**4.4 Diagnostic and stability test results**

The results of both diagnostic and stability tests based on statistical estimations are presented in **Tables 6** and **7** and **Figure 1**, respectively.

The residuals are normally distributed, and there is no serial correlation. In the presence of heteroskedasticity, the null hypothesis is rejected (homoscedasticity), and the alternative is accepted.

The results of stability test are presented in **Table 7** and **Figure 1**, respectively.

Based on the summary of results presented in **Table 7**, the null hypothesis of Ramsey RESET test shows that the model is correctly specified. In tandem with the Ramsey RESET test, the stability test results reveal that after incorporating the CUSUM and CUSUM of squares tests, ARDL model was found to be stable throughout the period of study.


#### **Table 5.**

Additionally, in **Table 4** the coefficient of determination (R2

correlation.

**96**

**Table 4.**

*Estimated Long run results.*

the long-run equilibrium after a shock.

R-squared 0.733 Durbin-Watson stat 2.192 F-statistic 6.237

productivity of labour and the labour unrest.

**4.3 Causality test results**

**Critical value bounds**

**Table 3.** *Bound test results.*

The implication is that about 73% of variation in international investment decisions in South Africa is caused by variations in the explanatory

**Test statistic Value K** F-statistic 9.101 5

*Perspectives on Economic Development - Public Policy, Culture, and Economic Development*

**Significance (%) I0 Bound I1 Bound** 10 2.26 3.35 5 2.62 3.79 2.5 2.96 4.18 1 3.41 4.68

**Variable Coefficient Std. Error t-Statistic Prob.** IL 0.254 7.948 0.032 0.975 PL 0.086 14.345 0.006 0.995 LGFCF 0.049 12.837 0.004 0.997 INTR 0.026 0.376 0.069 0.945 DUMMY 11.921 3.452 3.453 0.002 C 161.554 91.932 1.757 0.091

variables. The Durbin-Watson statistics of 2.19 shows the absence of serial

strongly confirmed given that the coefficient of the error correction term

The short-run relationship analysis results in **Table 5** show that cointegration is

(1.351344) has a negative sign. In line with [38], it shows that any deviation from the long-run equilibrium is corrected at the rate 135% for each period to return to

Since cointegration has been established, the study proceeded with Granger causality test, and the pairwise Granger causality test results are presented at the Appendix section. It was established that there was no causality between income level and FDI and between interest rate and FDI. Similarly, productivity of labour does not Granger-cause FDI; however, the null hypothesis of granger causality could not be rejected between FDI and labour unrests. A bidirectional causality between them was found. Likewise, Granger causality was established between

) is 0.732920.

*Estimated short run analysis results.*


#### **Table 6.**

*Diagnostic tests results.*


**Table 7.** *Ramsey RESET test results.*

FDI does not Granger Cause PL 1.3819 0.265 InfInv does not Granger Cause FDI 39 0.461 0.635 FDI does not Granger Cause InfInv 0.256 0.776 Intr does not Granger Cause FDI 39 1.477 0.243 FDI does not Granger Cause Intr 0.446 0.644 LU does not Granger Cause FDI 39 0.414 0.6645 FDI does not Granger Cause LU 9.883 0.0004 PL does not Granger Cause IL 39 1.512 0.235 IL does not Granger Cause PL 3.347 0.047 InfInv does not Granger Cause IL 39 0.918 0.409 IL does not Granger Cause InfInv 0.513 0.603 Intr does not Granger Cause IL 39 0.597 0.556 IL does not Granger Cause Intr 1.743 0.190 LU does not Granger Cause IL 39 1.923 0.162 IL does not Granger Cause LU 2.543 0.094 InfInv does not Granger Cause PL 39 1.116 0.339 PL does not Granger Cause InfInv 9.164 0.001 Intr does not Granger Cause PL 39 6.003 0.006 PL does not Granger Cause Intr 3.472 0.043 LU does not Granger Cause PL 39 1.784 0.183 PL does not Granger Cause LU 1.221 0.308 Intr does not Granger Cause InfInv 39 5.156 0.011 InfInv does not Granger Cause Intr 1.114 0.339 LU does not Granger Cause InfInv 39 4.243 0.023 InfInv does not Granger Cause LU 1.274 0.293 LU does not Granger Cause Intr 39 0.168 0.846 Intr does not Granger Cause LU 1.563 0.224

*An Analysis of Drivers of International Investment Decisions in South Africa*

*DOI: http://dx.doi.org/10.5772/intechopen.88592*

**Author details**

**99**

Itumeleng Pleasure Mongale\* and Livhuwani Baloyi

provided the original work is properly cited.

Faculty of Management and Law, University of Limpopo, South Africa

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: itumeleng.mongale@ul.ac.za

**Figure 1.** *Stability test results.*

The plot of the cumulative sum of recursive residuals (CUSUM) and cumulative sum of squares recursive residuals (CUSUMQ ) of the model presented in **Figure 1** indicates stability in the coefficients over the sample period as they fall within the critical bounds indicated by the 5% significance parameters.

#### **5. Conclusions**

The study investigated drivers of international investment decisions in South Africa by means of time series secondary data from the South African Reserve Bank and Quantec EasyData. The bound testing autoregressive distribution lag approach and the Granger causality analysis were employed to achieve the aim of the study.

The long-run analysis revealed that all the regressors have a positive relationship with FDI, but they were not statistically significant with the exception of the dummy with the p-value of 0.0020 which means it is statistically significant. Whilst the outcomes of this study about a positive association between FDI and some of the regressors like labour productivity, interest rates and infrastructural investment seem to be in line with studies such as [39–41], respectively, the findings of a positive relationship between FDI and labour unrest seem to be in inconsistent with [42] who found that labour unrest has a negative impact on FDI. The presence of cointegration was confirmed by the short-run analysis which also confirmed that any deviation from the long-run equilibrium is corrected to return to the long-run equilibrium after a shock. On the other hand, the pairwise Granger causality test results showed bidirectional causality between FDI and labour unrests.

Empirical findings suggest that government should ensure stable macroeconomic policies. Likewise, policies which promote increase in labour productivity should be encouraged, and labour disputes that result into prolonged strike actions must be minimised; hence consideration of modifying labour laws and regulations is submitted.


#### **Appendices and nomenclature**


#### *An Analysis of Drivers of International Investment Decisions in South Africa DOI: http://dx.doi.org/10.5772/intechopen.88592*
