Published: Last Edited:

This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

How does LIBOR-TBill spread affect the economy?

Recently the financial sector of the UK economy was hit by billions of pounds of write downs and losses which came about from subprime mortgages. These were mortgages that were ordered at a teaser rate to not very wealthy individuals in America and when they were taken out the banks would securitize these loans in what was called a collateral debt obligation and sell these products on. The purpose was to remove the loan from the books so they could loan more amounts but still received money from the sale of the CDO?s. The problem that arose was that many international banks were purchasing these securitised products including many leading UK Banks. When rates on the mortgages in America went up people began to default on these loans and this was the start of what was known as the credit crisis of 2007.

What does this have to do with LIBOR-TBill spread? Well LIBOR stands of the London Interbank Offered Rate and is the rate at which banks borrow unsecured funds from other banks. The rate that is offered and not the bid rate is the lowest perceived rate that a bank could go into the money markets and obtain funding for a maturity from overnight to 12 months. LIBOR is important to the economy because it has a fundamental effect on how many rates are calculated, it is used in calculations of mortgages and credit default swaps which is a form of insurance against default. It also has a much greater impact on the economy as interest rates can lead to changes in output LIBOR can lead to changes in the inflation rate and unemployment rate in the long run

When LIBOR is compared to a UK Treasury bill of the same period we get a spread. The spread is the amount of risk of holding LIBOR compared to a Treasury bill. The Treasury bill is considered to be riskless as the only risk involved is that the government is unable to meet its payment obligations. The risk premium which is the LIBOR-TBill spread is a measure of credit risk. There are many forms of credit risk the two main ones associated with LIBOR and Treasury bills are counterparty risk and sovereign risk.

Counterparty risk is the risk associated with two parties to a contract when they both agree on the contract the risk is that one of them will not fulfil the obligation. Sovereign risk is the risk associated with the government?s ability to pay on its obligations. This in recent times has become increasingly important as the collapse of Greece and Dubai to pay its obligations has led many investors to be more cautious and there are at present concerns about the UK?s ability to meet its obligations. However for the purpose of this dissertation we shall look at sovereign risk as negligible.

There are many implications of a wide and narrow spread. Having a wide spread indicates that banks are reluctant to lend to each other, this has consequences on the cost of finance which increases and thus by the law of supply and demand we can observe a reduction in the amount of finance being used. A narrow spread on the other hand means that banks are lending to each other and that there is little counterparty risk.

Another way we can look at the risk premium is by looking at the term structure of interest rates. This yield curve plots interest rates relative to maturities of Treasury bill. What we expect to find is that as maturity increases the interest on that increase this is because of the increased uncertainty of the future and therefore a greater rate of return is needed. When we compare a LIBOR yield curve to a Treasury bill yield curve we see there is a difference the LIBOR rate is greater than the T-Bill rate. This difference is called the risk premium so is the measure of risk of holding a LIBOR rate compared to a riskless TBill rate.


How does LIBOR-TBill spread affect the economy?

By looking at the 1st questions above we can greater our understanding of how the economy is affected by a wide/narrow LIBOR-TBill spread. To do this we shall use the 3 month figures for both the LIBOR and Treasury bill as this is a measure of a medium term and gives us a good indication of what will happen in the future.

The six variables I will use as a measure of the economy and what LIBOR-TBill spread may have an effect on are:

Equity Markets

We shall look at the equity prices because it is so important to the economy. A stock market according to some?. Is supposed to be informationally efficient therefore security prices adjust to arrival of new information rapidly this is also known as the efficient market hypothesis. By looking at asset prices in relation to the LIBOR-TBill spread what should happened is that as asset prices increase the spread should be narrow. This negative effect on spread can happened for a number of reasons one of them being that a rise in equity prices can imply that the risk premium in the market is lower due to greater confidence.

Retail Sales Index

The Retail Sales Index (RSI) is a ?Monthly measurement of all goods sold by retailers based on a sampling of retail stores of different types and sizes.? It is important to note that this figure represents less than half of total consumption. By looking at this figure we can gauge consumer confidence which is important in the economy because if people are not confident then they will not spend and thus begins a cycle which ultimately leads to unemployment and lower national output. By regressing on the LIBOR-TBill spread the result should be that a high RSI should have a negative effect on spread meaning that the narrow spread indicates increased spending by consumers.

Composite Leading Indicators

'The Composite Leading Indicators (CLI) are made up of 10 economic components whose changes tend to follow changes in the overall economy' Included in these components are .... By looking at the figure investors can form expectations about what is going to happen in the future. This aids in making informed future decisions. A high figure indicates.............

Housing Market Indicator (HMI): Properties in possession %

Looking at the number of properties in possession can help us to understand the implications of changes in the economic climate. A rise in the percentage of possessions can be caused by a number of variables, one of them being a rise in interest rates this would indicate an increase in the cost of borrowing which would mean that more people may struggle to pay the mortgage. Another reason why properties in possession may go up is that small sole traders and partnerships have unlimited liability therefore if there business becomes insolvent due to a lack of credit facilities from the bank than the risk to the property increase dramatically. A wide LIBOR-TBill spread is likely to indicate a rise in the properties in possession due to the fact that it is more expensive to obtain the credit.


Inflation is a price rise that can come about from a number of things. The main thing we want to look at is inflation that was bought about from the cash injection that the government made in order to try and prevent an absolute shutdown the banking system. Whether this helped is a matter of opinion but by injecting this cash into the system it has meant that prices of goods have started to rise. RSI is one measure of inflation but the main measure we shall look at is the CPI which is the cost of a basket of goods. A wide LIBOR-TBill spread should cause inflation to rise as governments try to inject cash into the system.

Unemployment: Claimant count

Unemployment is a key measure of the economy. Unemployment is thought of as countercyclical that is as the economy gets worst the unemployment rate should raise. A high unemployment number can lead to all sorts of problems in the economy for example by having many people unemployed the amount of money the government gives in benefits is likely to increase thus meaning less money to spend elsewhere and also it would be a decrease in taxable revenue thus leading to an inefficient output level as production capacity of the economy would likely decrease. By looking at the LIBOR-TBILL spread against the unemployment figure we hope to find that an increase in spread leads to an increase in the unemployment rate which would indicate that as risk in the interbank markets increase it would eventually lead to the economy.

Number of Loans Approved: Total

The number of loans is a very important variable in measuring the health of the banking system after all that is what banks are fundamentally meant to do. A lack of loans available can lead to collapse of small businesses which can affect the local economy as well as the wider economy. As well as this it would be harder to get mortgages for new homebuyers as the price of interest will be higher which would indicate higher repayments. By looking at the LIBOR-TBill spread we should observe that a higher spread would lead to a fall in the number of loans approved.

BOE Liquidity Index

Implied Option Volatility

Problems which I will face in running the regression will be a problem of ?Cause and Effect? also known as causality. Causality is caused by a relationship between variables and the problem is whether one causes the other or is caused by the other. Consider the subject of this dissertation where LIBOR-TBill spread is regressed against 6 economic variables. The question here is whether the LIBOR-TBill spread is influencing the economic variables or is being influenced by the variables. There are three types of causality the first one is simply where the is A occurs in correlation with B. the next one is termed reverse causation and is where B affects A an example of this is that more firemen fighting a fire the bigger the fire will be this implies that firemen cause fire. This is not the case in fact the firemen as dispatched according to the severity of the fire and therefore fire is the cause of the firemen. The last type is a common casual variable this is where C affects both B and A. An example of this is as the sales of ice cream increase the rate of drowning deaths also increase rapidly therefore ice cream causes drowning. One thing that is not included is the time of year, summer time when more swimming takes place. This means that there is a third variable involved which affects the relationship. From these 3 types of causality we come to the conclusion that correlation does not imply causation which is an important conclusion with regards to the dissertation. This is because there may be correlation between equity prices and LIBOR-TBill spread but we cannot conclude that an increase in equity prices causes a wider/narrow LIBOR-TBill spread this could just be down to coincidence.

A serious problem that will be faced when estimating the regression will be that of endogeneity, this is where there is correlation between the independent variable and the error term. An example will be in stock prices as well as a possible spread affect there will be other things that affect the stock prices such as interest rates. As we only want to look at how spread is affected by the stock market than we have to find a way to deal with endogeneity. There are two ways to deal with this the first would be to find and use a proxy variable which would best represent most of the error term or there is an instrumental variable. This allows a causal relationship to be formed for which we have already discussed the issues.

If we have an instrument a consistent estimate may still be obtained. The instrument is a variable that does not belong in the regression but is correlated with the explanatory variable. To use an instrumental variable there are two main requirements:

The instrument must correlate with the explanatory variable

It cannot be correlated with the error term

To calculate an instrumental variable we can use two stage least squares (2SLS). This is used because the dependent variable?s error term is correlated with the independent. The first stage is that a new variable is created using an instrumental variable. The second stage model estimated values from the first stage are placed as actual values of the problematic predictors.

Omission variable bias will also be a problem this is where in the regression we will have to exclude other important variables which may have an influence on the LIBOR-TBill spread. This exclusion will cause our regression to be less precise so in order to deal with this we will have to try to include the most important determinates of the LIBOR-TBill spread and exclude the less important ones. Also we shall be running a number of regressions with different variables being omitted as to see if it improves the accuracy................

The 1st regression equation will look like:

y_t= ?_t+ ?_1 X_t^1+ ?_2 X_t^2+?_3 X_t^3+ ?_4 X_t^4+ ?_5 X_t^5+ ?_6 X_t^6+e_t

In this regression all of the variables will be included and will be subject to the OLS conditions of BLUE...... This may be a problem as the data set can only be regressed from 1997 as the X_t^6 variable only begins than. The next stage regression will be run with the X_t^6 being omitted as to further the data length and hopefully see a change in the accuracy. The regression will look like this:

y_t= ?_t+ ?_1 X_t^1+ ?_2 X_t^2+?_3 X_t^3+ ?_4 X_t^4+ ?_5 X_t^5+ e_t

As well as looking at the independent variables (RHS) it would be interesting to see how a longer and shorter period change in risk premium would affect the regression. To do this we shall use LIBOR 12 months - Treasury Bill 12 months as a measure of a more longer term. For the short term looking at LIBOR 1 month and Treasury Bill 1 month.