Reza ranjpour; Mohammd reza salmani; zahra Karimi Takanlo; nosrat mokhtarzade khanghahi
Abstract
Exchange rate fluctuation is one of the most important economic variables which its impact on some macro indicators has changed the motivation of economic activists and has also affected the production of economic sectors. Therefore, in this article we have attempted to examine the impact of currency ...
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Exchange rate fluctuation is one of the most important economic variables which its impact on some macro indicators has changed the motivation of economic activists and has also affected the production of economic sectors. Therefore, in this article we have attempted to examine the impact of currency shocks on the performance of sub-industry in the East Azerbaijan Province. To this end, firstly, currency shocks were calculated with the help of the model of the generalized autoregressive heterogeneity variance and were introduced into the model as an explanatory variable. Then using the panel data based on the patterns of the variable and dynamic coefficients and pmge technique were analyzed and its impact on industry value-added of 23 sub-sections of East Azerbaijan Province based on two-digit codes of ISIC-REV4 for the period of 2000-2013 were studied. The results showed a positive and significant effect of variables such as capital, workforce, and export on the value-added of sub-industry in East Azerbaijan Province. Of the 23 industry subsections of the province, currency fluctuation has positive and significant impacts on only four subsections. This effect has been negative for each of 9 subsections, therefore, the fluctuation of real effective exchange rate has adverse impacts on the value-added of Province, and especially on the fluctuation of the production of 9 subsections.
Methodology
The purpose of this study was to investigate the effect of currency shocks on sub-sections of the industrial sector in East Azarbaijan Province. To do this, the effects of the exchange rate fluctuations affecting the value added of the industry sub-sections were examined through econometric models in order to determine which section is more vulnerable to exchange rate fluctuations. Based on theoretical foundations, the implicit form of the research model is offered as follows:
(1)
Where kav, erv, er, and x are respectively value added, the real effective exchange rate, the real exchange rate fluctuations and other factors affect the value added. Given the nature of the research and the purpose of the research, the Solo Growth Model (Aghion et al., 2009) used for the value-added function is as follows:
(2)
In this model, i represents the segment and t represents the time:
Logarithm of the real effective exchange rate, Uncertainty real effective exchange rate, logarithm Value added, Logarithm of the amount of available cash, Logarithm of the number of active labor force, logarithm of the value of the export value.
As stated above, the main objective of this study was to investigate the impact of currency exchange on various economic subdivisions of East Azarbaijan Province. Therefore, the study consists of two steps. In the first step, using the generalized conditional differential equation variance model, the exchange rate was calculated. In the second step, by introducing this variable in the model and using dynamic panel and dynamic variable coefficients and the PMGE technique, the effect of exchange rate uncertainty on 23 sub-sectors of the East Azarbaijan industry will be analyzed. According to the above-mentioned questions, the two generalized conditional non-conformance autoregressive variance techniques and the data panel were used to investigate the problem.
Results and discussion
In this study, 23 sub-sections of the industry sector in East Azarbaijan Province were selected based on two-digit ISIC-REV4 codes for the years between 2000-2013. The data and statistical information of the research variables were collected by the Central Bank, the World Bank and the Office of Management and Budget Program of East Azarbaijan Province.
In order to estimate the real effective exchange rate uncertainty, different GARCH, EGARCH models were estimated for a real effective exchange rate. Then based on the Jenkins Box and the AKA and Schwartz criteria, the best method to estimate the uncertainty of the real effective exchange rate of EGARCH (1, 1) was selected.
Before performing the panel coagulation test to determine the long-run relationship between the main indexes of the study, a single root test should be performed to prevent the occurrence of a regression problem for the variables. In this study, for determining the reliability of panel variables, the Fisher's root test was used, and the root test of the generalized Dickey-Fuller unit was used for root unit testing of the time series. All of the variables were accumulated from the first order. To examine the long-term relationship between variables, Pedroni's co-integration test was used, and the existence of such a relationship was confirmed.
After the root tests and a long-term relationship, it was necessary to perform appropriate diagnostic tests to determine the type of model. In order to ensure the meaningfulness of the sample subgroups, a meaningful test of the group was used. The F-Limer's optimal value is 0.028,; therefore, the hypothesis of the effect of the panel is accepted
As previously mentioned, the main objective of the present study was to investigate the effect of volatile exchange rate volatility on the value added of the industrial sector in East Azarbaijan Province. For this purpose, an econometric model was used (Fig. 2). Then, using the proposed model, the method was applied to the target using the panel data method based on the variable and steady-state coefficients. In the present study, the data were used for 23 sub-sections excluded from the study under the tobacco sector due to lack of information. In addition, the export variables, labor force and capital in all the sub-sectors had a significant and positive impact on the value added of the industry, and the exchange rate variable in the sub-sectors had different effects; however, the real effective exchange rate fluctuations in the 9 sub-sections of the industry had negatively impacted and reduced the value added of these sub-sections.
Conclusion
The results showed that the capital had a positive effect on the value added of the subsections so that the amount of this effect was within the range of 1.71 to 3.21, the highest and lowest impact on the non-metallic mineral industries, respectively. In fact, this is in line with the studies of Gelaii (2012) In addition, labor had a positive impact on the value added, which varies from sub-section to sub-section, with the highest and lowest impact on machinery and equipment industries and office machinery. Again this is consistent with the studies of Gelaii (2012). The results indicate that exports in all sub-sectors have a positive and significant impact on value added, which is consistent with the studies of Butang (2015). The value-added variable in any of the sub-sections is not significant, which contradicts the studies of Parhizkari et al. (2013). The magnitude of the coefficient for effective exchange rate fluctuations was only in the 9 sub-sections of the 23 sub-sections, which is negative and significant. This is in line with most studies, which is approximately 0.99 for all of these sub-sections. The estimated coefficient for industry sub-sectors was about 0.99, indicating that one percent increase in currency shocks would reduce over 99 percent of the value added of these sub-sectors.
