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Showing 48 results for Output
Volume 22, Issue 8 (8-2022)
Abstract
The series elastic actuators make more comfort in the use of assistive exoskeletons. In this paper, an assistive controller is designed for a series-elastic-actuator-driven knee exoskeleton to restore normative mobility of individuals with weak muscles. The main target of the proposed controller is to modify the dynamics performance of the coupled human-exoskeleton system. In other words, the proposed controller modifies the relationship between the net muscle torque exerted by the human and the resulting angular motion. There are fewer sensors in the proposed intent-independent method relative to other methods. Moreover, there are less controller coefficients to regulate where these coefficients are extracted from a type zero Takagi-Sugeno-Kang fuzzy system. The performance of the controller is evaluated by simulations and experiments. The amplitude of the EMG signals decreased in a healthy person worn the SUT-KneeExo. Moreover, the proposed algorithm has a better performance in comparison with integral admittance shaping mothed and output feedback assistive controller. In other words, the amplitude of the integral admittance is more and the phase lag is less than other methods.
Volume 23, Issue 1 (3-2023)
Abstract
Aim and Introduction
In the conventional Input-Output model, all final demand components including household consumption, government expenditures, capital accumulation and exports are considered as exogenous variables. The basic limitation of the open Input-Output model is ignorance the relationship between the production sector and the household. In this way, if there is an increase in demand for the products of some industries, such an event will directly lead to an increase in the production level of these industries in the first place. On the other hand, the increase in production in turn leads to an increase in the level of production in related industries through previous connections. The increase in income resulting from higher levels of household economic activities leads to an increase in household consumption and as a result stimulates more activities in the production sector. Based on this, the production sector and the households are related to each other through the income-consumption relationship.In order to estimate the income-consumption relationship, household consumption should be included as an endogenous variable in the Input-Output model, while in the conventional (open) Input-Output model, household consumption is considered as an exogenous variable. To solve this limitation, Miyazawa (1976) presented a new Input-Output model in which he considered household consumption as an endogenous variable. Miyazawa's model is known in the relevant literature as a semi-closed Input-Output model with endogenous consumption. Despite this, Miyazawa's model, similar to Keynes' consumption theory, considers household consumption solely as a function of current income, while according to other theories of consumption behavior, household consumption depends on other factors such as past consumption levels and income. It also depends on the expectation. Accordingly, in this research, the semi-closed Input-Output model with semi-endogenous consumption, introduced by Chen et al (2016), was used because this new model adapts the Input-Output model to other consumption theories and corrects the failure of the previous model. In this framework, household consumption is divided into two endogenous and exogenous parts, so that the endogenous component is influenced by current income and the exogenous component is influenced by other factors affecting consumption. In fact, it is only endogenous consumption that enters the mediation matrix.
Methodology
In this research, the results of the new semi-closed Input-Output model with semi-endogenous consumption (Chen et al (2016) model) and the semi-closed Input-Output model with completely endogenous consumption (Miyazawa (1976) model) were compared. In this regard, first, endogenous consumption coefficients for 12 product groups were estimated using the Kalman filter model, and then, the estimated endogenous consumption coefficient of each category of goods was compared to the endogenous consumption coefficient of the data sections by means of the interface matrix. The receipt was converted.
In order to compare the performance of the two models of Miyazawa (1976) and the model of Chen et al (2016), the effect of government capital formation on the value added of different sectors was evaluated using the two mentioned models.
Findings
Failure to consider other factors affecting consumption will lead to upward deviation in GDP estimation. In this way, it can be concluded that the semi-endogenous model solves the insufficiency of the completely endogenous model and its results are closer to reality.
Discussion and Conclusion
the gross domestic product was obtained based on fully endogenous and semi-endogenous models (9601201) and (9329172), respectively. These findings show that Miyazawa model considers all household consumption as a function of current income, and also due to the lack of consideration of other factors affecting consumption such as expected income, consumption level. Also, in Chen et al.'s model, the calculated added value is smaller compared to Miyazawa's model, because by analyzing and separating exogenous consumption from total consumption, only endogenous consumption entered the table of intermediary exchanges.
Volume 23, Issue 3 (8-2023)
Abstract
Aims and Introduction:
Limited resources and facilities require prioritizing their allocation. For this reason, determining the sectors in which investment stimulates the economy and causes more economic growth has always been the focus of economic planners. Investigating the contribution of different sectors of the economy in job creation is very important for better allocation of limited resources. The priority of investment will be given to a sector that has the highest employment generation capacity and the production level of the entire economy.
Methodology:
In this article, on the one hand, three methods of analyzing the key sectors of the economy in terms of creating employment were compared. On the other hand, by calculating the normalized backward and forward links of different sectors of the economy and using Spearman's rank correlation coefficient, the results of three methods were examined.
Finally, the most suitable method to introduce the important sectors of the economy to simultaneously improve production and employment was identified.
Results and Discussion:
By comparing the results of the analyzes of two traditional methods and the hypothetical removal of Meller and Marfan, it can be seen that the other services and professional, scientific and technical activities with an increase of one unit (one billion Rials) of investment have the highest direct and indirect employment generation capacity. In addition, mining activity with an increase of one unit (one billion Rials) of investment has the lowest direct and indirect employment generation capacity.
Also, in both primary tables, the fields of agriculture, forestry and fishing have been ranked fourth in terms of importance in creating employment.
Meanwhile, the industrial production sector (construction) has changed from the 13th rank in the traditional method to the 3rd rank in the hypothetical removal method of Meller and Marfan.
In Meller and Marfan's hypothetical elimination method, by considering production, the defect of the traditional employment generation method was largely eliminated.
In the third method, unlike the first two methods, industrial production activity is the most important sector of the economy.
In fact, this sector accounts for about 34% of the total lost indirect job opportunities. Also, according to the revised method, the agricultural sector ranked second among 19 fields of activity and is much more important than the two sectors of other services and professional activities, which were introduced as the most important sectors of the economy (from the point of view of employment creation) according to the first two methods. The calculation of normalized links showed that the industrial production sector (construction) with normalized coefficients of more than 20 had the greatest effect and influence from the production of other sectors. After the industrial production sector, transportation and storage sectors; agriculture, forestry and fishing; and the building have the most links (forward and backward) with other parts, respectively.
Conclusion:
Spearman's rank correlation coefficient, between the normalized links of production and the 3 described methods, showed that based on the results of the 2015 Input-Output table of Statistical Center of Iran, only the modified method of hypothetical elimination can correctly determine the important sectors of the economy from the two perspectives of production and employment.
Volume 23, Issue 4 (12-2023)
Abstract
The lack of statistical data at the regional level has led to the expansion of non-statistical methods for the regionalization of national input-output tables. The main idea of the current research is the regionalization of national dynamic input-output tables using the extension of the Charm method. This research using this non-statistical method provides an estimate of the sectoral capital matrix in the regional level, and finally, with the help of the numerical index of capital productivity and the Williamson’ capital index and comparing it with the relative advantage index, it measures the capacity of capital formation. Part of it is in Isfahan province. The results show that the industry sector with the largest share of output from the total output of the province has the lowest numerical index of capital productivity and the highest balanced diffusion effects of capital and the highest comparative advantage in 2015.
Introduction
One of the most efficient methods for examining intra-regional economic capacities is the use of intra-regional and inter-regional capital matrix. In Iran, due to the lack of sufficient statistical data, no attempt has been made to estimate the sectoral capital matrix in the regional level. The purpose of the current research is to regionalize the national dynamic input-output table with the help of expanding the CHARM non-statistical method and estimating the intra-regional and inter-regional capital matrix; to provide an analysis of the capital capacity of different economic sectors in the region with the help of these matrices. In the current research, among all the non-statistical regionalization methods of the national input-output tables, the Charm approach has been selected in accordance with the regional data. The reason for choosing Charm method is the existence of Cross Hauling in Isfahan province. One of the problems of Charm's method is the placement of national and regional technology coefficients. This simplifying assumption causes the intermediate demand within the region to increase and therefore the added value, which is estimated as a residual; it will be very small or even negative. For this purpose, the current research will regionalize the matrix of national technology coefficients with the help of spatial coefficients; to solve the problem. By estimating the regional capital matrix, an analysis of the final productivity of the sector's capital factor and inter-sector capital distribution will be presented, and the results of these sectors will be compared with the indicators of comparative advantage of the sector. Finally, the research questions will be answered:
At first, it is necessary to estimate the national capital matrix with the help of available data and simplifying assumptions. By estimating the national dynamic input-output table, we will have an estimate of the regional dynamic input-output table with the help of the extension of Charm method. To solve the problem of equality of national and regional technology coefficients, by multiplying the diagonal matrix of spatial coefficients in the matrix of national technology coefficients, we will obtain the spatial technology matrix of the region, and by multiplying this estimated matrix in the resulting diagonal matrix, we will obtain the regional technology matrix. Therefore, smaller regional coefficients will be estimated.
On the other hand, to estimate the intra-regional capital matrix, the difference ratio of the region's output in two periods is used to the same amount at the national level. In this case, the intra-regional capital matrix is estimated. A time interval of one year is considered. The reason for choosing this time interval is that the country's budget is one year and a huge part of the inter-sectoral investment in the region is done by the central government. To estimate the intra-regional capital matrix, the spatial ratio of the region's capital asset ownership to the entire country is used. Finally, by subtracting the national capital matrix from the intra-regional capital matrix, we will get an estimate of the correct inter-regional capital matrix. Finally, with the estimation of the capital matrix, the assessment of the capital formation capacity of the intra-regional sector of Isfahan province is carried out with the help of single-factor productivity analysis of capital and the Williamson index of capital and the estimation of the relative advantage index.
Results and Discussion
In the case that the coefficients of national technology are equal to regional technology, the added value is negatively estimated in four sectors, agriculture, mining, water and electricity, gas and construction. This is despite the fact that in the proposed method of the current research, these positive values are estimated. According to the capital matrix, the most productions were related to the industry, construction and agriculture sectors. Also, the most capital purchases were related to industry, services and real estate sectors. The highest level of sector productivity is related to the communication, mining and transportation sectors. One of the reasons for the increase in user productivity(( L ↑)/ K
Conclusion
In summary, the results show that the industry sector with the largest share of output from the total output of the province had low productivity in 2015. Meanwhile, according to Williamson's index, this sector has the most balanced emission effects with other economic sectors, and the results of the previous link also confirm this. Also, based on the RCA and SRCA indices, this sector has a comparative advantage. Therefore, paying attention to new investment in this sector and improving production technology can have good effects on the sector itself and ultimately on other economic sectors in the region.
Introduction
One of the most efficient methods for examining intra-regional economic capacities is the use of intra-regional and inter-regional capital matrix. In Iran, due to the lack of sufficient statistical data, no attempt has been made to estimate the sectoral capital matrix in the regional level. The purpose of the current research is to regionalize the national dynamic input-output table with the help of expanding the CHARM non-statistical method and estimating the intra-regional and inter-regional capital matrix; to provide an analysis of the capital capacity of different economic sectors in the region with the help of these matrices. In the current research, among all the non-statistical regionalization methods of the national input-output tables, the Charm approach has been selected in accordance with the regional data. The reason for choosing Charm method is the existence of Cross Hauling in Isfahan province. One of the problems of Charm's method is the placement of national and regional technology coefficients. This simplifying assumption causes the intermediate demand within the region to increase and therefore the added value, which is estimated as a residual; it will be very small or even negative. For this purpose, the current research will regionalize the matrix of national technology coefficients with the help of spatial coefficients; to solve the problem. By estimating the regional capital matrix, an analysis of the final productivity of the sector's capital factor and inter-sector capital distribution will be presented, and the results of these sectors will be compared with the indicators of comparative advantage of the sector. Finally, the research questions will be answered:
- Which effect will the adjustment of the national technology coefficients have on the added value of the province?
- What is the capital matrix of the sector in Isfahan province?
- Which sector in Isfahan province has the highest numerical index of capital productivity?
- Which economic sectors in Isfahan province have more distribution of capital formation?
- What are the economic sectors with the greatest comparative advantage in Isfahan province?
At first, it is necessary to estimate the national capital matrix with the help of available data and simplifying assumptions. By estimating the national dynamic input-output table, we will have an estimate of the regional dynamic input-output table with the help of the extension of Charm method. To solve the problem of equality of national and regional technology coefficients, by multiplying the diagonal matrix of spatial coefficients in the matrix of national technology coefficients, we will obtain the spatial technology matrix of the region, and by multiplying this estimated matrix in the resulting diagonal matrix, we will obtain the regional technology matrix. Therefore, smaller regional coefficients will be estimated.
On the other hand, to estimate the intra-regional capital matrix, the difference ratio of the region's output in two periods is used to the same amount at the national level. In this case, the intra-regional capital matrix is estimated. A time interval of one year is considered. The reason for choosing this time interval is that the country's budget is one year and a huge part of the inter-sectoral investment in the region is done by the central government. To estimate the intra-regional capital matrix, the spatial ratio of the region's capital asset ownership to the entire country is used. Finally, by subtracting the national capital matrix from the intra-regional capital matrix, we will get an estimate of the correct inter-regional capital matrix. Finally, with the estimation of the capital matrix, the assessment of the capital formation capacity of the intra-regional sector of Isfahan province is carried out with the help of single-factor productivity analysis of capital and the Williamson index of capital and the estimation of the relative advantage index.
Results and Discussion
In the case that the coefficients of national technology are equal to regional technology, the added value is negatively estimated in four sectors, agriculture, mining, water and electricity, gas and construction. This is despite the fact that in the proposed method of the current research, these positive values are estimated. According to the capital matrix, the most productions were related to the industry, construction and agriculture sectors. Also, the most capital purchases were related to industry, services and real estate sectors. The highest level of sector productivity is related to the communication, mining and transportation sectors. One of the reasons for the increase in user productivity
Conclusion
In summary, the results show that the industry sector with the largest share of output from the total output of the province had low productivity in 2015. Meanwhile, according to Williamson's index, this sector has the most balanced emission effects with other economic sectors, and the results of the previous link also confirm this. Also, based on the RCA and SRCA indices, this sector has a comparative advantage. Therefore, paying attention to new investment in this sector and improving production technology can have good effects on the sector itself and ultimately on other economic sectors in the region.
Volume 23, Issue 4 (12-2023)
Abstract
Introduction:
International trade is usually associated with competition. During this competition, successful producers have lower production costs. Reducing the cost of production requires the use of different ways. One of these ways is the better use of primary production factors such as labor force. Thus, this paper attempts to investigate the effect of changes in foreign trade along with other effective factors on changes in labor force usage in Iran.
Methodology:
There are several methods to study the quality of labor force usage. The labor force productivity is considered as a criterion that is used in many researches. To this end, this study investigates the effects of foreign trade on labor force productivity changes in different production sectors. The data required for this research are provided from the input-output tables of 2011 and 2016, the national accounts and the results of the population and housing census for the years 2011 and 2016. For this purpose, first, symmetric tables of the sample years have been made with the assumption of sector technology, using consumption and supply tables of these years. Then, in order to calculate productivity and compare them in the sample years, the dimensions of the created tables have been standardized. Finally, using the Structural Decomposition Analysis (SDA) approach, the effects of changes in trade balance, along with export and import ratio to trade balance, export and import structure, self-sufficiency, production technology and employment on changes in labor force productivity are determined.
At the sectoral level, the value of the production of the industrial sector in 2016 compared to the corresponding value in 2011 (at the price of 2016) has decreased due to the recession prevailing in this sector. The value of products at fixed prices in trade and repair and mining sectors, including crude oil and natural gas, has decreased due to reasons such as sanctions and low economic growth in these periods. In contrast, the value of production shows an increase at a fixed price in the public affairs, defense and social security /real estate and real estate services/transportation and agriculture sectors.
Results and Discussion:
The total value of production in 2016 compared to 2011 has increased nearly 2006.70 million Rials at the price of 2016. The number of employed people in the country has increased by 2,113,120 people during this period. Because of these changes, the productivity of the country's labor force has reached from 1038.12 million Rials in 2011 (at the price of 2016) to 1029.84 million Rials in 2016, which shows a decrease of 8.28 million Rials.
At the sectoral level, the value of the production of the industry sector in 2016 compared to the corresponding value in 2011 (at the price of 2016) has decreased due to the recession prevailing in this sector. The value of products at fixed prices in trade and repair/ and mining sectors, including crude oil and natural gas, has decreased in these years due to reasons such as sanctions and low economic growth. In contrast, the value of production shows an increase at a fixed price in the public affairs, defense and social security/real estate and real estate services/, transportation/ and agricultural sectors. In view of employment, the agricultural sector has faced a decrease in employment during the study period. In contrast, the industrial/, and trade and repair/ sectors have faced an increase in employment. Because of these changes, the industry/, trade and repair/ sectors have faced a decrease in labor productivity. Whereas the agriculture sector/, transportation/, public affairs administration, defense and social security/ and the activities of real estate and real estate service companies/ have faced an increase in labor productivity.
From the point of view of foreign trade, the industry sector has seen the largest increase in exports, while the electricity sector has faced the largest decrease in exports. In terms of imports, the industry sector has experienced the largest increase, while the education sector has experienced the largest decrease. The correlation coefficient between the exports of the sectors and the productivity of their labor force has been positive. While the correlation coefficient of the different sectors with the productivity of their labor force has been negative. However, the value of these correlation coefficients shows a decrease in 2016 compared to 2011.
Conclusion:
The results of research show that foreign trade has improved labor productivity in the country. In addition, the exports of sectors have relatively similar relationship with the productivity of their labor force, in contrast, the import of goods has an inverse relationship with the productivity of their producing sectors. However, this issue has received less attention in 2016 compared to 2011, which has led to changes in the structure of exports and imports to reduce labor force productivity.
International trade is usually associated with competition. During this competition, successful producers have lower production costs. Reducing the cost of production requires the use of different ways. One of these ways is the better use of primary production factors such as labor force. Thus, this paper attempts to investigate the effect of changes in foreign trade along with other effective factors on changes in labor force usage in Iran.
Methodology:
There are several methods to study the quality of labor force usage. The labor force productivity is considered as a criterion that is used in many researches. To this end, this study investigates the effects of foreign trade on labor force productivity changes in different production sectors. The data required for this research are provided from the input-output tables of 2011 and 2016, the national accounts and the results of the population and housing census for the years 2011 and 2016. For this purpose, first, symmetric tables of the sample years have been made with the assumption of sector technology, using consumption and supply tables of these years. Then, in order to calculate productivity and compare them in the sample years, the dimensions of the created tables have been standardized. Finally, using the Structural Decomposition Analysis (SDA) approach, the effects of changes in trade balance, along with export and import ratio to trade balance, export and import structure, self-sufficiency, production technology and employment on changes in labor force productivity are determined.
At the sectoral level, the value of the production of the industrial sector in 2016 compared to the corresponding value in 2011 (at the price of 2016) has decreased due to the recession prevailing in this sector. The value of products at fixed prices in trade and repair and mining sectors, including crude oil and natural gas, has decreased due to reasons such as sanctions and low economic growth in these periods. In contrast, the value of production shows an increase at a fixed price in the public affairs, defense and social security /real estate and real estate services/transportation and agriculture sectors.
Results and Discussion:
The total value of production in 2016 compared to 2011 has increased nearly 2006.70 million Rials at the price of 2016. The number of employed people in the country has increased by 2,113,120 people during this period. Because of these changes, the productivity of the country's labor force has reached from 1038.12 million Rials in 2011 (at the price of 2016) to 1029.84 million Rials in 2016, which shows a decrease of 8.28 million Rials.
At the sectoral level, the value of the production of the industry sector in 2016 compared to the corresponding value in 2011 (at the price of 2016) has decreased due to the recession prevailing in this sector. The value of products at fixed prices in trade and repair/ and mining sectors, including crude oil and natural gas, has decreased in these years due to reasons such as sanctions and low economic growth. In contrast, the value of production shows an increase at a fixed price in the public affairs, defense and social security/real estate and real estate services/, transportation/ and agricultural sectors. In view of employment, the agricultural sector has faced a decrease in employment during the study period. In contrast, the industrial/, and trade and repair/ sectors have faced an increase in employment. Because of these changes, the industry/, trade and repair/ sectors have faced a decrease in labor productivity. Whereas the agriculture sector/, transportation/, public affairs administration, defense and social security/ and the activities of real estate and real estate service companies/ have faced an increase in labor productivity.
From the point of view of foreign trade, the industry sector has seen the largest increase in exports, while the electricity sector has faced the largest decrease in exports. In terms of imports, the industry sector has experienced the largest increase, while the education sector has experienced the largest decrease. The correlation coefficient between the exports of the sectors and the productivity of their labor force has been positive. While the correlation coefficient of the different sectors with the productivity of their labor force has been negative. However, the value of these correlation coefficients shows a decrease in 2016 compared to 2011.
Conclusion:
The results of research show that foreign trade has improved labor productivity in the country. In addition, the exports of sectors have relatively similar relationship with the productivity of their labor force, in contrast, the import of goods has an inverse relationship with the productivity of their producing sectors. However, this issue has received less attention in 2016 compared to 2011, which has led to changes in the structure of exports and imports to reduce labor force productivity.
Volume 24, Issue 3 (9-2024)
Abstract
Introduction
Empirical analysis of export-led growth (ELG), growth-Led export (GLE), import-led growth (ILG) and growth-Led imports (GLI) hypotheses, are supported by a review of the trade literature and economic growth, which creates verifiable evidence using scientific methods for interpretation. To start with the first hypothesis, ELG is also expressed as the role of exports in economic growth in most empirical researches. The ELG hypothesis is described as a development strategy that focuses on foreign exports while simultaneously aiming to strengthen productive capacity that is consistent with economic growth. This hypothesis includes the promotion of exports and the acquisition of foreign exchange reserves by adopting certain policies supported by advanced technology can potentially benefit economic growth. Exporting is considered a tool for long-term economies of scale. Exports promote economic growth in the domestic market through the use of more technology and skilled labor. This process leads to improved efficiency and productivity in the economy.
In line with the above, it can be argued that there may be a non-linear causal relationship between output, export and import, and awareness of this issue and its extent is of great importance for planners and policy makers. Therefore, how to investigate the relationship between non-linear causality and mutual effects of output, export and import needs to be experimentally investigated in Iran. For this purpose, the present study examines the analysis of the non-linear causality relationship between output, export and import and confirms the hypotheses of import-output growth and export-output growth in Iran using quarterly data during the period 1988-2022. In this regard, the theoretical foundations related to the subject will be examined first, and then some related studies will be reviewed. In the following, the introduced model will be estimated and analyzed and the conclusion will be presented.
Methodology
In this study, the non-linear causality relationship between output, export, and import is investigated and the hypotheses of import-output growth and export-output growth in Iran is examined using a MS-VAR model. This paper employs a MS-VAR model to determine the asymmetric relationship between the variables. In this model, the parameters are time-dependent and the variables in the VAR model behave based on the types of regimes (states) and the transition probabilities between them. This model is used to explore the regime-dependent responses of the output to export and import under different regimes. In the MS model, regimes are expected to pursue a latent random process. One of the most prominent peculiarities of the MS model is its ability to specify the shock performances differently in diverse manners. They are a subset of time series models that are able to analyze the dynamic behavior of variables under different circumstances. In addition, these models are generally suitable for capturing unobserved asymmetries in time series.
Findings
Since the Iranian economy is export-dependent, it seems that in case of structural breaks, the linear correlation method of the model is insufficient to estimate the total unit effect. Therefore, the Markov regime switching vector autoregression model (MSVAR) is used to analyze the nonlinear causality relationship between economic growth, export and import and to confirm the hypotheses of export- output growth and import-output growth. Three main data sets including real GDP, real exports and real imports are considered in logarithmic and differential form. The results of the unit root test show that all variables are at a stationary level. According to the results obtained in table (2), lag 5, which has the lowest value of Akaike and Schwartz, is determined as the optimal lag order.
As can be seen in table (3), in the first stage, the value of the probability value of theχ 2
Discussion and Conclusion
In the present study, the non-linear causality relationship and the confirmation of export-output growth and import-output growth hypotheses in Iran have been investigated using quarterly data during the period from 1988 to 2022. For this purpose, the non-linear approach Markov regime switching vector autoregression model (MSVAR) was used to investigate the non-linear causality relationship.
The results show that the first regime (boom) is more stable and attractive than the second regime (bust). The results obtained from the causality relationship also indicate a two-way non-linear causality relationship and confirm the feedback hypotheses, i.e., export-output growth, import-output growth in Iran.
Empirical analysis of export-led growth (ELG), growth-Led export (GLE), import-led growth (ILG) and growth-Led imports (GLI) hypotheses, are supported by a review of the trade literature and economic growth, which creates verifiable evidence using scientific methods for interpretation. To start with the first hypothesis, ELG is also expressed as the role of exports in economic growth in most empirical researches. The ELG hypothesis is described as a development strategy that focuses on foreign exports while simultaneously aiming to strengthen productive capacity that is consistent with economic growth. This hypothesis includes the promotion of exports and the acquisition of foreign exchange reserves by adopting certain policies supported by advanced technology can potentially benefit economic growth. Exporting is considered a tool for long-term economies of scale. Exports promote economic growth in the domestic market through the use of more technology and skilled labor. This process leads to improved efficiency and productivity in the economy.
In line with the above, it can be argued that there may be a non-linear causal relationship between output, export and import, and awareness of this issue and its extent is of great importance for planners and policy makers. Therefore, how to investigate the relationship between non-linear causality and mutual effects of output, export and import needs to be experimentally investigated in Iran. For this purpose, the present study examines the analysis of the non-linear causality relationship between output, export and import and confirms the hypotheses of import-output growth and export-output growth in Iran using quarterly data during the period 1988-2022. In this regard, the theoretical foundations related to the subject will be examined first, and then some related studies will be reviewed. In the following, the introduced model will be estimated and analyzed and the conclusion will be presented.
Methodology
In this study, the non-linear causality relationship between output, export, and import is investigated and the hypotheses of import-output growth and export-output growth in Iran is examined using a MS-VAR model. This paper employs a MS-VAR model to determine the asymmetric relationship between the variables. In this model, the parameters are time-dependent and the variables in the VAR model behave based on the types of regimes (states) and the transition probabilities between them. This model is used to explore the regime-dependent responses of the output to export and import under different regimes. In the MS model, regimes are expected to pursue a latent random process. One of the most prominent peculiarities of the MS model is its ability to specify the shock performances differently in diverse manners. They are a subset of time series models that are able to analyze the dynamic behavior of variables under different circumstances. In addition, these models are generally suitable for capturing unobserved asymmetries in time series.
Findings
Since the Iranian economy is export-dependent, it seems that in case of structural breaks, the linear correlation method of the model is insufficient to estimate the total unit effect. Therefore, the Markov regime switching vector autoregression model (MSVAR) is used to analyze the nonlinear causality relationship between economic growth, export and import and to confirm the hypotheses of export- output growth and import-output growth. Three main data sets including real GDP, real exports and real imports are considered in logarithmic and differential form. The results of the unit root test show that all variables are at a stationary level. According to the results obtained in table (2), lag 5, which has the lowest value of Akaike and Schwartz, is determined as the optimal lag order.
As can be seen in table (3), in the first stage, the value of the probability value of the
Discussion and Conclusion
In the present study, the non-linear causality relationship and the confirmation of export-output growth and import-output growth hypotheses in Iran have been investigated using quarterly data during the period from 1988 to 2022. For this purpose, the non-linear approach Markov regime switching vector autoregression model (MSVAR) was used to investigate the non-linear causality relationship.
The results show that the first regime (boom) is more stable and attractive than the second regime (bust). The results obtained from the causality relationship also indicate a two-way non-linear causality relationship and confirm the feedback hypotheses, i.e., export-output growth, import-output growth in Iran.
Volume 26, Issue 1 (1-2024)
Abstract
Turkey is a favourable country for sugar beet production due to its climate and soil composition, and it holds a significant position among the countries producing sugar beet. Therefore, in this study, an Autoregressive Integrated Moving Average (ARIMA) was used to project the sugar beet production values for Turkey over the next ten years. The most effective model structure [ARIMA (2, 1, 3)] was created for this purpose using data from 1925 to 2020. The years 2019 and 2020 were utilized as the model’s validation years. When the observed and expected sugar beet production values are compared, the data indicates that the predicted values are slightly lower than the actual ones. The results also show that by 2030, sugar beet production in Turkey would reach 20.5 million tons. This research may help policymakers plan for the storage, export, or import of sugar beets. Also, by using these data, resource waste can be avoided.
Volume 26, Issue 4 (7-2024)
Abstract
Since the 1960s and the reduction in the share of agricultural sector in GDP in different countries, based on extensive forward and backward linkages of the agricultural sector, the concept of agribusiness has been introduced to explain the valuable contribution of agriculture to the national economy. This paper estimates the share of agribusiness in gross domestic product using input-output tables for 1986, 1991, 2001, and 2016. The results showed that the contribution of agribusinesses to GDP was about 2.5 times that of agricultural production (the average share of agribusinesses in 1986-2016 was about 23%, while the corresponding figure for agricultural value added was 9.25%). In a similar trend to developing and developed countries, the share of agribusinesses in GDP had decreased from 27.2 to 17% in 1986-2016. However, the examination of the components of agribusinesses in Iran compared to other countries shows significant differences, which can be attributed to Iran's arid and semi-arid climate, low rate of capital formation, low productivity of production factors, as well as lack of participation in regional and global chains due to long-term sanctions imposed on the economy.