscal policies to determine the less volatile and productive exchange rate for China to manage sustainable economic growth for a long time with its trading partners.
Highlights
Exchange rate is the value of one country’s currency into another country’s currency
Results indicate that inflation and interest rate are stationary at level with Augmented dickey fuller (ADF) unit root test, interest rate is stationary at level with Phillips and Perron (PP) while the remaining variables are non-stationary at level
All the time series variables stationarity are again checked at the first difference with both ADF and PP
Summary
Exchange rate is the value of one country’s currency into another country’s currency. Engel and Rogers (2001) study show that if any country has a greater price level of different commodities, the home currency of that country will be facing depreciation in exchange rates as compared to other countries. In this research, United States Dollar is treated as a home currency as compared to Chinese Yuan because both countries have trading relationship with each other. From the start of the floating exchange rate regime, China is facing depreciation in its home currency. This is very important to investigate in detail, the reasons of such impulsiveness of the exchange rate in China. Haug (2002) stated that Autoregressive distributed lag (ARDL) approach has processed better properties of small samples
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