(IJES) Shiraz University (Iranian Journal of Economic Studies (IJES 2322-1402 Shiraz University 15 10.22099/ijes.2018.30437.1475 مقاله پژوهشی تکانه احساسی و حباب های قیمت سهام در چارچوب الگوی تعادل عمومی پویای تصادفی: مطالعه موردی ایران تکانه احساسی و حباب های قیمت سهام در ایران اسدی احسان گروه اقتصاد، دانشکده اقتصاد و مدیریت، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران زارع هاشم گروه اقتصاد، دانشکده اقتصاد و مدیریت، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران ابراهیمی مهرزاد گروه اقتصاد، دانشکده اقتصاد و مدیریت، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران پیرایی خسرو گروه اقتصاد، دانشکده اقتصاد و مدیریت، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران 01 12 2018 7 2 115 150 10 08 2018 22 10 2018 Copyright © 2018, Shiraz University. 2018 https://ijes.shirazu.ac.ir/article_5022.html

در این مقاله یک الگوی DSGE بیزین از سیکل‌های تجاری حقیقی با هدف شناسایی عوامل شکل دهنده حباب قیمتی بازار سهام تهران تصریح شده است. الگوی مذکور در 2 سناریو انجام شده است: در سناریو اول مدل پایه‌ای تحقیق با وجود شوک احساسی بررسی می‌شود. در سناریو دوم تنها شوک احساسی در مدل حضور ندارد. بر اساس نتایج حاصل شده از براورد درستنمایی نهایی مدل بر اساس تقریب لاپلاس، مدل پایه‌ای با داده‌های واقعی و ساختار اقتصاد ایران سازگارتر است، لذا شوک احساسی در ایجاد نوسان در قیمت سهام و متغیرهای اقتصاد کلان ایران نقش مهمی داشته است. بر اساس نتایج تجزیه واریانس مدل نیز شوک احساسی به عنوان مهمترین منبع نوسانات حباب و به دنبال آن نوسانات قیمت سهام معرفی شده است. این شوک انعکاس دهنده باورهای خانوارها در مورد اندازه نسبی حباب قدیمی نسبت به حباب جدید می‌باشد و از طریق محدودیت-های اعتباری به اقتصاد واقعی انتقال می‌یابد. به این ترتیب این شوک بخش عمده‌ای از نوسانات مصرف و محصول را نیز بیان می‌کند. شوک احساسی حدود 86 درصد از نوسانات قیمت سهام، 47 درصد از نوسانات مصرف و 39 درصد از نوسانات محصول را توضیح می‌دهد.

 حباب قیمتی بازار سهام الگوسازی DSGE تکانه احساسی ادوار تجاری حقیقی ایران References  Abbasian, E., Farzanegan, E., & Nasiroleslami, E. (2016). Price bubble anomalies in Tehran stock exchange: Limits to arbitrage approach. Quarterly Journal of Economic Research and Policies, 23(76), 75-92. Abbasian, E., Mahmoudi, V., & Farzanegan, E. (2010). Bubble identification in Tehran's stock exchange: Evidence based on time-varying present value model. Journal of Accounting and Auditing Review, 17(2), 75-92. Amini, A. R., & Haji Mohammad, N. (2005). Estimation of time series of the capital stock in Iran’s economy during 1967-2002. The Journal of Planning and Budgeting, 10(1), 53-86. Asadi, G. H., Hamidi Zadeh, M. R., & Soltani, A. (2006). A survey of stock price bubbles in Tehran stock exchange on the basis of size and type of industries. Empirical Studies in Financial Accounting Quarterly, 4(14), 39-71. Balcilar, M., Gupta, R., Jooste, C., & Wohar, M. (2016). Periodically collapsing bubbles in the South African stock market. Research in International Business and Finance, 38, 191-201. Bashiri, S., Pahlavani, M., & Boostani, R. (2016). Stock market fluctuations and monetary policy in Iran. Journal of Economic Modeling Research, 6(23), 103-157. Bayat, M., Afshari, Z., & Tavakolian, H. (2016). Monetary policy and stock price index in DSGE models framework. Quarterly Journal of Economic Research and Policies, 24(78), 171-206. Beaudry, P., & Portier, F. (2006). Stock price, news, and economic fluctuations. American Economic Review, 96(4), 1293-1307. Beltratti, A., & Morana, C. (2006). Breaks and persistency: Macroeconomic causes of stock market volatility. Journal of Econometrics, 131(1-2), 151-177. Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). Financial accelerator in a quantitative business cycle framework. Handbook of Macroeconomics, 1, 1341-1393. Blanchard, O., & Watson, M. (1982). Bubbles, rational expectations and financial markets. Harvard Institute of Economic Research, Working Paper No 945. Boone, L., Giorno, C., & Richardson, P.(1998). Stock market fluctuations and consumption behavior. OECD Economics Department Working Papers. Carlstrom, C. T., & Fuerst, T. S. (1997). Agency costs, net worth, and business fluctuations: A computable general equilibrium analysis. American Economic Review, 87, 893-910. Central bank of the Islamic Republic of Iran (www.cbi.ir). Chaney, T., Sraer, D., & Thesmar, D. (2012). The collateral channel: How real estate shocks affect corporate investment. American Economic Review, 102(6), 2381-2409. Einian, M., & Barakchian, S. M. (2014). Measuring and dating business cycles in the Iranian economy. Journal of Monetary and Banking Researches, 7(20), 161-194. Fallah Shams, M. F., & Zare, A. (2013). The effective factors in the price bubble in Tehran stock market. Quarterly Journal of Securities Exchange, 6(21), 73-91. Gertler, M., & Kiyotaki, N. (2010). Financial intermediation and credit policy in business cycle analysis, Working Paper, NYU. Gilchrist, S., Himmelberg, C., & Haberman, G. (2005). Do stock price bubbles influence corporate investment? Journal of Monetary Economics, 54(2), 805-827. Goyal, V. K., & Yamada, T. (2004). Asset price shocks, financial constraints, and investment: Evidence from Japan. Journal of Business, 77(1), 175-199. Greenwood, J., Hercowitz, Z., & Krusell, P. (1997). Long-run implications of investment-specific technological change. American Economic Review, 87, 342-362. Gurkaynak, R. S. (2008). Econometric test of asset price bubbles: Taking stock. Journal of Economic Surveys, 22(1), 166-186. Hayashi, F. (1982). Tobin's marginal q and average q: A neoclassical interpretation. Econometrica, 50, 213-224. Hou, H., & Cheng, S. Y. (2017). The dynamic effects of banking, life insurance, and stock markets on economic growth.Japan and the World Economy,41, 87–98. Hui, C. S. (2010). Investor mood and financial markets. Journal of Economic Behavior and Organization, 76(2), 267-282. Ikeda, D. (2013). Monetary policy and inflation dynamics in asset price bubbles. Bank of Japan Working Paper Series, No.13-E-4. Jermann, U., & Quadrini, V. (2012). Macroeconomic effects of financial shocks. American Economic Review, 102(1), 238-271. Kahenman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Kiyotaki, N., & Moore, J. (1997). Credit cycles. Journal of Political Economy, 105(2), 211-248. Lamont, O. (1998). Earning and expected returns. Journal of Finance, 53(2), 1563-1587. Lee, I. (1993). On the convergence of informational cascades. Journal of Economic Theory, 61(2), 396-411. Liu, Z., Wang, P., & Zha, T. (2011). Land price dynamics and macroeconomic fluctuations. NBER Working Papers, No. w17045. Manzoor, D., & Taghipour, A. (2016). A dynamic stochastic general equilibrium model for an oil exporting and small open economy: The case of Iran. Quarterly Journal of Economic Research and Policies, 23(75), 7-44. Martin, A., & Ventura, J. (2012). Economic growth with bubbles. American Economic Review, 102(6), 3033-3058. Miao, J. (2014). Introduction to economic theory of bubbles. Journal of Mathematical Economics, 53, 130-136. Miao, J., & Wang, P. (2011). Bubbles and credit constraints. Working Paper, Boston University and HKUST. Miao, J., Wang, P., & Xu, Z. (2012). A Bayesian DSGE model of stock market bubbles and business cycles. Working Paper, Boston University. Miao, J., Wang, P., & Xu, Z. (2015). A Bayesian dynamic stochastic general equilibrium model of stock market bubbles and business cycles. Quantitative Economics, 6(3), 559-635. Modigliani, F. (1986). Life cycle, individual thrift, and the wealth of nations. Science, 234(4777), 704-712. Musai, M., Mehregan, N., & Amiri, H. (2010). Stock market and macroeconomic variables: A case study for Iran. QuarterlyJournal of Economic Research and Policies, 18(54), 73-94. Nazes, D., & Silva, D. (2007). Rational bubbles in emerging stock markets. MPRA Paper, 4641, 1-10. Paetz, M., & Gupta, R. (2016). Stock price dynamics and the business cycle in an estimated DSGE model for South Africa. Journal of International Financial Markets, Institutions and Money, 44, 166-182. Payandeh Najafabadi, A. T., Qazvini, M., & Ofoghi, R. (2012). The impact of oil and gold prices’ shock on Tehran stock exchange: A copula approach. Iranian Journal of Economic Studies, 1(2), 23-47. Salehabadi, A., & Dalirian, H. (2010). Testing the existence of price bubble in Tehran stock market. Quarterly Journal of Securities Exchange, 3(9), 61-75. Salmani Bishak, M. R., Barghi Oskooee, M. M., & Lak, S. (2016). The effects of monetary and fiscal policy shocks on stock market of Iran. Journal of Economic Modeling Research, 6(22), 93-131. Samadi, S., Vaez Barzani, M., & Ghasemi, M. R. (2010). The behavioral analysis of the formation price bubbles in capital market (case study: Tehran stock market 1997-2009). Economics Research, 10(3), 273-297. Senhadji, A. S., & Collyns, C. (2002). Lending booms, real estate bubbles, and the Asian crisis (No. 02/20). International Monetary Fund. Seven, U., & Yetkiner, H. (2016). Financial intermediation and economic growth: Does income matter? Economic Systems, 40(1), 39–58. Shahmoradi, A. (2008). The effects of energy price changes on the price level, production, and welfare in Iran’s economy. The Ministry of Economic Affairs and Finance. Shahmoradi, A., & Ebrahimi, E. (2010). The impact of monetary policies in Iran: A DSGE approach. Journal of Monetary and Banking Researches, 2(3), 31-56. Shiller, R.J. (1981). Does stock price move too much to be justified by subsequent changes in dividends? American Economic Review, 71, 421-436. Smets, F., & Wouters, R. (2003). An estimated stochastic dynamic general equilibrium model of the Euro area. Journal of the European Economic Association, 1(5), 1123–1175. Smets, F., & Wouters, R. (2007). Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review, 97(3), 586-606. Tirole, J. (1982). On the possibility of speculation under rational expectations. Econometrica, 50, 1163-1181. Uhlig, H. (1999). A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily in Computational Methods for The Study of Dynamic Economies. Oxford University Press. Vaez, M., & Torki, L. (2008). Price bubbles and capital market in Iran. Quarterly Research Bulletin of Isfahan University (Humanities), 31(3), 195-207. Zagaglia, P. (2009). Forecasting with a DSGE model of the term structure of interest rates: The role of the feedback. Central Bank of Sweden References Abbasian, E., Farzanegan, E., & Nasiroleslami, E. (2016). Price bubble anomalies in Tehran stock exchange: Limits to arbitrage approach. Quarterly Journal of Economic Research and Policies, 23(76), 75-92. Abbasian, E., Mahmoudi, V., & Farzanegan, E. (2010). Bubble identification in Tehran's stock exchange: Evidence based on time-varying present value model. Journal of Accounting and Auditing Review, 17(2), 75-92. Amini, A. R., & Haji Mohammad, N. (2005). Estimation of time series of the capital stock in Iran’s economy during 1967-2002. The Journal of Planning and Budgeting, 10(1), 53-86. Asadi, G. H., Hamidi Zadeh, M. R., & Soltani, A. (2006). A survey of stock price bubbles in Tehran stock exchange on the basis of size and type of industries. Empirical Studies in Financial Accounting Quarterly, 4(14), 39-71. Balcilar, M., Gupta, R., Jooste, C., & Wohar, M. (2016). Periodically collapsing bubbles in the South African stock market. Research in International Business and Finance, 38, 191-201. Bashiri, S., Pahlavani, M., & Boostani, R. (2016). Stock market fluctuations and monetary policy in Iran. Journal of Economic Modeling Research, 6(23), 103-157. Bayat, M., Afshari, Z., & Tavakolian, H. (2016). Monetary policy and stock price index in DSGE models framework. Quarterly Journal of Economic Research and Policies, 24(78), 171-206. Beaudry, P., & Portier, F. (2006). Stock price, news, and economic fluctuations. American Economic Review, 96(4), 1293-1307. Beltratti, A., & Morana, C. (2006). Breaks and persistency: Macroeconomic causes of stock market volatility. Journal of Econometrics, 131(1-2), 151-177. Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). Financial accelerator in a quantitative business cycle framework. Handbook of Macroeconomics, 1, 1341-1393. Blanchard, O., & Watson, M. (1982). Bubbles, rational expectations and financial markets. Harvard Institute of Economic Research, Working Paper No 945. Boone, L., Giorno, C., & Richardson, P.(1998). Stock market fluctuations and consumption behavior. OECD Economics Department Working Papers. Carlstrom, C. T., & Fuerst, T. S. (1997). Agency costs, net worth, and business fluctuations: A computable general equilibrium analysis. American Economic Review, 87, 893-910. Central bank of the Islamic Republic of Iran (www.cbi.ir). Chaney, T., Sraer, D., & Thesmar, D. (2012). The collateral channel: How real estate shocks affect corporate investment. American Economic Review, 102(6), 2381-2409. Einian, M., & Barakchian, S. M. (2014). Measuring and dating business cycles in the Iranian economy. Journal of Monetary and Banking Researches, 7(20), 161-194. Fallah Shams, M. F., & Zare, A. (2013). The effective factors in the price bubble in Tehran stock market. Quarterly Journal of Securities Exchange, 6(21), 73-91. Gertler, M., & Kiyotaki, N. (2010). Financial intermediation and credit policy in business cycle analysis, Working Paper, NYU. Gilchrist, S., Himmelberg, C., & Haberman, G. (2005). Do stock price bubbles influence corporate investment? Journal of Monetary Economics, 54(2), 805-827. Goyal, V. K., & Yamada, T. (2004). Asset price shocks, financial constraints, and investment: Evidence from Japan. Journal of Business, 77(1), 175-199. Greenwood, J., Hercowitz, Z., & Krusell, P. (1997). Long-run implications of investment-specific technological change. American Economic Review, 87, 342-362. Gurkaynak, R. S. (2008). Econometric test of asset price bubbles: Taking stock. Journal of Economic Surveys, 22(1), 166-186. Hayashi, F. (1982). Tobin's marginal q and average q: A neoclassical interpretation. Econometrica, 50, 213-224. Hou, H., & Cheng, S. Y. (2017). The dynamic effects of banking, life insurance, and stock markets on economic growth.Japan and the World Economy,41, 87–98. Hui, C. S. (2010). Investor mood and financial markets. Journal of Economic Behavior and Organization, 76(2), 267-282. Ikeda, D. (2013). Monetary policy and inflation dynamics in asset price bubbles. Bank of Japan Working Paper Series, No.13-E-4. Jermann, U., & Quadrini, V. (2012). Macroeconomic effects of financial shocks. American Economic Review, 102(1), 238-271. Kahenman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Kiyotaki, N., & Moore, J. (1997). Credit cycles. Journal of Political Economy, 105(2), 211-248. Lamont, O. (1998). Earning and expected returns. Journal of Finance, 53(2), 1563-1587. Lee, I. (1993). On the convergence of informational cascades. Journal of Economic Theory, 61(2), 396-411. Liu, Z., Wang, P., & Zha, T. (2011). Land price dynamics and macroeconomic fluctuations. NBER Working Papers, No. w17045. Manzoor, D., & Taghipour, A. (2016). A dynamic stochastic general equilibrium model for an oil exporting and small open economy: The case of Iran. Quarterly Journal of Economic Research and Policies, 23(75), 7-44. Martin, A., & Ventura, J. (2012). Economic growth with bubbles. American Economic Review, 102(6), 3033-3058. Miao, J. (2014). Introduction to economic theory of bubbles. Journal of Mathematical Economics, 53, 130-136. Miao, J., & Wang, P. (2011). Bubbles and credit constraints. Working Paper, Boston University and HKUST. Miao, J., Wang, P., & Xu, Z. (2012). A Bayesian DSGE model of stock market bubbles and business cycles. Working Paper, Boston University. Miao, J., Wang, P., & Xu, Z. (2015). A Bayesian dynamic stochastic general equilibrium model of stock market bubbles and business cycles. Quantitative Economics, 6(3), 559-635. Modigliani, F. (1986). Life cycle, individual thrift, and the wealth of nations. Science, 234(4777), 704-712. Musai, M., Mehregan, N., & Amiri, H. (2010). Stock market and macroeconomic variables: A case study for Iran. QuarterlyJournal of Economic Research and Policies, 18(54), 73-94. Nazes, D., & Silva, D. (2007). Rational bubbles in emerging stock markets. MPRA Paper, 4641, 1-10. Paetz, M., & Gupta, R. (2016). Stock price dynamics and the business cycle in an estimated DSGE model for South Africa. Journal of International Financial Markets, Institutions and Money, 44, 166-182. Payandeh Najafabadi, A. T., Qazvini, M., & Ofoghi, R. (2012). The impact of oil and gold prices’ shock on Tehran stock exchange: A copula approach. Iranian Journal of Economic Studies, 1(2), 23-47. Salehabadi, A., & Dalirian, H. (2010). Testing the existence of price bubble in Tehran stock market. Quarterly Journal of Securities Exchange, 3(9), 61-75. Salmani Bishak, M. R., Barghi Oskooee, M. M., & Lak, S. (2016). The effects of monetary and fiscal policy shocks on stock market of Iran. Journal of Economic Modeling Research, 6(22), 93-131. Samadi, S., Vaez Barzani, M., & Ghasemi, M. R. (2010). The behavioral analysis of the formation price bubbles in capital market (case study: Tehran stock market 1997-2009). Economics Research, 10(3), 273-297. Senhadji, A. S., & Collyns, C. (2002). Lending booms, real estate bubbles, and the Asian crisis (No. 02/20). International Monetary Fund. Seven, U., & Yetkiner, H. (2016). Financial intermediation and economic growth: Does income matter? Economic Systems, 40(1), 39–58. Shahmoradi, A. (2008). The effects of energy price changes on the price level, production, and welfare in Iran’s economy. The Ministry of Economic Affairs and Finance. Shahmoradi, A., & Ebrahimi, E. (2010). The impact of monetary policies in Iran: A DSGE approach. Journal of Monetary and Banking Researches, 2(3), 31-56. Shiller, R.J. (1981). Does stock price move too much to be justified by subsequent changes in dividends? American Economic Review, 71, 421-436. Smets, F., & Wouters, R. (2003). An estimated stochastic dynamic general equilibrium model of the Euro area. Journal of the European Economic Association, 1(5), 1123–1175. Smets, F., & Wouters, R. (2007). Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review, 97(3), 586-606. Tirole, J. (1982). On the possibility of speculation under rational expectations. Econometrica, 50, 1163-1181. Uhlig, H. (1999). A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily in Computational Methods for The Study of Dynamic Economies. Oxford University Press. Vaez, M., & Torki, L. (2008). Price bubbles and capital market in Iran. Quarterly Research Bulletin of Isfahan University (Humanities), 31(3), 195-207. Zagaglia, P. (2009). Forecasting with a DSGE model of the term structure of interest rates: The role of the feedback. Central Bank of Sweden
(IJES) Shiraz University (Iranian Journal of Economic Studies (IJES 2322-1402 Shiraz University 15 10.22099/ijes.2018.29589.1459 مقاله پژوهشی بررسی تاثیر کیفیت نهادی بر رابطه بین ثبات بانکی و بازاری‌کردن: مطالعه موردی ایران بررسی تاثیر کیفیت نهادی بر رابطه بین ثبات بانکی و بازاری‌کردن: مطالعه موردی ایران رستم زاده پرویز بخش اقتصاد، دانشگاه شیراز، شیراز، ایران. صمدی علی حسین بخش اقتصاد، دانشگاه شیراز، شیراز، ایران. یادگار زینب بخش اقتصاد، دانشگاه شیراز، شیراز، ایران. 01 12 2018 7 2 151 167 18 06 2018 08 10 2018 Copyright © 2018, Shiraz University. 2018 https://ijes.shirazu.ac.ir/article_4969.html

بخش بانکی از جمله مهم‌ترین بخش‌ها در اقتصاد هر کشور به حساب می‌آید، بنابراین بی‌ثباتی در این بخش سبب اختلال در سایر بخش‌های اقتصاد می‌شود. یکی از عواملی که می‌تواند بر ثبات بانکی تاثیر بگذارد فرآیند بازاری‌کردن در نظام بانکی است. هدف اصلی این مقاله بررسی رابطه میان بازاری‌کردن و ثبات نظام بانکی در ایران و همچنین بررسی میزان اثر بخشی کیفیت نهادی بر رابطه بین این دو است. در برآوردها الگو از روش گشتاورهای تعمیم یافته (GMM) و رگرسیون آستانه‌ای در داده‌های پانلی (PTR) استفاده می‌شود. نتایج حاصل از روش گشتاورهای تعمیم یافته نشان می‌دهد که با بازاری‌کردن نظام بانکی، ثبات بانکی کاهش می‌یابد و افزایش کیفیت نهادی می‌تواند این رابطه را بهبود ببخشد. همچنین نتایج روش رگرسیونی آستانه‌ای در داده‌های پانلی نشان می‌دهد که کیفیت نهادی دارای یک مقدار آستانه‌ای برای تاثیر بر رابطه بازاری‌کردن و ثبات بانکی است که سبب می‌شود رابطه بازاری‌کردن و ثبات بانکی در دو رژیم مختلف، متفاوت باشد.

 ثبات بانکی کیفیت نهادی بازاری‌کردن رگرسیون آستانه‌ای پانلی گشتاورهای تعمیم یافته ایران References Alawode, A., & Al-Sadek, M. (2008). What is financial stability? Financial Stability Paper Series, Central Bank of Bahrain. 1- 26. Allen, F., & Gul, X. (2011). Corporate governance and intra-group transactions in European bank holding companies during the crisis, Vol. 14. Global Banking, Financial Markets and Crises. Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 189–209. Anginer, D., Demirguc-Kunt, A., & Zhu, M. (2011). How does bank competition affect systemic stability? Journal of Financial Intermediation, 23, 1-26 Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carol evidence and application to employment equation. Review of Economic Studies, 58, 117-142. Bahmani, M., & Mirhashemi, S. (2015). Investigating the effect of banking marketing on the transfer of monetary policy from the duct of lending. Quarterly Journal of Applied Economics Theory, 2, 119-142. Barth, J. R., Caprio, G., & Levine, R. (2009). Bank regulations are changing: For better or worse? World Bank Policy Research Working Paper, No 4646. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87, 115-143. Choi, I. (2002). Combination unit root test for cross-sectionally correlated panel. Hong Kong University of Science and Technology, 12. Feng, Y., Hasan, I., & Marton, K. (2012). Institutional development and bank stability: Evidence from transition countries. Journal of Banking & Finance, 39, 160-176. Doll, M. (2010). Bank concentration, competition, and financial stability. Tilburg University. Hansen, B. E. (2000). Sample splitting and threshold estimation. Econometrica, 68, 575–603. Harris, R., & Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics, 91, 201-226. Hou, X., & Wang, Q. (2016). Institutional quality and banking marketization and bank stability: Evidence from China. Economic System, 40, 539-551. Hu, J., Li, Y., & Chiu, Y. (2004). Ownership and nonperforming loans: Evidence from Taiwan banks. Developing Economies, 42(3), 1-35. Hurlin, C., & Mignon, V. (2007). Second generation panel unit root test, Halshs Archives, 1-24. Im, K., Pesaran, M. H., & Shin, Y. (1997). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115, 53-74. Ishibashi, I., & Matsumura, T.  (2009). Privatization and entries of foreign enterprises in a differentiated industry. Japan Economics, 98, 203-219. Jin, Y., Kanagratnam, K., Lobo, G., & Mathieu, R. (2017). Social capital and bank stability. Journal of Financial Stability, 32, 99–114. Khoshnoodi, A., Sabagh, M., Yavari, K., & Hosseininasab, E. (2012). Financial banking vulnerability assessment and its effective factors using the Z-Score index. Journal of Economic Research and Policy, 7, 79-100. Kutlu, V. (2009). Panel cointegration analysis to exchange rate determination: monetary model versus Taylor rule model. Doctoral Dissertation, Bilkent University. Levin, A., & Lin, C. (1992). Unit root test in panel data: Asymptotic and finite sample Properties. University of California at San Diego, Discussion Paper, 92-93. Maddala, G. S. & Wu, S. H.  (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics (Special Issue), 0305-9049. Mishkin, F. (1998). International experiences with different monetary policy regimes. Journal of Monetary Economics, 43(3), 579-605. North, D. (1996). Institutions, organizations and market competition. NBER Working Papers from National Bureau of Economic Research, 6965. Moon, H., & Perron, B. (2004). Testing for a unit root in panels with dynamic factors. Journal of Econometrics, 122, 81-126. Pesaran, M. H. (2003). A simple panel unit root test in the presence of cross sectional dependence. Mimeo, University of Southern California. Pesaran, M. H. (2004). General diagnostic tests for cross-section dependence in panels. Cambridge Working Papers in Economics, 0435. Pesaran, M. H. (2015). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6-10), 1089-1117. Poostinchi, M., Tahsili, H., & Karimzadeh, M. (2016). Impact of competition in the banking industry on banking stability, Economics, 11, 123-145. Taqavi, M., Ahmadian, A., & Kianvan, M. (2013). An analysis of the effect of corporate governance on the stability of the banking system in developing countries. Journal of Financial Analysis, 19, 45-76. Zalbagi, H. (2014). Factors affecting stability in Iranian banking network. Quarterly Journal of Monetary-Banking Research, 20, 307-327. Zamanzadeh, H., & Al-Husseini, S. (2016). Iran's economy: In straits of development. Vol .1. Tehran, Iran: Markaz Press [In Persian].
(IJES) Shiraz University (Iranian Journal of Economic Studies (IJES 2322-1402 Shiraz University 15 10.22099/ijes.2018.30739.1485 مقاله پژوهشی عوامل موثر بر توسعه گردشگری پزشکی در ایران : رهیافت الگوسازی معادلات ساختاری عوامل موثر بر توسعه گردشگری پزشکی در ایران نجفی نصاب میر حجت بخش توسعه اقتصادی و برنامه ریزی، دانشگاه تربیت مدرس، تهران، ایران. عاقلی لطفعلی پژوهشکده اقتصاد، دانشگاه تربیت مدرس، تهران، ایران. آندراده مونیکا ویه گاس صادقی حسین فرجی دیزجی سجاد 01 12 2018 7 2 169 189 11 09 2018 19 11 2018 Copyright © 2018, Shiraz University. 2018 https://ijes.shirazu.ac.ir/article_5041.html

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(IJES) Shiraz University (Iranian Journal of Economic Studies (IJES 2322-1402 Shiraz University 15 10.22099/ijes.2018.30128.1467 مقاله پژوهشی تحلیلی از آثار اطلاعات نامتقارن در بازار پول بر سرمایه‌گذاری، اشتغال و تولید در اقتصاد ایران تحلیلی از آثار اطلاعات نامتقارن در بازار پول مهینی زاده منصور دانشکده اقتصاد، مدیریت و حسابداری دانشگاه یزد، یزد، ایران یاوری کاظم دانشکده اقتصاد و مدیریت دانشگاه تربیت مدرس، تهران، ایران ولی بیگی حسن مؤسسه مطالعات و پژوهشهای بازرگانی، تهران، ایران شفیعی علی دانشکده اقتصاد، مدیریت و حسابداری دانشگاه یزد، یزد، ایران 01 12 2018 7 2 191 217 17 07 2018 22 10 2018 Copyright © 2018, Shiraz University. 2018 https://ijes.shirazu.ac.ir/article_5020.html

امروزه بانک‌ها بعنوان یکی از اجزای اصلی نظام مالی یک کشور محسوب می‌شوند و مکمل فعالیت در بخش حقیقی می‌باشند و نارسایی در فعالیت بخش بانکی بر عملکرد بخش حقیقی تأثیر منفی خواهد گذاشت. بنابراین بررسی رفتار بانک‌ها و عوامل مؤثر بر رفتار آنها اهمیت بالایی پیدا کرده است. یکی از مسائلی که رفتار بانک‌ها را متأثر می‌کند تقارن اطلاعات می‌باشد. بنابراین هدف اصلی این تحقیق، بررسی تأثیر اطلاعات نامتقارن در بازارهای پول بر سرمایه‌گذاری، تولید و اشتغال است. از این روی، یک مدل تعادل عمومی پویای تصادفی (DSGE) متناسب با ساختار اقتصاد ایران تصریح شد. مدل مورد نظر دارای هشت بخش خانوارها، بنگاه‌ها، بانک‌ها، بانک مرکزی ، نفت، دولت، صادرات و واردات و سایر کشورهای دنیا می‌باشد و چسبندگی قیمت‌ها، دستمزده‌ها و چسبندگی قیمت‌های کالاهای وارداتی و صادراتی درآن دیده شده است و با استفاده از روش بیزین و داده‌های ایران (1395-1353)پارامترهای مجموعه معادلات برآورد و اثر افزایش تقارن اطلاعات بررسی شد. نتایج تحقیق نشان می‌دهد که افزایش عدم تقارن اطلاعات و کاهش صداقت در جامعه، از کانال کاهش منابع در اختیار بانک و همچنین افزایش هزینه بانک‌ها؛ باعث افزایش سود تسهیلات می‌شود. افزایش سود تسهیلات بانکی باعث کاهش سرمایه‌گذاری، تولید و اشتغال می‌شود.

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(IJES) Shiraz University (Iranian Journal of Economic Studies (IJES 2322-1402 Shiraz University 15 10.22099/ijes.2018.28032.1460 مقاله پژوهشی آثار بازتخصیص درآمد فروش نفت و گاز ایران به توسعه امور بالادستی آن فرحناک فردین گروه اقتصاد، دانشگاه سمنان، سمنان، ایران مداح مجید گروه اقتصاد، دانشگاه سمنان، سمنان، ایران شاکری عباس گروه اقتصاد، دانشگاه علامه طباطبائی، تهران، ایران. 01 12 2018 7 2 219 237 13 06 2018 01 10 2018 Copyright © 2018, Shiraz University. 2018 https://ijes.shirazu.ac.ir/article_4984.html

بخش نفت و گاز با سهم قابل توجه در تولید ملی و تامین هزینه‏های عمومی نقش مهمی را در اقتصاد ایران ایفا می‏کند. علیرغم، عقب ماندگی در تأمین سهم متناسب از عرضه جهانی، ایران در بالاترین رتبه از حیث ذخایر اثبات شده جهانی مرتبط قرار دارد. این تحقیق با استفاده از یک مدل CGE، به بررسی اثرات افزایش سهم امور بالادستی نفت و گاز از درآمدهای نفتی، بر تولید ناخالص ملی و بودجه عمومی مشروط به حفظ تعهدات اصلی دولت که اغلب از درآمدهای نفتی تامین می‏شود، می پردازد.با افزایش سهم 18 درصد از درآمد نفت و گاز به جای 14.5% کنونی، در کوتاه مدت رکود و درمقابل در بلند مدت رونق رخ خواهد داد. بر این اساس، با حفظ سطح اولیه؛ 1- ستانده کالاها و خدمات عمومی، یا 2- میزان حمایت مالی دولتی در تأمین کالاها و خدمات عمومی، GNP همگام با انقباض 15٪ در بودجه عمومی می‏تواند تا 5٪ افزایش یابد. در مقابل، با حفظ سطح اولیه؛ 3- پرداخت‏های انتقالی یا 4- حفظ همزمان پرداختهای انتقالی و حمایت مالی از تأمین کالاهای عمومی، ضمن الزام به انقباض بسیار ناچیز بودجه عمومی برای دولت GNP تنها 1٪ افزایش می‏یابد. بنابراین، با توجه به پتانسیل رشد چشمگیر GNP، پیشنهاد می‏شود که بازتخصیص سهم بیشتری از درآمد نفتی برای توسعه امور بالادستی آن (حتی بشرط حفظ تعهدات کنونی دولت) اجرایی شود.

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(IJES) Shiraz University (Iranian Journal of Economic Studies (IJES 2322-1402 Shiraz University 15 10.22099/ijes.2019.31010.1490 مقاله پژوهشی چه زمانی بیمه درمان در کاهش هزینه کمرشکن سلامت موثر است؟ چه زمانی بیمه درمان در کاهش هزینه کمرشکن سلامت موثر است؟ مهربان ستار حاجی ملا درویش نرگس دانشکده علوم اجتماعی و اقتصاد دانشگاه الزهرا راغفر حسین 01 12 2018 7 2 239 254 03 10 2018 02 02 2019 Copyright © 2018, Shiraz University. 2018 https://ijes.shirazu.ac.ir/article_5094.html

هدف این مقاله بررسی نتایج تجربی متناقض در رابطه با اثر بیمه درمانی در کاهش خطر ابتلا به هزینه کمرشکن سلامت است. طیف گسترده ای از عوامل موثر بر ریسک ابتلا به هزینه کمرشکن سلامت در بیماران بستری شده در بیمارستان های تهران بررسی شده است. ما بیمارستان ها را به پنج گروه از بیمارستان‌های خصوصی تا بیمارستان‌های خیریه تقسیم کردیم. داده های استفاده شده در این مقاله ازمرحله دوم طرح سنجش عدالت در سلامت شهر تهران استخراج شده است. عوامل تعیین کننده هزینه کمرشکن سلامت با استفاده از رگرسیون لجیت مشخص شدند. نتایج ما نشان می دهد که تأثیر قابل توجه بیمه سلامت در داده های جمع آوری شده منحصر به تأثیر آن در کاهش هزینه کمرشکن سلامت در بیمارستان‌های سازمان تأمین اجتماعی است. بیمه شدگان این سازمان، نسبت بیشتری از حقوق و دستمزد خود را برای بیمه درمان می‌پردازند و در بیمارستانهای سازمانی به صورت رایگان پذیرش می‌شوند. این نتیجه، سوگیری ذاتی در جمع پذیری را نشان می دهد و از ساز و کارهای پیش پرداخت حمایت می‌کند. یافته های ما نشان می‌دهد که هزینه کمرشکن سلامت به بیمارستان های انتخاب شده توسط افراد بستگی دارد و این بیمارستانها باید متناسب با پوشش بیمه های درمانی افراد و شرایط اجتماعی-اقتصادی آنها انتخاب شوند.

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