تأثیر رشد مصرف انرژی بر رشد ارزش‌افزوده بخش‌های مختلف اقتصاد ایران: مدل‌های مارکف

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه اقتصاد دانشگاه آزاد اسلامی واحد تهران جنوب

2 استادیار گروه اقتصاد دانشگاه بوعلی سینا

چکیده

رشد اقتصادی از فاکتورهای بسیار مهمی است که باید به‌منظور بررسی تغییرات برنامه‌ریزی‌شده در مصرف انرژی در نظر گرفته شود؛ بر این اساس در این تحقیق با استفاده از داده­های سالیانه 1346 تا 1392، ارتباط بین مصرف انرژی و رشد ارزش‌افزوده بخش­های مختلف اقتصاد ایران بررسی‌شده است نتایج تحقیق حاضر بیانگر اثر مثبت رشد مصرف انرژی بر رشد ارزش‌افزوده بخش صنعت و معدن و حمل نقل کشور در فاز رکود اقتصادی حاکم بر این بخش­های است، از طرفی در بخش کشاورزی، در رژیم رکود شاهد اثرگذاری منفی رشد مصرف انرژی بر رشد ارزش‌افزوده این بخش هستیم. نتایج بیانگر این است که در فاز رونق، رشد مصرف انرژی دارای اثر معنی­داری بر ارزش‌افزوده بخش­های مختلف اقتصاد کشور نمی­باشد. نتایج فوق بیانگر این است که اجرای سیاست­های مانند هدفمندی یارانه­های انرژی، درصورتی‌که زمینه­ساز کاهش مصرف انرژی شود، بسته به شرایط حاکم بر اقتصاد کشور می­تواند اثرات متفاوتی را بر روی ارزش‌افزوده بخش­های مختلف اقتصاد ایران داشته باشد، درصورتی­که چنین سیاست­های زمینه‌ساز رکود اقتصادی گردند یا در شرایط رکود حاکم بر اقتصاد کشور اجرا گردند، می‌توانندزمینه­ساز رکود فزاینده‌تری در اقتصاد شوند.

کلیدواژه‌ها


عنوان مقاله [English]

The Effect of Energy Consumption Growth on Value-added Growth of Economic Sectors: Markov Models

نویسندگان [English]

  • mohammad khezri 1
  • mohsen khezri 2
چکیده [English]

In this paper an attempt is made to study the impact of energy consumption growth on forming regimes of low and high value-added growth of economic sectors of Iran economy by using seasonal data from 1346 to 1392. So, in some models, Markov switching model with the supposition of fixed transition probabilities by value-added growth of economic sectors variable were expanded. According to modeling results, increase in energy consumption growth, leads to increase in value-added growth of economic sectors in Iran economy. In addition in modeling value-added growth of agriculture group and value-added growth of manufacturing and mining group, the positive effect with motion of low value-added growth regime to high value-added growth regime is increased. also in value-added growth of transportation storage and communications group, the positive effect for both regimes are great.

کلیدواژه‌ها [English]

  • Energy Consumption
  • value-added growth of economic sectors
  • Markov switching model
صادقی، سیدکمال؛ قمری، نیر و فشاری، مجید (1993)، بررسی رابطه علی مصرف انرژی و تولید ناخالص داخلی در کشورهای منطقه MENA (رهیافت گشتاور تعمیم‌یافته در داده­های تابلویی. پژوهشنامه اقتصادی، 17: 121-140.
دامن­کشیده، مرجان؛ عباسی، احمد؛ عربی، حسین و احمدی، حسن (1392)، بررسی رابطه مصرف انرژی و رشد اقتصادی، مطالعه موردی: کشورهای منتخب سند چشم‌اندازبیست‌ساله ایران. فصلنامه سیاست­های راهبردی و کلان، 2: 61-97.
Ang, A.G. and Bekaert, G. (1998); Regime Switches in Interest Rates. Stanford University. Research Paper 1486.
Apergis, N. and Payne, J.E. (2009a); Energy consumption and economic growth inCentral America: evidence from a panel cointegration and error correctionmodel. Energy Economics 31: 211-216.
Apergis, N. and Payne, J.E. (2009b); Energy consumption and growth: evidence from theCommonwealth of Independent States. Energy Economics 31: 641-647.
Apergis, N. and Payne, J.E. (2010); Energy consumption and economic growth in SouthAmerica: evidence from a panel error correction model. Energy Economics 32: 1421-1426.
Asafu-Adjaye, J. (2000); The relationship between energy consumption, energyprices and economic growth: time series evidence from Asian developingcountries. Energy Economics 22: 615-625.
Belloumi, M. (2009); Energy consumption and GDP in Tunisia: cointegration andcausality analysis 37 (7): 2745-2753.
Cologni, A. and Manera, M. (2008); Oil Prices, Inflation and Interest Rates in a Structural Cointegrated VAR Model for the G-7 Countries. Energy Economics 38: 856-888.
Clements, M.P. and Krolzig, H.M. (2000); Modeling Business Cycle Features using Switching Regimes Models. Discussion Paper, Institute of Economics and Statistics Oxford.
Clements, M.P. and Krolzig, H.M. (1998); A Comparison of the Forecast Performance of Markov-switching and Threshold Autoregressive Models of US GNP. Econo-metrics Journal1, C47-C75.
Cologni, A. and Manera, M. (2009); The Asymmetric Effects of Oil Shocks on Output Growth: a Markov-Switching Analysis for G7 Countries. Economic Modelling 26, 1–29.
Diebold, F.X. and Rudebusch, G.D. (1996); Measuring Business Cycles: a Modern Perspective. Review of Economics and Statistics 78, 67-77.
Diebold, F.X. (1986); Modeling the Persistence of Conditional Variance: a Comment. Econometric Reviews 5: 51-56.
Eggoh, J.C.; Bangake, C. and Rault, C. (2011); Energy consumption and economic growth revisited in African countries. Energy Policy 39: 7408-7421.
Esso, L.J. (2010); Threshold cointegration and causality relationship between energyuse and growth in seven African countries. Energy Economics 32: 1383-1391.
Fallahi, F. (2011); Causal relationship between energy consumption (EC) and GDP: A Markov-switching (MS) causality. Energy 36: 4165-4170.
Garcia, R. and Perron, P. (1996); An Analysis of the Real Interest Rate under Regime Shifts. Review of Economics and Statistics 78: 111-125.
Gregory, A.W. and Hansen, B.E. (1996a); Residual-based tests for cointegration inmodels with regime shifts. Journal of Econometrics 70: 99-126.
Gregory, A.W. and Hansen, B.E. (1996b); Tests for cointegration in models with regimeand trend shifts. Oxford Bulletin of Economics and Statistics 58: 555-560.
Hamilton, J.D. and Susmel, R. (1994); Autoregressive conditional heteroscedasticity and changes in regime. Journal of Econometrics 64: 307-333.
Hamilton, J.D. (1989); A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57: 357-384.
Huang, B.N.; Hwang, M.J. and Yang, C.W. (2008); Causal relationship between energyconsumption and GDP growth revisited: a dynamic panel data approach.Ecological Economics 67: 41-54.
Johansen, S. (1988); Statistical analysis of cointegration vectors. Energy Journal ofEconomics Dynamic and Control 12: 231-254.
Jumbe, C.B.L. (2004); Cointegration and causality between electricity consump-tion and GDP: empirical evidence from Malawi. Energy Economics 26, 61-68.
Kim, C.J. and Nelson, C.R. (1999); In: State-Space Models with Regime Switching. Massachussetts Institute of Technology Press, Cambridge.
Kraft, J. and Kraft, A. (1978); On the relationship between energy and GNP. Journal ofEnergy and Development 3, 401-403.
Krolzig, H.M. (1997); Markov Switching Vector Autoregressions: Modeling, Statistical Inference and Application to Business Cycles Analysis.Lecture Notes in Economics and Mathematical Systems, Volume 454. Springer, Berlin (out of print).
Kim, C.J. and Nelson, C.R. (1998); Business Cycles Turning Points, A New Coincident Index and Tests of Duration Dependence based on a Dynamic Factor Model with Regime Switching. Review of Economics and Statistics80, 188-201.
Lee, C.C. (2005); Energy consumption and GDP in developing countries: a coin-tegrated panel analysis. Energy Economics 27: 415-427.
Lee, C.C. and Chang, C.P. (2005); Structural breaks, energy consumption, and economicgrowth revisited: evidence from Taiwan. Energy Economics 27: 415-427.
Lee, C.C. and Chang, C.P. (2008); Energy consumption and economic growth in Asianeconomies: a more comprehensive analysis using panel data. Resource andEnergy Economics 30: 50-65.
Mahadevan, R., Asafu-Adjaye, J. (2007); Energy consumption, economic growth andprices: a reassessment using panel VECM for developed and developingcountries. Energy Policy 35: 2481-2490.
Odhiambo, N.M. (2010); Energy consumption, prices and economic growth in threeSSA countries: a comparative study. Energy Policy 38 (5): 2463-2469.
Ozturk, I.; Aslan, A. and Kalyoncu, H. (2010); Energy consumption and economic growthrelationship: evidence from panel data for low and middle income countries.Energy Policy 38: 4422-4428.
Psaradakis, Z. and Spagnolo, N. (2003); On the Determination of the Number of Regimes in Markov–Switching Autoregressive Models. Journal of Time Series Analysis 24: 237-252.
Toda, H.Y. and Yamamoto, T. (1995); Statistical inference in vector autoregressions withpossibly integrated process. Journal of Econometrics 66: 225-250.
Wang, J.; Wang, Y.; Zhou, J.; Zhu, X. and Lu, G. (2011); Energy consumption and economic growth in China: A multivariate causality test. Energy Policy 39: 4399-4406
Wolde-Rufael, Y. (2006); Electricity consumption and economic growth: a timeseries experience for 17 African countries. Energy Policy 34: 1106-1114.
Wolde-Rufael, Y. (2009); Energy consumption and economic growth: the AfricanExperience revisited. Energy Economics 31: 217-224.
Zhang, Y.J. (2011); Interpreting the dynamic nexus between energy consumption and economic growth: Empirical evidence from Russia. Energy Policy 39: 2265-2272.