1. Factors of Movement of Exchange Rate
between Chinese Yuan and US Dollar
and comparison with Indian Scenario
Department of Humanities and Social Science
Under supervision of Dr. S. K. Mathur, Associate Professor of Economics, HSS Department
IIT Kanpur
By Ved Prakash 10790
M. Sc. Integrated Mathematics
IIT Kanpur

2. Introduction
Chinese economy and currency have influenced international economy for a long time and
China has become the second largest economy in the world. The movements of Chinese
Renminbi (RMB) have affected balance of payment of several major economies on large
scale. The historical movement of RMB from an overvalued currency before 80’s to
undervalue currency after 2005 have made a huge impact on Chinese balance of payment
and Chinese GDP. An overvalued currency allowed Chinese government to provide imported
machinery and equipment to priority industries at a relatively lower domestic currency cost
than otherwise would have been possible. Cheap machinery mixed with high cheap labor
availability led to high production. A devaluation of currency after the reforms of 1979 led
to high exports and China continuously started having a current account surplus and
accumulated large stock of foreign reserves. In fact China currently has the highest reserves
in the world of US Dollar.
But this exchange rate is depended on several variables such as open interest parity, PPP
Theory, Covered interest parity, money supply in domestic and foreign country, and income
in two country, difference between interest rates and difference of prices in the two
countries.
Through this paper I intend to establish following task:
1. What factors have major significance in deciding the movement of Renminbi-
Dollar exchange rate and why?
2. What is the equation that can be used to make prediction for coming years?
3. How the case of China is different from India?
4. What should China’s government do to ensure that country’s growth rate doesn’t
go down?
Various econometric models have been used in the paper and also explained as much
required. Ordinary least square, Generalized Square model and Variance Auto regression
have been used in this paper.

3. Literature
1. International Economics by Peter B. Kenen
This book discusses the various factors that affect the Exchange rate for any country. There
are several factors but the most important are:
• Inflation Differential
As a general rule, a country with a consistently lower inflation rate exhibits a rising
currency value, as its purchasing power increases relative to other currencies. During
the last half of the twentieth century, the countries with low inflation included Japan,
Germany and Switzerland, while the U.S. and Canada achieved low inflation only
later. Those countries with higher inflation typically see depreciation in their currency
in relation to the currencies of their trading partners. For this paper I have used
Inflation differential as
Inflation Differential = Inflation China (in %) - Inflation US (in %)
It can also be said that as inflation increases, commodities that you can buy with a given
amount of currency decreases and hence the value of your currency decreases. So with
rising inflation, currency depreciates.
• Interest Rate Differential
Interest rate is one major instrument to attract foreign capital to move inside the home
country. When interest rate in home country are more than interest rate in foreign
country, then investors make more profit by depositing their money in the country with
higher returns. So their exist open interest parity,
u= r-r*,
Where r= interest rate in home country and r* id interest rate in foreign country
When interest rate is high there is more demand for home currency and hence the value
of currency appreciates in home country and depreciates in the foreign country.
In this paper I have used the data of
Real interest rate = Lending Rate – Deposit Rate
So higher the Real interest rate less is the money coming in. So the sign of coefficient
will reverse in this case.
• Money Supply
The effect of money supply can be understood through monetary approach to balance
of payment. When money supply increases, incentive to save is reduced thus people
start demanding more goods which leads to increase in imports and thus the demand
supply curve shifts causing home currency to depreciate with respect to the trading
partner’s currency.

4. • Gross Domestic Product/ National Income
More income gives the people a reason to spend more, thus when a country gains
income, it starts getting more imports, which again leads to depreciation of importing
country’s currency.
2. The Future of China’s Exchange Rate Policy by Morris Goldstein
and Nicholas R. Lardy
This paper was very useful in gaining insight into the various exchange rate eras that
China has passed through. It discusses evolution of China’s Exchange Rate Regime in the
reform era, its transition to an equilibrium exchange rate and what development took
place after 2005.
China had a much overvalued currency from 1949 to 1970s, the state fixed China’s
exchange rate at a highly overvalued level as part of the country’s import substitution
industrialization strategy. In 1979, the State allowed exporters to retain a share of
foreign exchange. Slowly these kinds of reforms increased in number and more and
more foreign exchange was now controlled by Chinese exporters. The value of
Renmimbi depreciated to 4.79 per $ in 1990 from 1.49 per $ in 1980. From mid 90s to
2005, China continuously maintained an exchange rate of 8.28 approx. After 2005, China
started managing its currency “with reference to a basket of currencies” rather than
pegged to the dollar. This change caused appreciation in value of Renminbi to 6.3 per $
as in 2012.
Later in the paper, authors explain the surge in China’s Global Trade Surplus and in the
end authors discuss the approaches that China can take in future.
One is Stay- the- Course Strategy which says that China don’t need to do anything
explicitly for exchange rates. China has done quite well with present structure and even
if there were problems they were short lived and internal. China has maintained low
inflation and dealt with all imbalances quite well.
The other strategy is the Three- Stage Approach, the first stage being the time when
economy is going through recession and second stage as the time when economy starts
to recover. Third stage would be when China’s global current account surplus has been
reduced.
I take the future approach a little differently, through my result I say that exports of
China will be going down in coming years because decreasing cheap labor and
government of China will have to design policies such that the country’s growth will
not go down in spite of changing global scenarios. I comment on the reasons behind
difference in significant factors in deciding exchange rate in India/US and China/US. I
derive my reasoning from the amount of trading taking place between these countries
with other countries.

5. Econometric Model
First task was to decide on the right hand side variables which explain the dependent
variable and form a regression equation.
π = f (Ls, L*s, Y,Y*, r-r*, p-p*)
π = a + bLs + cL*s + dY*+ pY + q(r-r*) + r (p-p*)
Expected Sign= +, -, -, +, +, +
Where,
• π = Exchange rate of Chinese Renminbi against Dollar,
• Ls= Money Supply in China,
• L*s= Money Supply in US,
• Y= National Income or GDP of China,
• Y*= National Income or GDP of US,
• r = Real Interest rate of China ,
• r*= Real Interest Rate of US,
• p= Inflation in China,
• p*= Inflation in US,
The reason of these expected sign have been explained above and summarized here:
When money supply increases in home country, people starts to save less and spend
more which leads to increased imports and hence currency depreciates. For the foreign
country, increased money supply will cause more exports for home country and thus
appreciation of currency.
Income behaves in the same way as money supply and thus for Home Income sign is
+ve, and for foreign income sign is –ve.
Interest rate changes are responsible for flow of money inside the home economy and
outside of it. When real interest rate rises, deposit rate decreases, which leads to flow of
currency outside home economy leading to depreciation of currency. So interest rate
differential has positive sign.
Similarly with rise in inflation differential, currency loses its value resulting in
depreciation hence a positive sign.

6. Estimated Model
The factors that are mentioned above are not the only variables that affect the exchange
rate movements. There are several other factors; some of them are forward premium
and other exchange rate with major trading partners. If the country is a managed float
exchange rate economy, then it depends on the set of currencies that it has been
pegged to.
So the exact model should have been:
π = a + bLs + cL*s + dY*+ pY + q(r-r*) + r (p-p*) +s (πf- πf*)
+a1πPound-Yuan+ a2πEuro-Yuan + a3πYen-Yuan
Here,
πf- πf* = Forward premium difference,
πPound-Yuan = Exchange rate between Great Britain Pound and Chinese Yuan,
πEuro-Yuan = Exchange rate between Great Britain Pound and Chinese Yuan,
πYen-Yuan = Exchange rate between Great Britain Pound and Chinese Yuan,
The reason that these extra variables were not included is that for the case of China,
including other exchange rate was disturbing all other results. Secondly, the data for
forward premium was not available for both the countries.
Also, the limited number of variables was able to explain the majority of variability in the
results, so the significance of including other variables reduced considerably.
Data Source
Most of the data has been downloaded from World Bank, World Development Indicators
Procedure to access data,
Step 1- Go to http://databank.worldbank.org/ddp/home.do
Step 2- Select the database as World Development Indicators
Step 3 – Select China and United State as country
Step 4- Select the variables for which the data is required
Step 5- Download the data in excel sheet.
This source is the most reliable source of economic data and the data is available across all
databases and for almost all countries.

7. Results
EViews 3.1 and STATA 8 were used for carrying out several tests. The result of each of
those test are described below:
Data
GDP
Inflation Interest MS China(Mil GDP US Exchange
Year Differential Rate Diff. China $ MS US $ $) (Mil $) Rate
1980 -5.32717 -4.43059 1.67E+11 1.99E+12 306520 2768900 1.4984
1981 -7.07981 -5.99789 1.98E+11 2.23E+12 293852 3105400 1.704533
1982 -6.34266 -0.79597 2.27E+11 2.45E+12 295370 3229500 1.892542
1983 -2.95531 -0.44004 2.71E+11 2.65E+12 314637 3508800 1.975675
1984 1.180511 -5.82954 3.6E+11 2.98E+12 317352 3902600 2.320042
1985 7.150013 -8.748 4.87E+11 3.23E+12 309083 4187500 2.936658
1986 2.51245 -2.93539 6.35E+11 3.53E+12 304348 4427700 3.452792
1987 2.228091 -2.49679 7.96E+11 3.68E+12 329851 4702100 3.7221
1988 8.59983 -8.3863 9.6E+11 3.93E+12 413439 5063900 3.7221
1989 4.746342 -4.24368 1.14E+12 4.14E+12 459782 5441700 3.765108
1990 2.045907 -2.66218 1.47E+12 4.25E+12 404494 5757200 4.783208
1991 3.451021 -3.22267 1.86E+12 4.31E+12 424117 5946900 5.323392
1992 6.13114 -3.68793 2.43E+12 4.3E+12 499859 6286800 5.514592
1993 12.92879 -7.32316 3.57E+12 4.33E+12 641069 6604300 5.761958
1994 18.57137 -12.9829 4.69E+12 4.35E+12 582653 7017500 8.618667
1995 11.4098 -7.82868 6.07E+12 4.65E+12 756960 7342300 8.35125
1996 4.664643 -2.96274 7.61E+12 5.01E+12 892014 7762300 8.314083
1997 -0.41487 0.63018 9.19E+12 5.41E+12 985046 8250900 8.289833
1998 -2.26338 0.458259 1.06E+13 5.93E+12 1045199 8694600 8.279
1999 -2.72108 0.761529 1.21E+13 6.5E+12 1100776 9216200 8.278083
2000 -0.1015 -3.20864 1.36E+13 7.02E+12 1192836 9764800 8.278417
2001 -0.21421 -0.83065 1.56E+13 7.55E+12 1316558 10075900 8.277167
2002 -1.03969 1.695993 1.77E+13 7.88E+12 1454040 10417600 8.277
2003 0.505075 0.655339 2.11E+13 8.23E+12 1647918 10908000 8.277
2004 4.10138 -2.7334 2.42E+13 8.7E+12 1936502 11657300 8.276833
2005 0.610488 -1.18985 2.83E+13 9.41E+12 2302719 12397900 8.194083
2006 0.559569 -2.33435 3.46E+13 1.03E+13 2787254 13163870 7.973333
2007 4.70286 -5.12841 4.03E+13 1.15E+13 3494351 14028700 7.607583
2008 5.586504 -5.12181 4.75E+13 1.24E+13 4531831 14369100 6.94875
2009 -1.6568 3.775042 6.1E+13 1.23E+13 5050543 13863600 6.831417
2010 5.531783 -2.89312 7.26E+13 1.21E+13 5739358 14447100 6.770167
2011 5.022673 -1.61297 8.52E+13 1.3E+13 7318449 15075000 6.4615

8. Ordinary Least Square Test
Fig 1 Results of OLS
• It can be noticed that the value of Durbin –Watson Stat is 1.47 which indicates
the presence of correlation among the variables.
• The value of R- Squared is 0.94 which shows that these variables are quite nicely
explaining the variability of exchange rate.
• Differential Inflation, Differential Interest rate, GDP US and money supply US
are significant factors explaining exchange rate value. (Probability value is less
than 5% for each of them and also absolute value of t-stat is greater than 1.96
for each of them)
These results are interesting. It is important to know that why money supply and
GDP of China are not as important as MS and GDP of US.
• China is an export based industry. Much of its income comes from export of
manufactured goods. Complete report of its trade statistics can be obtained at
https://www.uschina.org/statistics/tradetable.html. US are major trade partner of China
with a trade volume of 500 billion Dollars. So the money supply and GDP changes in US
affect China’s export to US a lot more than its own GDP and money supply’s effect on its
imports.
• The reason behind interest rate being significant factor is that China has continuously
invested in US treasury bills, so whenever the differential interest rate support the
purchase of US treasury bills, China purchases those bill increasing money supply and
expenditure in US and thus ultimately increasing China’s export to US. The exact volume
of US treasury bills held by China can be obtained at http://www.treasury.gov/resource-
center/data-chart-center/tic/Documents/mfh.txt.

9. • When Differential index is low, it means that inflation is low in China and high in US.
Because of this reason US people prefer more of China’s cheap and inexpensive
products. Thus US’s imports from China increases and low inflation appreciates Chinese
currency.
But as the value of Durbin- Watson Stat is indicating the presence of correlation,
remedial measure is required to correct the results. We run generalized least square
test on the same data. The results are presented below,
Generalized Least Square
Fig 2 Results of GLS
• After applying the remedial measure, i.e. by using the GLS test on the data, the value of
Durbin-Watson constant has reached closer to 2, so much of the correlation error has
been reduced now.
• Also, the value of t-stat for Differential inflation and differential interest rate reduced to
1.83 and 1.84 which are less than 1.96, and these factors also lose significance.
• Although both differential inflation and differential interest rate still have probabilities
under10 % and Money supply and GDP of US remains the significant factors.
• The most important thing to note is that the data that is being used here is a time series
data, so auto correlation is not the only thing that I required to be checked.
• The Unit Root test is needed to be checked to find out, whether the data series are
stationary or not.

10. Unit Root Test
On running Unit test root on all the series, the following results were obtained:
• All series had unit root problem and were non stationary. With this finding, it is sure
that the results obtained from linear regression are wrong since OLS and GLS results
are valid only for stationary series.
• The options that are left now are that either co-integration test can be run on the
data or Vector Auto Regression test.
• If all series turn out to be of same order (I0 or I1 or I2), then co-integration test can be
applied because the series are integrated to same level.

11. Fig 3 Results of Unit Root Test
1. Inflation differential series was integrated to I1 level.
2. Differential Interest Rate series was integrated to I2 level.
3. Money Supply China series was integrated to I3 level.
4. Money Supply US was series integrated to I1 level.
5. GDP China series was integrated to I0 level and,
6. GDP US was integrated to I1 level.
Since the integration level of all series is not same, so the use of co-integration test
would not give correct results. The only choice remains to run Vector Auto
Regression test.
Vector Auto Regression
VAR is a very important model in econometrics; it’s a concise way of summarizing
data; the residuals generated by VAR have very little correlation; can be used to
examine complex relation among many variables.
A simple vector auto regression for two variables y and z is
Yt = αy +βyyt-1 + γy zt-1 + εyt
Zt = αz + βzyt-1 + γzzt-1 + εtz
Where,
The α’s and β’s are parameters,
The epsilons are white noise, i.e. Eεit =0, Var εit = σ2 and Cov(εit, εjt) =0

12. This model can be generalized for more variables. EViews comes with an inbuilt algorithm to
execute VAR estimation, that is what has been used here,
Fig 4 VAR estimate Results for Dependent Variable
Variance Decomposition Result
Impulse Response in 10 time period
GDP US Exchange
5% Rate
5%
Inflation
GDP
44%
China
23%
M S US Interest
10% M S Rate
China 5%
8%
Fig 5 Impulse Response Results with normal ordering

13. In impulse response, the ordering of the variables matter because the amount of variability
explaining ability of variable goes down as its sequence number decreases. So it’s important
to check results with different ordering.
With this particular ordering, the results show that inflation will be major influential factor
in determining the exchange rate in 10 time period and GDP China and MS China will also
become important factor in future.
Results with different ordering
1. MS US, GDP US, MS China, Diff. Inflation, GDP China, Diff. Interest Rate, Exchange Rate
2. MS China, GDP China, MS US, GDP US, Diff. Inflation, Diff. Interest Rate, Exchange Rate
Fig 6 Ordering 1 Result
GDP US
5% Exchang
e Rate
5% With this ordering, Inflation (38%)
still remains a major factor but along
Inflation with it, GDP (22%) and Money
GDP 38% Supply (19%) in China also become
China
important factor with the
22%
significance of GDP (5%) and Money
M S US supply (10%) going down in next 10
10%
MS time periods.
China Interest
19% Rate
1%
GDP US
5% Exchang
According to this ordering, GDP of e Rate
China (54%) will take place of 5%
Inflation
Differential inflation as most
5%
significant factor, MS in China will GDP Interest
explain 19 % variability in next 10 China Rate
time period. The significance of GDP 54% MS 1%
China
and MS is reduced to low levels and
19%
interest rate and inflation become M S US
almost irrelevant. 11%
Fig 7 Ordering 2 results

14. These results with different ordering have something in common, i.e.
• The significance of money supply and GDP will go up in future and China’s exchange
rate dependence on US economy will go down.
• This can be interpreted as fall in China’s exports to US and China’s overall trade going
down.
• China’s exchange rate will depend more on internal demand and supply of foreign
exchange.
• A possible reason of this may be that, in coming year China will lose it comparative
advantage over products from other countries because of diminishing availability of
cheap labor. [http://www.bbc.co.uk/news/world-asia-19630110]
• Population of China is getting old (average age is increasing), so the wage rates are
going high in China and that’s why the Chinese product will not be cheap as before,
so a net decline in exports will cause more home based changes than US based
changes.
To get the final equation and to do forecasting, we need the value of normalized
beta coefficients, which can be obtained in STATA. The results from STATA are given
below,
Fig 8 Normalized Beta Coefficients
Var2= Differential Inflation, Var3= Differential Interest Rate, Var4= Money Supply in
China, Var5= Money Supply in US, Var6= GDP China, Var7= GDP US
I will consider only those variable for which absolute value of t-stat is greater than
1.96 and the probability value is less than 5%.
These variables are:
1. Differential Inflation
2. Differential Interest Rate
3. Money Supply in US
4. GDP US

15. Final Equation:
π = a + bLs + cL*s + dY*+ pY + q(r-r*) + r (p-p*)
π = .1706 + 0*Ls – (2.16E-12)L*s + (2.42E-06)Y*+ o*Y + .1376(r-r*) + .0923 (p-p*)
π = .1706– (2.16E-12)L*s + (2.42E-06)Y* + .1376(r-r*) + .0923 (p-p*)
In- Sample Forecasting
Fig 8 Table for Forecasted values of Exchange Rate (In Sample)
Year Actual Exchange Rate Forecasted Values Difference
1980 1.4984 1.479765 0.018635
1981 1.704533 1.398976 0.305557
1982 1.892542 2.001109 -0.10857
1983 1.975675 2.601297 -0.62562
1984 2.320042 2.476583 -0.15654
1985 2.936658 2.781104 0.155555
1986 3.452792 3.079855 0.372936
1987 3.7221 3.467739 0.254361
1988 3.7221 3.58156 0.14054
1989 3.765108 4.259095 -0.49399
1990 4.783208 4.751651 0.031557
1991 5.323392 5.125678 0.197714
1992 5.514592 6.145956 -0.63136
1993 5.761958 6.986216 -1.22426
1994 8.618667 7.690343 0.928324
1995 8.35125 7.879416 0.471834
1996 8.314083 8.153351 0.160732
1997 8.289833 8.494864 -0.20503
1998 8.279 8.251661 0.027339
1999 8.278083 8.294993 -0.01691
2000 8.278417 8.179949 0.098467
2001 8.277167 8.117598 0.159569
2002 8.277 8.499348 -0.22235
2003 8.277 8.925396 -0.6484
2004 8.276833 9.587266 -1.31043
2005 8.194083 9.73684 -1.54276
2006 7.973333 9.593501 -1.62017
2007 7.607583 9.081372 -1.47379
2008 6.94875 7.959028 -1.01028
2009 6.831417 7.483228 -0.65181
2010 6.770167 9.177648 -2.40748
2011 6.4615 8.840639 -2.37914

16. It can be seen that the forecasting is right for most of the years, it is only after year 2005,
that the forecasting is giving wrong results. One of the reasons of it can be that after year
2005, China changed its exchange rate regime, it pegged its currency to a basket of
currencies, and thus the value of Chinese Yuan was dependent on other exchange rates
also.
Based on this model the out of sample forecasting is done the following way,
For next five years, GDP growth rate has been used to determine future GDP. The trend of
Money supply increase has been used to get future money supply values and the mean of
last five years of differential inflation and differential interest rate is being used for
obtaining the values of future inflation and interest rate differentials.
Fig 9 Forecasted Values using same model (Out Of Sample)
Year Diff. Diff Interest Money GDP US Forecasted Rate
Inflation Rate Supply US
2012 3.837405 -2.19625 1.4E+13 15373485 7.233181
2013 3.837405 -2.19625 1.5E+13 15677880 5.795345
2014 3.837405 -2.19625 1.6E+13 15988302 4.33775
Differential Inflation = average value of inflation differential for year 2007, 08, 09, 10, 11
Differential Interest Rate = average value of interest rate differential for year 2007, 08, 09,
10, 11
Money supply Excess= (1.59E+10)*Year value – (3.1E+13) Obtained through linear
regression on money supply increase every year
GDP US: A forecast of GDP growth rate of 1.98 as provided by World Bank is used to get the
future value of GDP
Variation in the current regression model
As the result for forecasted value were not appropriate after the year 2005, so I tried a
modification in regression model and included Exchange Rate of Yuan –Yen and Yuan –
Pound as my explanatory variables. After running the similar results on these variables, I
found that only Yuan –Yen exchange rate and Yuan – Pound Exchange rates are significant
variables, so using the beta coefficients I formed the following equation:
Π= .9461+ .2194*πPound-Yuan+ 44.2215*πYen-Yuan

17. Based on this modified model, I again forecasted the value of Exchange rate for last 7 years,
the result of which is given below:
Fig 10 Forecasted values with improvised model
Year Actual Exchange Rate Forecasted Rate
2005 8.194083 7.504279
2006 7.973333 7.201861
2007 7.607583 7.14476
2008 6.94875 6.741718
2009 6.831417 6.522745
2010 6.770167 6.656823
2011 6.4615 6.804896
These results can be explained by the facts that Chinese government on 21 July, 2005
announced that the Chinese Currency is a managed float and is now pegged to a basket of
currencies among which Pound and Yen are two important ones.
[http://en.wikipedia.org/wiki/Renminbi#Value] That’s the reason this forecast are much
closer to actual values.
Comparison with India
While comparing with India, the number of variables included on right hand side were more
than in case of China, the extra addition were Pound Rupee Exchange Rate, Euro/Rupee
Exchange Rate and Japanese Yen/Rupee Exchange Rate.
The results of normalized beta coefficients for Indian data are given below:
Fig 11 Results for beta coefficients and regression for Indian Data

18. The differences between Chinese model and Indian model can be sketched in following
manner:
India China
• All the three exchange rates, i.e. • Chinese Yuan also was significantly affected by
pound/rupee, euro/rupee and Yen/rupee these rates since China manages its exchange
come out to be significant. The reason for rate based on the value of these currencies.
this India has a lot of trade with these Japan is China second major trade partner and
three regions on Indian map and also UK is also one of the important trade partner.
because the basket of currencies to which [https://www.uschina.org/statistics/tradetable.h
India has pegged its exchange rate tm]
contains these exchange rates. [Export-
Import bank of India, Catalyzing India's
trade and investment]
• For India, not only GDP of US is significant • In case of China, China’s own GDP and money
variable, but also its own GDP and money supply were insignificant instead US GDP and
supply. Money supply were important factors.
• By applying VAR and impulse response on • By applying variance decomposition and impulse
Indian data, it can be said that Pound response, it can be said that Chinese GDP and
Rupee exchange rate, Yen Rupee Chinese Money Supply will become significant in
Exchange Rate and Interest rate coming years
differential will gain even more
significance.
• By this result it can be said that India • The average age of Chinese population is
trade with these countries will further increasing. In next 10-15 years the number of
increase in future. Inflation, GDP and people above retirement age will be 65million.
Economic changes in these regions will be This indicates to a lack of cheap labor in future
reflected in the way India’s currency which will cause rise in prices of manufactured
value changes. goods from China. This will lead to decreased
exports and thus Chinese currency value will
depend more on its own internal GDP and
Money supply condition.
This theory is well explained in my own research
work available at
[http://www.scribd.com/doc/113469484/Term-
Paper-SOC-479]

19. Conclusion and Discussion
After this study, we are in the situation to answer the questions asked in the beginning of
this paper which were:
1. What factors have major significance in deciding the movement of Renminbi-
Dollar exchange rate and why?
2. What is the equation that can be used to make prediction for coming years?
3. How the case of China is different from India?
4. What should China’s government do to ensure that country’s growth rate doesn’t
go down?
The factors that have most significance and effect on Chinese currency value are
differential inflation in China, differential interest rate in China, Money supply and
National Income of US.
Inflation rise in China causes fall of exports and hence demand of Yuan goes down
leading to depreciation of Yuan, that’s why a positive sign is seen in the results. Rise in
differential inflation causes more purchases of US treasury bills by China’s central bank,
leading to excessive supply of Yuan and thus depreciation. This explains the reason of
positive sign.
With increasing GDP levels, US engages even more in international trade causing dollar
to lose value against major currencies such as euro, yen and pound. Since China has
pegged its currency to dollar for a long time, so any such depreciation causes Yuan to
depreciate against US Dollar. That’s why a positive sign for US GDP.
When China buys more of US treasury bills, it increase money supply in US and hence US
takes more imports from China, leading to appreciation of Yuan and hence a negative
sign for money supply in US.
The equation obtained is
π = .1706– (2.16E-12)L*s + (2.42E-06)Y* + .1376(r-r*) + .0923 (p-p*),
This equation gives correct forecasting till year 2005, but then because change in exchange
rate regime in China, a new improvised model was implemented where Yuan exchange rate
versus British Pound and Japanese Yen were found to be significant factors. And the new
equation was
Π= .9461+ .2194*πPound-Yuan+ 44.2215*πYen-Yuan
This equation gave far better results of forecasting (in sample) after 2005, then the previous
equation.

20. China’s case is different from India in the way that China’s economy is based around exports
of good to outside countries mainly to US and Japan while India’s economy is more driven
by both direction trade and direct investments. Also, India trade with US is much less
compared to China’s trade so India is not so much affected by economic changes of United
States.
China’s future growth depends on the value of Yuan and the competitive advantage of
Chinese goods. China faces pressure from all over the world to appreciate its currency but
that will lead to reduced exports which China would not like at all. To let the Yuan freely
float, China should allow all its residents to hold foreign currency and buy foreign assets.
This would allow the Chinese Government to hold fewer dollars and lessen the trade
imbalance with the U.S. Then there would be less focus by the U.S. Congress calling for an
increase in the Yuan's value [The Future of China’s Exchange Rate Policy by Morris Goldstein
and Nicholas R. Lardy].
China should start to invest in its service sector and information technology sector like India,
so that even in case of reducing exports of manufactured good, the total exports don’t go
down and hence China would be able to maintain its export oriented growth.
Most of the results match with what other studies have shown and almost every result are
justified by theory behind it. The literature completely supports the predictions made by
this study.
Ending Note
This study can be extended further; many more variables should be included in the
regression if data is available for them. The result will improve significantly if someone can
get data for Chinese economy even before 1980 and regress it on US data.
The dependence of Yuan on Euro should also be considered and further studies can be done
to calculate what weightage each currency has got in its currency basket.

21. References
1. International Economics by Peter B. Kenen
2. The Future of China’s Exchange Rate Policy by Morris Goldstein and Nicholas R. Lardy
3. World Bank, Databank http://databank.worldbank.org/ddp/home.do
4. Statistics of China’s International Trade
https://www.uschina.org/statistics/tradetable.html
5. Details of countries holding US treasury bills
http://www.treasury.gov/resource-center/data-chart-center/tic/Documents/mfh.txt
6. Ageing China: Challenges and Solution
http://www.bbc.co.uk/news/world-asia-19630110
7. Renminbi Rate Regime Information
http://en.wikipedia.org/wiki/Renminbi#Value
8. Export-Import bank of India, Catalyzing India's trade and investment
9. Impact of Changing Chinese Demography on Economic Growth
http://www.scribd.com/doc/113469484/Term-Paper-SOC-479