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Constant

Variables Trend and Intercept

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UN -4.004066**

LNRGDP -4.25111***

CPI -3.711698**

FDI -3.878565**

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First Different

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Constant

Variables Trent and Intercept

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UN -5.051320***

LNRGDP -4.894707***

CPI -4.473139***

FDI -5.388260***

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notes: ***, **, * denotes the rejection of the null hypothesis at 1%, 5% and 10% of significance levels, the null of hypothesis of Augmented Dickey-Fuller unit root test is the existence of unit root. Augmented Dickey-Fuller unit root test includes a constant and linear trend of this result has shown in table 1 above.

According to the result above which we tested, it shows that, all variables used are achieving the stationary at level and then the first difference. Therefore, it can proceed to cointegration test which is to examine the short run and long run relationship of variables used.

Cointegration test

Table 2: Cointegration Test (Short Run Relationship)

Dependent

Variables ? UN ? LRGDP ? CPI ? FDI

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? UN - 2.516837 5.714336 *** 7.519445***

? LRGDP 0.224436 - 5.7667463*** 8.95123**

? CPI 0.139868 1.148525 - 1.930135

? FDI 0.187126 0.024194 0.461171 -

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Note: The asterisks indicate the following levels of significant: ***, **, * denotes 1%, 5% and 10%

The figure in Table 2 with *** shows that there are granger causality between dependent variable and independent variable. In the short run, do not reject the null alternatives means that independent variables will not cause the dependent variable.

4.4 Multiple regression model analysis and interpretation

Based on this study, the time series data consists of thirty-eight observations, ranging from the year 1970 to 2007. The Unemployment (UN) is the dependent variable; Ln Real Gross Domestic Product (LNGDP), Consumer Price Index (CPI) and Foreign Direct Investment (FDI) are used as the independent variables in the regression to examining the impacts on the unemployment.

Ordinary least square (OLS) method is used in this paper. The model estimated is as follows:

Unt = β0 + β1 (LNRGDP) + β2 (CPI) + β3 (FDI) + εt

Unemployment = 143.5731 – 16.77569Ln (RGDP) + 0.107573(CPI)

– 0.00000707 (FDI)

The OLS regression gives the following output:

Table 3: OLS results

Dependent variable – Unemployment

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