بررسی اجتماعی سیاسی و زیست محیطی رشد صنعتی ایران
محورهای موضوعی : فصلنامه اقتصاد محاسباتی
محمد طاهری
1
,
کیا پارسا
2
*
,
ناصر میکائیل وند
3
1 - دانشجوی دکتری واحد تهران شمال
2 - تهران شمال
3 - Department of Mathematics, Central Tehran Branch, Islamic Azad University, Tehran, Iran
کلید واژه: تولید صنعتی, صادرات صنعتی, مولفه خطا 3 مرحله حداقل مربع, مدل دادههای تابلویی همزمان, مهندسی سیستمهای اجتماعی-اقتصادی.,
چکیده مقاله :
برای ارزیابی عملکرد زیرسیستمهای صنعتی ایران از نظر اجتماعی (جینی)، سیاسی (دموکراسی)، محیطی (انتشار CO2) و ارزیابی عملکرد زیرسیستمهای صنعتی ایران، یک سیستم دادههای پانل همزمان معادلات ساخته و آن را با مولفه خطای 3SLS (با TSP و Eviews) تخمین زدیم. متغیرهای اقتصادی نتایج نشان می دهد که افزایش ارزش افزوده صنعتی منجر به آلودگی بیشتر (از نظر CO2) و تولید ناخالص داخلی نیز می شود، در حالی که افزایش ارزش افزوده و صادرات باعث کاهش ضریب جینی می شود. اما حتی افزایش دستمزدهای واقعی باعث افزایش جینی می شود. وقتی ضریب جینی افزایش یابد، دستمزد واقعی نیروی کار به شدت کاهش می یابد. افزایش نرخ تعرفه باعث افزایش تقاضا برای نیروی کار و صادرات و کاهش واردات زیربخش ها می شود و افزایش نرخ بهره باعث افزایش ارزش افزوده و صادرات می شود. همچنین نتایج نشان میدهد که انباشت سرمایه انسانی تأثیر مثبتی بر تولید و کاهش واردات زیربخشها دارد. در مجموع میتوان گفت که زیربخشهای صنعتی که بر اساس کدهای 2 رقمی ISIC تعریف میشوند، مسیر توسعه بسیار پیچیدهای دارند که سیاستگذاران را برای برنامهریزی یک سیاست صنعتی مطلوب برای اقتصاد و سایر بخشهای آن با چالشهای جدی مواجه میکند.
Extended Abstract
Purpose
In this paper, we study whether the industrial sector of Iran, and the economy as a whole, could tolerate these pressures to manage the society according to guidance of government plan known as resistive economy. For this purpose, we chose an industrial engineering view to construct a model for socio-political and economic systems which together constitute a grand system of industrial growth and development at the 1974-2009 period exactly before declaration of the plan to study the potentials of grand system according to the social, political, environmental and economic criteria and set a hypothetical system of equations according to industrial engineering view.
We construct a panel data model from the sector specific statistical data of industry-specific variables and will setup with them a system to unfold the facts of this sector and see whether it has the sufficient and necessary characteristics to perform the objectives and desires and estimate the hypothetical grand system by error component 3 stage least square (EC3SLS) and will draw a clear picture of history of industrial sub-sectors and their accordance to objectives of the plan.
Methodology
We construct a system out of four subsystems of Economic, social, political and environmental dimensions of industrial growth of Iran in 36 years, 5 years before Islamic Revolution and 31 years after that. The main reason why we employ this time period is that first, the statistical availability of data on these aspects in terms of 2degit ISIC codes, and then, tracking the historical evolution of the industrial sector.
Finding
Based on the path the industrial sector of Iran followed from 1974 up to 2009, we construct a simultaneous panel data model and the claims that industrial sector is not capable of delivering inclusive growth, and good performance in resistive economy, is tested. The period of study is from 1974 to2009, the last year in which data in terms of ISIC 2-digit codes are available. This panel data approach (ec3sls) is used to study the effects of market competition and foreign direct investment on the technical efficiency of firms in Indonesia. we put together 4 subsystems of social, economic, environmental and political, and estimate the grand system.
conclusion
As a conclusion, we need a new plan for resistive economy and other plans to solve new problem faced industrial sector. Especially now that we encounter other crisis such as covid-19 viruses, recession in the world economy and slowing down the price of crude oil, the main export of Iran and provider of foreign exchange necessary to run the path of development and industrial growth.
-Alaedini, P. and Ashrafzadeh, H.R. (2016). Iran’s Post-Revolutionary Social Justice Agenda and Its Outcomes: Evolution and Determinants of Income Distribution and Middle-Class Size. Economic Welfare and Inequality in Iran, 15-45. Retrieved from https:// doi.org/ 10.1057/978-1-349-95025-6_2/ (In Persian)
-Alsaleh, M., Abdul-Rahim, A.S. and Mohd-Shahwahid, H.O. (2017). An empirical and forecasting analysis of the bioenergy market in the EU28 region: Evidence from a panel data simultaneous equation model. Renewable and Sustainable Energy,80(12),1123-1137. Retrieved from https:// doi.org/ 10.1016/j.rser.2017.05.167/
-Ashrafi, y. (2002). Estimating the effects of trade policies on industrial exports. Journal of Economic Research and Policies, 10(21),71-98. (In Persian)
-Ashrafzadeh, S.H.R. and Asgari, M. (2006). The Effects of Trade and Exchange Rate Policies on Industrial Goods in Iran. Iranian Journal of Trade Studies (IJTS), 10(39), 83-108. SID. https://sid.ir/paper/7177/en/ (In Persian)
-Ashrafzadeh, S.H.R and Rahmani, M. (2015), The effects of monetary, fiscal, exchange rate, and trade policies on the export and employment of industrial sectors of Iran. Quarterly journal of Applied Economic studies Iran, 4(15),133-148. (In Persian)
-Bairam, E. (1990), Government size and Economic Growth: The African Experience 1960-85. Applied Economics, 22(10),1427-1435. Retrieved from https:// doi.org/ 10.1080/00036849000000113/
-Baltagi, Badi. H. and Liu, L. (2009). A note on the application of EC2SLS and EC3SLS estimators in panel data models. Statistics & Probability Letters,79(20),2189-2192.
Retrieved from https:// doi.org/10.1016/j.spl.2009.07.014/
-Baltagi, Badi. H. and Deng, Y. (2015). EC3SLS Estimator for a Simultaneous System of Spatial Autoregressive Equations with Random Effects. Econometric Reviews, 34(6-10), 659-694. Retrieved from https://doi.org/10.1080/07474938.2014.956030
-Baradaran, V. and Mohammadi, S.H. (2016). The Effects of Macroeconomic Variables on Industry Sub Sectors Value Added: An Econometrics Approach.
Journal of Trade Studies ,20(78) ,29-60. Retrieved from http://dor.isc.ac/
20.1001.1.17350794.1395.20.78.2.1/
-Behar, A. and Edwards, L. (2005). Estimating elasticities of demand and supply for South African manufactured exports using a vector error correction model. The Center for the study of African Economics, Working paper series paper 204, 1-16.
-Bernard, A.B., Bradford, B.J. and Schott, P.K. (2003). Falling Trade Costs, Heterogeneous Firms, and Industry Dynamics. National Bureau of Economic Research (NBER), Working Paper 9639. Retrieved from https://doi.org/ 10.2139/ssrn.392340/
-Enders, W. and Jun, M. (2011). Sources of the great moderation: A time-series analysis of GDP subsectors. Journal of economic Dynamics and control, 35(1),67-79. Retrieved from https://doi.org/10.1016/j.jedc.2010.07.008/
-Esquivias, M. A. P. and Harianto, S.K. (2020). Does competition and foreign investment spur industrial efficiency? firm-level evidence from Indonesia. Heliyon, 6(8), 1-10. Retrieved from https://doi.org/ 10.1016/j.heliyon. 2020.e04494/
-Falihi, N. and Amini, A. (2000). Study on the Effects of money volume and Banking Facilities On the supply and demand of labor force. the ninth conference of monetary and foreign exchange Policies, the Institute of money and Banking Research, Iran, Tehran.
-Hsiao, C. and, Zhou, Q. (2015) Statistical inference for panel dynamic simultaneous equations models. Journal of Econometrics,189(2),363-396. Retrieved from https://doi.org/10.1016/j.jeconom.2015.03.031/
-Jalali Naeini, S.A.R. and Nazifi, F. (2001). Asymmetric Effects of Monetary Shocks on Output. Iranian Journal of Economic Research,3(9),13-41. (In Persian)
-Landau, D. (1986). Government and Economic Growth in the Less Developed Countries: An Empirical Study for 1960-1980. Economic Development and Cultural change, 35(1),35-75.
-Lindauer, D. L. and Velenchik, A, D. (1992). Government spending in development countries: Trends, Causes and consequences. The world Bank Research observer, 7(1),59-78.
Retrieved from https://doi.org/10.1093/wbro/7.1.59/
-Lundberg, M. and Squire, L. (2003). The simultaneous evolution of growth and inequality. The economic journal, 113(487) ,326-344. Retrieved from https://doi.org/10.1111/1468-0297.00127/
-Melitz, Marc J. (2003). The Impact of Trade on Intra‐Industry Reallocations and Aggregate Industry Productivity. Journal of the Econometric society,71(6),1695-1725.
-Moller, N. F. (2016). Energy Demand, Substitution and Environmental Taxation: An econometric analysis of eight subsectors of the Danish economy. Energy Economics,61,97-109.
Retrieved from https://doi.org/10.1016/j.eneco.2016.10.004/
-Nazari, M and Gouharian, F. (2002). The study on the effects of monetary policy variables on Employment of Main Economic sector in Iran (1345-1378), Journal of Economic Research,37(1),187-207. (In Persian)
-Ram, R. (1986). Government Size and Economic Growth: A New Framework and Some Evidence from Cross-Section and Time-Series Data. The American Economic Review, 76(1),191-203.
-Rodrick, D. (2005). Why we learn nothing from regressing economic growth on policies, Seoul Journal of Economics, 25(2),137-151.
-Shahbazi, K. and Karimzadeh, E. (2015). Impacts of Monetary and Fiscal Policies on Value Added of Industrial Sector in Iran in Line with the General Policies of the Industrial Sector. A Quarterly journal of Macro strategic policies, 2(8),93-110. (In Persian)
- Lin, X., Zhang, Y. and Zou, C. (2019). CO2 emission characteristics and reduction responsibility of industrial subsectors in China. Science of the Total Environment,699,134386.
Retrieved from https://doi.org/10.1016/j.scitotenv.2019.134386/
-Yang, H., Zhengnan L., Xunpeng, S., Isaac, A. M., Yusen, L. and Weijian, C. (2021). Multi-region and multi-sector comparisons and analysis of industrial carbon productivity in China. Journal of Cleaner Production, 279, 123623. Retrieved from https://doi.org/10.1016/j.jclepro.2020.123623/
-Yang, K. and Lung-fei, L. (2019). Identification and Estimation of Spatial Dynamic Panel Simultaneous Equations Model. Regional Science and Urban Economics, 76, 32-46.
Retrieved from https://doi.org/10.1016/j.regsciurbeco.2018.07.010/
-Yeaple, S. R. (2005). A simple model of firm heterogeneity, international trade, and wages. Journal of international Economics, 65(1),1-20. Retrieved from https://doi.org/10.1016/j.jinteco.2004.01.001/