خلاصة:
The aim of this paper is to assess the relation between exports instability investment and economic growth in Iran. The few previous studies have not attempted to utilize the dynamic methods of assessment and the time series techniques and ARCH models. In this study, we found that the variables are unstable in level; therefore, a distorted view on studies was conducted according to regressive formats alone without no concern to the unstable state of variation. Nevertheless, our results indicate that in the long-run export instability has a negative effect on investment and economic growth. However, in the short -run the effects are minimal.
ملخص الجهاز:
"Table 2: The results obtained from the integration test for economic growth models’ variables Integrated vectors based on the assumption Ho H1 assumption The trace statistics 1% critical value 5% critical value 72/34 54/46 47/21 26/91 29/68 35/65 Source: ibid Based on trace statistics there exists only one integrated vector among the variables as follows: GYN = 4/428Gyk - 36/7v+36/76Dum (11) The above equation shows that despite instability effect in the short-term, in the long-term the instability effect of exports on growth is negative and has significant relation (Table 4).
Gyk = -9/167v-7/97DUM (12) The above equation shows that the exports long-term instability effect on capital growth is negative and has significant relation (Table 5).
Table 3: The results obtained from the integration test for the patterns variable Cumulative indicator based on the assumption Ho H1 assumption The trace statistics 1% critical value 5% critical value 56/84 35/65 29/68 23/17 20/04 15/41 2/75 6/65 3/76 Source: ibid C) In the finial stage, we calculate the remaining obtained from regressive integration and obtain the short-term parameters by ECM approximations or the error correction model as follows: (13) where: is the long-term coefficient matrix, is the differential processor, is the shock deductive and is the parameter which can be approximated.
V shocks: Tables 1 & 2: Estimation of Equations (3),(4) and ARCH test Dependent Variable: LX Method: ML - ARCH (Marquardt) Date: 12/09/06 Time: 15:56 Sample(adjusted): 1351 1383 Included observations: 33 after adjusting endpoints Convergence achieved after 22 iterations Variance backcast: ON Coefficient Std. Error z-Statistic Prob."