The Relationship between Investment and Interest Rates - Research Proposal Example

inter Abstract According to economic scholars investment is a source of employment, monetary and fiscal policy makers have their decisions based on the prevailing inflation rates, unemployment rates and investment level, unemployment and inflations are the major concerns to policy makers and one way to reduce investment is through increase in investment. The multiplier effect and the accelerator theory depict the relationship between investment and employment. Increasing investment will increase employment and for this reason this paper is dedicated to check the validity of the multiplier effect concentrating on interest rates and investment relationship. The data is from the UK economy from 1990 to 2007 and from the results an increase in interest rates will reduce investment and a reduction in interest rates will increase investment. Table of Contents I. Introduction II. Theoretical concepts III. Literature reviews IV. Data V. Methodology VI. Results and discussion VII. Conclusion VIII. References Introduction This paper focuses on the relationship between investment and interest rates, investments are important in the economy and in this relationship it is expected that when the interest rates rise then the level of investment is low, this is because interest rates are the cost of borrowed funds and if this cost rises then there is low investment in an economy. An increase in Investment has various advantages associated, these advantages include an increase in the level of employment, economic growth and smooth running of the economy, investment is also considered when determining the level of GDP and income level in the economy and therefore an increase will lead to the realisation of all these advantages. the paper discusses this relationship through regression of data from the UK economy from the year 1990 to 2007 which contains interest rates and investment levels, data used is retrieved from the UK economy statistic website which give us the series of data over time, this data helps us to analyse the investment interest rate relationship as discussed in theory. Theoretical concept According to the neoclassical theory on investment an increase the interest rate will reduce investment through a raise in the cost of capital requirement of investment. In this paper investment has an inverse relationship to the interest rate. to the multiplier effect an increase in investment will increase employment and income levels, for this reason therefore investment is an important factor in determination of employment and unemployment levels in an economy. Keynes also explain the relationship between investment and interest rates, Keynes theory states that the level of investment depends on interest rates and when rates increase then the level of investment decline. For this reason therefore we will specify our model using this theoretical background whereby we will consider investment as the dependent variable and that interest rates are the independent variable, we expect that the model will have a negative slope meaning that as interests increase then the level of investment declines. However this study is based on assumptions that only investment determines the level of investment, this is because there are other factors that affect the level of investment apart from interest rates. Data: The data was collected from reliable website including the UK government statistics website where data regarding investment was collected, investment data was also collected and the trends of the data was first determined to check for consistence of the data with theory, the following charts summarise the data collected: The chart represents investment trend over the years from 1990 to 2007, there has been an increase in the level of investment, and the line chart represents a gradual increase in the level of investment. The chart below represents the trend on interest rates. the chart shows interest rates over the years showing periods of high and low interest rates, however the graph also portrays a decline in the rates of interest over the years from 1990, the 1990 interest rates were 14% and over the years the interest rates have gradually declined to 5% in the recent periods. From the data therefore we can conclude that there has been a decline in the level of interest rates over the years and also an increase in the level of investment in the economy from the year 1990. Methodology Data was retrieved from the UK statistics website which included time series data for our two variables, the mean, median, mode, variance, standard error and regression was determined for the purpose of statistical analysis. From the discussion of theory regarding investment and interest rates we state the level of investment asd the dependent variable and the interest rates ads the independent variable, for this reason therefore the estimated model will be Y = a + bX where Y is investment and X is interest rates. Results and discussion The correlations coefficient for the two sets of data is -0.582093849, this means that there is a moderate negative relationship between the interest rates and investment level, this shows that an increase in one variable then the other variable is declining. Correlations coefficient closer to one means that there is a very strong relationship between variables; However the value in our case shows moderate strength in the relationship. From the data retrieved there were various statistical inferences that could be undertaken, the results are discussed below: Investment data: From the investment data the mean for the 18 years was 100,299.83, the median for this data was 108,136.5, the variance was 715500523.8 while the standard deviation was 26748.84. This means that the data deviates 26748 from the mean. The minimum value for the investment data is 64648 while the maximum value is 142801 meaning that the range for this data is 78153. This data may be negatively skewed due to the fact that the median is greater than the mean, this means that it is negatively skewed and therefore the data takes the following shape. Interest rate data: The mean for the interest rate data is 6.42% while the mode and median are 5.75% and 5.75% respectively, due to the fact that mean is greater than the mode and median the data therefore is positively skewed, meaning that the data takes the following form: The minimum value in the interest rate data is 3.67% while the maximum amount is 14.0% meaning therefore that the range of this data is 10.33. The variance in this case is 0.0695% while the standard deviation is 2.637. This means that the data deviate 2.637 units from the mean Regression analysis: Regression analysis involves first the statement of the model according to the theory or hypothesis, this is then followed by the collection of data and in this case we collect time series data which will help us formulate our model, this model will then be used for forecasting and therefore hypothesis tests should be undertaken to check the statistical significance of the estimated coefficients. From the estimation of the model Y = a + bX the following were the results, A = 138228.4374 and b = -590430.5747. From our discussion of the theory it was evident that investment and interest rates have an inverse relationship. Therefore from our estimation the model was Y = 138228.4374 - 590430.5747 X. to expound on this model it is evident that if we hold all other factors constant and the level of interest rate is zero then the level of investment will be 138228.4374 which is the autonomous value in our model, if we hold all other factors constant and increase the level of interest by one unit then the level of investment will drop by 590430.5747 units, this is also the value of the slope coefficient. This model can be represented in a chart as follows: This chart shows that as the level of interest rates increase then the level of investment decreases, from the chart also it is evident that our R squared value is equal to 0.3388; this means that 33.88% variations in investment are described by the independent variable. Statistical significance of the estimated coefficients: The standard error for the autonomous value a is 14260.71757 and for the slope coefficient b the standard error is 206191.7761, given their estimated value we can dtermeine the Z value for both coefficients as follows, coefficient Z calculated Z critical 95% a 9.692951053 b -2.86350206 Having stated our null hypothesis for the constant as H0: a = 0 Alternative hypothesis: Ha: a ≠ 0 Given that our calculated value exceed the critical value at 95% for the constant a then we reject the null hypothesis that the constant is zero, for this reason therefore we conclude that the constant is statistically significant. For the the slope: null hypothesis H0: b = 0 Alternative hypothesis: Ha: b ≠ 0 Due to the fact that the critical value at 95% is less than the calculated value we reject the null hypothesis the slope is equal to zero, therefore the slope is statistically significant. Conclusions From our above discussion it is clear that the level interest rates will determine the level of investment, in this case therefore the estimated model was Y = 138228.4374 - 590430.5747 X meaning that y is the dependent variable which represents investment and x is the independent variable which is interest rates, from this model it is clear that the investment interest relation is an inverse relationship whereby when the policy makers increase interest rates this will discourage investors due to the increase in the cost of capital. Investment has its own advantages in an economy including provision of employment, increased economic growth and also the smooth running of an economy, for this reason therefore the policy makers have to be concerned with the effect of increase in interest rates on investment when making policies. Our study assumes that investment is only determined by interest rates, however there is need to formulate a model that considers other factors that determine investment; this would involve adding independent variables and this will reduce the disturbance term caused by the consideration of only one independent variable. There is also a need to undertake this study using a larger or different sample, this will help us to validate the conclusions of this study regarding the determinants of investment, the other samples should be consistent with our study which is supported by the theory and also data provided, we can therefore conclude that investment depends on the rate of interest rates that prevail in the economy. References Coddington A. (2003) Keynesian Economics: The Principles, Rout ledge publishers, New York Douglas G. (1967) Macro economic Theory, Macmillan publishers, New York Fender J.(1981) Understanding Keynes: An Analysis of the General Theory, Wiley publishers, New York Government Statistics UK (2008) Business investment time series data, retrieved on 8th April, available at http://www.statistics.gov.uk/StatBase/tsdataset.asp?vlnk=700&More=N&All=Y Interest rates (2008) UK interest rates, retrieved on 8th April, available at http://www.houseweb.co.uk/house/market/irfig.html William A (1991) Classical Economists and Economic Policy, University of Michigan press, Michigan Appendices: X Y mean annual interest rate total investment in economy Y2 X2 YX 1990 0.1400 75789 5743972521 0.0196 10610.46 1991 0.1175 69720 4860878400 0.01380625 8192.1 1992 0.0850 67084 4500263056 0.007225 5702.14 1993 0.0575 64648 4179363904 0.00330625 3717.26 1994 0.0575 67809 4598060481 0.00330625 3899.0175 1995 0.0663 73067 5338786489 0.00439569 4844.3421 1996 0.0600 80700 6512490000 0.0036 4842 1997 0.0675 88805 7886328025 0.00455625 5994.3375 1998 0.0694 105973 11230276729 0.00481636 7354.5262 1999 0.0542 110300 12166090000 0.00293764 5978.26 2000 0.0588 115194 13269657636 0.00345744 6773.4072 2001 0.0496 116971 13682214841 0.00246016 5801.7616 2002 0.0400 118331 14002225561 0.0016 4733.24 2003 0.0367 117167 13728105889 0.00134689 4300.0289 2004 0.0475 119928 14382725184 0.00225625 5696.58 2005 0.0450 138768 19256557824 0.002025 6244.56 2006 0.0488 132342 17514404964 0.00238144 6458.2896 2007 0.0550 142801 20392125601 0.003025 7854.055 TOTAL 1.1563 1805397 1.93245E+11 0.08610187 108996.3656 MEAN 0.0642 100299.8333 MODE 0.0575 MEDIAN 0.0575 108136.5000 VARIANCE 0.000695438 715500523.8 STANDARD DEVIATION 0.026371155 26748.84154 MIN 0.0367 64648.0000 MAX 0.1400 142801.0000 RANGE 0.1033 78153.0000 corrreltaiotn -0.582093849 N 18 ∑YX 108996.3656 ∑X2 0.08610187 ∑Y2 1.93245E+11 ∑X 1.1563 ∑Y 1805397 B -125645.9703 0.21280397 -590430.5747 A 138228.4374 Read More