The Impact Of Interest Rate On Domestic Investment

PRESENTATION AND ANALYSIS OF RESULTS

4.1 Unit Root Test

In a research involving the use of time series data, it is ideal to carry out stationarity tests on the series to be used. This is justified on the grounds that data not found stationary have the tendency of yielding spurious regression results and thus misleading policy projections. Below is the variables made stationary with their corresponding order of integration.

Table 4.1: Unit Root Test

Source: E-views Computation.

The table above shows that investment is stationary at level form while interest rate, inflation and money supply are all stationary at first difference. This further reveals that investment has a constant mean, mode and other statistical properties at order zero while interest rate, inflation and money supply has a constant mean, mode and other statistical properties at order one. 

4.2 Cointegration Test

The Cointegration using the Engel-Granger technique was adopted to evaluate if there exists a long run relationship among the variables. The summary is displayed in table 4.2 while the main output is displayed in the appendix I.

Table 4.2: Cointegration Result

Source: Cointegration Result in Appendix I

This essence of carrying out a cointegration test is to evaluate the long-run relationship status of the variables under analysis. The test was carried out using the Engel-Granger Approach. It can be seen that in absolute terms, the ADF statistic is less that the critical value at 5%. Hence, there exists no long-run relationship among the variable under investigation. 

4.3 Regression Analysis

A regression analysis was conducted on interest rate against investment. The summary of the regression is displayed in table 4.3 below while the main output is deposited in appendix I.
Table 4.3: Regression Table

Dependent Variable: Domestic Investment

Method of Analysis: Regression Analysis

Time Scope: 1980-2016

F-statistics = 1.960880

Durbin-Watson = 0.751843

4.3.1 Coefficient Interpretation of the Variables

It can be clearly seen from table 4.3 above that the coefficient of interest rate yielded a negative value. The negative value implies that on the average, interest rate contributes negatively to investment in Nigeria. It entails that a 1% increase in interest rate will lead to a -0.51053 decrease in investment and vice versa. This entails that there exists a negative relationship between interest rate and investment. This conforms to economic a priori expectation because an increase in interest rate make borrowing costly and hence investment is reduced and vice-versa.

The result also shows that inflation yielded a positive coefficient valued at 0.002142. This implies that there exists a positive relationship between inflation and investment in Nigeria. Hence, a 1% increase in inflation will increase investment by 0.002142 naira. This conforms to economic a priori expectation because inflation means increase in price and investors will be propelled to invest more to take advantage of the high prices to maximize more profit and when inflation is low, investment will also reduce in accordance.  

Finally, money supply coefficient yielded a positive value at the magnitude of 0.017821. This implies that money supply increased by 1% will lead to an increase in investment by 0.017821 naira. This conforms to economic a priori expectation because increase money supply introduces liquidity in the economy and hence increases investment through the simple multiplier effect and vice-versa.  

4.3.2 Coefficient of Determination (R-Squared, R2)

Based on the regression analysis in table 4.3, the R2  which measures the goodness of fit yielded 0.551292. This implies that the explanatory power of the independent variables is approximately 55%. It further shows that the variation in the dependent variable is explained by the independent at 55%. This is reasonably above average and it shows that variables outside the model influence the dependent variable at 45%.  

4.3.3 Autocorrelation Test

The autocorrelation test with the instrumentality of Durbin-Watson is used to ascertain if the error terms are serially correlated. The Durbin-Watson statistic yielded a value of 0.751843. This value which is absolutely less than two implies that there exists a positive serial correlation in the model. 

4.4 Statistical Test of Significance

The table below is a summary display of the computed and tabulated values of t and f statistics.

Table 4.4

4.5 Test of Hypotheses

Hypothesis One

Ho: Interest rate has no significant impact on domestic investment in Nigeria.

Decision: Based on the results in table 4.4, it can be seen that the computed t-statistics for interest rate is greater than its tabulated value. Hence, we reject the guiding null hypothesis and accept its alternative. Hence, interest rate has significant impact on domestic investment in Nigeria.

Hypothesis Two

Ho: Inflation has no significant impact on domestic investment in Nigeria

Decision: Based on the results in table 4.4, it can be seen that the computed t-statistics for inflation is less than its tabulated value. Hence, we accept the guiding null hypothesis. Hence; inflation has no significant impact on domestic investment in Nigeria.

Hypothesis Three

Ho: Money supply has no significant impact on domestic investment in Nigeria

Decision: Based on the results in table 4.4, it can be seen that the computed t-statistics for money supply is less than its tabulated value. Hence, we accept the guiding null hypothesis. Hence; money supply has no significant impact on domestic investment in Nigeria.

4.6 Implications of the Results

The main finding of the research is that interest rate has a significant but negative relationship and impact on investment for the years under analysis. This implies that an increase in interest rate leads to a significant decrease in investment. The implication of this is that investment can be enhanced in Nigeria through an optimal decrease in interest rate.