Macroeconomics
Hadi Keshavarz; Ramezan Hosseinzadeh
Abstract
1- INTRODUCTION
Investigation of the importance and the impact of various factors on the economic growth of countries is crucial in short-term and long-term planning in various countries. Traditional theories and models of economic development only consider capital and labor as economic growth ...
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1- INTRODUCTION
Investigation of the importance and the impact of various factors on the economic growth of countries is crucial in short-term and long-term planning in various countries. Traditional theories and models of economic development only consider capital and labor as economic growth factors for nations and regions. Today, economists consider innovation, along with knowledge and technology, to be one of the fundamental variables in the economic development and development of countries.
Knowledge and innovation can generate social welfare in diverse regions and countries and contribute to achieving sustainable economic growth. In this regard, it is crucial to note that the path of innovation development varies across regions and countries, and that a distinct innovative geography is created based on these differences. The issue of inter-regional or inter-country spillover effects of various variables, such as innovation spillovers, is a second crucial aspect of economic growth and development planning in different regions or countries. Thus, innovation can impact both the economic development of the innovating country and the economic growth of neighboring countries with trade linkages to that country. Examination the spatial dimension of the problem will be crucial for determining how spillovers occur and their effectiveness in the innovation process as well as economic growth and development, whereas excluding inter-regional (inter-country) effects will bias the results and misleading results. On the other hand, considering the inter-regional (inter-country) effects of innovation and other variables in the model can help in the planning of regional development in different countries.
2- THEORETICAL FRAMEWORK
According to new theories, there are four distinct categories of innovation: product innovation, process innovation, organizational innovation, and marketing innovation. There is substantial evidence that various categories of innovation have distinct economic effects in countries. These differences are primarily attributable to variations in the level of pertinent externalities (spillovers) and the capacity of innovators to internalize the public benefits of these activities (fit). Thus, innovative knowledge penetrates the production process in two different ways. The first instance is when a company utilizes new technical knowledge developed during the production process. The second consequence is the spillovers of such knowledge. However, knowledge diffusion in other innovation institutions can only be observed once innovation and technology have reached a certain level.
The concept of knowledge spillover is closely associated with the correlation effect, where in the recipient of an innovation assimilates it to facilitate economic advancement. The spillover effect has the potential to yield beneficial outcomes by fostering innovation and facilitating economic progress, but it can also have negative consequences. The adverse impact of knowledge spillover primarily arises from external circumstances, as well as the inherent uncertainties and risks associated with research and development endeavors. Consequently, the inability of spillovers to fully realize the benefits of their research and development endeavors diminishes enterprises' motivation to allocate resources towards innovation. The positive impact of knowledge spillover is directed towards individuals or organizations that possess absorptive potential, enabling them to effectively assimilate and utilize sophisticated information and technology.
3- METHODOLOGY
The primary objective of the present study is to examine the direct and spillover effects of innovation on economic growth within the D8 group of countries during 2012 -2021. This investigation will be conducted through the utilization of a spatial econometric model. Spatial econometrics is widely regarded as a major development in the field of estimation, having emerged alongside the introduction of the "New Economic Geography (NEG)" theory. This technique is associated with the research conducted by Krugman (1991), Fujita, Krugman, and Venable (2001), as well as Venables and Puga (1998). The econometric models under consideration has the capability to incorporate both spillover and indirect impacts of variables, in addition to the direct effects that are typically addressed in classic econometrics.
4- RESULTS & DISCUSSION
Based on the results of the model, the direct effect of innovation index on economic growth has been positive and significant. Also, the indirect effects of this variable have been positive and significant. Therefore, it can be said that the amount of innovation in the studied countries has both domestic and international spillover effects (through the establishment of trade relations) on the economic growth of the countries.
5- CONCLUSIONS & SUGGESTIONS
Based on this, it is suggested that the studied countries pay special attention to the issue of innovation. Provide the necessary incentives to strengthen innovation in these countries, such as paying special attention to patents. Because having a patent is one of the motivating factors for innovation and further to achieve new technologies. This can be the basis for creating new processes in production, inventing new methods in countries. Paying attention to the spillover and indirect effects of innovation can also be very important. Based on this, it can be suggested that countries should pay attention to the fact that they prioritize the trade of goods with more knowledge (accumulation of knowledge and its transfer) in order to benefit more from the spillover effects of innovation. The higher the trade and especially the import of goods with knowledge and innovation, the countries can use the knowledge and innovation stored in these goods to strengthen knowledge and innovation within the country and economic growth will be strengthened.
Marziyeh Esfandiari; Ahmad Vandaki
Abstract
Expended Abstract: Introduction Recently, the role of industrial structure on regional employment has attracted much attention. One of the branches of these studies, focusing on Jacobs (1960), suggests that more diversity of industrial structure leads to employment and protects the areas against the ...
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Expended Abstract: Introduction Recently, the role of industrial structure on regional employment has attracted much attention. One of the branches of these studies, focusing on Jacobs (1960), suggests that more diversity of industrial structure leads to employment and protects the areas against the adverse effects of external shocks. Jacobs's hypothesis has been validated experimentally in many studies. These studies provide a positive relationship between regional economic diversification and employment growth. Following the increasing trend of studies related to economic diversity on employment growth, regional employment models have also been focused on considering spatial dependency. In terms of industry structure, the more diverse areas can be benefited from their externalities, while more diversity within a region improves technical innovations and their impacts. According to Iran's provinces' employment rate, we found a significant regional dispersion between different regions. Although regional employment growth has received more attention from scholars and policymakers than ever before, few empirical studies have been conducted on the relationship between R&D specialization and diversification and regional employment growth. Therefore, this paper aimed to investigate the spatial effects of R&D specialization and diversification on employment growth in the Iranian provinces from 2005 to 2015. Methodology For this study, R&D specialization and diversification in Iran's provinces were first measured, and then the spatial effects of each of these variables on the employment growth of Iranian provinces were estimated using an econometric model. According to Chen& et al. (2015), the Gini index has been used to measure the degree of R&D specialization. Following Ocaner et al. (2018), total diversity is measured by total entropy and related and unrelated diversification. Results and Discussion Given that this study's spatial unit of choice is based on administrative boundaries rather than economic regions, it might be expected that spillovers would exist from the neighboring region. So a full Spatial Durbin Model (SDM) specified, which takes the form of the following: (1) The SDM allows for the observed value of neighboring region employment growth () and other regional characteristics of neighboring regions' employment () to impact a regions’ employment growth rate. The coefficient shows the impact of employment growth in neighboring regions on the employment growth rate of a particular region or, in other words, the spatially lagged dependent variable. (Ocaner et al., 2018) According to Table 1, the results of the estimation of equation1 showed that employees in the sector of services and relevant or irrelevant specialization and diversification had a significant positive effect on employment growth so that the effect of specialization was more than that of irrelevant diversification and the effect of irrelevant diversification was greater than that of the relevant diversification. Table 1- The results of estimation Total Effect Indirect Effect Direct Effect Coefficient Variables 0/0471102 (0/031) -0/0185246 (0/332) 0/0656348 (0/000) 0/072241 (0/000)[1] Se -0/0025043 (0/059) -0/0031737 (0/016) 0/0006693 (0/275) 0/001489 (0/005) I -0/3063919 (0/948) -2/219845 (0/594) 1/913453 (0/027) 2/730136 (0/000) S 0/5342869 (0/869) 1/750773 (0/539) -1/216486 (0/055) -1/779766 (0/000) Ss 0/0063199 (0/152) 0/0044254 (0/272) 0/0018945 (0/022) 0/0008242 (0/074) Cp 0/0455051 (0/026) 0/0413635 (0/023) 0/0041415 (0/186) -0/0017879 (0/263) U 5/291128 (0/011) 1/46458 (0/421) 3/826548 (0/000) 1/047751 (0/000) Ue -2/636651 (0/010) -2/894039 (0/002) 0/257388 (0/567) 0/7295003 (0/045) Re -0/0322283 (0/000) w*se -0/0014365 (0/027) w*i -0/2231892 (0/889) w*s 0/8760202 (0/428) w*ss -0/0019838 (0/063) w*cp -0/0056924 (0/162) w*u 0/0448905 (0/920) w*ue -2/34029 (0/000) w*re 0/1652477 rho Conclusions and Suggestions The findings of this study supported the Jacobs hypothesis for the Iranian provinces. Also, there was a reverse U-shaped relation between economic specialization and employment growth, indicating that as R&D specialization increased, provincial employment growth increased, but the specialization led to a decrease in employment growth at higher levels. Therefore, as R&D specialization increased, productivity increased, and it was replaced by employment growth. So, the Marshall hypothesis was supported by a range of specialization. For more precise analysis, direct, indirect, and total effects have been calculated. The indirect effect measures the effect of changes in the region j on the dependent variable in region i, which i≠j. The direct effect measures a particular explanatory variable in region i on the dependent variable in region i. The calculation of direct and indirect effects showed that increasing R&D specialization in one region could affect employment growth of the same region; however, it had no significant effect on the adjacent regions' employment growth. Increasing the irrelevant diversification in each region also led to employment growth in the same region, but increasing the relevant diversification in the adjacent regions resulted in a decrease in the host region's employment growth. Increasing the average income of the adjacent regions decreases the host region's growth rate and leads to the host region's employment growth. Thus, the limited influence of entropy related to the growth of provincial employment indicates evidence of transmission mechanisms between regions. Indirect results indicate a significant spatial spillover, and the evidence from estimating direct effect indicates that geography is essential in terms of neighborhood zones. Therefore, in developing programs and policies of increasing employment, it is necessary to pay attention to the potentials of the region and the influence of neighboring areas. It is suggested to deploy industries with more diversity in provinces with lower employment rates. So, creating industrial clusters as a unit for all of the provinces is not a suitable policy. Also, increasing the specialization index by increasing R&D expenditures in areas with a high unemployment rate can increase employment. From this perspective, granting specific and increasing tax credits to the firms in exchange for R&D can be helpful in increasing the employment rate of the province. The numbers in parentheses are prob.
Mohammad Reza Eskandari Ata; nader mehregan; Alireza Pourfaraj; Saeed Karimi Petanlar
Abstract
Introduction Regional unbalanced growth and the factors affecting it are one of the most important economic issues in developing countries. One of the characteristics of developing countries is the presence of significant regional inequalities. The existence of this phenomenon is one of the main impediments ...
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Introduction Regional unbalanced growth and the factors affecting it are one of the most important economic issues in developing countries. One of the characteristics of developing countries is the presence of significant regional inequalities. The existence of this phenomenon is one of the main impediments to balanced development in these countries. One of its specific consequences is the creation of inequalities and the consolidation and expansion of deprivation. Inequality alongside widespread poverty can provide grounds for public discontent and thus be one of the concerns of socio-economic policymakers. Considering the importance of balanced regional development in the country and the environmental-spatial potentials and political characteristics of the provinces, this study considers the effects of environmental and political factors on the distribution of inequality in provinces of Iran, considering the neighborhood effects. Theoretical framework Environmental differences play a decisive role in the distribution of regional inequality. At the early stage of economic development, environmental conditions are one of the most determining factors. For example, favorable environmental conditions are often the basis for rapid growth in developing countries. Although the effects of environmental conditions on regional development at higher levels are less pronounced, the specific functions of these factors are still unknown in many countries. In economic literature, several environmental factors influence and are influenced by the distribution of regional inequality. Variables such as cities with coastal boundaries, commercial areas, tourism, water resources, railways, border areas and urban development are among the areas considered in regional studies. Modern governments, unwittingly or unwillingly, engage in various economic policies such as monetary policy, fiscal policy, and commercial policy. Applying these policies shift interests and the pattern of income distribution and create winners and losers across different segments and groups of society, thereby changing regional inequalities. Methodology Spatial inequality refers to situations in which different spatial or geographical units of some variables are at different levels. In the present study, after investigating the regional inequality with regard to the effects of spillover in the provinces, an assessment of the environmental and political factors on it during 2006 to 2015 has been examined. The explanatory variables were compiled according to the purpose of the study, based on environmental and political factors that cause regional imbalances and also according to the statistical constraints of the country. According to the theoretical foundations, identifying variables in previous studies as well as statistical feasibility in the country, from three models has been used to investigate the impact of environmental and political factors on regional inequality. The variables used include urban index, dummy variable for business areas, tourist and religious centers, the logarithm of GDP, ratio of government expenditure to GDP, Ratio of education cost to the government expenditure and the members of parliament. Results and discussion The evaluation of Population-Weighted Coefficient of Variation (PW-CV) indices show that Iranian provinces during the research period have been very inadequate. The results of estimating Spatial Autoregressive with Autoregressive Error (SARAR) regression models indicate a strong spatial dependence among the provinces. So that the inequality index of each province with an approximate coefficient of 45% is affected by the economic inequality in neighborhood provinces. In the analysis of environmental factors affecting regional inequality; urban development, water resources and tourism have a negative relationship with provinces' inequality and as each of these factors increases, the inequality index of the provinces will decrease. But religious and commercial provinces have a positive impact on economic inequality; as a result, inequalities are higher in these provinces. Results of the estimation of the impact of political variables on regional inequality show that the provinces with a more gross domestic product, have a higher inequality index. Moreover, the larger the size of the government in the provinces, the more economic inequality. Also, increasing the share of education costs from provincial budgets increase regional inequality and in the provinces where the number of members of parliament is higher, there are more economic inequalities. Conclusions and suggestions According to the results of the present study, the importance of the distribution of inequality in different provinces and the effects of neighborhoods with regard to environmental and political factors are overemphasized. Governments and trusted entities in different areas can be more successful in delivering social justice and reducing regional inequalities by designing and implementing management policies tailored to each province's environmental and political potentials. Managing water resources, paying attention to tourism, controlling suburbs in big and religious cities, and implementing income redistribution policies are some of the policies that can be implemented in environmental and operational areas. Reducing government tenure and administrative bureaucracy are also some of the factors that will be effective in reducing regional inequalities.
