Volume 9, Issue 34 (12-2018)
jemr 2018, 9(34): 7-30 |
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Arman A, Azari Beni B. The Effects of the Housing Shock on Income Dynamics in Iran: an Application of Data Pseudo-Panel. jemr 2018; 9 (34) :7-30
URL: http://jemr.khu.ac.ir/article-1-1569-en.html
URL: http://jemr.khu.ac.ir/article-1-1569-en.html
1- Shahid Chamran University of Ahvaz , saarman2@yahoo.com
2- Shahid Chamran University of Ahvaz
2- Shahid Chamran University of Ahvaz
Abstract: (4661 Views)
Fluctuations in housing prices in recent years in Iran has always been one of the most important economic issues on the economic welfare changes affect lifetime. In this paper, the effects of housing on the dynamics of income generations age is examined. This phenomenon type of model is designed to assess the generation of data building. The model is designed household budget generations by combining cross-sectional data from households in the years 2007 to 2015 are tracking. In this research, in order to clarify the contents of the review results in four steps without shock and shock 5, 10 and 15 percent reported. The results show that the average income of households without shock reduced from 86 years to 89 and then 89 years with little speed has increased, although the increase in revenue in less than 86 years is 90 years. As well as small shock in 2007 has led to middle income households in that year and the following years than before the occurrence of shocks is reduced. While the occurrence of a great shock (15%) reduces the average household income has been greatly. This could mean that in the event of a large shock of vulnerable households are barely able to restore income dropped while repairing a small shock is possible.
Type of Study: Applicable |
Subject:
بخش عمومی
Received: 2017/05/2 | Accepted: 2018/12/23 | Published: 2019/02/25
Received: 2017/05/2 | Accepted: 2018/12/23 | Published: 2019/02/25
References
1. Central Bank of the Islamic Republic of Iran, Economic profiles to different years.
2. Collado, M. D. (1998). Estimating Dynamic Models From Time Series of Independent Cross-Sections. Journal of Econometrics 82, pp. 37-62. [DOI:10.1016/S0304-4076(97)00015-8]
3. Chen Ming-Chi and Patel Kanak. (1998). House Price Dynamics and Granger Causality: An Analysis of Taipei New Dwelling Market. journal of the asian real estate society 1998 vol.1 no 1: pp. 101 -126.
4. Deaton, A. (1985). Panel Data from time series of cross-sections. Journal of Econometrics, 30, pp. 109-126. [DOI:10.1016/0304-4076(85)90134-4]
5. Gholizadeh, Ali Akbar. (2010). Price Bubble and Mechanism of Effect of Monetary Policy on Housing Prices in Urban Urban Areas. Research project of the Ministry of Housing and Urban Development (ex).
6. Gholizadeh, Ali Akbar. (2010). The theory of housing prices in Iran. Hamadan: Noor Alam Publications.
7. Gholizadeh, Ali Akbar and Bakhtiyarpour, Samira. (2010). The effect of credits on housing prices in Iran. Quarterly Journal of Applied Economic Studies in Iran. first year. No. 3, pages 179-159.
8. Hu, Jianying & su Liangjun & Jin , sainan &. Jiang , Wanjun. (2006). The Rise in House Prices in China: Bubbles or Fundamentals? Economics Bulletin 37 1-9
9. Iranian Statistics Center, Information on Cost and Income of Urban Households (2007-2015), Tehran: Statistics Center of Iran.
10. Gimeno, R. and Martinez-Carrascal, C. (2010 ). The Relationship between Housing Prices and House Purchase Loans: The Spanish case. Journal of Banking and Finance, No 34 , pp. 1849-1855. [DOI:10.1016/j.jbankfin.2009.12.011]
11. Khosrowinezhad, Ali Akbar and Fathi, Farzaneh. (2012). Check the bubble in the housing market using panel data. Quarterly Journal of Applied Economics. third year. No. eighth Pages 169-142.
12. Lokshin, M. , & Ravallion, M. (2004). Household income dynamics in two transition economies. studies in nonlinear dynamics and econometrics, 8(3). [DOI:10.2202/1558-3708.1182]
13. Wang,zhi & Zhang, Qinghua.(2014 ). Fundamental factors in the housing market of chaina - journal of Housing Economics (2014 ) 53-61. [DOI:10.1016/j.jhe.2014.04.001]
14. McKenzie, D. (2004). Asymptotic Theory for Heterogeneous Dynamic Pseudo-panels. Journal of Econometrics, 120(2), pp. 235-262. [DOI:10.1016/S0304-4076(03)00213-6]
15. Moffitt, R. (1993). Identification and Estimation of Dynamic Models with. Journal of Econometrics 59, pp.99-124. [DOI:10.1016/0304-4076(93)90041-3]
16. Neukirchen, M. and Lang, H. (2005 ). Chareacteristics and Macroeconomic Drivers of Housing PriceChanges in Australia. www.u21 global.edu.sg/PartnerAdmin/. [DOI:10.2139/ssrn.1614697]
17. Nazari, Azimand Syri, Davod. (2009). Precious Bubble Study in Iran's Housing Market. Quarterly Journal of Housing Economics. Office of Planning and Housing Economics, 43 and 44, 91-63.
18. Rezaei Ghahroudi, Zahra. Mostafavi, Neda and Samaneh Honorary. (2013). Consumer Pattern Analysis in Urban Life Cycle. Social Welfare, 49 (13): 234-213.
19. Verbeek, M. Vella, F. (2002) Estimating Dynamic Models from Repeated Cross-Section. Journal of Econometrics.
20. Jalan, Jyotsna and Martin Ravallion (2001). Household Income Dynamics in Rural China. Journal of Comparative Economics, 26: 1-28.
21. Shiller، R. (1981). Do stock prices move too much to be justified by subsequent changes in dividends?. American Economic Review، vol 71، pp 421-36. [DOI:10.3386/w0456]
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