The Specific research questions that the paper addresses are as follows.
How manufacturing value added influences economic growth of a nation?
How share of FDI inflow affects economic growth of a nation?
Economic growth is measured as a percentage change in aggregate output as compared to the previous year. Economic growth of a nation depends on different factors (Tsoku et al. 2017). Of these factors particular interest of the paper is to evaluate the impact of manufacturing value added and foreign direct investment on economic growth.
The economic growth law as proposed by Kaldor suggests that there exists string positive relationship between growth of aggregate output or GDP and growth of manufacturing. The law states the direction of relationship as it runs from manufacturing growth to aggregate output. Manufacturing not only contributes to a larger portion of GDP but it also regarded as a main drivers of economic growth. The importance of manufacturing lies in two significant factors. Firstly, it produces a higher return for the nation. Secondly, the use of advanced technology in manufacturing lead to an increase in employment (Adugna 2014). A study based on 86 countries for the period ranging from 1970 to 2009 analyzed the relationship between growth of manufacturing export and economic growth. The author found manufacturing sector to be beneficial for economic growth. The study suggests a positive relation between manufacturing expansion and economic growth (Sheridan 2014).
Inflow of foreign fund is another crucial factor affecting economic growth. Economic growth of a nation depends on the growth in productive capacity which is determined from saving and investment of a nation. In an integrated world, foreign direct investment has become an important source of economic growth (Dornean and Oanea 2013). There are several linkages between economic growth and FDI. These include learning by doing, human capital, export, stability in macroeconomic environment and other financial development. Based upon these determinants FDI flows affects economic growth through three channels. These are direct transmission of capital through greenfield investment, indirect flow in form of ownership participation and spillover through technology (Clowes and Bilan 2014).
Hypothesis 1
Null Hypothesis: There exists no significant relationship between economic growth and manufacturing
Alternative Hypothesis: There exists a statistically significant relationship between economic growth and foreign direct investment
Hypothesis 2
Null Hypothesis: Foreign direct investment has no significant influence on economic growth of a nation.
Alternative Hypothesis: Foreign direct investment has a significant influence on economic growth of a nation.
In order to model the relationship between economic growth, manufacturing and foreign direct investment time series data are collected for different nations. A sample period ranging from 1996 to 2012 is taken into consideration. Apart from variables like economic growth, manufacturing and foreign investment other related variables like private credit, remittances, services, workforce participation, wages, inflation, inequality, income, control of corruption and stability. The relevant data are collected from Word Development Indicators and Word Governance Indicators.
The best way to establish a causal relation between two or more variables is to develop a multiple regression model. Multiple regression is a powerful statistical tool that is used for predicting a dependent variable based on its relationship with two or more variables (Chatterjee and Hadi 2015). The multiple regression model used in the paper is as follows
Dependent variable: Growth
Independent variables: Manufacturing and foreign direct investment
Control variables: private credit, remittances, services, workforce participation, wages, inflation, inequality, income, control of corruption and stability.
Error term captures the influence of unpredictable events or shocks on the dependent variable.
Table 1: Descriptive Statistics for Economic growth, Manufacturing and Foreign Direct Investment
Growth |
Manufacturing |
Foreign direct investment |
|||
|
|
|
|
|
|
Mean |
4.101414222 |
Mean |
17.1120782 |
Mean |
5.1302471 |
Standard Error |
0.145212955 |
Standard Error |
0.201004194 |
Standard Error |
0.256125875 |
Median |
4.1497642 |
Median |
16.8686835 |
Median |
3.2698942 |
Mode |
5.9 |
Mode |
#N/A |
Mode |
#N/A |
Standard Deviation |
4.307712398 |
Standard Deviation |
5.962747997 |
Standard Deviation |
7.597921317 |
Sample Variance |
18.55638611 |
Sample Variance |
35.55436367 |
Sample Variance |
57.72840834 |
Kurtosis |
10.38638801 |
Kurtosis |
0.477179236 |
Kurtosis |
25.40585474 |
Skewness |
0.39266564 |
Skewness |
0.185970841 |
Skewness |
3.146020994 |
Range |
55.439938 |
Range |
34.0817719 |
Range |
129.776097 |
Minimum |
-17.954994 |
Minimum |
1.5501441 |
Minimum |
-55.065499 |
Maximum |
37.484944 |
Maximum |
35.631916 |
Maximum |
74.710598 |
Sum |
3609.244515 |
Sum |
15058.62882 |
Sum |
4514.617448 |
Count |
880 |
Count |
880 |
Count |
880 |
The average economic growth is obtained as 4.10%. The estimated standard deviation from the descriptive statistics is 4.30. As the value of standard deviation exceeds that of its mean, the distribution of growth is highly volatile. Median growth rate is 4.15% indicating exactly half of the sample period the nations experience a growth rate of 4.15. The distribution is positively skewed with value of skewness being 0.39 and value of kurtosis is 10.39. In the sample period, the maximum growth rate recorded to be 37.48% while the minimum growth rate is -17.95.
The average share of manufacturing in GDP is obtained as 17.11. The estimated standard deviation from the descriptive statistics is 5.96. As the value of standard deviation is lower than that of its mean, the distribution of manufacturing share is not much volatile. Median share of manufacturing is 16.86 indicating exactly half of the sample period the nations experience a manufacturing share of 16.86. The distribution is positively skewed with value of skewness being 0.18 and value of kurtosis is 0.47. In the sample period, the maximum share of manufacturing value added is recorded to be 35.63% while the minimum share of value added be 1.55%.
The mean share of FDI in GDP is estimated to be 5.13. The estimated standard deviation from the descriptive statistics is 7.60. As the value of standard deviation exceeds that of its mean, the distribution of FDI inflow is highly volatile. Median percentage of FDI inflow is 3.26. The distribution is positively skewed with value of skewness being 0.3.14 and value of kurtosis is 25.41. The percentage of FDI inflow is as high as 74.71 and as low as 55.07.
Table 2: Correlation between economic growth and independent and control variables
From the correlation matrix economic growth is likely to be negatively correlated with manufacturing value added. So far as foreign direct investment is concerned, it has a positive relation with economic growth.
|
Growth |
Growth |
1 |
Controlofcorruption |
-0.2454046 |
Stability |
-0.18263531 |
Manufacturing |
-0.102811026 |
Services |
0.100827264 |
Privatecredit |
-0.320159758 |
Foreigndirectinvestment |
0.168186013 |
Workforceparticipation |
-0.042583221 |
Wages |
-0.337342485 |
Remittances |
-0.272313733 |
Inflation |
-0.002756515 |
Inequality |
0.100211719 |
Income |
-0.291307488 |
Income2 |
-0.226188767 |
Table 3: Results of regression
Regression Statistics |
|
Multiple R |
0.47 |
R Square |
0.23 |
Adjusted R Square |
0.21 |
Standard Error |
3.82 |
Observations |
880 |
ANOVA |
|||||
|
df |
SS |
MS |
F |
Significance F |
Regression |
13 |
3679.317 |
283.024 |
19.403 |
0.000 |
Residual |
866 |
12631.746 |
14.586 |
|
|
Total |
879 |
16311.063 |
|
|
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Intercept |
13.726 |
2.002 |
6.855 |
0.000 |
9.796 |
17.655 |
Controlofcorruption |
0.918 |
0.298 |
3.079 |
0.002 |
0.333 |
1.502 |
Stability |
-0.058 |
0.242 |
-0.238 |
0.812 |
-0.533 |
0.417 |
Manufacturing |
-0.078 |
0.025 |
-3.145 |
0.002 |
-0.127 |
-0.029 |
Services |
-0.001 |
0.032 |
-0.036 |
0.971 |
-0.065 |
0.063 |
Privatecredit |
-0.016 |
0.004 |
-3.854 |
0.000 |
-0.024 |
-0.008 |
Foreigndirectinvestment |
0.123 |
0.018 |
6.652 |
0.000 |
0.087 |
0.159 |
Workforceparticipation |
-0.001 |
0.019 |
-0.043 |
0.965 |
-0.038 |
0.037 |
Wages |
-0.131 |
0.020 |
-6.602 |
0.000 |
-0.169 |
-0.092 |
Remittances |
0.013 |
0.011 |
1.117 |
0.264 |
-0.010 |
0.035 |
Inflation |
-0.063 |
0.016 |
-3.804 |
0.000 |
-0.095 |
-0.030 |
Inequality |
0.016 |
0.017 |
0.944 |
0.345 |
-0.017 |
0.048 |
Income |
-0.105 |
0.056 |
-1.880 |
0.060 |
-0.214 |
0.005 |
Income2 |
0.001 |
0.001 |
0.958 |
0.338 |
-0.001 |
0.002 |
Based on the regression result the regression equation is estimated to be
The multiple R square estimate from the regression model is obtained as 0.47. This mean the independent and control variables together explain 47 percent variation in economic growth. The coefficient of manufacturing value added is -0.078. The negative coefficient implies a negative relation between manufacturing and economic growth. The corresponding coefficient of foreign direct investment is 0.123. This shows foreign direct investment has a positive influence on economic growth. Both the variables are statistically significant as obtained from the significant P value (value less than 0.05).
The first hypothesis proposes that manufacturing does not have any significant influence on economic growth. The regression result however does not support this claim. An inverse significant relation is found between economic growth and manufacturing. This states that with increase in share of manufacturing value added economic growth of a nation declines. This result however goes against the standard norms of development theory. It is widely argued that as a nation transforms from the state of a developing nation to a developed one the share of agriculture in GDP decreases while that of manufacturing and services increase (Johnson 2014). This might be the case that for developed nation after experiencing a rapid industrialization, further addition of value added in GDP has a negative influence as found in the current paper.
The second hypothesis possesses that no significant relation exists between economic growth and foreign direct investment. Findings from regression suggest foreign direct investment significantly influence economic growth in a positive manner. Foreign direct investment by providing additional capital extends the area of economic growth (Iamsiraroj 2016). Many resources in a nation remain unutilized due to lack of capital. Investment by foreign investors helps to use the unutilized resources and hence supports economic growth.
The paper aims to find the influence of manufacturing value added and foreign direct investment on economic growth of a nation. An increase in manufacturing value added generally assumed to have a positive influence on economic growth. Manufacturing value added promotes economic growth by putting economic resources in a more productive way. Finding of this paper however contradicts the traditional norms. The paper establishes a negative significant relation between economic growth and percentage share of manufacturing value added. Another component that affect economic growth is inflow of foreign capital. In the presence of favorable environment investors invest in foreign nation to a higher return from invested capital. This benefits the domestic economy in terms of supporting more productive activities and hence, economic growth. The paper finds a positive influence of FDI flow on economic growth. That is increase in FDI inflow ensures a faster pace of economic growth.
Adugna, T., 2014. Impacts of manufacturing sector on economic growth in Ethiopia: akaldorian approach. Journal of Business Economics and Management Sciences, 1(1), pp.1-8.
Chatterjee, S. and Hadi, A.S., 2015. Regression analysis by example. John Wiley & Sons.
Clowes, D. and Bilan, Y., 2014. Tracking Income Per Head In Central-Southern Europe. Economic Computation & Economic Cybernetics Studies & Research, 48(2).
Dornean, A. and Oanea, D.C., 2013. Foreign Direct Investment And Post Crisis Economic Growth. Evidence from European Union. Revista Economica, 65(6).
Iamsiraroj, S., 2016. The foreign direct investment–economic growth nexus. International Review of Economics & Finance, 42, pp.116-133.
Johnson, R.C., 2014. Five facts about value-added exports and implications for macroeconomics and trade research. Journal of Economic Perspectives, 28(2), pp.119-42.
Sheridan, B.J., 2014. Manufacturing exports and growth: When is a developing country ready to transition from primary exports to manufacturing exports?. Journal of Macroeconomics, 42, pp.1-13.
Tsoku, J.T., Mosikari, T.J., Xaba, D. and Modise, T., 2017. An Analysis of the Relationship between Manufacturing Growth and Economic Growth in South Africa: A Cointegration Approach. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(2), pp.428-433.
The Specific research questions that the paper addresses are as follows.
How manufacturing value added influences economic growth of a nation?
How share of FDI inflow affects economic growth of a nation?
Economic growth is measured as a percentage change in aggregate output as compared to the previous year. Economic growth of a nation depends on different factors (Tsoku et al. 2017). Of these factors particular interest of the paper is to evaluate the impact of manufacturing value added and foreign direct investment on economic growth.
The economic growth law as proposed by Kaldor suggests that there exists string positive relationship between growth of aggregate output or GDP and growth of manufacturing. The law states the direction of relationship as it runs from manufacturing growth to aggregate output. Manufacturing not only contributes to a larger portion of GDP but it also regarded as a main drivers of economic growth. The importance of manufacturing lies in two significant factors. Firstly, it produces a higher return for the nation. Secondly, the use of advanced technology in manufacturing lead to an increase in employment (Adugna 2014). A study based on 86 countries for the period ranging from 1970 to 2009 analyzed the relationship between growth of manufacturing export and economic growth. The author found manufacturing sector to be beneficial for economic growth. The study suggests a positive relation between manufacturing expansion and economic growth (Sheridan 2014).
Inflow of foreign fund is another crucial factor affecting economic growth. Economic growth of a nation depends on the growth in productive capacity which is determined from saving and investment of a nation. In an integrated world, foreign direct investment has become an important source of economic growth (Dornean and Oanea 2013). There are several linkages between economic growth and FDI. These include learning by doing, human capital, export, stability in macroeconomic environment and other financial development. Based upon these determinants FDI flows affects economic growth through three channels. These are direct transmission of capital through greenfield investment, indirect flow in form of ownership participation and spillover through technology (Clowes and Bilan 2014).
Hypothesis 1
Null Hypothesis: There exists no significant relationship between economic growth and manufacturing
Alternative Hypothesis: There exists a statistically significant relationship between economic growth and foreign direct investment
Hypothesis 2
Null Hypothesis: Foreign direct investment has no significant influence on economic growth of a nation.
Alternative Hypothesis: Foreign direct investment has a significant influence on economic growth of a nation.
In order to model the relationship between economic growth, manufacturing and foreign direct investment time series data are collected for different nations. A sample period ranging from 1996 to 2012 is taken into consideration. Apart from variables like economic growth, manufacturing and foreign investment other related variables like private credit, remittances, services, workforce participation, wages, inflation, inequality, income, control of corruption and stability. The relevant data are collected from Word Development Indicators and Word Governance Indicators.
The best way to establish a causal relation between two or more variables is to develop a multiple regression model. Multiple regression is a powerful statistical tool that is used for predicting a dependent variable based on its relationship with two or more variables (Chatterjee and Hadi 2015). The multiple regression model used in the paper is as follows
Dependent variable: Growth
Independent variables: Manufacturing and foreign direct investment
Control variables: private credit, remittances, services, workforce participation, wages, inflation, inequality, income, control of corruption and stability.
Error term captures the influence of unpredictable events or shocks on the dependent variable.
Table 1: Descriptive Statistics for Economic growth, Manufacturing and Foreign Direct Investment
Growth |
Manufacturing |
Foreign direct investment |
|||
|
|
|
|
|
|
Mean |
4.101414222 |
Mean |
17.1120782 |
Mean |
5.1302471 |
Standard Error |
0.145212955 |
Standard Error |
0.201004194 |
Standard Error |
0.256125875 |
Median |
4.1497642 |
Median |
16.8686835 |
Median |
3.2698942 |
Mode |
5.9 |
Mode |
#N/A |
Mode |
#N/A |
Standard Deviation |
4.307712398 |
Standard Deviation |
5.962747997 |
Standard Deviation |
7.597921317 |
Sample Variance |
18.55638611 |
Sample Variance |
35.55436367 |
Sample Variance |
57.72840834 |
Kurtosis |
10.38638801 |
Kurtosis |
0.477179236 |
Kurtosis |
25.40585474 |
Skewness |
0.39266564 |
Skewness |
0.185970841 |
Skewness |
3.146020994 |
Range |
55.439938 |
Range |
34.0817719 |
Range |
129.776097 |
Minimum |
-17.954994 |
Minimum |
1.5501441 |
Minimum |
-55.065499 |
Maximum |
37.484944 |
Maximum |
35.631916 |
Maximum |
74.710598 |
Sum |
3609.244515 |
Sum |
15058.62882 |
Sum |
4514.617448 |
Count |
880 |
Count |
880 |
Count |
880 |
The average economic growth is obtained as 4.10%. The estimated standard deviation from the descriptive statistics is 4.30. As the value of standard deviation exceeds that of its mean, the distribution of growth is highly volatile. Median growth rate is 4.15% indicating exactly half of the sample period the nations experience a growth rate of 4.15. The distribution is positively skewed with value of skewness being 0.39 and value of kurtosis is 10.39. In the sample period, the maximum growth rate recorded to be 37.48% while the minimum growth rate is -17.95.
The average share of manufacturing in GDP is obtained as 17.11. The estimated standard deviation from the descriptive statistics is 5.96. As the value of standard deviation is lower than that of its mean, the distribution of manufacturing share is not much volatile. Median share of manufacturing is 16.86 indicating exactly half of the sample period the nations experience a manufacturing share of 16.86. The distribution is positively skewed with value of skewness being 0.18 and value of kurtosis is 0.47. In the sample period, the maximum share of manufacturing value added is recorded to be 35.63% while the minimum share of value added be 1.55%.
The mean share of FDI in GDP is estimated to be 5.13. The estimated standard deviation from the descriptive statistics is 7.60. As the value of standard deviation exceeds that of its mean, the distribution of FDI inflow is highly volatile. Median percentage of FDI inflow is 3.26. The distribution is positively skewed with value of skewness being 0.3.14 and value of kurtosis is 25.41. The percentage of FDI inflow is as high as 74.71 and as low as 55.07.
Table 2: Correlation between economic growth and independent and control variables
From the correlation matrix economic growth is likely to be negatively correlated with manufacturing value added. So far as foreign direct investment is concerned, it has a positive relation with economic growth.
|
Growth |
Growth |
1 |
Controlofcorruption |
-0.2454046 |
Stability |
-0.18263531 |
Manufacturing |
-0.102811026 |
Services |
0.100827264 |
Privatecredit |
-0.320159758 |
Foreigndirectinvestment |
0.168186013 |
Workforceparticipation |
-0.042583221 |
Wages |
-0.337342485 |
Remittances |
-0.272313733 |
Inflation |
-0.002756515 |
Inequality |
0.100211719 |
Income |
-0.291307488 |
Income2 |
-0.226188767 |
Table 3: Results of regression
Regression Statistics |
|
Multiple R |
0.47 |
R Square |
0.23 |
Adjusted R Square |
0.21 |
Standard Error |
3.82 |
Observations |
880 |
ANOVA |
|||||
|
df |
SS |
MS |
F |
Significance F |
Regression |
13 |
3679.317 |
283.024 |
19.403 |
0.000 |
Residual |
866 |
12631.746 |
14.586 |
|
|
Total |
879 |
16311.063 |
|
|
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Intercept |
13.726 |
2.002 |
6.855 |
0.000 |
9.796 |
17.655 |
Controlofcorruption |
0.918 |
0.298 |
3.079 |
0.002 |
0.333 |
1.502 |
Stability |
-0.058 |
0.242 |
-0.238 |
0.812 |
-0.533 |
0.417 |
Manufacturing |
-0.078 |
0.025 |
-3.145 |
0.002 |
-0.127 |
-0.029 |
Services |
-0.001 |
0.032 |
-0.036 |
0.971 |
-0.065 |
0.063 |
Privatecredit |
-0.016 |
0.004 |
-3.854 |
0.000 |
-0.024 |
-0.008 |
Foreigndirectinvestment |
0.123 |
0.018 |
6.652 |
0.000 |
0.087 |
0.159 |
Workforceparticipation |
-0.001 |
0.019 |
-0.043 |
0.965 |
-0.038 |
0.037 |
Wages |
-0.131 |
0.020 |
-6.602 |
0.000 |
-0.169 |
-0.092 |
Remittances |
0.013 |
0.011 |
1.117 |
0.264 |
-0.010 |
0.035 |
Inflation |
-0.063 |
0.016 |
-3.804 |
0.000 |
-0.095 |
-0.030 |
Inequality |
0.016 |
0.017 |
0.944 |
0.345 |
-0.017 |
0.048 |
Income |
-0.105 |
0.056 |
-1.880 |
0.060 |
-0.214 |
0.005 |
Income2 |
0.001 |
0.001 |
0.958 |
0.338 |
-0.001 |
0.002 |
Based on the regression result the regression equation is estimated to be
The multiple R square estimate from the regression model is obtained as 0.47. This mean the independent and control variables together explain 47 percent variation in economic growth. The coefficient of manufacturing value added is -0.078. The negative coefficient implies a negative relation between manufacturing and economic growth. The corresponding coefficient of foreign direct investment is 0.123. This shows foreign direct investment has a positive influence on economic growth. Both the variables are statistically significant as obtained from the significant P value (value less than 0.05).
The first hypothesis proposes that manufacturing does not have any significant influence on economic growth. The regression result however does not support this claim. An inverse significant relation is found between economic growth and manufacturing. This states that with increase in share of manufacturing value added economic growth of a nation declines. This result however goes against the standard norms of development theory. It is widely argued that as a nation transforms from the state of a developing nation to a developed one the share of agriculture in GDP decreases while that of manufacturing and services increase (Johnson 2014). This might be the case that for developed nation after experiencing a rapid industrialization, further addition of value added in GDP has a negative influence as found in the current paper.
The second hypothesis possesses that no significant relation exists between economic growth and foreign direct investment. Findings from regression suggest foreign direct investment significantly influence economic growth in a positive manner. Foreign direct investment by providing additional capital extends the area of economic growth (Iamsiraroj 2016). Many resources in a nation remain unutilized due to lack of capital. Investment by foreign investors helps to use the unutilized resources and hence supports economic growth.
The paper aims to find the influence of manufacturing value added and foreign direct investment on economic growth of a nation. An increase in manufacturing value added generally assumed to have a positive influence on economic growth. Manufacturing value added promotes economic growth by putting economic resources in a more productive way. Finding of this paper however contradicts the traditional norms. The paper establishes a negative significant relation between economic growth and percentage share of manufacturing value added. Another component that affect economic growth is inflow of foreign capital. In the presence of favorable environment investors invest in foreign nation to a higher return from invested capital. This benefits the domestic economy in terms of supporting more productive activities and hence, economic growth. The paper finds a positive influence of FDI flow on economic growth. That is increase in FDI inflow ensures a faster pace of economic growth.
Adugna, T., 2014. Impacts of manufacturing sector on economic growth in Ethiopia: akaldorian approach. Journal of Business Economics and Management Sciences, 1(1), pp.1-8.
Chatterjee, S. and Hadi, A.S., 2015. Regression analysis by example. John Wiley & Sons.
Clowes, D. and Bilan, Y., 2014. Tracking Income Per Head In Central-Southern Europe. Economic Computation & Economic Cybernetics Studies & Research, 48(2).
Dornean, A. and Oanea, D.C., 2013. Foreign Direct Investment And Post Crisis Economic Growth. Evidence from European Union. Revista Economica, 65(6).
Iamsiraroj, S., 2016. The foreign direct investment–economic growth nexus. International Review of Economics & Finance, 42, pp.116-133.
Johnson, R.C., 2014. Five facts about value-added exports and implications for macroeconomics and trade research. Journal of Economic Perspectives, 28(2), pp.119-42.
Sheridan, B.J., 2014. Manufacturing exports and growth: When is a developing country ready to transition from primary exports to manufacturing exports?. Journal of Macroeconomics, 42, pp.1-13.
Tsoku, J.T., Mosikari, T.J., Xaba, D. and Modise, T., 2017. An Analysis of the Relationship between Manufacturing Growth and Economic Growth in South Africa: A Cointegration Approach. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(2), pp.428-433.
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