Shahid Bahonar University of Kerman

 Statistics

Number of Journals26
Number of Issues447
Number of Articles4,563
Article View5,389,768
PDF Download3,592,574
Heidari, F., Nadri, K., Haji, G. (2023). Investigating Factors Affecting Housing Prices with an Emphasis on Non-Current Claims of Banks (VAR-TVPDMA Models Approach). , 8(2), 91-112. doi: 10.22103/jdc.2023.21279.1384
Fariba Heidari; Kamran Nadri; Gholamali Haji. "Investigating Factors Affecting Housing Prices with an Emphasis on Non-Current Claims of Banks (VAR-TVPDMA Models Approach)". , 8, 2, 2023, 91-112. doi: 10.22103/jdc.2023.21279.1384
Heidari, F., Nadri, K., Haji, G. (2023). 'Investigating Factors Affecting Housing Prices with an Emphasis on Non-Current Claims of Banks (VAR-TVPDMA Models Approach)', , 8(2), pp. 91-112. doi: 10.22103/jdc.2023.21279.1384
Heidari, F., Nadri, K., Haji, G. Investigating Factors Affecting Housing Prices with an Emphasis on Non-Current Claims of Banks (VAR-TVPDMA Models Approach). , 2023; 8(2): 91-112. doi: 10.22103/jdc.2023.21279.1384

Investigating Factors Affecting Housing Prices with an Emphasis on Non-Current Claims of Banks (VAR-TVPDMA Models Approach)

توسعه و سرمایه
Article 5, Volume 8, Issue 2 - Serial Number 15, December 2023, Pages 91-112    PDF (1.7 M)
Document Type: Research Paper
DOI: 10.22103/jdc.2023.21279.1384
Authors
Fariba Heidari* 1; Kamran Nadri2; Gholamali Haji3
1Ph.D. Candidate of Economics, Aligudarz Branch, Islamic Azad University, Aligudarz, Iran.
2Assistant Professor of Economics, Faculty of Islamic Studies and Economics, Imam Sadeq University, Tehran, Iran.
3Assistant Professor of Economics, Arak Branch, Islamic Azad University, Arak, Iran.
Abstract
Objective: The housing sector in Iran is considered one of the most important economic sectors, so that around 20-30% of the country's capital formation was allocated to this sector in the last decade. Price vibratilitys are one of the most important economic challenges of this sector. Examining the conditions governing the economy in the past years shows that the conditions of recession and inflation governing the country's economy have created one of the most difficult periods for the country, and in the meantime, the housing sector, as one of the economic sub-sectors, has not been protected from the Adverse effects of the conditions governing the macro economy. And it has experienced relatively long periods of recession and relatively high inflation before that. On the other hand, one of the basic problems that banks and financial and credit institutions are dealing with today is the problem of non-current claims and uncollected facilities. In addition to reducing the profitability of banks, this issue causes the slow circulation of liquidity in the economy, the lack of allocation of credits to productive requests on time, in the fields of industry, mining, trade and agriculture, and ultimately economic stagnation. One of the most important factors affecting the non-current claims of the banking system can be the business cycles and periods of the housing sector, since the civil partnership facilities of banks have a significant share, the booms and busts of the housing and non-residential buildings sectors can affect the ability to repay the received facilities. be influential. The boom in the housing sector and investors in this sector will help repay loans. While the stagnation of the housing sector and its expansion will reduce the willingness and ability of investors to repay loans; Therefore, examining the cycles of the housing sector as one of the factors affecting non-current claims is necessary and necessary. Also, it seems that the increase in demand is not the only factor affecting housing prices and the unfavorable conditions of other economic sectors of the country make the housing sector attractive to all investors (banks and non-banks). Considering the importance of the issue and considering that one of the effects and consequences of the monetary activities of credit institutions is the emergence of non-current claims that have negative effects on the cycle of resources and expenses of banks and can also affect housing prices; Therefore, the main goal of this research is to answer the question that to what extent does the investment of banks in real estate affect the price of housing?
Method: In this research, using the TVP-DMA method, the most important factors affecting housing prices have been identified. To examine a forecasting model or to choose the best model among different models for a time series, an index is needed to make the necessary decision regarding the acceptance or rejection of the forecasting model. In this study, two standard indices of the Mean Squared Forecast Error (MSFE) and the Mean Absolute Forecast Error (MAFE) are used.
Results: Based on the results, the most important variables affecting housing prices in Iran's economy are inflation variables; exchange rate; liquidity; Economic Growth; Bank payment facilities for housing; Overdue claims and increase in bank debt; the amount of fixed assets of banks; Land price index in Tehran; sanctions index; population; housing tax; Urbanization coefficient and price index of construction materials. Based on the results of inflation variables; exchange rate; liquidity; Bank payment facilities for housing; the amount of fixed assets of banks; Land price index in Tehran; sanctions index; population; Urbanization coefficient and price index of construction materials have a positive effect and economic growth variables; Overdue claims and increase in bank debt and housing tax have a negative effect on housing prices. Based on these results, inflation with the longest period of influence is the most important variable affecting housing prices in Iran.
Conclusion: Based on the results, the following suggestions are made to improve the situation in the housing sector:
Tax policies: According to the current conditions, the most effective way to deal with housing speculation is to apply effective taxes in the field of housing and real estate. These taxes can be placed in 5 areas: real estate capital gains tax, real estate transfer tax, annual real estate tax, real estate rental income tax, and real estate construction and sale income tax.
Pending claims policies: Considering the results of the research and the significance of the effect of housing prices on non-current claims of banks in the period under review, it seems that policymakers and supervisors should consider housing prices as a key indicator affecting the stability of banks. In this context, it is desirable to provide a framework to control the relationship between housing prices, bank loans and loan losses.
Facilitation policies: as a policy solution arising from the results and findings of this research and considering the existence of potential accumulated demand in the housing market and the existing imbalance, it is suggested to prevent the stimulation of potential demand and the increase of housing prices, the share of bank facilities granted for the purchase housing will be reduced and on the other hand, the share of bank facilities granted for housing construction will increase and then the facilities allocated for housing construction will be converted into long-term contracts for installment sales and rent as a condition of possession. It is worth mentioning that the interest rate of bank facilities can also be effective on housing prices from the cost aspect; Therefore, in the housing market, both supply and demand factors must be monitored and controlled.
Keywords
Housing Price; Housing Bubble; Outstanding Claims; Dynamic Averaging
References
اسدپور، احمدعلی (1398). اثر نااطمینانی تورم و متغیرهای کلان اقتصادی بر قیمت مسکن در ایران. پژوهش‌های رشد و توسعه اقتصادی، 10(37)، 141-131 https://sid.ir/paper/192076/fa.

اصغرزاده، آلاء؛ رهبر، فرهاد و موسوی، امیرحسین (1400). رتبه‌بندی عوامل مؤثر بر ابزارهای نظارتی بانک مرکزی بر ثبات مالی در نظام بانکی ایران. اقتصاد کاربردی، 11(39)، 53-39 https://sanad.iau.ir/Journal/jae/Article/803969.

امجدی، محمدحسین؛ شکیبایی، علیرضا و جلائی، سید عبدالمجید (1401). تأثیر نرخ ارز، نااطمینانی نرخ ارز و پاندمی کووید 19 بر قیمت مسکن (مطالعه موردی: شهر تهران). پژوهش‌های اقتصادی ایران، 27(92)، 241-213 https://ijer.atu.ac.ir/article_13523.html

تهمتنی، مریم و گلستانی، شهرام (1390). برآورد تابع قیمت هدانیک مسکن در شهر کرمان. مجله توسعه و سرمایه، 7(4)، 99-75 https://jdc.uk.ac.ir/ article_2061.html.

جعفری صمیمی، احمد؛ علمی، زهرا و هادی‌‎زاده، آرش (1386). عوامل مؤثر بر تعیین رفتار شاخص قیمت مسکن در ایران. پژوهش‌های اقتصادی ایران، 9(32)، 53-31 https://ijer.atu.ac.ir/article_3624.html.

خیابانی، ناصر (1382). عوامل تعیین‌کننده قیمت مسکن در ایران. اقتصاد مسکن، 34، 52-46 https://www.sid.ir/paper/440107/fa.

سوری، ا.، حیدری، ح.، افضلی، ح. (1391). بررسی رابطه متغیرهای طرف تقاضا و عرضه مؤثر بر بخش مسکن بر قیمت مسکن در ایران. فصلنامه پژوهش‎های اقتصادی، 12(1): 140- 113 https://ecor.modares.ac.ir/browse.php?a_id=466&sid=18&slc_lang=fa

شیخلی، سمانه؛ نصیری‌اقدم، علی؛ آماده، حمید و درودیان، حسین (1401). مدل‎سازی پیش‎ بینی بحران بانکی ایران با رویکرد مدل‌های میانگین‎‎گیری بیزین. نظریه های کاربردی اقتصاد، 9(4)، 36-1 doi: 10.22034/ecoj.2022.53817.3125.

صارمی، حمیدرضا؛ حیدری، محمد و آقایی، فاطمه (1397). تحلیل فضایی قیمت مسکن با استفاده از تکنیک رگرسیون موزون جغرافیایی مورد مطالعه: منطقه دو شهرداری تهران. اقتصاد شهری، 3(2)، 38-19 https://ue.ui.ac.ir/article_23662.html.

صباغ کرمانی، مجید؛ احمدزاده، خالد و موسوی نیک، سید هادی (1389). عوامل تعیین‌کننده قیمت مسکن با رویکرد روابط علیتی در مدل تصحیح خطای برداری: مطالعه موردی تهران. فصلنامه پژوهش‎های اقتصادی، 10(2)، 293-267 https://joer.atu.ac.ir/article_2779.html.

عدالت خواه، دانیال و حسینی نیا، مهدیه (1400). ارزیابی عوامل مؤثر بر قیمت مسکن در تهران بین بازه سال ۱۳۸۵ تا ابتدای سال ۱۴۰۰، هفتمین کنگره سالانه بین المللی عمران، معماری و توسعه شهری، تهران. https://civilica.com/doc/1373752.

فرحزادی، مهدی (1397). بررسی شاخص‌های بخش مسکن و ساختمان در سال‌های ۱۳۶۵ تا ۱۳۹۵. مجله بررسی‌های آمار رسمی ایران. ۲۹(۲)، ۱۵۱-۱۶۳. https://ijoss.srtc.ac.ir/article-1-276-fa.html.

قادری، جعفر و ایزدی، بهنام (1395). بررسی تاثیر عوامل اقتصادی و اجتماعی بر قیمت مسکن در ایران (1391-1350). اقتصاد شهری، 1(1)، 75-55 https://sid.ir/paper/265237/fa

قرشی، منیره‌السادات (1385). بررسی تأثیر درآمدهای بخش نفت بر قیمت و سطح فعالیت مسکن در ایران. پایان‎نامه کارشناسی ارشد، دانشگاه علامه طباطبائی.

قلی‌زاده، علی اکبر؛ گلزاریان پور، سیاوش و شکوری منفرد، فریبا (1398). بررسی اثر قیمت مسکن بر مطالبات غیرجاری درسیستم بانکی ایران. نظریه‌های کاربردی اقتصاد، 6(3)، 214-189 https://ecoj.tabrizu.ac.ir/article_9467_1147.html.

قلی‌زاده، علی اکبر و احمدزاده، ابراهیم (۱۳۸7). بررسی تاثیرگذاری اعتبارات اعطایی بانک مسکن بر قیمت مسکن. بانک مسکن. مرکز پژوهش و توسعه،110-128.

قلی‎زاده، علی‌اکبر، بختیاری پور، سمیرا (1389). اثر اعتبارات بر قیمت مسکن در ایران. مجله مطالعات اقتصادی کاربردی در ایران. 3، 179-159 https://sid.ir/paper/481863/fa.

کمالی دهکردی، پروانه (1399). تحلیل اثر شوک ارزی، تحریم‌های اقتصادی و قیمت نفت بر بازار مسکن (با بکارگیری الگوی خود رگرسیونی برداری ساختاری SVAR). نظریه‌های کاربردی اقتصاد، 7(4)، 27-56 https://journals.tabrizu.ac.ir/article_12266.html

کوهی لیلان، بابک؛ دباغ، رحیم؛ کیاالحسینی، سید ضیاءالدین و رهبر، فرهاد (1400). بررسی عوامل مؤثر بر ثبات نظام بانکی در کشورهای منتخب منطقه منا. مجله توسعه و سرمایه، 6(1)، 18-1 DOI: 10.22103/jdc.2021.16550.1107.

محمدی، تیمور؛ بهرامی، جاوید و فهیمی‎فر، فاطمه (1400). مقایسه پیش ‏بینی نرخ تورم مصرف‌کننده ایران با استفاده از تعداد بسیاری متغیر پیش ‏بینی کننده. اقتصاد مقداری، 18(4)، 190-159 DOI: 10.22055/jqe.2020.31882.2190.

محمدی، تیمور؛خیابانی، ناصر؛ بهرامی، جاوید و فهیمی‎فر، فاطمه (1399). مقایسه روش‎های مختلف پیش‎بینی رشد اقتصادی ایران با تأکید بر مدل‎های گزینشی نمودن و متوسط‎گیری الگوی پویا، پژوهش‎های رشد و توسعه پایدار، 20(4)، 123-93  URL: http://ecor.modares.ac.ir/article-18-38166-fa.html.

موسوی، میرحسین و درودیان، حسین (1394). تحلیل عوامل مؤثر بر قیمت مسکن در شهر تهران. فصلنامه علمی مدلسازی اقتصادی، 9(31): 103-127 موسوی میرحسین، درودیان حسین. تحلیل عوامل موثر بر قیمت مسکن در شهر تهران. مدلسازی اقتصادی، 9(3)، 127-103 https://sid.ir/paper/176181/fa.

نصیری، زهرا؛ صراف، فاطمه؛ تنهایی، محمدرضا؛ امام وردی، قدرت‌الله و مقدم، علی نجفی (1402). پیش‌بینی نوسان شاخص‌های بورس اوراق بهادار تهران از طریق مدل نوسان‌گر هماهنگ کوانتومی. تحقیقات حسابداری و حسابرسی، 15(57)، 110-89 DOI: 10.22034/iaar.2023.172754.

References

Adalatkhah, D., & Hosseininia, M., (2021). Evaluation of factors affecting housing prices in Tehran between 2006 until 2020, Seventh Annual International Congress on Civil Engineering, Architecture and Urban Development, Tehran. https://civilica.com/doc/1373752/ [In Persian].

Adrian, T., Boyarchenko, N., & Giannone, D. (2019). Vulnerable growth. American Economic Review, 109(4), 1263–1289 DOI: 10.1257/aer.20161923.

Amjadi, M.H., Shakibaei, A., & Jalaei, S.A. (2022). The impact of exchange rate, exchange rate uncertainty and covid 19 pandemic on housing prices (case study: Tehran). Economic Research of Iran, 27(92), 213-241 https://ijer.atu.ac.ir/article_13523.html [In Persian].

Asadpour, A.A. (2020). The effects of uncertainty in inflation and macroeconomic variables on housing prices in Iran. Journal of Economic Growth and Development Research, 10(37), 131-141 https://sid.ir/paper/192076/en[In Persian].

Asgharzadeh, A., Leader, F., & Mousavi, M. (2021). Ranking of the factors affecting the central bank's supervisory tools on financial stability in Iran's banking system. Applied Economics, 11(39), 39-53 https://sanad.iau.ir/Journal/jae/Article/803969 [In Persian].

Banai, Á., & Nikolett V. (2018). The effect of house prices on bank risk: Empirical evidence from Hungary. NBP Working Paper, 289 https://static.nbp.pl/publikacje/materialy-i-studia/289_en.pdf.

Barrell, R., Davis, E.P., Karim, D., & Liadze, I. (2010). Bank regulation, property prices and early warning systems for banking crises in OECD countries. Journal of Banking and Finance, 34(9), 2255–2264 https://www.sciencedirect.com/ science/article/abs/pii/S0378426610000798.

Berger A.N., & Udell G.F. )1998(. the economics of small business finance: The roles of private equity and debt markets in the financial growth cycle. Journal of banking & finance. 22(6-8), 613-673 https://ssrn.com/abstract=137991.

Berger, A.N., & Bouwman, C.H. (2015). How does capital affect bank performance during financial crises? Journal Finance Economic, 109(1), 146-176 https://www.sciencedirect.com/science/article/abs/pii/S0304405X13000512.

Bernanke, B., & Gertler, M. (1989). Agency costs, net worth, and business fluctuations. American Economic Review, 79(1), 14-31 https://www.jstor.org/stable/1804770.

Cho, D. (2006). Interest Rate, Inflation, and Housing Price: With an Emphasis on Chonsei Price in Korea. 18-32 http://www.nber.org/chapters/c10147.

Crow, L., & Chyi, L. (2019). Modelling housing prices and market fundamentals: Evidence from the Sydney housing market. International Journal of Housing Markets and Analysis, 12, 746–62 DOI: 10.1108/IJHMA-10-2018-0082.

Davis, E.P., & Zhu, H. (2011). Bank lending and commercial property cycles: some cross-country evidence. Journal Int. Money Financ, 30(1), 1-21 https://doi.org/10.1016/j.jimonfin.2010.06.005.

Farahzadi, M. (2019), Evaluation of housing and building indices in censuses from 1365 to 1395. Ijoss Iranian Journal of Official Statistics Studies, 29(2), 151-163 URL: http://ijoss.srtc.ac.ir/article-1-276-fa.html  [In Persian].

Galati, G.T., & Federica, A.R. (2011). Macro and micro drivers of house price dynamics: An application to Dutch data. DNB Working Paper, Working Paper No. 288 https://www.dnb.nl/publicaties/publicaties-onderzoek/working-paper-2011/288-macro-and-micro-drivers-of-house-price-dynamics-an-application-to-dutch-data.

Garratta, A., Mitchellb J., & Shaun, P. (2011). Real-time inflation forecast densities from ensemble Phillips curves. North American Journal of Economics and Finance, 22, 78-88 https://econpapers.repec.org/article/eeeecofin/v_ 3a22_3ay_3a2011_3ai_3a1_3ap_3a77-87.htm

Ghaderi, J., & Izadi, B. (2017). Studying the effects of social and economic factors on the housing prices in iran (1972-2013). Journal of Urban Economics, 1(1), 55-75 https://sid.ir/paper/265237/en [In Persian].

Gong, L., Chan, Wang, Fuyang, Zhao and Heng-fuZou, (2017), Land -price dynamics and macroeconomic fluctuations with nonseparable preferences, Journal of Economic Dynamics and Control, 83, 149 -161. https://doi.org/10.1016/j.jedc.2017.07.008

Greve, J., Grün, B., Malsiner-Walli, G., & Frühwirth-Schnatter, S. (2020). Spying on the prior of the number of data clusters and the partition distribution in bayesian cluster analysis, arXiv: 2012.12337 https://doi.org/10.1111/anzs.12350.

Groen, J., Paap R., & Ravazzolo, F. (2009). Real-time inflation forecasting in a changing world. Econometric Institute Report, 2009-19, Erasmus University Rotterdam https://www.newyorkfed.org/medialibrary/media/ research/staff_reports/sr388.pdf.

Huber, F., Koop, G., & Onorante, L. (2021), Inducing Sparsity and Shrinkage in Time-Varying Parameter Models, Journal of Business & Economic Statistics, 39, 669–683 DOI: 10.1080/07350015.2020.1713796.

Hun, L. (2021). Does money supply drive housing prices in China? International Review of Economics and Finance, 60, 85–94 DOI: 10.4236/jmf.2021.112015.

Jafari Samimi, A., Elmi, Z., & Hadizadeh A. (2006). Factors influencing the behavior of housing price index in Iran. Iranian Economic Research Quarterly, 9(32), 53-31 https://ijer.atu.ac.ir/article_3624.html [In Persian].

Johnstone, H., & Watuwa, R. (2007). House price in Canada: An empirical investigation. Journal of Urban Economics, 35(1), 1-27.

Jud, G.D. & Winkler, D.T. (2002). The dynamics of metropolitan housing prices. Journal of Real Estate Research, 23(1/2), 29-46 https://libres.uncg.edu/ir/uncg/f/D_Winkler_Dynamics_2002%20(MULTI%20UNCG%20AUTHORS).pdf.

Kamali Dehkordi, P. (2019). Analysis of the effect of currency shocks, economic sanctions and oil prices on the housing market (using the SVAR structural vector autoregression model). Scientific Quarterly of Applied Economic Theories, 7(4), 56-27 https://journals.tabrizu.ac.ir/article_12266.html [In Persian].

Khayani, N. (2012). Determinants of housing prices in Iran. Housing Economics Quarterly, (34), 46-52 https://www.sid.ir/paper/440107/fa [In Persian].

Koop, G., & Korobilis, D. (2011). UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so? Economic Modelling, 28(5), 2307–2318 https://doi.org/10.1016/j.econmod.2011.04.008.

Koop, G., McIntyre, S., Mitchell, J., & Poon, A. (2020). Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970. Journal of Applied Econometrics, 35(2), 176–197 https://ideas.repec.org/p/nsr/escoed/escoe-dp-2018-14.html.

Kouhi leilan, B., Dabbagh, R., Kiaalhosseini, S. Z., & Rahbar, F. (2021). A study of the influence and influence of factors affecting the stability of the banking system in selected countries of the Mena region. Journal of Development and Capital, 6(1), 1-18 DOI: 10.22103/jdc.2021.16550.1107 [In Persian].

Leamer, E. (2007). Housing is the business cycle. The national bureau of economic research Working Paper, (13428). https://www.nber.org/papers/w13428

Liang, Q., & Cao, H. (2007). Property prices and bank lending in China. Journal of Asian Economics, 18(1), 63-75 https://doi.org/10.1016/j.asieco.2006.12.013.

Mandell, S. (2011). Bank Lending and House Prices in Sweden 1992-2010, ERES eres2011_91, European Real Estate Society (ERES), https://eres.architexturez.net/doc/oai-eres-id-eres2011-91.

Mohammadi, T., khiabani, N., Bahrami, J., & fahimifar, F. (2020). Comparison of different methods of predicting Iran's economic growth with an emphasis on dynamic model selection and dynamic model averaging. QJER, 20(4), 93-123 http://ecor.modares.ac.ir/article-18-38166-fa.html [In Persian].

Mohammadi, T., Bahrami, J., & Fahimifar, F. (2022). Comparing the forecasting of Iranian inflation with many predictors. Quarterly Journal of Quantitative Economics, 18(4), 159-190 DOI: 10.22055/jqe.2020.31882.2190.

Mousavi, M., & Drodian, H. (2014). Analysis of factors affecting housing prices in Tehran. Economic Modeling Scientific Quarterly, 9(31), 103-127 https://sid.ir/paper/176181/fa [In Persian].

Nasiri, Z., Sarraf, F., Tanhayi, M. R., EmamVerdi, Q., & Moghaddam, A. N. (2023). Predicting fluctuations in Tehran Stock Exchange indices through a Harmonic Quantum Oscillator model. Accounting and Auditing Research, 15(57), 89-110 DOI: 10.22034/iaar.2023.172754 [In Persian].

Nuri, H., Drachal, K., & Halil Eksi, I. )2022(. Predicting house prices using DMA method: Evidence from Turkey. Economies 10: 64. https:// doi.org/10.3390/economies10030064.

Pan, H., & Wang, C. (2013). House prices, bank instability, and economic growth: Evidence from the threshold model. Journal of Banking &Finance, 37(5), 1720-1732 https://doi.org/10.1016/j.jbankfin.2013.01.018.

Panagiotidis, T., & Panagiotis, P. (2015). On the macroeconomic determinants of the housing market in Greece: A VECM approach. Hellenic Observatory Papers on Greece and Southeast Europe, GreeSE Paper No.88. DOI: 10.1007/s10368-016-0345-3.

Pesaran, M.H., & Timmermann, A. (2005). Small sample properties of forecasts from autoregressive models under structural breaks, Journal of Econometrics, Elsevier, 129(1-2), 183-217 RePEc:eee:econom:v:129:y:2005:i:1-2:p:183-217.

Qolizadeh, A., Golzarian, P., & Shakuri Monfared, F. (2018). Investigating the effect of housing prices on non-current claims in Iran's banking system. Scientific Quarterly of Applied Economic Theories, 6(3), 189-214 https://ecoj.tabrizu.ac.ir/article_9467_1147.html [In Persian].

Qolizadeh, A., & Ahmadzadeh, A. (2008). Investigating the effect of loans granted by Maskan Bank on housing prices. Maskan Bank. Research and Development Center, 110-128 [In Persian].

Qolizadeh, A., & Bakhtiaripour, S. (2010). The effect of loans on housing prices in Iran. Journal of applied economic studies in Iran, 3, 179-159 https://sid.ir/paper/481863/fa [In Persian].

Qureshi, M. (2006). Investigating the effect of oil sector revenues on the price and level of housing activity in Iran. Master Thesis, Allameh Tabatabai University [In Persian].

Raftery, A., Miroslav, K., & Pavel, E. (2010). Online prediction under model uncertainty via dynamic model averaging: Application to a cold rolling mill. Technometrics, 52, 52–66 DOI: 10.1198/TECH.2009.08104.

Risse, M., & Martin, K. (2017). Forecasting house-price growth in the Euro area with dynamic model averaging. The North American Journal of Economics and Finance, 38, 70–85 https://doi.org/10.1016/j.najef.2016.08.001.

Sabbagh Kermani, M., Ahmadzadeh, Kh., & Mousavi Nik, H. (2010). Determinants of housing prices with the approach of causal relationships in the vector error correction model: a case study of Tehran. Economic Research Quarterly, 10(2), 267-293 https://joer.atu.ac.ir/article_2779.html [In Persian].

Sarmi, H.R., Heydari, M., & Aghaei, F. (2017). Spatial analysis of housing prices using the geographically weighted regression technique. The study area: two districts of Tehran municipality. Urban Economics, 3(2), 19-38 https://ue.ui.ac.ir/article_23662.html [In Persian].

Sheikhli, S., Nasiri Aqhdam, A., Amadeh, H., & Doroodian, H. (2023). Modelling of banking crisis forecasting in Iran by BMA. Quarterly Journal of Applied Theories of Economics, 9(4), 1-36 DOI: 10.22034/ecoj.2022.53817. 3125 [In Persian].

Stock, J., & Watson, M. (1998). Diffusion indexes. NBER Working Paper No.w6702. RePEc:nbr:nberwo:6702.

Stock, J., & Watson, M. (2006). Macroeconomic forecasting using many predictors. In: Elliott, G., Granger, C., Timmerman, A. (Eds.), Handbook of Economic Forecasting. North Holland, Amsterdam.

Stock, J., & Watson, M. (2008). Phillips curve inflation forecasts. NBER Working Paper, No. 14322, 2008.

Suri, A., Heydari, H., Afzali, H. (2011). Investigating the relationship between demand side variables and effective supply on the housing sector on housing prices in Iran. Economic Research Quarterly, 12(1), 113-140. https://ecor.modares.ac.ir/browse.php?a_id=466&sid=18&slc_lang=fa [In Persian].

Tahmtani, M., & Golestani, S. (2011). Estimation of hedonic housing price function in Kerman city. Journal of Development and Capital, 4(1), 75-99 https://jdc.uk.ac.ir/article_2061.html?lang=en.

Tajik, M., Aliakbari, S., & Ghalia, T. (2015). House prices and credit risk: Evidence from the United States. Journal of Economic Modelling, 51(2), 35-48 DOI: 10.1016/j.econmod.2015.08.006.

Statistics
Article View: 361
PDF Download: 121


Journal management system. designed by sinaweb