Research Question
What is the effect of the real exchange rate and interest rate in the UK and US banking sectors during a financial crisis?
Research Hypotheses
Ho: The real exchange rate and interest rate has no effect in the UK and US banking sector during a financial crisis.
Ha: The real exchange rate and interest rate has an effect in the UK and US banking sector during a financial crisis.
Ho: There is no positive relationship between real exchange rate and interest rate.
Ha: There is a positive relationship between real exchange rate and interest rate.
Research Objectives
- To study the effects of real exchange rate and interest rate in the UK and US banking sector during a financial crisis.
- To study the relationship between real exchange rate and interest rate.
Literature Reviews
Chartareas, Kapetanio and Shin (2002)
This research was done in all the G7 countries. Regression analysis as well as unit-root test was used to analyze the data. Real exchange rate was the main variable that was measured. The research found evidence in support of the existence of “nonlinear mean-reversion” (Chartareas, Kapetanios, & Shin, 2002).
Lai (2011)
This research was done in UK and the participants included 10 financial institutions (Lai, 2011). Correlation analysis was used to analyze the data. The variable was interest rate. The research found that lenders are likely to charge high interest rates in order to protect themselves from the effects of financial crisis.
Sollis (2008)
This research was done in the United States of America. The unit-root test was used to analyze the data. The variable was real exchange rate. The research found that the “US dollar real exchange rates are nonlinear mean reverting processes” (Sollis, 2008) which are also characterized by structural changes.
Esaka (2010)
This research was done in 84 countries which included US and UK. The data was analyzed through correlation analysis. The variable was exchange rate. The research found that a fixed exchange rate can help in avoiding a currency crisis (Esaka, 2010).
Berkman (2010)
This research was done in US (Berkman, 2010). Regression analysis was used to analyze the data. The variable was liquidity and interest rate. The research found that cross listed companies benefits from favorable exchange rates and high interests in the overseas markets. This translates into high liquidity in the economy.
Johnson (2009)
This research was done in US. The data was analyzed using correlation analysis. The variables were exchange rate and interest rates. The research found that there is a positive relationship between interest rate and exchange rate (Johnson G. , 2009).
Unde and Heimshoff (2009)
This research was done in UK and the rest of Europe. The data was analyzed through time series analysis. The variable was exchange rate. The research found that the exchange rate fluctuates regularly and this impacts negatively on investments especially during a financial crisis (Heimshoff & Unde, 2009).
Hadiwibowo (2011)
This research was done in US and Europe. Regression analysis was used to analyze the data. The variable was interest rate parity. The research found that differences in interest rate levels among countries are responsible for capital outflow (Hadiwibowo, 2011).
Coriceli and Jazbec (2004)
This research was done in the European countries. Regression and correlation analyses were used to analyze the data. The real exchange rate was the main variable. The research found that “real exchange rate in transition economies is affected by the adverse initial conditions and structural reforms in the first 5 years of the transition period” (Coriceli & Jazbec, 2004).
Koedijk, Kool and Nissen (1998)
This research was done in UK, Western Europe and Asia. The method that was used to analyze the data was correlation analysis. Interest rate was the main variable. The research found that it is necessary to “incorporate monetary uncertainty that is represented by a proxy of the conditional variance of money growth in order to explain shifts in the interest rate” (Koedijk, Kool, & Nissen, 1998).
Methodology
This research aims at investigating the roles of real exchange rate and interest rate in the US and UK banking sectors during a financial crisis. It also aims at studying the relationship between real exchange rate and interest rate. Due to the wide scope of the investigation, several econometric models will be used to analyze the relationship between the variables that have been mentioned above. The study will be conducted in the UK and US banking sectors. Random selection will be used to recruit the participating firms in order to avoid bias (Harrell & Bradly, 2009). Correlation analysis will be used to study the variables (Johnson & Gowi, 2009).
Regression and correlation analysis will be used to investigate the relationship between real exchange rate and interest rate in the UK and US financial markets. The “GARCH regression model” (Attwood, 2000) will be used for this analysis. This will be done using time series data that will be collected from financial institutions in the two countries. The sample size will be informed by the available financial resources (Ardilly, 2006). All regions will be represented in order to enhance accuracy (Isaksson, 2000).
The general relationship between interest rate and real exchange rate can be expressed as follows.
Ef = α + βi + ε.
Where Ef is the real exchange rate between UK and US, α is the initial exchange rate, β is the percentage increase in interest rate while ε represents other factors that affect the level of real exchange rate between UK and US during the financial crisis. The expression shows that the value of the exchange rate will increase if the interest rate increases (Saville & Wood, 1991). The co-integration between real exchange rate and the interest rate will be tested using the Engle Granger co-integration tests. If co-integration is found to exist between real exchange rate and the interest rate, the parameters of the relationship will be estimated. Thus Johansen co-integration tests will be used to estimate the values of α and β as shown in the above expression.
The value of real exchange rate and interest rate changes over time. Thus the relationship between real exchange rate and interest rate will be investigated at a particular time (t) (Freud & Wilson, 2003). Consequently, co-integration and causality analysis will be used to analyze the relationship between interest rate and the real exchange rate between UK and US during the financial crisis. The Granger causality tests will be used to test if the interest rate can provide statistically significant information for predicting the real exchange rate. The relationship between these variables can be derived as follows.
Model A
The relationship between interest rate and real exchange rate can be expressed as follows.
(1+ ih)
Ef = – 1
(1+if)
Ef represents the real exchange rate between UK and US, ih is the interest rate at home (US) while if is the interest rate in the foreign country (UK). This shows that the value of the UK currency will be positive (appreciate) if the interest rate in US is higher than in UK (Coriceli & Jazbec, 2004).
Model B
The value of Ef can be derived as follows.
St+1 – St
Ef = St
Where St+1 is the real exchange rate between US and UK at time (t+1) while St is the value of US dollar against the UK pound. Thus the relationship between the two variables is as follows.
Model C
St+1 – St (iht –ift) = St (1+ ift)
Where St+1 is the exchange rate between US and UK at time (t+1), St is the value of US’s dollar against UK’s pound, iht is US’s interest rate at time (t), ift is UK’s interest rate at time (t). This relationship shows that the UK currency will appreciate if the interest rate in US is higher than in UK (Baltagi, 2002).
“Time series data will be used in this analysis” (Freud & Wilson, 2003). ANOVAs, Chi squares and means will be used to analyze the data (Pratt & Loizos, 2009). The findings will be expressed in the form of a report (Ken, 2009). Statistical tools such as charts and graphs will also be used to express the findings (Grawley, 2009).
References
Ardilly, P. (2006). sampling methods. London: Springer.
Attwood, G. (2000). Statistics. Heineman : London.
Baltagi, B. (2002). Econometrics. London: Springer.
Berkman, H. (2010). Domestic liquidity and cross-listing in the USA. Journal of Banking and Finace, vol. 34, (6) , 1139-1151.
Chartareas, G., Kapetanios, G., & Shin, Y. (2002). Nonlinear mean reversion in real exchange rates. Economics Letters, vol. 77 (3) , 411-417.
Coriceli, f., & Jazbec, B. (2004). Real exchange rates dynamics. Stractural Change and Economic Dynamics, vol. 15 (1) , 83-100.
Esaka, T. (2010). De facto exchange rate regiems and currencey crisis. Journal of banking and Finace, vol. 34 (6) , 1109-1128.
Freud, R., & Wilson, W. (2003). Statistical methods. London: Academic Press.
Grawley, M. (2009). Statistics: an introduction using R. New York: John Wiley and Sons.
Hadiwibowo, Y. (2011). Uncovered interest parity and monetory policy freedom in countries with the highest degree of financial openess. International Journal of Economics and Finance, vol. 3 (1) , 389-430.
Harrell, M., & Bradly, M. (2009). data collection methods. RAND : New York.
Heimshoff, P., & Unde, A. (2009). Consololidation and financial stability in Europe: emperical evidence. Journal of Banking and Finanace, vol. 33, (7) , 1299-1311.
Isaksson, M. (2000). sampling methods. Frankfurt: Nordisk.
Johnson, G. (2009). Interactions of US interest rate, bank loans and foreign exchange rate between USand Japan. Journal of International Finanace and Economics, vol. 23 (1) , 401-413.
Johnson, R., & Gowi, B. (2009). Statsitics: principles and methods. New York: John Wiley and Sons.
Ken, B. (2009). Business statistics. New York: McGraw-Hill.
Koedijk, K., Kool, C., & Nissen, F. (1998). Relationship between inflation and interest rate. Journal of Emperical Finance, vol. 5 (3) , 241-261.
Lai, K.-W. (2011). The cost of dept when all equity firms raise finanace. Journal of Banking and Finance, vol. 5 (2) , 100-147.
Pratt, B., & Loizos, P. (2009). Choosing research methods. London: Oxfam.
Saville, D., & Wood, G. (1991). Statistical methods. New York: Springer.
Sollis, R. (2008). US dollar real exchange rate: nonlinearity revisited. Journal of International Money and Finance, vol. 27 (4) , 516-528.