Chapter II 

 

Review of Literature 

 



8 

CHAPTER II 

REVIEW OF LITERATURE 

2.1 INTRODUCTION 

Indian foreign exchange market is the decentralised market in the Indian 

economy. It is the stronghold to the players of foreign exchange market for conversion of 

one nation currency into other nation currency. The regulatory role of foreign exchange 

market enlighten the nation’s trade a competitive one and determines the growth of the 

economy. The trading volume of the market has increased rapidly due to raise in foreign 

exchange transactions with trading in multinational currencies. The regulatory act has 

been amended to govern the foreign exchange transactions and to maintain the market.  

In this backdrop, this chapter chronologically presents the earlier studies on the concepts 

of exchange rate volatility, macroeconomic determinants affecting exchange rate, 

exchange rate and trade balance, which are classified into Indian and foreign reviews.  

2.2 INDIAN REVIEWS 

i) Reviews on exchange rate 

Sumanjeet Singh (2009)1 in his paper on, “Depreciation of the Indian currency 

implications for the Indian economy” has investigated the causes of the depreciation of 

the Indian rupee on the Indian economy with a theoretical background. He has also stated 

that the rupee depreciation would increase the exports and makes imported goods as 

costlier one, which has resulted a trade deficit in the Indian economy. The fall in the 

value of rupee has affected the economic growth with high interest rate, decrease in 

foreign investment inflows, made Indian companies to borrow loans in terms of dollar, 

which has resulted in an increase in the foreign debt. He has suggested that Reserve Bank 

of India should intervene in the market to strengthen the value of rupee by taking an 

effective measure and by attracting more foreign investments.  

Ritanjali Majhi and Panda (2009)2 in their paper entitled on “Efficient prediction 

of exchange rates with low complexity artificial neural network models” have predicted 

the exchange rate of US dollar against three currencies, such as, British pounds, Indian 

rupee and Japanese yen by developing forecasting models. They have developed two 



9 

models i.e Functional Link Artificial Neural Network (FLANN) and Cascaded Functional 

Artificial Neural Network (CFLANN) with the parameters of nonlinear inputs and simple 

ANN structure with neurons to forecast the exchange rate. The results of developed 

models have been compared with the performance of LMS forecasting model. It is 

concluded that CFLANN model is the best model in forecasting the exchange rate rather 

than FLANN and LMS forecasting models.  

Nagaraju (2009)3 in his research paper on “A measure of exchange rate volatility: 

scenario analysis of the effect of RBI’s Intervention in the Indian forex market” has 

observed the effect of RBI’s intervention on the volatility of USD/INR exchange rate by 

applying scenario analysis. The variables, such as, volumes of transactions in the foreign 

exchange market, volume of intervention by RBI and exchange rate have been taken for 

the study. Monthly and daily observations have been collected from RBI monthly 

bulletin. Scenario analysis has been applied to study the exchange rate, based on the 

demand and supply market conditions prevailing in the market. The results of the study 

have shown that there exists a contribution of Reserve Bank of India intervention in the 

foreign exchange market to reduce the volatility of the exchange rate.  

Neeti Khullar and Upasna Joshi Sethi (2011)4 in their paper on “Measuring the 

volatility of foreign exchange market” have analysed the behaviour of foreign exchange 

rates in the foreign exchange market in India. They have used the daily observations to 

analyse the volatility on spot exchange rates of Indian rupee against US dollar, Euro and 

Japanese yen for the period of 13 years from January 1, 1996 to December 31, 2008. 

Skewness, Kurtosis, Jarque bera test and Correlation analysis have been used in the 

study. The study has resulted that the exchange rate of Euro is highly volatile than the 

other foreign exchange rates, namely, Yen and US dollar in the Indian foreign exchange 

market. They have concluded that the movement of Indian rupee against Yen and US 

dollar was positively correlated during the study period.  

Ashima Goyal and Sanchit Arora (2012)5 undertook a study on, “The Indian 

exchange rate and central bank action : An EGARCH analysis” They have analysed the 

exchange rate volatility with the impact of monetary policy measures and dummy 

variables of central bank communication by estimating Generalised Autoregressive 



10 

Heteroscedastic (GARCH) models. Exchange rate of Euro / dollar, Rupee / dollar and the 

policy measures, such as, interest rate, intervention, news and speeches have been taken 

to study the exchange rate volatility. GARCH models have been applied to the daily data for 

the period from November 2005 to December 2008 and monthly data for the period from 

January 2002 to December 2008. The dummy variables of central bank communication and 

effect of policy measures have been considered to analyse whether the measures control 

the exchange rate level and volatility. The results of the study have shown that, the 

variations in exchange rate of euro against dollar have affected the exchange rate of rupee 

against dollar at its level and volatility. Among the variables taken under monetary policy 

measures, the interest rate has strong effects on exchange rate, it increases the volatility 

and depreciate the currency while other variables affect the exchange rate both at the 

level and volatility. They have suggested that Central Bank communication measures 

have to be used and developed effectively to control the exchange rate volatility in the 

foreign exchange market.  

Satyananda Sahoo (2012)6 has made a research on, “volatility transmission in the 

exchange rate of the Indian rupee”. The closing exchange rates of major foreign 

currencies, such as, Russian Ruble, Brazilian Real, South Korean won, Singapore dollar, 

Japanese yen, Swiss franc, British pound sterling, euro against Indian rupee for the period 

from January 2005 to December 2011 have been taken for the study. To investigate the 

effect of spillover on volatility of exchange rate, two - step multivariate GARCH models 

and pair-wise granger causality test have been applied. The results of the study have 

shown that there is a presence of conditional autocorrelation and persistent level of 

volatility in all the currencies taken for the study. He has concluded that, the effect of 

volatility of foreign currencies have affected the daily exchange rate of Indian rupee.  

Yusuf Perwej and Asif Perwej (2012)7 in their study on, “Forecasting of Indian 

rupee/US dollar currency exchange rate using artificial neural network” have examined 

the effects of neural network factors on model and have forecasted the behaviour of 

Indian rupee (INR) against US dollar (USD). They have used three factors of artificial 

neural network model for forecasting the daily observations of exchange rate of 

INR/USD for the period from 1989 - 2009. To forecast the exchange rate, the artificial 

neural network model with the parameters of the effect of number of inputs nodes, hidden 



11 

nodes and the size of training sample on the in-sample and out- of -sample of exchange 

rates have been applied. The results of the study have shown that the number of input 

nodes has played an important role in neural network time series model in forecasting of 

exchange rate.  

Samsudheen and Shanmugasundaram (2012)8 have conducted a study on 

“Foreign exchange volatility of Indian rupee against US dollar”. They have analysed the 

behaviour of foreign exchange rate of Indian rupee against US dollar and its volatility 

characteristics. Daily observations of exchange rate INR/USD for the period of 40 years 

from April 1, 1973 to March 31, 2012 have been collected. To analyse the volatility of 

exchange rate the ARCH family models (symmetric and asymmetric), such as, ARCH 

(1,1), GARCH(1,1), EGRACH(1,1) and TGARCH (1,1) have been applied. The study 

period from 1973 – 2012 has been sub divided into pre and post Liberalised Exchange 

Rate Management System (LERMS) period i.e from 1973 - 1993 as pre LERMS period 

and 1993 – 2012 as post LERMS period in order to assess the changes in the India 

exchange rate system from pegged exchange rate system to liberalised exchange rate 

management system and to determine the market exchange rate system. The results of 

GARCH (1,1), EGARCH and TGARCH models exist a presence of volatility for the 

three sample period and a presence of higher volatility in the exchange rate in post 

LERMS period than pre LERMS period.  

Shelly Singhal (2012)9 have discussed the reasons for the currency depreciation 

and its effects in her study on, “An analytical study on Indian currency rupee depreciation 

against the US dollar and its economic impact”. She has stated that there was a huge 

depreciation in the value of rupee after the year 1991 and has resulted a great effect on 

balance of payments. A rise in imports in the economy has remained current account 

deficit for a longer period despite of dramatic rise in exports. She also pointed out that the 

policy measures taken by Reserve Bank of India, such as, raising policy rates, adequate 

foreign exchange reserves, easing capital control and administrative measures to prevent 

the fall in value of rupee. The researcher has suggested that rise in exports and increased 

inflows may reduce the current account deficit.  



12 

Anshu Grewal (2013)10 in her study on, “Impact of rupee - dollar fluctuations on 

Indian economy: Challenges for RBI and Indian government” has explored the 

implications of depreciation of rupee against dollar in the Indian economy. She has 

conceptually discussed the movement of rupee, the reasons behind the currency 

fluctuations in the Indian economy and the steps taken by Reserve Bank of India for the 

effect of currency depreciation. She has suggested that the Government of India should 

take necessary measures to have control on the currency fluctuations and for the 

economic development of the country.  

Biswajit Maitra. et al (2013)11 have conducted a study on, “ARIMA forecasting 

of exchange rate in India”. The purpose of the study is to predict the exchange rate of 

rupee / dollar by applying ARIMA forecasting model and GARCH model. The monthly 

series of exchange rate of an Indian rupee against US dollar covering the period from 

1994 to 2013 have been collected from Reserve Bank of India. The exchange rate of 

rupee against dollar has been forecasted by applying ARIMA model and then GARCH 

model has been estimated for the forecasted residuals of exchange rate to measure the 

volatility. From the analysis it was found that GARCH (1,1) and ARIMA(1,1,6) were the 

better fit models in forecasting the exchange rate of rupee against dollar.  

Nand Kishor Soni and Ajay Parashar (2013)12 have made a study on, 

“Fluctuationing value of rupee and impact on economy”. They have discussed the 

exchange rate relationship in terms on appreciation and depreciation of rupee against 

dollar and the various reasons for the impact of changes in currency relations on various 

sectors of the economy. They have suggested that the country has to focus on investment 

pattern, innovative driven economy, effective reform process and also to take prominent 

policy measures to develop the economy.  

Chellasamy (2013)13 in his article on, “Depreciation of Indian currency and its 

impact on Indian economy”. He has analysed the growth of exchange rate in Indian rupee 

against selected foreign exchange rates and compared between pre and post liberalization 

period. He has determined the macroeconomic factors affecting exchange rate. He has 

taken selected exchange rates of an Indian rupee against SDR, US dollar, Japanese yen, 

Euro and Pound sterling and the macroeconomic factors, such as, Inflation rate, Interest 



13 

rate, External debt, Gross Domestic Product and Foreign Direct Investment. Secondary 

data have been collected for the period from 1989 - 1970 to 2012 - 13 from RBI bulletins. 

The Statistical tools, such as, mean, standard deviation, coefficient of variance, CAGR 

(compounded annual growth rate), correlation and paired “t” test have been used in the 

study. The results of the study have revealed that there was a positive growth in Indian 

rupee and Japanese yen in pre liberalisation period and the interest rate is highly 

correlated with Indian currency value.  

Partap Singh (2013)14 in his study on, “Depreciation of rupee in Indian economy: 

An analysis” has focused on the real implications and causes for depreciation of Indian 

economy. He has stated that the multiple reasons for fluctuations in the value of Indian 

rupee. The value of the currency depends on the factors that affect the economy, such as, 

imports, exports, inflation, interest rate, growth rate and foreign exchange reserves etc. 

RBI has intervened with key policies for the fall in the value of rupee. He has concluded 

that, the fluctuations in the value of the rupee/dollar had some effects on the  

Indian economy.  

Anuradha Patnaik (2013)15 in her study on, “A study of volatility spillover 

across select foreign exchange rates in India using dynamic conditional correlations” has 

focused on the volatility spillover among the exchange rates by applying multivariate 

GARCH framework. The multivariate dynamic conditional correlations model is a model 

that has been derived from multivariate GARCH framework, which is a tool to measure 

the volatility spillover and it has been applied to measure the volatilities of exchange 

rates of Indian rupee against US dollar, Euro, British Pounds and Japanese Yen. A daily 

observations covering the period from 5. 4. 2010 to 18. 7. 2011 have been collected from 

RBI Handbook of statistics. The period of the study has been subdivided in to four sub 

periods in order to measure the volatility spillover and dynamic correlation of exchange 

rates. The results of the study have shown that there exists a presence of volatility 

clustering in all the periods among the exchange rates. The volatility of Indian rupee 

against US dollar was very low while there was high volatility in euro and yen. The study 

has concluded that the policy interventions can be framed from the dynamic conditional 

correlation implications to reduce the exchange rate volatility.  



14 

Vandana Kotai (2013)16 has made a research on, “An empirical study on currency 

volatility in foreign exchange market” to explore the fluctuations of currency pairs, 

namely, INR / USD, JPY / USD, EURO / USD, GBP / USD and CNY / USD. She has 

used the close ended exchange rates and collected the data covering the period of three 

months from July – September 2013. She has concluded that the Indian currency market 

was found to be more volatile and unstable compared to other countries.  

Gautam Kamble and Parmeshwar Honrao (2014)17 have undertaken a study on,“ 

Time-series Analysis of exchange rate volatility of Indian rupee/US dollar - An empirical 

Investigation ” for the period from January 2011 to September 2013. They have analysed 

the consistency of exchange rate volatility on bilateral exchange rate of Indian rupee 

against US dollar by applying GARCH model. Daily observations of exchange rate have 

been collected from Reserve Bank of India, International Monetary Fund and US Federal 

reserve websites. The econometrics tools, such as, unit root test, ARCH effect, 

correlogram and GARCH models have been used in the study to measure the volatility. 

The results have shown that there exist a high volatility during the study period from 

2011 to 2013, due to rise in capital flows which has affected the revenue and expenditure 

of the trade and corporates. They have concluded that the foreign exchange transactions 

in the Indian foreign exchange market are always a transactional one. The conversions of 

currency from domestic country to foreign countries are controlled by the Government of 

the country, monetary and fiscal policies in the economy.  

Viney Narang (2014)18 in his article on, “Indian rupee vs Dollar: A Deep insight” 

has elucidated the current trends of the movement of rupee against US dollar during the 

period of independence from 1947 to 2013. He has conceptually discussed the long term 

and short term reasons for the depreciation of Indian rupee and its implications on the 

Indian economy. The reasons for movement of rupee against dollar have been collected 

from secondary sources, namely, Annual reports of Reserve Bank of India, news papers, 

magazines, International Monetary Fund and CRISIL reports. The trend of depreciation 

of rupee have impacted in the Indian economy with rise in domestic inflation rate and 

widening of current account deficit. He has concluded that the potential measures can be 

taken by the Government to have a control over the rupee depreciation and to reduce the 

current account deficit in the economy.  



15 

Paridhi Saini and Shivali Dhameja (2014)19 have entitled a study on, “Rupee 

dollar value trends: A study of influencing factors”. They have elaborated theoretically 

the concept of volatility of rupee, the macroeconomic factors influencing the value of 

Indian rupee and exchange rate management in India. The trend of volatility of Indian 

rupee has been differed from time to time and it is influenced by global events, economy 

shocks, speculation activities and other various macroeconomic factors in the economy. 

They have concluded that Reserve Bank of India intervenes in the foreign exchange 

market to reduce exchange rate volatility and buying and selling of foreign currencies in 

the market.  

Sanjeev Gupta and Sachin Kashyap (2014)20 in their study on, “Modelling 

exchange rate volatility in Indian foreign exchange market ” have examined the volatility 

for the exchange rates of US dollar and Euro against Indian rupee and recommended the 

model to forecast the exchange rate volatility in the foreign exchange market. A daily 

basis of USD/INR and EUR/INR covering the period from January 1, 2000 to October 

30, 2013 have been collected from Reserve Bank of India website to estimate a suitable 

model to forecast. They have used GARCH family models, such as, GARCH (1, 1), 

GARCH (1,2), GARCH (2,1) and GARCH (2,2). The results of the study have shown 

that the models GARCH (2,1) and GARCH (1,1) have confirmed the presence of 

volatility for the exchange rate of USD and EURO in the foreign exchange market and 

found to be best fit models to forecast the exchange rate. They have suggested that 

controlling measures have to be taken by Government of India and Reserve Bank of India 

on the factors that have impacted a negative variation in the exchange rate movements.  

Narasimhan (2014)21 in his research paper on, “The Recent Depreciation of the 

INR against the USD: An Analysis of Currency Fluctuations”. He has theoretically stated 

the effect of post crisis period and factors that pretended for currency depreciation of 

Indian rupee against US dollar in the Indian economy. Indian rupee depreciated largely 

against US dollar after crisis and created instability in the economy. He has concluded 

that policy measures and proper governance are the essential factors for the economy 

prosperity and to control depreciation of the currency.  



16 

Vaibhav Patni, Nikunj Batheja and Somesh Mathur (2014)22 have conducted a 

study on, “Effect of rupee decline on Indian economy”. They have examined the impact 

of decline of exchange rate on the variables by applying ARDL model and Granger 

causality test. The variables, such as, Real Effective Exchange rate, Imports, Exports, 

Forex with RBI, Oil prices, Gold prices, Index of Industrial Production, Consumer Price 

Index and Oil imports have been taken for the study. The monthly data have been 

collected from the secondary source of Indian government website and Reserve Bank of 

India database. Unit root test have been applied to test the stationarity of the variables. 

The results have revealed that the variables are stationary and with the level of 

cointegration between the variables. ARDL model has been applied to the variables in the 

long run. The results have shown that exchange rate has a positive effect on exports and 

Index of Industrial Production and negative effect on imports. In long run, inflation rate 

has a negative impact on the exports and industrial production. It also implied that the 

decline in the exchange rate affects the prices of goods and exports as well, which in turn 

affects the industrial production in the economy.  

Vandana Kotai (2015)23 in her article on, “A study on volatility of the rupee 

exchange rates against major currencies” has examined the volatile nature of Indian rupee 

and found which pair of currency of Indian rupee against other currencies are more 

volatile in the foreign exchange market. The currencies which are mostly traded in the 

foreign exchange market, such as, Indian rupee against US dollar, Japanese yen, Chinese 

Yuan, Euro, Pound sterling for the period of 10 years from 2001 – 2010 were taken for 

the study. The Statistical tools, such as, coefficient of variance and standard deviation 

have been used to calculate the fluctuations in the currency. The result of the study have 

shown that the Indian rupee had been depreciating among all the currencies and the 

currency pair Indian rupee against US dollar were fluctuating widely because India 

accepted US dollar as intervention currency. She has concluded that Indian foreign 

exchange market, after globalisation has been more volatile and unstable due to rise in 

capital flows and cross border trading activities.  

Priyadarshi Dash (2015)24 has conducted a study on, “Exchange rate volatility on 

post - floating regime in India”. The researcher has analysed the exchange rate volatility 

of Indian currency in the post floating period. A daily data of bilateral exchange rate of 



17 

Indian rupee against currencies, namely, US dollar, pound sterling, euro and yen covering 

a period from 1993 - 2009 have been taken for the study. The econometric models, such 

as, GARCH, VAR and VECM models have been used to identify the existence of 

volatility in the exchange rates. The result has shown that there is a presence of volatility 

in the exchange rate of Indian currency with the international currencies, and also found 

that the volatility of nominal exchange rate of Indian rupee against USD affects the 

changes in bilateral exchange rate of other currencies. It is also suggested that a better 

policy measure can be brought to reduce the exchange rate volatility.  

Miao Wang, Burak Yungucu and Yousuf Sultan (2015)25 in their paper on, 

“Exchange rate and volatility of Indian rupee against five currencies” have investigated 

the economic implications of different periods, which has affected the economy and 

behaviour of Indian rupee against currencies between different countries. The sample of 

five selected major currencies of Indian rupee against US dollar, Euro, British pounds, 

Singaporean dollar and Malaysian ringgit for the period of 13 years from 2001 - 2014 

have been collected and analysed by applying mean, standard deviation and correlation. 

They have examined the behaviour of exchange rates. The study period has been 

subdivided into three periods, such as, pre crisis period (January 2001 - November 2007), 

Crisis and post - crisis period (December 2007 – April 2013) and Monetary tightening 

period (May 2013 - September 2014). The results of the analysis have shown that Indian 

rupee has been depreciated among all five currencies and it was highly depreciated 

against Euro, Singaporean dollar. Indian rupee was volatile among the currencies during 

the study period. Correlation analysis has resulted that there was a positive correlation 

among the currencies and it has concluded that Indian rupee against US dollar has been 

appreciated during pre crisis period and depreciated during and after the crisis period. 

Besides the depreciation of the currency, the Indian economy has maintained a stable 

economic growth.  

Krishna Murari (2015)26 in his paper on, “Exchange rate volatility estimation 

using GARCH models, with special reference to Indian rupee against world currencies” 

has made an attempt to estimate a model for exchange rate return volatility of an Indian 

rupee against major currencies, such as, US dollar, Euro, Pound sterling, Japanese yen by 

applying different univariate specification GARCH models. A sample of daily data for 



18 

the period of January 3, 2000 to September 30, 2013 has been collected from Reserve 

Bank of India online database. The volatility of the Indian rupee exchange rate returns 

against major currencies have been studied by applying both symmetric GARCH (p,q) 

and asymmetric models, such as, TGARCH, EGARCH and PGARCH have been used to 

analyse the most common facts about currency returns, such as, volatility clustering and 

leverage effect. The results of the study have shown that the rupee exchange rate returns 

are volatile due to positive shocks than negative shocks and found that exchange rate 

returns affect the future exchange rate movements in the foreign exchange market. From 

the study, it has been concluded that the asymmetric models are the better fit models to 

explain the exchange rate volatility.  

Ayush Singh, Vinaytosh Mishra and Akhilendra Singh (2016)27 in their study 

on, “Impact of rupee - dollar fluctuations on Indian economy” have discussed 

conceptually the concept of Indian currency fluctuation and have stated the real 

implications for the depreciation of the rupee in Indian economy. They have stated that 

Reserve Bank of India can easen the capital controls by increasing the Foreign 

Investment Inflows limit on investment in government and corporate debt instruments 

and also introduce higher ceilings in External Commercial Borrowings. They have 

suggested that the Government can create a stable political and economic environment to 

prevent the depreciation of Indian rupee in future.  

ii) Review on Macroeconomic Determinants 

Jorge Canales – Kriljenko and Karl Habermeier (2004)28 undertook a study on 

“Structural factors affecting exchange rate volatility: A cross-section study” in 

developing and transition economies. They have focused on the macroeconomic factors 

affecting exchange rate volatility. The economic factors, such as, inflation, GDP growth, 

fiscal deficit and openness of the economy have been selected from the 85 developing 

and transition economies and the data collected by IMF on Foreign exchange market 

organisation has been used in the study. They have examined cross sectionally, the 

exchange rate volatility with the selected macroeconomic factors, exchange rate regimes 

and with the features of foreign exchange market in the developing and transition 



19 

economies by applying regression analysis. It was found that the macroeconomic factors 

and features of foreign exchange market affect the exchange rate volatility.  

Mita Suthar (2006) 29 in her article on, “Determinants of exchange rate in India” 

applied OLS regression to evaluate the determinants in relation to the exchange rate of an 

Indian rupee and US dollar. A sample of monthly data for the period from 1996 – 2007 

has been collected. She has analysed whether the determinants interest yield differentials 

of India and US securities, bank rate of RBI, forex reserves and money supply that has 

impacted the exchange rate movements. The results of the study has shown that the 

monetary policy variable, such as, bank rate of RBI, interest rate differentials and the rate 

of foreign exchange reserves have a significant influence on the monthly exchange rate of 

Indian rupee against US dollar.  

Sunil Kumar (2010)30 in his study on, “Determinants of Real Exchange Rate in 

India: An ARDL Approach” has investigated the real exchange rate with its macroeconomic 

determinants. He has identified theoretically the determinants affecting exchange rate and 

analysed the short run and long run relationship between exchange rate and 

macroeconomic determinants using unit root test, Bound test cointegration analysis, Error 

correction analysis and Autoregressive Distributed Lag (ARDL) Modelling approach. 

The bilateral real effective exchange rate have been taken as dependent variable and the 

independent variables, such as, productivity differential, external openness, terms of 

trade, net foreign assets, government final consumption expenditure have been 

considered in the study. A Quarterly observation for the period from 1997 to 2009 has 

been collected from Reserve Bank of India, International Monetary Fund and 

International Financial Statistics websites. The researcher after checking the stationary of 

the variables, have estimated the variables to study the long run cointegration relationship 

and short run effect. The results of the study have shown that there exists a long run 

relationship between the exchange rate and the macroeconomic determinants while there 

exist a negative effect in the short run. Among the determinants taken, productivity 

differential, external openness, terms of trade, net foreign assets are found to be 

statistically significant with the exchange rate. He has concluded that the factors 

determining the appreciation of exchange rate would also improve the economic growth.  



20 

Divyang Joshi (2011)31 has made a study on, “Impact of dollar fluctuation on 

gold and crude oil prices”. The objective of the study is to analyse the effect of exchange 

rate volatility on gold and crude oil prices in India using unit root test, correlation and 

regression analysis. The variables, namely, gold, crude oil and exchange rate INR/USD 

have been taken. Secondary data for a sample of five years weekly data have been 

collected from financial websites for the period from 2005 to 2009. The results of the 

study have shown that there is an inverse relationship between exchange rate of rupee 

against dollar, crude oil and gold prices. The study has concluded that the change in 

exchange rate would result in an opposite effect with the prices of gold and crude oil.  

Shylajan and Sreejesh (2011)32 in their article on, “Rupee-dollar exchange rate 

and macroeconomic fundamentals: An empirical analysis using flexible-price monetary 

model” They have evaluated the relationship between Indian rupee - US dollar and 

macroeconomic fundamentals using flexible-price monetary model. The determinants, 

such as, spot nominal exchange rate, money supply of USA, Index of Industrial 

Production of USA and India and interest rate of USA have been taken. A sample of 

monthly data for the period from 1996 to 2010 have been collected from OECD stat 

database, Business Beacon data base, Centre for Monitoring Indian Economy and Federal 

Reserve System website. Due to non availability of monthly data, they have considered 

Index of Industrial Production as a proxy variable of GDP and call money rate are taken 

as proxy variable for interest rate for the analysis. Augmented Dickey Fuller test has been 

applied to test the presence of unit root among the variables. Johanson - Juselius 

cointegration and Vector error correction model (VECM) analysis have been used to 

examine the short run and long run relationship between exchange rate and determinants. 

The results have shown that the exchange rate and the determinants have a long run effect 

and supported the implications of flexible-price monetary model.  

Sajal Ghosh (2011)33 has made a research paper on, “Examining crude oil price - 

exchange rate nexus for India during the period of extreme oil price volatility” by 

applying GARCH and EGARCH models. Researcher has examined the volatility of oil 

price shocks on nominal exchange rate. Daily observations of exchange rate and crude oil 

prices for the period from July 2, 2007 to November 28, 2008 have been collected from 

websites of energy information administration and Reserve Bank of India. The results 



21 

have shown that oil price shocks have a positive and negative effect on the exchange rate 

volatility. It also implies that the rise in crude oil prices have depreciated the Indian rupee 

against US dollar to a large extent.  

Maram Srikanth and Braj Kishor (2012)34 have conducted a study on “Exchange 

rate dynamics in Indian foreign exchange market: An empirical investigation on the 

movement of USD/INR”. The objective of the study is to determine the factors affecting 

the movements in exchange rate of USD/INR using multiple regression analysis. Both 

primary data and secondary data have been used in the study. Primary data have been 

collected through a questionnaire from 175 professionals. Secondary data have been 

collected for the period from January 1999 to March 2011 from the websites of Reserve 

Bank of India and Federal system of the US. Exchange rate of USD/INR was taken as 

dependent variable and the independent variables, such as, interest rate, inflation rate, 

current account balance, capital account balance, RBI’s net intervention, foreign currency 

reserves, foreign exchange market turnover, Index of Industrial Production, money 

supply and forward premia have been taken in the study. The results have shown that the 

variables, such as, current account balance, relative money supply, Index of Industrial 

Production and interest rate differential were the most significant variables in 

determining the exchange rate. Primary data results have shown that, forward premia 

influences the movements of exchange rate and they have concluded that foreign 

exchange market has become deep and liquidity market during the recent period.  

Yamini Karmarkar and Muskan Karamchandani (2012)35 made a research on 

“Exchange Rate and Macro - economic indicators: A Causal Study for India of the Past 

Decade” have analysed whether the macroeconomic indicators of the economy affect the 

exchange rate of Indian rupee against US dollar. They have taken variables under each 

four sectors of the economy, namely, external sector – foreign exchange reserves, 

financial market - central government outright buy and sale of government securities, 

repo rates, financial sector- reserve money, RBI open market operations and real sector- 

whole sale price index. A weekly data have been collected for the variables for the period 

from January 2001 to June 2009 from Handbook of statistics on Indian economy - RBI, 

OANDA forex trading and exchange rate services online databases. Statistical tools, such 

as, unit root test- Augmented Dickey fuller test and Phillips Perron test, multivariate 



22 

Vector Auto Regression framework and Granger causality tests have been applied. The 

results have shown that exchange rate has been affected by the variables of external 

sector, financial market and financial sector in long run. There exist a bidirectional casual 

relationship between exchange rate with foreign exchange reserves, Sensex and RBI open 

market operations. They have suggested that Government of India should take control 

measures considering the aspects like decline of rupee, control of foreign inflows and 

outflows, political corruption for a stable economy.  

Krishna Murari and Rajesh Sharma (2013)36 undertook a study on, “OLS 

modelling for Indian rupee fluctuations against US Dollar”. They have examined the 

dynamics of exchange rate in the Indian economy. The purpose of the study is to analyse 

the factors of the economy that affect the fluctuation of Indian rupee against US dollar 

using Ordinary least square analysis. The annual data covering a period of thirteen years 

from 2001 to 2013 from RBI data base on Indian economy. They have explored the 

History of exchange rate mechanism after independence, Rupee appreciation and 

depreciation and factors affecting exchange rate. The variable exchange rate has been 

taken as a dependent variable, and the independent variables, such as, foreign exchange 

reserves, foreign investment inflows, interest rate, inflation rate, money supply and trade 

balance have been taken in the study. The result of analysis have shown that the 

variables, such as, inflation rate, interest rate, trade balance and money supply are found 

to be significant and these variables have explained the dynamics of Indian rupee against 

US dollar to the extent of 94. 8 per cent.  

Anita Mirchandani (2013)37 in her article “Analysis of Macroeconomic 

Determinants of Exchange Rate Volatility in India” has probed the reasons for 

depreciation of Indian currency and has examined the macroeconomic determinants 

affecting the exchange rate volatility in India using correlation analysis. Secondary data 

have been used in the study. The annual data have been collected for the period from 

1991 – 2010. The variables, namely, exchange rate, external debt, inflation rate, interest 

rate, Gross domestic product and foreign direct investment were taken and analysed. She 

has reviewed the probable reasons for the depreciation of the rupee and the results have 

shown that the variables interest rate, inflation rate, Gross domestic product, growth rate 

and Foreign direct investment have been correlated positively and negatively with the 



23 

exchange rate. She has concluded that low capital inflows, rise in prices of import 

commodities have caused the Indian rupee depreciation among international currencies.  

Vadivel and Ramachandran (2013)38 in their research paper on, “Does exchange 

rate intervention trigger volatility” have aimed to investigate on the two concepts, 

whether the intervention of Reserve Bank of India policies on exchange rate has 

controlled the volatility and the presence of asymmetric in the intervention by applying 

GARCH and A-PARCH models. Reserve Bank of India has intervened in the market to 

reduce the fluctuations of exchange rate. They have taken percentage change in exchange 

rate as a dependent variable and percentage change in size of intervention as an 

explanatory variable for the study. A weekly observations for the sample period from 

December 1996 to April 2013 have been collected. The results of GARCH and  

A-PARCH have shown that Reserve Bank of India intervened in the exchange rate 

volatility and found there is a asymmetric effect on selling of foreign exchange which has 

a higher volatility than the purchase of foreign exchange in the foreign exchange market.  

Adhiraj Arora and Somesh Mathur et al. (2014)39 made a study on, “What 

determines US Dollar - Indian Rupee exchange rate movements”. The purpose of the 

study is to analyse the Indian rupee fluctuations against US dollar and the variables that 

influence the exchange rate movements for the period of 21 years from January 1993 to 

December 2013. They have used quarterly observations and secondary data have been 

collected from Reserve Bank of India’s database on Indian economy, Economic research 

of Federal Bank of St. Louis, IMF’s e-Library data, trading economics. com and World 

Bank Development. The study has considered the eight variables, such as, exchange rate 

of Indian rupee against US dollar, Differential interest rate, differential inflation rate, 

differential money supply, differential output growth rates, exchange rate of Pound - 

rupee, Euro - rupee and Yen - rupee. The statistical tools, such as, unit root test, 

cointegration test, ordinary least square and feasible generalised least square have been 

applied for the study. The results of unit root test have shown that the variables are 

stationary and found there is no cointegration between the variables. It is found that the 

variables differential interest rate, differential inflation rate, differential money supply, 

differential output growth rates, exchange rate of Pounds and Euro have a large extent on 



24 

influencing the exchange rate movements. The results of the study have supported the 

implications of interest rate parity theory and purchasing power parity theory.  

Piyush Sharma and Shivam Rai (2014)40 entitled a study on, “Determinants of 

foreign exchange rate volatility in the Indian economy” for a period of 20 years from 

1992 to 2012. They have analysed whether the factors of the economy affect the 

movements of Indian currency. Two major important currencies in the international 

market, such as, US Dollar and Great British pounds against Indian rupee have been 

considered to determine the factors influencing exchange rate volatility. They have 

applied autocorrelation function to find which currency is frequently used in the market. 

It was found that INR/USD is the widely used in the foreign exchange market. The 

statistical tools, such as, Unit root test, Auto correlation function, Pair wise Granger 

causality test, Correlation and Regression analysis have been employed for the exchange 

rate of INR/USD, GDP growth rates, Index of Industrial production, Wholesale price 

Index, BSE-30. The results of the study have shown that BSE-30 is the most significant 

factor determining the volatility of Indian currency.  

Ravi Bhandari (2014)41 in his study on, “An analytical study on Depreciation of 

rupee against dollar and Fundamental analysis on the impact of macroeconomic factors 

on exchange rate of rupee” has explored the reasons for depreciation of Indian currency 

and its relationship with the economic factors. The period of the study was from 2000 to 

2013. Correlation analysis has been applied for Gross domestic product, foreign direct 

investment, Money supply, Foreign investment inflows, Export growth, Inflation rate and 

exchange rate to identify the relationship between the variables. He has also forecasted 

the average exchange rate for the year 2014 by applying forecasting analysis. It was 

found that the rupee is positively correlated with Inflation and Foreign direct investment. 

Exchange rate is negatively correlated with the Gross Domestic Product, Export growth, 

Money supply, Foreign investment inflows. It also implied form the results that the 

increase or decrease in the economic factors have an impact on the currency depreciation. 

He has suggested that the country has to increase the exports by correcting economic 

fundamentals and serious, structural and economic policy reforms have to be brought to 

make the exchange rate stable.  



25 

Hidhayathullai and Mahammad Rafee (2014)42 conducted a study on 

“Relationship between crude oil price and Rupee, Dollar exchange rate: An Analysis of 

preliminary evidence” in India for the period from 1972-73 to 2012-13. The purpose of 

the study is to analyse the impact of crude oil prices on the Indian currency. Secondary 

data have been collected from the website of Knoea. com and Handbook of Indian 

Statistics 2012 -13, RBI publications. Multiple linear regression model has been applied 

to study the relationship between imports of crude oil, world crude oil prices and 

exchange rate of rupee against USD. They have framed two models to evaluate the 

impact of imports of crude oil and future crude oil prices. Crude oils are priced in terms 

of dollar in the international market. The results have shown that exchange rate of rupee 

is influenced by imports of crude oil. They have concluded that the continuous increase 

in imports and prices of crude oil would lead rupee to depreciate against dollar. The rupee 

depreciation can be overcome by the increase in domestic oil production and control of 

oil demand in the economy.  

Ramana Raju (2015)43 in his article on, “An econometric analysis pertaining to 

exchange rate dynamics in India” has evaluated the influence of interest rate and inflation 

rates on exchange rates by applying Unit root test, Vector Autoregression (VAR) model, 

Wald test and Regression analysis in long run and short run. Exchange rate of Indian 

rupee against US dollar has been taken as an independent variable. Inflation and interest 

rate were taken as dependent variables. Consumer price index was taken as proxy 

variable for inflation and call rates or money rates have been taken as proxy variable for 

Interest rate. The period of the study was from 1990 to 2010. Secondary data have been 

used and collected from RBI website. He has employed the stationarity of the variables, 

to estimate the variables for VAR analysis and Wald test to study the long run and short 

run relationship. It was found that in long run the variables, such as, interest rate and 

inflation rate does not influence the exchange rate while in short run the variables have 

jointly influenced the exchange rate movements. It is also implied that interest rate and 

inflation rate affect the exchange rate volatility in India.  

Vincent Bodart and Bertrand Candelon (2015)44 in their research paper on  

“Real exchange rates, commodity prices and structural factors in developing countries”. 

They have focused whether the structural factors of the economy, exchange rate regime 



26 

of the countries would affect the price of commodities and the exchange rate for the 

period from 1980 to 2012. So for that, based on International Monetary Fund 

classification of developing countries and Country’s export performance a sample of 33 

developing and emerging countries has been selected. They have evaluated the major 

export commodity and the share of particular commodity to the total export of the 

countries. They have sorted 12 commodities from the countries. They have considered 

five structural factors, namely, type of exportable commodity, degree of trade openness, 

degree of export specialisation and degree of financial openness to find whether exchange 

rates and market price of commodities dependent on structural factors. Secondary data 

have been used. The data have been collected from International financial Statistics 

database of IMF, Annual reports of IMF and World Bank. The tools, such as, cross 

sectional dependence test, Panel unit root test and cointegration test, Robustness check 

have been applied for the exchange rate and prices of commodities with the dummy 

variables. The result have shown that there is no cross sectional dependence between the 

exchange rate and commodity price. After applying the Panel unit root test of the 

variables, the Cointegration test results has shown that the factors exchange rate regime, 

degree of financial and trade openness are statistically significant in the long run. They 

have suggested that the developing countries can depend relatively less of their exchange 

rate for the prices of commodity in trade.  

Ravindran Ramasamy and Soroush Karimi Abar (2015)45 undertook a study on, 

“Influence of Macroeconomic Variables on Exchange Rates” by estimating regression 

models. The annual data of three countries of exchange rates, namely, United States 

(AUD /USD), Australia (Euro /USD) and Germany (AUD /Euro) have been considered. 

Multi model technique has been applied to identify the best model by linking the variables 

in the model. The period of the study is for ten years. Exchange rates are taken as 

dependent variable and the interest rate, inflation rate, balance of payment, employment 

rate, corruption index, gross domestic product, deficit / surplus rate, namely, borrowing rate 

and tax rate have been taken as independent variables in the study. The regression result 

has shown that model B is the best fit model indicated that the variables borrowing rate, 

tax rate, interest rate, inflation rate, balance of payment, corruption index, gross domestic 

product and surplus rate are statistically significant and influenced the exchange rate.  



27 

Kanika Khera and Inderpal Singh (2015)46 have made a research on, “Effect of 

macroeconomic factors on rupee” that influenced the fluctuations of Indian rupee value 

against US dollar during post globalisation period by applying correlation and regression 

analysis. The variables, such as, inflation rate, lending interest rate, foreign direct 

investment, gross domestic product and current account deficit have been considered. 

The period of study covered for 22 years from 1991 to 2013. Secondary data have been 

collected from RBI bulletin and World Bank website. They have found that GDP is 

positively correlated with exchange rate and the variables lending interest rate, inflation 

rates and current account deficit are negatively correlated. The regression results have 

shown that the exchange rate is 85. 2 per cent dependent on independent variables. They 

have suggested that the currency depreciation can be controlled by promoting foreign 

direct investment inflows and decrease in imports.  

Poornima and Ganeshwari (2016)47 in their article on, “An analysis of 

macroeconomic determinants of exchange rate volatility in India” have explored the 

macroeconomic factors that influence the value of Indian currency. Secondary data for 10 

years for the period from 2000 to 2015 have been collected and analysed. OLS regression 

techniques have been applied for the variables exchange rate, inflation rate, trade balance, 

current account, money supply and Interest rate. The result has shown that these 

macroeconomic variables have explained the relationship to the exchange rate to a large 

extent of 92. 4 per cent.  

Vidyavathi, Kulkarni Keerti and Ainapur Pooja (2016)48 have entitled a study 

on, “A study on macroeconomic indicators and their impact on exchange rates”.  

They have analysed the major determinant that affect the exchange rate volatility for the 

period of 10 years from 2006 to 2016. Correlation analysis have been applied for the 

variables, such as, interest rate, inflation rate, Foreign Direct Investment, Gross Domestic 

Product, External debt, Current account deficit to study the interrelationship between the 

variables. Secondary data have been collected from books, journals and articles. The 

results of the study have revealed that Gross Domestic Product, Inflation rate, Interest 

rate, External debt and Current account deficit are negatively correlated with exchange 

rate and FDI was positively correlated. They have concluded that these are the major 

determinants that cause the exchange rate volatility and have probed that due to 



28 

insufficient of capital inflows and unfavourable trade balance and other economic 

changes are reasons for the appreciation and depreciation of the currency.  

Thilak venkatesan and Ponnamma (2017)49 have carried out a research on,  

“An analysis of macroeconomic factors affecting foreign exchange rate”. The objective 

of the study was to examine the various macroeconomic factors affecting the exchange 

rates and to develop a model to forecast the exchange rate. The exchange rates of US 

dollar, Euro, Yen and Pound sterling and macroeconomic factors, such as, inflation rate, 

forex reserve, Gross Domestic Product, Money Supply, oil price, Index of Industrial 

Production, bank rate, current account deficit, Foreign Investment Inflows, Foreign 

Direct Investment, Wholesale Price Index, exports and imports have been taken for the 

study. Secondary data have been collected for the period of 15 years for 2000 - 2015 

from the reports of Reserve Bank of India. The econometric tools, namely, Unit root test, 

Vector Autoregression, Autoregression Distributed Lag model and Granger causality test 

have been applied and forecasted. The results of the study have revealed that among the 

variables taken Foreign Direct Investment was highly significant in affecting the 

exchange rate and inflation rate have a negative impact in long run. Inflation rate has a 

causal relationship with Foreign Direct Investment in short run. They have concluded that 

the exchange rate volatility is affected by the macroeconomic factors, such as, inflation 

rate and Foreign Direct Investment. These are the important determinants that predict the 

movement of exchange rate in future.  

Jain Mathew, Suvitha and Rekha (2015)50 have made a study on, “Analysis of 

macroeconomic determinants of exchange rate in India”. They have discussed the 

probable reasons for fluctuations for Indian currency and analysed the macroeconomic 

determinants that have direct or indirect impact on exchange rate by employing 

correlation analysis. The variables, namely, exchange rate of Indian rupee against US 

dollar, Inflation rate, Interest rate, External debt, Gross Domestic Product and Foreign 

Direct Investment have been taken. Secondary data have been collected annually from 

world development indicators and OECD countries website for the period of ten years 

from 2004 to 2013. The result of the study have shown that the variables, such as, 

Inflation rate, Interest rate, External debt, Gross Domestic Product and Foreign Direct 



29 

Investment have affected significantly. Out of this Gross Domestic Product, External debt 

and Inflation rate have strongly correlated with the exchange rate.  

Rabia Naif (2016)51 has entitled a paper on, “Analysis of macroeconomic 

determinants of exchange rate volatility in India” to explore the long run and short run 

relationship between the macroeconomic variables and exchange rate volatility.  

The variables, such as, exchange rate, inflation rate, money supply and interest rate have 

been taken for the study. A monthly data of 109 observations have been collected.  

The statistical tools, namely, Augmented Dickey Fuller test, Johansen cointegration test, 

Vector Error Correction Model (VECM) and Granger causality test have been applied. 

The results of the study have shown that exchange rate was positively related with 

inflation rate and negatively related with interest rate and money supply. It is also implied 

that the change in these variables affect the exchange rate fluctuations. She has concluded 

that high money supply and interest rate would increase the inflation rate and that leads to 

increase in the exchange rate volatility.  

iii) Review on Trade Balance 

Tarlok Singh (2002)52 in his study on “India’s trade balance: the role of income 

and exchange rates” has analysed the effects of exchange rate and national income on 

balance of trade in India by estimating reduce - form balance of trade model. The study 

has covered a period from 1960 to 1995. He has selected the variables, such as, trade 

balance, real effective exchange rate, nominal effective exchange rate, exports, imports, 

domestic income, foreign income and Gross Domestic Product for the study. He has 

applied Johansen Cointegration and Error Correction model to analyse the long run and 

short run relationship between the variables. The results of Johansen Cointegration test 

have shown that there is a significant relationship exists between exchange rate and 

domestic income with trade balance in long run. He has suggested that the effect of real 

effective exchange rate on trade balance has to be observed due to the policy changes in 

the economy. He has concluded that the policies have to be framed to stabilise the 

domestic price of goods and to control the effects of exchange rate changes on trade 

balance in India.  



30 

Ozturk and Ilhan (2006)53 have done a study on “Exchange rate volatility and 

trade: A literature survey”. They have reviewed the earlier research studies related to the 

exchange rate volatility and trade. They have examined the study by comparing exchange 

rate and trade theories and with the results of various empirical studies relating to the 

trends and changes in exchange rate volatility and trade. It is also found that most of the 

earlier studies have resulted that the changes in exchange rate volatility have affected the 

foreign trade.  

Sushanta Mallick and Helena Marques (2010)54 in their study on, “Data frequency 

and exchange rate pass – through : Evidence from India’s exports” have analysed the Indian 

export prices to exchange rate changes during short run and long run exchange rate pass 

through in the sectors. The variables, such as, exchange rate, export prices have been 

taken for the study. Secondary data have been collected both annually and monthly.  

The annual data covering the period from 1991 to 2006 have been collected from United 

Nations COMTRADE database and monthly data for the period from 1996 to 2001 have 

been taken from India Trades database from CMIE for the study. Panel data unit root test 

and panel cointegration test have been applied for the study. The results of the study have 

shown that the variables are stationary. It also indicates that the monthly data have 

incomplete exchange rate pass through to the destination of market prices in long run. 

They have concluded that the price competitiveness and policy impact relating to export 

should be improved to increase exports.  

Srinivasan and Kalaivani (2012)55 in their study on, “Exchange rate volatility 

and export growth in India: An empirical Investigation” have examined the impact of 

exchange rate volatility on Indian exports using Autoregression Distribution Lag (ARDL) 

model. Secondary data have been collected for the study covering the period of 1970 to 

2011 from Handbook statistics of Indian economy, RBI and central statistical 

organisation. The variables, namely, India’s exports, Gross domestic product, real 

exchange rate, real exchange rate volatility and the world GDP have been taken. 

Augmented Dickey Fuller test have been applied to test the stationarity of the variables. 

The results of unit root test have shown that the variables are stationary. ARDL model 

has been applied to evaluate the cointegration between the variables in long run and short 

run. The results have revealed that exchange rate volatility has a significant negative 



31 

impact on real exports both in long run and short run where as real exchange rates has a 

negative effect in short run and positive effect in long run on real exports. It is also found 

that GDP has a positive impact on India’s exports. They have concluded that exchange 

rate fluctuations would affect the exports in the Indian economy.  

Mehernosh Mehta and Hatim Kayumi (2013)56 have determined the impact of 

current account deficit on India’s external debt and the selected foreign exchange rates 

such as - US dollar, Pound Sterling, Japanese Yen and Euro for the period of two decades 

from 1990 - 91 to 2012 – 13. Secondary data have been taken from Reserve Bank of 

India web pages. The Statistical tools, such as, Percentage analysis, CAGR and 

correlation have been used in the study. Percentage analysis and CAGR have been 

applied to analyse the trend of India’s current account deficit and the components of total 

external debt. Correlation has been used to determine the relationship between current 

account deficit on external debts and the selected foreign exchange rates. They have 

concluded that current account balance has a positively correlation with external debts 

and negatively correlation with the exchange rates of Japanese Yen and Euro among the 

selected foreign exchange rates.  

Jayachandran (2013)57 in his study on, “Impact of exchange rate on trade and 

GDP for India –A study of last four decade” has analysed the short run and long run 

relationship between impact of exchange rate volatility on the India’s exports and 

imports. Secondary data have been used. The study has covered a period of 30 years from 

1981 to 2010. Variables such as, exchange rate, imports, exports and gross domestic 

product has been taken for the study. Trend analysis and simple linear model of 

regression analysis have been used to examine the relationship between export, imports 

and exchange rate on GDP. The results of the study have revealed that exchange rate has 

a negative impact on exports and imports and Gross Domestic Product has a positive 

impact on exports only in the long run. There is no significant relationship exist in short 

run. The results of the study have implied that the variables taken for the study are 

cointegrated and higher the exchange rate volatility influenced the trade and reduced the 

exports. He has suggested that the trade liberalisation and supportive monetary policies 

would tend to save the tax yield and improves the trade by stabilising exchange rate.  



32 

Vijayasri (2013)58 in her research paper on, “The importance of international 

trade in the world” has explained the theoretically the importance of international trade 

for the economic development. She has discussed the need for international trade, 

relationship between international trade and economic development and has also stated 

the disadvantages of international trade in the country. She has concluded that the 

international trade used as a strategy for the growth of the economy. The economic 

infrastructure and policy measures have been taken in an efficient manner to adopt the 

socio economic changes in the economy.  

 Shubhada Sabade (2014)59 has made a study on, “India’s foreign trade and 

socio-economic development (Trio of WTO compliance, currency depreciation and 

global crisis)” has analysed the reasons for the fluctuations of exports and imports, 

depreciation of rupee and risen trade deficit in India. The researcher has selected the 

variables, such as exports, imports, trade balance and exchange rate for the study. 

Secondary data have been collected for the period of 23 years from 1991 to 2013 and 

analysed by using percentage analysis. She has found that India’s trade balance have been 

negative indicated that it has faced high and continuous trade deficit for a longer period. 

The trade deficit has affected the Indian currency to depreciate and increased import bills. 

She has pointed out that the India’s trade WTO agreements; trade barriers, currency 

depreciation and global crisis are some of the reasons that affect the trade fluctuations. 

She has concluded that, India has to adopt ‘inward looking approach’ for the economic 

development which has implied that exports can be increased with rise in production and 

quality of goods and thereby reducing the imports. This will result in increase of income 

and employment and would also pave the way for economic development.  

Kanda Naknoi (2014)60 have conducted a study on “Exchange rate volatility and 

fluctuations in the extensive margin of trade” He has taken the extensive margin of 

exports and imports in US that fluctuated over the business cycle. He has used quarterly 

data of US bilateral trade of more than 10,000 products between 99 countries covering 

the period from 1990 - 2009. Reasonable model of trade dynamics and correlation have 

been used for analysis. The results of the study have shown that the extensive margin of 

exports from the U. S and the extensive margin of imports to the U. S are more volatile 

than the other trading countries respectively. He has concluded that fixed exchange rates 



33 

with U. S dollar, Free Trade Agreement with the U. S and an increase in country size are 

significantly associated with the stable pattern of trade.  

Chellasamy and Shankar (2014)61 have made a research on, “Composition and 

contribution of current account to Indian economy” to evaluate the impact of elements of 

current account on Gross Domestic Product in India. They have taken Gross Domestic 

Product as dependent variable and Merchandise Exports, Imports, Invisibles as independent 

variables for the study. Secondary data have been collected for the period of 10 years 

annually from 2004 to 2014 and analysed by applying regression and correlation analysis. 

The results of the study have shown that current account has a significant impact on Gross 

domestic product. They have concluded that the current account balance of a nation plays a 

significant role in the economy growth. India has to enlargen the exports to meet the global 

demands and to find oil resources in the country to reduce the oil imports.  

Pushpalatha singh (2014)62 in her study on, “Performance of foreign trade in 

India in the post liberalisation era” has examined the trend, composition of foreign trade 

and analysed the role of foreign trade on economic growth in India. Secondary data have 

been used in the study. The annual observations for the variables, such as, Exports, 

Imports, GDP at factor cost at constant prices and economic openness covering the period 

of thirteen years from 1991-2013 have been collected. The statistical tools, such as, 

Growth rate percentage analysis, Augmented dickey fuller (ADF) test and Regression 

analysis have been applied in the study to examine the impact of foreign trade of the 

economic growth in India. The results of the study have revealed that exports and economic 

openness are positively related to economic growth while imports are negatively related to 

economic growth. She has concluded that there is increase in the growth rate of imports 

than the growth rate of exports. Among the composition of India’s trade, the major 

percentage share of exports is the manufactured goods respectively. The crude and 

petroleum products have contributed as major imported goods in India’s imports.  

 Sushil Kumar Rai and Purvashree Jhala (2015)63 have undertaken a study on, 

“Impact of exports and imports on growth rate of India: An empirical study” to find the 

cause and effect relationship of exports and imports of the Indian economy. The study 

has covered a period from 2000 to 2013. Secondary data have been collected from 

websites of United Nations Economic and Social Commission for Asia and Pacific.  



34 

The variables taken for the study are exports, imports and average growth rates of GDP. 

Unit root test has been applied to test the stationarity of the variables. The results of the 

study have shown that the variables are stationary. Pair wise granger causality test has 

been applied to test the causal relationship between the exports, imports and growth rate. 

The results of the study have shown that exports are affected by imports. Cointegration 

test have been applied to examine the long run relationship and it was found that 

variables are cointegrated in long run. Regression analysis has been applied in the study 

to analyse the impact of exports and imports on growth rate. The result of regression 

analysis has shown that exports and imports are statistically significant and found that 

growth rate is affected by imports than the exports.  

Abinaya and Jerinabi (2017)64 have made a study on, “Causal relationship 

between exchange rate and exports of SAARC nations” The purpose of the study is to 

examine the effect of exchange rate on export performance of SAARC nations using 

Granger causality test and Vector error correction model. The period of the study was 

from 2005 to 2015. Secondary data have been collected for exchange rate and value of 

exports of the SAARC countries, namely, Afghanistan, Bangladesh, Bhutan, Maldives, 

Nepal, Pakistan, Srilanka, India from International financial statistics, International 

monetary fund, Yahoo! finance and Oanda. The results of the study has revealed that 

there is no causal relationship exist between exchange rate and exports of SAARC 

countries, while the results of Vector error correction model has shown that there is a 

negative effect between exchange rate and exports.  

Khandare (2017)65 has conducted a study on, “The impact of exchange rate 

fluctuations on the economic growth of India”. He has found that there is an effect in the 

economic growth due to the exchange rate fluctuations. For the purpose of the study, 

secondary data have been collected from 1987 to 2014. The variables, such as, Exchange 

rate, Gross domestic product, Inflation rate, interest rate have been taken. Correlation and 

Multiple regression analysis have been applied to analyse the relationship between 

exchange rate fluctuations on economic growth. The results of the study revealed that 

Gross domestic product has a positive effect with the exchange rate fluctuation while the 

other variables, namely, inflation rate and interest rate have revealed that there is an 

inverse effect with the economic growth of Indian economy.  



35 

2.2 FOREIGN REVIEWS 

i) Review on Currencies 

Yasir Kamal and Hammad-UI-Haq et al. (2011)66 have made a study on, 

“Modelling the exchange rate volatility, using generalised autoregressive conditionally 

heteroscedastic (GARCH) type models: Evidence from Pakistan” They have examined 

the performance of GARCH models in forecasting the volatility of Pakistan foreign 

exchange market. Daily and monthly observations of exchange rate of Pakistan rupee 

against US dollar covering the period from January 2001 to December 2009 have been 

collected from International financial statistics online website. Unit root test has been 

applied to test the stationary of the data. GARCH models, such as, symmetric GARCH - 

M (1,1), and two asymmetric models EGARCH (1,1) and TGARCH (1,1) have been used 

to forecast the exchange rate volatility in Pakistan foreign exchange market. The results 

of the study have shown that EGARCH (1,1) model is the best fit model that explains the 

presence of asymmetric effect in the exchange rate volatility. They have concluded that 

the results of the study will be helpful in predicting the movements of exchange rate in 

future period.  

Suliman Zakaria and Suliman Abdalla (2012)67 in their research paper on, 

“Modelling exchange rate volatility using GARCH models: Empirical evidence from 

Arab countries” have analysed the volatility of daily returns of nineteen currencies of 

Arab countries. Daily observations covering a period from January 1, 2000 to November 

19, 2011 have been collected from financial web pages of Arab countries. Both 

asymmetric and symmetric GARCH models specifications have been used in the study to 

capture common facts, such as, volatility clustering and leverage effect in the exchange 

rate returns. The result of GARCH model has shown that only for ten currencies, the sum 

of coefficients have exceeded one, which implied that exchange rate volatility is high and 

whereas for seven currencies, it has resulted that there exist a moderate level of exchange 

rate volatility. The result of asymmetric model EGARCH (1,1) has shown that there exist 

a presence of leverage effect in all the currencies. They have concluded that the level of 

exchange rate volatility is increased due to the negative shocks of the economy than the 

positive shocks.  



36 

Milton Abdul Thorlie et al. (2014)68 have conducted a study on, “Modelling 

exchange rate volatility using asymmetric GARCH models (Evidence from Sierra 

Leone)”. They have forecasted the exchange rate returns of Sierra Leones against US 

dollar using volatility models, such as, ARMA, GJR-GARCH and asymmetric GARCH 

models with normal and non normal (student-t and skewed student-t) distributions. The 

monthly observations of exchange rate returns of Leone against US dollar for the period 

of January 2004 to December 2013 have been collected. The result of asymmetric model 

has shown that there is a presence of leverage effect in the returns of exchange rate. GJR-

GARCH model was the better forecasting model to forecast the Sierra Leone exchange 

rate volatility. They have suggested that the prediction of exchange rate volatility would 

provide better information to the investors and policy makers for decision making 

regarding investing strategies and also to enhance the exchange market stability in an 

emerging economy.  

ii) Reviews on Macroeconomic Determinants 

Golan Benita and Beni Lauterbach (2007)69 in their paper on, “Policy factors 

and exchange rate volatility: Panel Data versus a specific country analysis” have 

examined the policy implications and macroeconomic variables that affect the daily 

exchange rate volatility. A sample of daily exchange rate of US dollar against 43 

currencies has been selected for the study. They have used policy and macroeconomic 

variables, such as, exchange rate volatility, real interest rate, central bank intervention, 

exchange rate regimes, capital flows, domestic stock market volatility, gross domestic 

product, real and financial openness. Secondary data have been collected for the period 

1990 – 2001. Panel data analysis has been applied to study between countries and a 

specific country, namely Israel. The results of cross country analysis have shown that 

there exist a positive correlation between exchange rate volatility, interest rate and central 

bank intervention which reveals that the countries with high exchange rate volatility 

would have high interest rate and more central bank intervention. The results of specific 

country analysis have shown that the exchange rate volatility is negatively correlated with 

interest rate and central bank interventions.  



37 

Iqbal Mahmood and Major Ehsanullah (2010)70 undertook a study on 

“Exchange Rate Volatility & Macroeconomic Variables in Pakistan”. The purpose of the 

study was to analyse whether the exchange rate volatility affect the macroeconomic 

variables in Pakistan. The annual observations for the period from 1975 to 2005 have 

been used. As, GARCH model is the measure of volatility which has been applied to 

calculate the volatility of Pakistan real exchange rate. Unit root test and regression 

analysis have been applied to investigate whether the exchange rate fluctuations affect the 

macroeconomic variables. The volatility of real exchange rate has been taken as an 

independent variable and the variables, such as, foreign direct investment, gross domestic 

product and trade openness are as dependent variables. The results of the study have 

shown that exchange rate volatility have a positive impact on Gross Domestic Product 

and Growth rate, while it has negative impact on the variables trade openness and foreign 

direct investment. They have suggested that the policy makers of Pakistan should 

consider the exchange rate volatility in framing the trade policies to improve the level of 

trade and attract foreign inflows in to the country.  

Anca Elena Nucu (2011)71 in her study on, “The relationship between exchange 

rate and key macroeconomic indicators case study: Romania”. The purpose of the study 

was to analyse the macroeconomic variables on the exchange rate of Romania leu against 

Euro and US dollar for the period 2000 - 2010. Secondary data have been used in the 

study. Correlation and Regression analysis have been employed for exchange rate of 

Romania leu against Euro and US dollar, inflation rate, interest rate, Gross Domestic 

Product, money supply and balance of payments to examine the relationship between the 

variables. The results of the study have shown that exchange rate of Romania leu against 

Euro is directly related to inflation and interest rate, while it is inversely related to Gross 

Domestic Product and money supply. It is found that these are the variables that 

determine the exchange rate of Romania leu against Euro in Romania.  

Rasaq Akonji Danmola (2013)72 in his study on, “The impact of exchange rate 

volatility on the macroeconomic variables in Nigeria” elucidated the selected 

macroeconomic variables affecting the exchange rate volatility. Secondary data have been 

collected for the period 1980 - 2010 from the financial websites of Nigeria. The exchange 

rate of Nigeria has been taken as dependent variable and Gross Domestic Product, 



38 

Inflation rates, foreign direct investment and trade openness are taken as independent 

variables in the study. The Statistical tools, such as, Unit root test - Augmented dickey 

fuller test and Phillips Perron test, Granger Causality test, Correlation and Regression 

analysis have been employed in the study. The results of unit root test have shown that 

the selected variables are stationarity. Regression analysis of the study have shown that 

the exchange rate volatility has a positive influence on the variables Gross domestic 

product, foreign direct investment, trade openness and negatively related with inflation 

rates. It is found that these are the variables that cause the exchange rate volatility and 

make currency depreciation. He has suggested that Nigeria has to improve the export 

performance and thereby reducing the import of petroleum products through increase in 

the domestic production to maintain a favourable balance the trade.  

Kazi Mohammed Kamal Uddin and Azmal Ali Quosar (2013)73 in their study 

entitled on “Factors affecting the exchange rate of the Bangladesh: A co-integration 

approach” have evaluated the exchange rate of the Bangladesh in short run and long run. 

To examine the exchange rate movements, the exchange rate of Bangladesh Taka against 

US dollar (BDT/USD) and the factors relative money, foreign exchange reserve and total 

debts of Bangladesh have been considered. Political instability is taken as dummy 

variable to determine the exchange rate. A sample of monthly data for the period from 

January 1984 to April 2012 have been collected from International Financial Statistics, 

Handbook of statistics published by Bangladesh Bureau of statistics, Central Bank of 

Bangladesh and US Treasury direct website of Government of United States.  

The econometric tools, such as, Augmented Dickey Fuller test (ADF) and Autoregressive 

distributive lag (ARDL) approach have been applied to cointegrate the relationship 

between exchange rate and variables. The results of the study have revealed that the 

variables are found stationary at first difference and the variables relative money and debt 

service are found to be correlated and significant in determining the exchange rate. 

Political instability has a negative relationship with the exchange rate of Bangladesh. 

These are the factors that impact the currency depreciation in Bangladesh. They have 

concluded that the policy makers should focus on efficient policy measures considering 

the factors control of inflation and exchange rate stability.  



39 

Katarzyna Twarowska and Magdalena Kakol (2014)74 have made a research on 

“Analysis of factors affecting fluctuations in the exchange rate of Polish Zloty against 

Euro” in Poland. The aim of the study was to find out the factor, which has played an 

important role in affecting the exchange rate of Polish Zloty for the period from 2000 to 

2013. Regression analysis has been used for the six variables, such as, rate of economic 

growth, interest rate, inflation rate, Government deficit, balance of payment, level of 

foreign exchange market and speculative capital inflows to identify the factors that 

determine the exchange rate fluctuations. Secondary data have been used in the study. 

The study has shown that financial account balance, interest rate and inflation rate are the 

most important factor affecting exchange rate of Polish Zloty against Euro in Poland. 

They have concluded that effective monetary, fiscal policies and trade policies should be 

implemented in Poland exchange rate system in order to reduce high inflation rate and to 

enhance economic growth of the country.  

Wan Mohd Yaser Mohd Abdoh, Noor Hafizha Yusuf, Shaliza Azreen Mohd 

(2016)75 in their study on, “Macroeconomic factors that influence exchange rate 

fluctuation in ASEAN countries” have determined the macroeconomic factors affecting 

the exchange rate in ASEAN countries by using panel data analysis. The variables, 

namely, exports, inflation rate, interest rate have been taken for the study. Secondary data 

have been collected covering the period 2005 - 2014 from World Bank and IMF 

websites. They have applied random walk model and correlation for analysing the 

variables. The results of the study have shown that export is significant with the exchange 

rate. They have concluded that the policy makers should be aware of control of 

macroeconomic variables in the economy.  

iii) Reviews on Trade Balance 

Satis Chandra Devkota (2004)76 in his research paper on, “Impact of exchange 

rate change on foreign trade balance in Nepal”. The purpose of the study is to investigate 

the impact of exchange rate on trade and the trade policies that have been taken to reduce 

the trade deficit in Nepal. Secondary data have been collected for the variables exports, 

imports and trade balance and analysed by applying regression analysis. He has found 

that, historically Nepal has faced the scenario of trade deficit and exchange rate has 



40 

influenced the trade balance in Nepal. He has concluded that trade deficit has been 

reduced with the rise in exports than the imports and by adopting efficient tax 

administration in the economy.  

Abba Abubakar Shehu (2007)77 in his paper on, “Impact of foreign exchange 

volatility on Imports: A case of Nigerian foreign exchange market (1987-2008)” has 

analysed the impact of foreign exchange rate volatility on Nigerian imports under three 

foreign exchange market regime for a period of 22 years from 1987 - 2008. Daily 

observations have been collected from central bank of Nigerian statistical bulletins. 

Linear regression has been applied to analyse the relationship between exchange rate 

volatility and change in the value of imports under three foreign exchange market 

regimes (i. e) in second - tier foreign exchange market, autonomous foreign exchange 

market and Inter-bank foreign exchange market. The results of the study have shown that 

there was a positive and negative significant relationship exists between the exchange 

rate shocks and the value of imports under second-tier foreign exchange market and 

Inter-bank foreign exchange market respectively. He has concluded that flexible 

exchange rate mechanism can be adopted, so that the exchange rate can fluctuate and 

fixed exchange rate should be avoided to make convenience of the participants in the 

foreign exchange market.  

Ng Yuen-Ling and Har Wai-Mun and Tan Geoi-Mei (2008)78 have undertaken a 

study on, “Real exchange rate and trade balance relationship: An empirical study on 

Malaysia”. They have investigated the condition of Marshall- Lerner and J-curve exists 

between the long run and short run relationship of exchange rate on trade balance in 

Malaysia. The period of the study is from 1955 to 2006. Secondary data have been 

collected from International monetary fund. The econometric tools such as Unit root test, 

Co-integration test, Granger causality test, Vector error correction model and impulse 

response function has been employed to examine the effect of exchange rate on trade 

balance. After confirming the stationarity of the variables, the long run and short run 

relationship has been tested among the variables. It was found that there exist a long run 

relationship between exchange rate and trade balance follows the theory of Marshall- 

Lerner. There is no short run relationship exist between the variables, does not follow the  

J-curve effects implied that variables does not influence the trade deficit of Malaysia.  



41 

They have concluded that effective policy measures can be taken related to production of 

import goods and improving the domestic income of the country to reduce the trade deficit.  

Nusrate Aziz (2008)79 has made a study on, “The role of exchange rate in Trade 

balance: Empirics from Bangladesh”. He has focused on the impact of exchange rate on 

balance of trade in Bangladesh in long run and short run. Secondary data have been 

collected for the period from 1972 to 2005. The variables, such as, real effective 

exchange rate, nominal effective exchange rate, trade balance, domestic income and 

foreign income have been considered. He has taken 22 trading countries of Bangladesh to 

identify the effect of exchange rate on trade. The econometric tools, namely, unit root 

test, granger causality test, Johansen cointegration test, error correction method have been 

applied. The results of the study have shown that real effective exchange rate has a 

significant positive influence on Bangladeshi trade balance both in short and long run.  

Carmen Sandul and Nicolae Ghiba (2011)80 in their study on, “The relationship 

between exchange rate and exports in Romania using a vector autoregressive model” 

have analysed the influence of exchange rate on Romania exports. The quarterly 

observations have been collected for the period from 2003 – 2011 from financial websites 

of Romania. The variables, namely, export volume and exchange rate of EUR/RON were 

taken. Unit root test, Vector Autoregression and Impulse responsive function have been 

applied. The results of Unit root test have shown that the variables are stationary.  

The result of Vector Autoregression analysis have shown that at the first lag of the model 

there exist a positive relationship between exchange rate and exports, at the second lag 

there was a negative relationship between exchange rate and exports value, which 

implied that change in exchange rate has influenced the exports.  

Anli Suresh (2012)81 in his article on, “Exchange rate Impact on bilateral trade 

between India and China” has identified whether the appreciation of China currency 

affects the trade relationship between India and China. Secondary data have been used in 

the study. A quarterly observations for the period from 2001 - 2010 have been collected 

from Direction of trade statistics of the IMF and DGCI&S, Ministry of Commerce, 

Government of India and Reserve Bank of India websites. The variables, such as, 

exchange rate of Chinese Renminbi, value of bilateral trade of India and China and Gross 



42 

domestic product have been taken for the study. Unit root test has been applied to check 

the stationarity of the variables. The results have shown that the variables are stationary. 

To find the cointegration of the variables Johansen cointegration and Vector error 

correction test have been applied. The results have shown that the exchange rate has a 

cointegration relationship between exports and imports. She has concluded that the 

appreciation of exchange rate of Chinese Renminbi has affected the exports and imports 

of India and China.  

Mehmet Yaya and Xiaoxia Lu (2012)82 have made a study on, “The short-run 

relationship between real effective exchange rate and balance of trade in China”. They 

have analysed the short term relationship between exchange rate and the balance of trade 

in China by applying granger causality test. A monthly observations have been collected 

for the period of January 1994 – August 2009. The results have shown that in short run 

there exist a casual relationship between balance of trade and exchange rate. Transform 

function estimation has been applied to test whether the shock in balance of trade has 

affected the exchange rate. It is found that the trade performance affects the exchange 

rate in China.  

Ing. Lucie Tomanova (2013)83 in her study on, “Exchange rate volatility and 

foreign trade in CEEC” has examined the impact of exchange rate volatility on export 

performance of Central and Eastern European countries for a period from January 1999 

to March 2013. A sample of four Central and Eastern European countries – Czech 

Republic, Poland, Hungary, Slovakia and the variables binominal exchange rate of Euro 

and exports have been considered. Secondary data have been collected from European 

Central Bank and Eurostat Statistical databases. The econometric tools, namely, Unit toot 

test, Error Correction Model, Autoregressive Distributed Lag Model and GARCH models 

have been applied to analyse the data. It is revealed from the analysis that the variables 

are stationary and the exchange rate volatility has no significant relationship between 

export performance of Central and Eastern European countries.  

Mohammad Reza Lotfalipour and Bhre Bazargan (2014)84 in their study on 

“The impact of exchange rate volatility on trade balance of Iran” have evaluated the 

effect of real effective exchange rate volatility on balance of trade of Iran during the 



43 

period from 1993 - 2001 by applying GARCH models and Panel data approach.  

The variables, namely, export, import, trade balance and 11 trading partners of Iran 

(Germany, United Arab Emirates, Japan, France, Brazil, Korea, Italy, Russia, China, Britain 

and India) have been taken for the study. Secondary data have been collected from World 

Bank website, Islamic Republic of Iran’s Customs website and Chamber of Commerce. The 

results of the study have shown that the real effective exchange rate volatility has no 

significant effect on trade balance. They have found that the import has a significant effect on 

trade balance than exports. They have also suggested that the government should take policy 

implementations to enhance the production of import goods.  

Elif Guner Genc and Oksan Kibritci Artar (2014)85 have made a research on, 

“The effect of exchange rate on exports and imports of emerging countries”. They have 

focused on the relationship between exchange rate on exports and imports of selected 

countries. A sample of 22 counties has been taken. Secondary data have been collected 

for the period from 1985 to 2012 form World Bank. Panel cointegration model have been 

applied to test the long run relationship between exchange rate with exports and imports. 

The results of the study have revealed that there exist a cointegration relationship 

between exchange rate of exports and imports of five countries, namely, Bolivia, 

Cameron, Dominica, Gabon, and Mexican among the sample of 22 countries in long run.  

Khaled Alotaibi (2016)86 in his research titled on, “How exchange rate influence a 

country’s import and export” has conceptually discussed the currency fluctuation 

affecting the export and import. Appreciation and depreciation of the currency affect the 

business persons, government, imports and exports throughout the globe. The change in 

supply and demand of the currency affects the value of the currency. If the domestic 

country’s currency is stronger than the other nation currency the imported goods are 

found to be cheaper causes a trade deficit and there is a contra effect for the exports.  

He has concluded that currency fluctuations are influenced by several factors, namely, 

interest rate, inflation rate and capital gains. The currency crisis of foreign countries 

affects the domestic country’s currency as well.  

Ghulam Mujtaba Chaudhray and Shujahat Haider Hashmi. et al. (2016)87 have 

conducted a study on, Exchange Rate and Foreign Trade: A Comparative Study of Major 



44 

South Asian and South-East Asian Countries” have investigated the relationship between 

exchange rate with exports and imports of the countries for the period from 1979 to 2010. 

They have stated that exports and imports are the major contributors of the development 

of the economies. The variables such as, exchange rate, value of exports and imports of 

Pakistan, India, Bangladesh, Sri Lanka, Malaysia, Indonesia, Singapore and Thailand 

have been taken for the study. Secondary data have been collected from the database of 

World Bank. The econometric tools, such as, Autoregressive Distribution Lag model and 

Vector error correction model have been employed to study the short run and long run 

relationship between exchange rate and trade of countries. The results have shown that in 

long run, the relationship exist between exchange rate and exports of Pakistan, India, Sri 

Lanka, Bangladesh and Indonesia and also the relationship exists between exchange rate 

and imports of Sri Lanka. In short run relationship the variables are not related with the 

countries. In short run, the relationship exists between exchange rate with Sri Lanka and 

Bangladesh.  

Kedir Bekeru Genemo (2017)88 made a study on, “Effect of exchange rate on 

trade balance in major east African countries: Evidence from panel cointegration”.  

He has analysed whether the depreciation of the currency affects the trade balance of five 

east African countries, such as, Ethiopia, Kenya, Tanzania, Rwanda and Uganda in long 

run by using panel data analysis. Secondary data have been collected for the period from 

1990 to 2014 for the selected east African counties and also for the variables imports, 

exports, real gross domestic product, real effective exchange rate and real world income 

from United Nation Statistic Database, United Nation Conference on trade development 

database. Panel unit root test has been applied to test the stationarity of the variables.  

The researcher after confirming the stationarity of the variables has applied the panel 

cointegration and FMLOS panel approach for the cross sectional data to examine the 

cointegration between the variables in the long run. The results have shown that there is 

an inelastic relationship between exchange rate and trade balance, real domestic income 

is negatively related with trade balance in long run. He has concluded that currency 

depreciation worsens that trade balance and where as rise in income increases the 

purchasing power of the people that in turn will rise the imports and results in trade 



45 

deficit. He has suggested the policy makers not to devaluate the exchange rate and to 

select countries of trading partners with high income to increase the exports in long run.  

Hicham Sadok (2018) 89 has conducted a study on, “The effect of exchange rates 

on Trade Balance: An empirical study of Morocco”. He has examined whether the 

Marshall- Lerner condition and J-curve exist between the exchange rates and trade 

balance in Morocco. The variables, such as, exchange rates, exports and imports have 

been taken. Secondary data have been collected for the period from 2000 to 2015. 

Growth rate have been calculated for the exchange rate, exports and imports. The results 

of the study have shown that there is an impact of exchange rate fluctuations on trade.  

2.4 CONCLUSION 

There are a number of studies conducted by researchers discretely on the topics 

‘Movements of exchange rate’, ‘factors affecting the exchange rate movement’ and ‘Role 

of exchange rate in trade’ in developed and developing economies. There are barely few 

studies which have been taken up by the researchers by combining these aspects with the 

Indian currency in respect of the Indian economy. This has elucidated the need for 

studying the exchange rate volatility of Indian rupee against major currencies, 

macroeconomic determinants influencing the exchange rate and the impact of exchange 

rate fluctuations of currencies on trade balance in India. The research in different 

dimensions of foreign exchange market will guide and assist the policy makers and 

economists to take economic and monetary measures for the sustainable economic 

development and to maintain stability in the foreign exchange market. The research in 

this particular area is a phenomenal one among the academicians, fellow researchers, 

economists, policy makers and a common man and those who deal with the foreign 

exchange transactions.  

 

 

 

 

 



46 

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