Econometric analysis can be used to help explain the importance of certain factors on a dependent variable. In this project the dependent variable is the “demand for money in the UK between 1963-1989”. Although it is very difficult, if not impossible to find perfect econometric models, this project will attempt to explain the relationship between the demand for money and other various explanatory factors.
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The Economic Theory
Money is one of many forms of wealth. A simply economic explanation, using two of the more important forms of wealth, is that people have a choice between holding money and holding bonds. Money is used for everyday transactions and includes currency (coins and notes) and checkable deposits. Bonds will pay an interest rate but cannot be used for transactions, i.e. you cannot buy a cup of coffee with a bond. The interacting relationship between money and its substitutes (bonds being an example) can help explain the demand for money.
The measure of money in this project is the liquid money, M1. The demand for M1 will basically depend on the opportunity cost of not holding M1 money, i.e. saving it instead of spending it. The interest rate is, by definition, the opportunity cost of holding money, i.e. by keeping ï¿½20 in my pocket I am losing out on ï¿½20*the interest rate, which would be more, if only by a small margin. It is becoming clear, even only after scraping the surface of this project, that the interest rate is likely to be an important factor affecting the demand for money. Economic theory suggests that certain factors can influence the demand for money, theses will be included in econometric analysis but may not be included in the final model for various reasons that I shall come to later.
An obvious factor that affects the demand for money is consumer expenditure. If people want to buy more goods they need more money. During periods of high consumer spending, of which the main one is usually the Christmas period, people will cash in alternative forms of wealth, such as stocks and bonds, in exchange for money. This money is then used to pay for services and goods such as Christmas presents. Consumer expenditure is related to the level of disposable income available to households Whether consumers’ expenditure (ca), or Real personal disposable income of households (ia) is used in the model will be addressed when looking into the econometric model in the next section.
The cost of goods, i.e. rising levels of inflation, will also affect the demand for money. If goods become more expensive then people will need more money in order to buy what they need. Although this is the case in the form of “nominal” demand for money, the “real” demand for money is liable to remain the same, as the level of money holdings tends to rise at the same rate as the price level. Peoples demand for money will also depend on what has happened in the last year or two, perhaps longer in some cases. “Due to force of habit, people do not change their consumption habits immediately following a price decrease or an income increase, perhaps because the process of change involves some immediate disutility.”2
This theory can be applied to the project and there is now demand for at least one lagged variable, whether it is a lag of the dependent variable or one of the explanatory variables will be addressed later in this analysis, after having started with a basic model. The Econometric Model Using economic theory it is decided that the dependent variable will be ma-mp, which is a measurement of M1 money (which was addressed earlier), minus the “implicit price deflator for total final expenditure”. This is a measure of the “real” money, while if only M1 was used for the dependent variable, the “nominal” level of money would have been measured.
The interest rate, which has already been labelled a likely important factor in this analysis, will be measured using the RNET variable. The RLA variable was not used because it only measures the interest rate on deposits held for at least three months. It is interesting to note that the RLA and RNET values are identical up until the third quarter of 1984. The hardest decision is whether to use the ca (consumers’ expenditure) or ia (real personal disposable income) variable in the model. After careful deliberation it is decided that the ia variable will be used, as it will address what “proportion” of income is dedicated to money, which seems a more interesting analysis that simply the level of expenditure. If there is time, however, the ca variable will be looked at later. So finally analysis can start, with the basic model given below: ma-pat = B1 + B2 RNETt + B3 iat + ut
As mentioned above the use of lagged variables will be important in our regression analysis. The most obvious variable to lag is going to be ma-mp, suggesting that the level of money demanded this year, will be affected by the amount of money demanded last year. The ia variable may also be lagged to see if disposable income last year, affects this year’s demand for money. (Note: when regressing theses lagged variables one will have to be aware of the possibility of correlation and multicollinearity.) This note neatly brings this project straight on to the next important topic.
Data Issues and the Hypotheses to be Tested The data used is seasonally adjusted so there is no need to add dummy variable to represent different part of the year. Dummy variables could be used to distinguish between other external variables such as the type of government in power at the time but this would be an unnecessary complication. Because this is a “log-linear” model, the coefficients will be a measure of elasticity. The regression will cover the time period, i.e. from 1963_1 to 1989_2 (Note: 1983_3/4 will not be included due to incomplete data)