478285 *** The truncation lag is based on Newey and West (1987) bandwidth ** and *** denote statistical significance at the 5 and 1% levels, respectively Table 4 Bounds F-test for cointegration Dependent variable Function

F-test statistic In y/N In y/N(In UEMP, In GOV) 5.

01) as refer to the p-value of

F-Test statistic is at 307.

However, turning to the joint hypothesis test of strong rational expectations (2), the

F-test statistic is 10.

7) If the

F-test statistic exceeds the upper critical value, the null hypothesis of no long-run relationship can be rejected regardless of whether the underlying orders of integration of the variables are I(0) or I(1).

To this end, an F- test is performed: the production function is estimated with and without the training-related variables, and the

F-test statistic for returns to training is calculated using the residual sum of squares of these alternative specifications.

The

F-test statistic for each model is as follows: Ml is 5.

In other words a large

F-test statistic, and a correspondingly small p-value, indicates that there are statistically significant differences in yields offered in different states.

The following

F-test statistic was used to test the homogeneity of the variances of the 1-month percentage changes for the PPI data series and for the corresponding measures based on alternative data sources:

The equation has an improved fit, as measured both by R-bar square and the

F-test statistic.

866066 *** I(1) ** and *** denote significance at 5 % and 1 % respectively Table 3 Bounds F-test for co integration Dependent variable Function

F-test statistic Uruguay InGrowth InGrowth (InENC, InExpt) 5.

Table 3 Bounds F-test for cointegration Dependent variable Function

F-test statistic [DELTA]Iny/[N.

It is now well established in econometric literature that the

F-test statistic is not valid if times series are integrated as argued by Toda and Yamamoto [1995], Enders [1995], Zapata and Rambaldi [1997], and Gujarati [1995].