The following sections discuss the impact of FDI on labour productivity. The results are given in Table 5.6 as equation (5 .9). The model performs satisfactorily in terms of the conventional tests, i.e. the Adjusted R2 and F-statistics. The Adjusted R2 implies that the independent variables explain about 99 percent of the variation in the dependent variable, while the F-statistic is also significant at the one percent level of significance, thus implying that selected variables of the equation jointly contributed to labour
productivity improvement in New Zealand during the period of study. In addition, the
equation's diagnostics are not subject to econometric pathologies, such as serial correlation, heteroscedasticity, non-functional form and non-normality of the residuals.
TABLE 5.5 FDI-CAPIT AL FORMATION MODELS
Equation (5.6) Long-run Coefficients:
In TDI = 1 5.87 + 3.27 In GDPPC + 0.23 ln FDI + O.Ol ln REX + 0.38 ln DC (10.16)"· (6.00)··· (2.93)·· (3.59)··· (3.1 1)··· R 2 = 0.94 FI1 26 = 79.60··· SEE = 0.06 DW = 1 .8 LMX2 (1) = 0.35
Re setx2 (1) = 1 .48 JNBX2 = 2.76 ARCHX2 = 0.48 Short-run Coefficients:
In TDI = 8.41 +0.53 li ln GDPPC + 0.08 liln FDI + 0.01 li ln REX + 0.20 li ln DC
(5.80)··· (1 .57) (2.67)·· (2.09)·· (4.34)···
- 0.52 ecmt-l (4.62)·"
R2 = 0.54 F's.32 = 10.62··· DW = 1 .8
Equation (5.7) Long-run Coefficients:
In Ipr; = 14.28 + 3.16 In GDPPC + 0.22 In FDI + O.O l In REX + 0.26 In DC (7.35)"· (4.75)··· (2.54)·· (2.SS)" (I.S3)··
R2 = 0.95 F6 32 = 1 09.74·· SEE = 0.08 DW = 1 .84 LMX2 (l) = 0.35 Resetx2 (l) = 337 JNBX2 = 0.63 ARCHX2 = 0.88
Short-run Coefficients:
In Ipri = 7.25 + 0.83 li ln GDPPC + 0. 1 1 li In FDI + 0.01 li In REX (5.21)··· (1.95)·· (3.41)·· (2.78)"
+ 0. 1 3 li In DC - 0.5 1 ECTH (2.34 ).. ( 4.25)···
R2 = 0.45 Fs 29 = 7.23··· D W = 1 .8
Equation (5.8) Long-run Coefficients:
In Ipub = 1 3 .2 1 + 4.93 In GDPPC + 0.20 In FDI - 2.49 In REX + 0.96 In DC (2.7s).. (2.91)" (1.00) (1.86)· (2.57)·· R2 = 0.76 F7 31 = 1 8.21"· SEE = 0. 1 2 DW = 2.2 LMX2 (1) = 0.84 Resetx2 (1) = 0.0 1 JNBX2 = 0.63 ARCH X2 = l .7 1
Short-run Coefficients:
In Ipub =
(1o�)1.
-?o
·.�
7�
li In GDPPC +9
...�?
li In FDI +9
0.�
9?
li In REX- 0.30 li In DC - 0.3 1 ECT (3.S6)... (3.03)
•• ' I-I
R2 = 0.3 1 F's.33 = 4.73··· DW = 2.2
The coefficients for all independent variables are positive and statistically signi ficant in the long run with the exception of the labour force. The results of the equation suggest that the immediate impact of an increase in domestic capital intensity is positive and highly significant. This indicates that capital intensity is a very important determinant of labour productivity. At first glance this may not appear to be a surprising result, because in a small, developed country like New Zealand, the productivity may be highly influenced by domestically available capital. On the other hand, an increase in the labour force has, as expected, a negative impact on labour productivity. The coefficient of negative 0.02 implies that a one percent increase in labour force r esults in a 0.02 percent decrease in labour productivity.
The F DI variable has a p ositive as well as significant impact on labour productivity.
These results are not altogether surprising because the positive externalities generated in the form of a greater transfer of technology and managerial know-how are likely to favourably affect labour productivity in a host country. An increase in the level of FDI results in a positive and significant impact on labour productivity in the long-run (i.e. a one percent increase in FDI stock will improve I abour productivity by 0. 1 6 percent). Linkages between FDI and labour productivity are, as noted by Rodriguez-Clare (1 996) more pronounced, when the size of the host market is larger. Thus, in relative terms, the lower contribution from FDI, compared to domestic capital intensity, could be due to the small domestic market in New Zealand.
Moreover, the labour productivity model has been extended to include a human capital factor (proxied by secondary school attainments) for examining the impact of human capital along with FDI on labour productivity growth. The human capital variable has the correct sign and is statistically significant at the one percent level. This suggests that the human capital component is an important variable contributing towards productivity improvement along with FDI. It is important to note that, when interpreting the results, it could be biased due to the human capital variable used. As explained before, the proxy variable used was determined by the limitations of the published statistics.
The short-run specification of the equation indicates a good relative fit, and the
significance of the error correction term of the equation (5.9) is quite good and, as the
theory predicts, the ECTC-1) is negative and statistically significant, suggesting a
deviation from the long-run labour productivity growth during this period. The deviation is corrected by 0.92 percent in the next year. In terms of the short-run relationship, the coefficient of FDI is again positive and significant at the 1 0 percent level, and domestic capital intensity has a positive correlation with productivity in the short-run.
TABLE 5.6 FDI-PRODUCTIVITY MODELS
Equation (5.9) Long-run Coefficients:
lo LP = -4.36 - 0.02 lo L + 2.22 lo CI + 0. 1 6 lo FDIY + 4.7 1 lo OT + 0.94 lo HC (2.37)" (0.25) (4.49)'" (2.00)" (2.76)'" (3.32)··' R2 = 0.99
�
30 = 558.47'" SEE = 0.002 DW = 1 .7 LM X2(1) = 0.49 Re set X2 (1) = 0.04 JNB X2 = 0.007 ARCH X2 = 1 .05 Short-run Coefficients: lo LP = -0.33 - O.OI � lo L + 0.91 � lo CI + 0.12 � lo FDIY + 0.57 � lo OT (1.62) (0.25) (6.06)'" (2.52)" (4.20)'" + 0.98 � ln HC - 0.07 EC7;_1 (7.80)'" (4.34)'" R2 = 0.99�
.33 = 409.88'" DW = 1 .8Collectively, the results indicate that the level of the FDI makes a positive contribution towards improving the labour productivity of a small, developed host country. The estimated results indicate that all explanatory variables have the expected sign. Although FDI has a statistically positive impact on labour productivity, in terms of the relative magnitude of the impact on labour productivity, the openness to trade variable has b een t he most i mportant determinant followed b y d omestic c apital i ntensity and, then, the FDI. The results also show the importance of having a sound educational background in increasing labour productivity, which is also vital for absorbing the new technologies introduced by investors. Productivity improvements will have a long-term
impact on the economy, and productivity spillovers gained by local firms can be an added advantage for the host country.