£ 149
Variable | Obs | Mean | SD | Min | Max |
GDPcapgr | 28 | 3.92 | 1.73 | 0.64 | 8.03 |
DINV | 28 | 26.62 | 3.39 | 20.73 | 33.11 |
Inflation | 28 | 5.03 | 2.95 | -0.65 | 10.78 |
Openness | 28 | 119.25 | 10.06 | 97.13 | 137.11 |
Schooling | 28 | 7.00 | 0.00 | 7.00 | 7.00 |
Govtspend | 28 | 14.05 | 0.69 | 12.44 | 15.44 |
Prcred | 28 | 68.66 | 22.88 | 33.06 | 106.31 |
FDI | 28 | 1.91 | 1.66 | -0.61 | 5.80 |
FDIPRI | 12 | 1776.25 | 1579.10 | 199.00 | 6100.00 |
FDIMAN | 27 | 295.48 | 376.56 | 3.00 | 1597.00 |
FDISER | 21 | 325.00 | 428.05 | 3.00 | 1536.00 |
INSTQUAL | 19 | 0.73 | 0.10 | 0.42 | 0.86 |
Table 1 presents the following averages: GDP growth (3.92%), domestic private investment (26.62%), initial GDP (6460.03 USD), inflation (5.03%), trade openness (119.25), human capital (7 years), government spending (14.05%), private credit (33.06–106.31), and FDI inflows (1.91%). Ranges for these variables vary as shown.
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Variables |
| logGDPCAP | logFDI | logFDIPRI | logFDIMAN | logFDISER |
logGDPCAP |
| 1 |
|
|
|
|
logFDI | r-value | 0.3542 | 1 |
|
|
|
| p-value | 0.0644 |
|
|
|
|
logFDIPRI | r-value | 0.2270 | 0.6997 | 1 |
|
|
| p-value | 0.2454 | 0.000** |
|
|
|
logFDIMAN | r-value | 0.0106 | 0.4191 | 0.5518 | 1 |
|
| p-value | 0.9571 | 0.0264* | 0.0023** |
|
|
logFDISER | r-value | -0.3015 | -0.6224 | -0.6705 | -0.3066 | 1 |
| p-value | 0.1189 | 0.0004** | 0.0001** | 0.1125 |
|
**p<0.01
Table 2 shows that FDI in the primary sector has a strong positive correlation with total FDI (r=0.700, p<0.001). FDI in manufacturing is positively correlated with both total FDI and FDI in the primary sector, while FDI in services has a negative correlation with both. There is no significant relationship between GDP per capita growth and FDI inflows or its sectors.
Hypothesis
H1: The direct aggregate effect of the level of FDI inflows has a significant and positive effect on economic growth of Mauritius.
Dependent variable: GDP Per capita | Model 1 | Model 2 |
Independent variables |
|
|
FDI | 0.333* (0.138) | 0.410 (0.303) |
DPI | 2.022** (0.683) | 3.888* (1.702) |
Control variables |
|
|
Inflation | – | -0.052 (0.222) |
Govtspend | – | -1.263 (2.801) |
Privatcredit | – | -0.424 (1.407) |
Openness |
| -1.989 (2.180) |
Schooling |
| – |
Instquality |
| -0.563 (1.320) |
Constant | -2.461* (0.978) | 1.709 (7.093) |
Observations | 28 | 28 |
R2 | 0.352 | 0.573 |
Figures within the brackets denotes Standard error
The model for direct aggregate effect of the level of FDI inflows on economic growth are
GROWTH = β0+ β1FDIi+β2DPIj +Vi
When Control variables are added,
GROWTH = β0+ β1FDIi+β2DPIj +β3INSTQij+ β4OPENNESSij + β5PRIVCREDITij + β6GOVTSPENDij + β7INFLATIONij +β8SCHOOLINGij + Vi
Table 3 presents the regression analysis with GDP per capita as the dependent variable. In Model 1, both FDI (β=0.333, p=0.02) and DPI (β=2.022, p=0.007) significantly impact growth, with an R-square of 35.2%. In Model 2, after adding control variables, DPI remains significant (β=3.888, p=0.04), while FDI becomes insignificant (p>0.05), and R-square increases to 57.3%. The hypothesis testing shows that DPI consistently impacts growth, while FDI does not after controlling for other factors.
H1: The direct aggregate effect of the level of FDI inflows has a significant and positive effect on economic growth of Mauritius is accepted.
H2: The sectoral composition of FDI inflows positively and significantly affects the economic growth of Mauritius.
Dependent variable: GDP Per capita | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 |
Independent variables |
|
|
|
|
|
|
|
|
DPI | 2.511** (0.717) | 3.393* (1.686) | 1.924* (0.758) | 4.619* (1.889) | 1.902** (0.712) | 4.719 (2.384) | 2.644** (0.774) | 4.729 (2.549) |
FDIPRI | 0.063* (0.025) | 0.083 (0.060) | – | – | – | – | 0.087* (0.042) | 0.102 (0.073) |
FDIMAN | – | – | 0.017 (0.059) | 0.036 (0.139) | – | – | -0.083 (0.064) | -0.027 (0.149) |
FDISER | – | – | – | – | -0.064 (0.036) | 0.017 (0.010) | 0.003 (0.049) | 0.065 (0.105) |
Control variables |
|
|
|
|
|
|
|
|
Inflation | – | -0.070 (0.214) | – | -0.197 (0.211) | – | -0.232 (0.312) | – | -0.189 (0.319) |
Govtspend | – | -0.618 (3.019) | – | -2.742 (2.880) | – | -3.401 (3.495) | – | -1.757 (3.708) |
Privatcredit | – | -1.432 (1.733) | – | -0.235 (1.872) | – | 0.079 (1.467) | – | -1.499 (2.073) |
Openness | – | -2.236 (2.199) | – | -1.733 (2.354) | – | -1.715 (2.370) | – | -2.559 (2.453) |
Schooling | – | – | – | – | – | – | – | – |
Instquality | – | -0.088 (1.377) | – | -0.506 (1.543) | – | -0.587 (1.494) | – | 0.217 (1.697) |
Constant | -3.112** (1.032) | 3.013 (7.134) | -2.228* (1.097) | 1.665 (7.638) | -2.065* (1.015) | 1.788 (7.689) | -3.165** (1.140) | 3.794 (7.802) |
Observations | 28 | 19 | 28 | 19 | 28 | 19 | 28 | 19 |
R2 | 0.364 | 0.576 | 0.205 | 0.505 | 0.293 | 0.503 | 0.407 | 0.595 |
FDI inflow data include foreign investment in all sectors of the economy (primary, manufacturing, services).
The estimation of FDI inflows in each sector are,
Primary sector
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDIPRIij +Vi
When Control variables are added,
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDIPRIij +
β7INFDEFij + β8GOVTSPENDij + β9PRCREDij + Vi
Manufacturing Sector
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDIMANij +Vi
When Control variables are added,
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDIMANij+ β7INFDEFij + β8GOVTSPENDij + β9PRCREDij + Vi
Service Sector
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDISERij +Vi
When Control variables are added,
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDISERij+ β7INFDEFij + β8GOVTSPENDij + β9PRCREDij + Vi
Primary sector, Manufacturing Sector and Service Sector
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDIPRIij+ β7FDIMANij + β8FDISERij +Vi
When Control variables are added,
GROWTH = β0+ β1+INITIAL GDPi+β2HCi+β3INSTQij+ β4TRADEij + β5FDIij + β6FDIPRIij + β7FDIMANij + β8FDISERij+ β9INFDEFij + β10GOVTSPENDij + β11PRCREDij + Vi
Table 4 presents the regression analysis with GDP per capita as the dependent variable. In Model 1, DPI and FDIPRI are significant (β=2.511, p<0.001 and β=0.063, p<0.05). In Model 2, FDIPRI becomes insignificant after adding control variables. In Model 3, DPI is significant (β=3.393, p<0.05), while FDIMAN is not. In Model 5, DPI is significant (β=1.902, p<0.001), but FDISER is not. In Model 7, both DPI (β=2.644, p<0.001) and FDIPRI (β=0.087, p<0.05) are significant. Overall, DPI shows consistent significance, while sector-specific FDIs are mostly insignificant.
H2: The sectoral composition of the FDI inflows has a significant and positive effect on economic growth of Mauritius is partially accepted.