Exchange Rate of Chinese, Indian, US Currency

Relation analysis of China/US exchange rate and India/US exchange rate

The mean averages of the Chinese and Indian exchange rates vis-à-vis US dollar from 2001 to 2012 are 7.5 (standard deviation 0.76) and 46.28 (standard deviation 3.36) respectively (see table 1). The difference standard deviation shows that the mean monthly exchange rate of the Yuan has not varied significantly while the Indian exchange rate has been highly volatile with a standard deviation of 3.36. Over the years, the monthly exchange rate of China to the US dollar has reduced from 8.27 in January 2001 to 6.23 in December 2012. The fall in the exchange rate indicated a strengthening of the Chinese Yuan vis-à-vis the US dollar. While, in the case of the Indian currency, the exchange rate increased from 46.6 in January 2001 to 54.6 in December 2012, indicating a weakening of INR vis-à-vis the US dollar. Comparing the two data sets using single-factor ANOVA it is evident that the Chinese Yuan is a stronger currency than the Indian rupee (see table 1). The F value is higher than the F-crit indicating that the result is statistically significant and that the average exchange rate of Chinese Yuan is significantly higher than Indian rupee (p value<0.05).

Table 1: Single Factor ANOVA of Chinese Yuan and Indian Rupee

Analysis of Variance (One-Way)
Summary
Groups Sample size Sum Mean Variance
China / U.S. Foreign Exchange Rate 144 1,082.40 7.52 0.59
India / U.S. Foreign Exchange Rate 144 6,665.48 46.29 11.30
ANOVA
Source of Variation SS df MS F p-level F crit
Between Groups 1,08,231.88 1 1,08,232 18,211.07 0 3.87
Within Groups 1,699.75 286 5.94
Total 1,09,931.63 287

In order to calculate the rate of depreciation or appreciation of US dollar against both the currencies, I calculated the monthly change in the exchange rate. Mean for the rate of change is then calculated from 2001 to 2012. This shows the mean of the rate of change of Yuan is -0.19 while that of Indian rupee is 0.12. This shows that over the period, US dollar has depreciated by -0.19 vis-à-vis Chinese Yuan, while has appreciated by 0.12 vis-à-vis Indian Rupee. Figure 1 shows that the US dollar appreciated for Indian rupee while it depreciated vis-à-vis Chinese Yuan. The difference in the depreciation of dollar vis-à-vis Yuan was primarily due to the Chinese policy to limit the appreciation of its currency against all foreign currencies (Morrison and Labonte 1). Due to regulated exchange rate, Chinese Yuan has appreciated by 0.19% every month since 2001 through 2012. While in India, due to absence of any such government regulation, the exchange rate has appreciated according to the principles of free market economy.

Linear trend line of monthly percentage change in exchange rate of Yuan and Rupee demonstrating appreciation/depreciation of US dollar
Figure 1: Linear trend line of monthly percentage change in exchange rate of Yuan and Rupee demonstrating appreciation/depreciation of US dollar (“India / U.S. Foreign Exchange Rate” par. 1; “China / U.S. Foreign Exchange Rate” par. 1)

Relation analysis inflation and exchange rate

Inflation may be defined as the expansion of the circulation of money vis-à-vis low production of goods. Therefore, inflation occurs when there is a situation of high circulation of currency notes in an economy with low production. This results in higher availability of money, increasing the prices of products in the economy (Ehrmann and Tzamourani 175). The monthly inflation rate calculated from the Consumer Price Index (CPI) index (“Consumer Price Index for All Urban Consumers: All Items” par.1 ) shows that there has. Table 1 in the appendix shows the relationship between inflation rate and US dollar/EURO exchange rate from 2001 t0 2012. The regression analysis provides the following equation:

Monthly percentage of US/EURO exchange rate = – 0.11901 + 1.98766 * Inflation Rate%

The above equation shows that there is a positive relationship between inflation rate and change in US dollar/EURO exchange rate as inflation has a positive intercept value (1.98766). This shows that if there is an increase in inflation rate, there will be an increase in US dollar/EURO exchange rate, i.e., one euro will convert into higher number of dollars, indicating depreciation in the value of dollar vis-à-vis EURO. Thus, with increase in inflation dollar will depreciate vis-à-vis EURO. With decrease in inflation, on the other hand, dollar will appreciate vis-à-vis EURO. Intuitively, when exports are high this indicates the country has advantage of producing the products domestically and selling them abroad due to their low currency value, which would make their exports cheaper and therefore more attractive in foreign market. Thus, when exports are high, currency value is low and vice versa. This supports the general economic principle that increase in inflation will reduce the value of the domestic currency. Intuitively, this principle can be explained with a simple example. When inflation increases, it reduces the credibility of the domestic market, as there is less production vis-à-vis money supply. This creates a negative perception about the domestic currency because the market believes that the fundamentals of the economy have weakened. Therefore, if market perception indicates political or economic instability within a country, it will tend to devalue the country’s exchange rate. Similarly, when the inflation rate increases considerably, it gives a negative signal to the market which then looses confidence on the nation’s economy and therefore on its currency that leads to the currency’s devaluation.

Relation between export and exchange rate

The analysis of the correlation between US exchange rate vis-à-vis Euro and exports show a negative relations i.e. with an increase in exchange rate there will be an increase in exports. An increase in exchange rate implies a decline in value of the currency. For instance, if exchange rate of US/EURO rate increases it will indicate a devaluation of US dollar vis-à-vis one euro. Therefore, one has to pay more dollars for one euro, indicating a decline in value of US dollar. Regression analysis of US/Euro exchange rate vis-à-vis export data, the former taken as an independent variable, shows that an increase in exchange rate devalues the domestic currency. Numerically, this can be explained using the following regression equation:

US/EURO exchange rate = 0.03 + 0.01 * US Exports

When there is an increase in export index, indicating export expansion, there will be an increase in US/Euro exchange rate by 0.01 indicating a decline in the value of the currency. Therefore, it can be said that there exists a negative relationship between exports and value of currency. Intuitively, an increase in export would indicate that producing in the country is cheaper, which is due to lower value of domestic currency.

The historical study of the relation between export and import suggest that there is a negative impact of fluctuations in exchange rate on export of the country. Therefore, when the US/Euro currency is observed it is seen that there is a negative relationship between the US exports and the value of the domestic currency. Intuitively, this relationship can be explained with an example. A firm exports its products in the foreign market. Since the firm is mostly paid in the foreign currency for its export transactions, a change in the exchange rate will impact the value of trade that it undertakes. Now, if there were an increase in the foreign exchange rate, it would imply a reduction in the value of the domestic currency. Thus, the product will become cheaper for the firm’s foreign buyers due to the devaluation of the domestic currency who can now buy more goods with the same amount of money. This will increase the demand, as a reduction in the price will shift the demand curve upward, thereby increase the quantity sold by the firm. This explains why there will be an increase in export if the value of the domestic currency reduces. On the other hand, if there is an increase in the export, due to higher demand in foreign market it should be understood that there is a comparative advantage of choosing exports from this particular country. Comparative advantage is determined through price advantage that the other country gets while purchasing the product from one particular country. The country that purchases the goods will do so only if the products are relatively cheaper in that country. Products can be relatively cheaper only if the value of the currency reduces. Thus, when there is an increase in export, it will tend to devalue the currency.

Relation between import and exchange rate

The relationship between China/US exchange rate and US imports can be understood from the following equation (see Appendix table 3):

China / U.S. Foreign Exchange Rate = 12.35 – 0.042 * Import

The equation shows that with increase in imports, the China/US exchange rate falls, due to a negative intercept for imports. When there is an increase in imports, there will be a decline in the value of Chinese Yuan and dollar will appreciate. Thus, when US import increase, there is expected to be an increase in the value of US currency. In other words, when there is an increase in the imports of goods in the US, the value of Chinese currency decreases, thereby, increasing the value of the US currency. Intuitively, when the domestic currency is weak, it will make imports dearer, thereby reducing it, and vice-versa. On the other hand, if the domestic currency is strong, it will increase imports and vice versa. This shows that there is a positive relation between import and the currency value. For instance, a domestic automobile firm imports a certain part of its production from a foreign country belonging to the Euro zone. With a devaluation of the currency, euro becomes dearer to the firm. In other words, for one euro the firm has to give more dollars, thus, devaluating the domestic currency. Thus, with the same amount of money, the firm can now import fewer goods, thereby reducing imports. When there is a decline in value of currency it reduces imports. On the other hand, if there is an increase in imports, it will tend to reduce the value of domestic currency. Intuitively, when import increases, foreign countries look at the domestic market as a viable market option and try to invest more in the economy. This increases inflow of foreign investment and thus, increases the demand for the domestic currency, thereby increasing the value of domestic currency.

Works Cited

China / U.S. Foreign Exchange Rate. 2015.

Consumer Price Index for All Urban Consumers: All Items. 2015.

Ehrmann, Michael and Panagiota Tzamourani. “Memories of high inflation.” European Journal of Political Economy 28(2) (2012): 174-191. Print.

Export (End Use): All commodities. 2015.

Import (End Use): All commodities. 2015.

India / U.S. Foreign Exchange Rate. 2015.

Morrison, Wayne M. and Marc Labonte. “China’s Currency Policy: An Analysis of the Economic Issues.” 2013. Congressional Research Service. PDF file.

U.S. / Euro Foreign Exchange Rate. 2015.

Appendix

Table 1: Regression analysis of EURO/Dollar exchange rate and Inflation rate from 2001 to 2012 (“Consumer Price Index for All Urban Consumers: All Items” par.1; “U.S. / Euro Foreign Exchange Rate” par.1)

Linear Regression
Regression Statistics
R 0.27049
R-square 0.07316
Adjusted R-square 0.06659
S 2.39707
N 143
Monthly percentage of US/EURO exchange rate = – 0.11901 + 1.98766 * Inflation Rate%
ANOVA
d.f. SS MS F p-level
Regression 1 63.95347 63.95347 11.1302 0.00109
Residual 141 810.17766 5.74594
Total 142 874.13112
Coefficient Standard Error LCL UCL t Stat p-level H0 (5%)
Intercept -0.11901 0.23124 -0.57616 0.33813 -0.51467 0.60759 Accepted
Inflation Rate% 1.98766 0.59579 0.80983 3.16549 3.3362 0.00109 Rejected

Table 2: Regression analysis of Export and US/Euro exchange rate from 2001 to 2012 (“U.S. / Euro Foreign Exchange Rate” par. 1; “Export (End Use): All commodities” par. 1)

Linear Regression
Regression Statistics
R 0.74
R-square 0.55
Adjusted R-square 0.54
S 0.12
N 144
US/EURO exchange rate = 0.03 + 0.01 * US Exports
ANOVA
d.f. SS MS F p-level
Regression 1 2.47 2.47 170.30 0
Residual 142 2.06 0.01
Total 143 4.54
Coefficient Standard Error LCL UCL t Stat p-level H0 (5%)
Intercept 0.03 0.09 -0.16 0.21 0.30 0.76 Accepted
US Exports 0.01 0.00 0.01 0.01 13.05 0.00 Rejected

Table 3: Regression analysis of China/US foreign exchange and US imports from 2001 to 2012 (“China / U.S. Foreign Exchange Rate” par. 1; “Import (End Use): All commodities” par. 1)

Linear Regression
Regression Statistics
R 0.91
R-square 0.82
Adjusted R-square 0.82
S 0.32
N 144
China / U.S. Foreign Exchange Rate = 12.35 – 0.042 * Import
ANOVA
d.f. SS MS F p-level
Regression 1 68.76 68.76 655.04 0
Residual 142 14.91 0.10
Total 143 83.67
Coefficient Standard Error LCL UCL t Stat p-level H0 (5%)
Intercept 12.35 0.19 11.97 12.73 64.75 0 rejected
Import -0.04 0.00 -0.04 -0.04 -25.59 0 rejected

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