The Effect of Liquidity on Private Investment in the Urban Housing Market in Iran

Subject Areas : Regional Planning

Siamak Shokouhifard ¹ , Ali Salmanpour ² , Farzad Rahimzadeh ³ , Zahara Ebrahimi ⁴

1 - Department of Economics, Payame Noor University, Tehran, Iran.
2 - Assistant Professor, Department of Economics, Marand Branch, Islamic Azad University, Marand, Iran
3 - Assistant Professor, Department of Economic and Accounting, Faculty of Literature and Humanities, University of Guilan, Rasht, Iran
4 - Department of Business Management, Faculty of Management, Al-Zahra University, Tehran, Iran

Received: 2021-05-20 Accepted : 2021-12-25 Published : 2024-02-20

Keywords: liquidity, Auto Regressive Distributed Lag Model, Urban Housing Market, Private Sector Investment,

Abstract :

The Effect of Liquidity on Private Investment in the Urban Housing Market in Iran
Abstract
The housing market, as a major economic sector, has an important role in the country's economy. Regarding the structure of the country's economy and also considering the characteristics of housing as a commodity, housing prices are always affected by fluctuations and surplusThe housing market is one of the important channels for the impact of monetary policy on the country's economy. Therefore, considering the importance of the issue in the present article, in order to study the effects of liquidity on private sector investment in the housing sector during the period 1990- 2021 a Auto regressive distributed lag model has been used. Also a model of error correction is used for studding of short-term dynamics and their relation with long-term dynamics is presented. In general, the results of the study show that the effects of variables on national income, liquidity, housing loan facilities, construction services price index with a one-year break and population with a one-year break and on private sector investment in urban housing are positive and significant. But the impact of housing price variables and the average return of parallel markets on private sector investment in the urban housing market are negativeand significant. As a result, considering the main positive and significant independent effect of the research, namely liquidity on private sector investment in Iran's urban housing market, it can be said that increasing liquidity increases people's purchasing power and consequently increases demand and thus encourages the private sector. There will be more investment in the housing sector.
Keywords: Urban Housing Market, Private Sector Investment, Liquidity, Auto Regressive Distributed Lag Model.
Extended Abstract
 
Introduction
The housing market, as a major economic sector, has an important role in the country's economy, and due to its past and present relations, it is strongly affected by its economic fluctuations. Due to the structure of the country's economy and also due to the characteristics of housing as a capital commodity, housing prices are always affected by fluctuations and excess liquidity movements in society and periodically, face a jumping increase. The housing market is one of the important channels for the impact of monetary policy on the country's economy. Due to the intermittent increase in housing prices in Iran, especially in the years after the imposed war and the intermittent creation of housing price bubbles and the stagnation after the bursting of the housing price bubble, it has been suggested that intermittent increases in housing prices are due to Is the country. Liquidity from monetary policies in the economy has undeniable effects on private sector investment in the sector. In this regard, the hypotheses of the leading research are as follows:

Liquidity affects private sector investment in the Iranian urban housing market.
National income affects private sector investment in Iran's urban housing market.
Construction services price index has an impact on private sector investment in Iran's urban housing market.
Urban population affects private sector investment in Iran's urban housing market.
Urban housing prices affect private sector investment in Iran's urban housing market.
Housing purchase facilities have an impact on private sector investment in Iran's urban housing market.
The average return of parallel markets has an impact on private sector investment in Iran's urban housing market.

 
Methodology
This research is applied in terms of purpose. Leading research is also regression in terms of type of analysis. Multivariate linear regression models and microfiche software were used to analyze the data. In this research, documentary method has been used to collect information related to the literature and research background. Considering the importance of the issue the impact of liquidity on private sector investment in the housing sector during the period 1990- 2021 a Auto regressive distributed lag model has been used. In addition, we use the ECM to investigate short-term dynamics and relate them to the long-run relationship presented by summative regression, and also to examine how to adjust short-term dynamics for long-run equilibrium.For estimation, a Auto regressive distributed lag is used using Microfit software and in estimation, all possible interrupts of the final model with SBC are selected by the software.It is worth mentioning that the data and information related to the model have been extracted from the database of the Central Bank and the Statistics Center of Iran.
 
Results and Discussion
The results of estimating the Auto regressive distributed lag model show that all variables except private sector investment which is significant at the level of 10%, all are significant at the level of 5% and the variable of construction services price index with one year interval at the level 1% is significant. Liquidity, population with a one-year break, as well as construction services price index with a one-year break and national income are directly related to private sector investment. But the population in the first year shows negative relationships.According to the table of critical values of Benarji, Dolado and Master statistics at the level of 95% significance, since the value of computational statistics (-6/5549) is more than the absolute statistics of the table (3/55), so the null hypothesis of no The existence of a long-term relationship between the research variables is rejected and we conclude that there is a long-term relationship between them.According to the results, it can be seen that all variables in the long run are significant at the level of 5% and 1% and except for the urban population variable, other variables have a positive effect on private sector investment in housing.Also, according to the obtained results, ECM shows the adjustment of short-term dynamics in the direction of long-term equilibrium relationships. Also, according to the estimated results of the error correction model, if the shock causes the variables to deviate from the initial short-term equilibrium, in each period about 77% of the short-term imbalance is corrected to the long-term equilibrium. Based on the estimated results, it can be seen that the CUSUM and CUSUMQ charts are located between the two critical lines at the level of 5%. Based on these results, the coefficients of the variables are stable during the period under study.
 
Conclusion
The results of research estimates show that all independent variables have a significant relationship with the dependent variable, namely private sector investment. National income, liquidity and the price index of construction services with a one-year break are directly related to private sector investment in urban housing.It should be noted that increasing liquidity will increase people's purchasing power and consequently increase demand and thus encourage the private sector to invest more in the housing sector. Apart from the fact that increasing demand can lead to rising prices or any other changes in other macroeconomic variables.Regarding liquidity, it is important to mention that in most developing countries, including Iran, due to the lack of financial markets (money and capital) and appropriate areas of activity, liquidity is directed to the housing sector or quick-return activities.Suggestions in the scope of the discussions and the results of the present article estimates can also be mentioned as follows:
1- Supporting the private sector in more investments in the housing sector, by giving various credits and privileges.
2- Targeting liquidity that, along with the housing sector, also leads to the mobilization of production activities, ie leads to a balance in the supply and demand market.
3- Supporting different sections of society, especially low-income people, by providing bank loans to support private sector investment in the housing sector. Investors are forced to withdraw their capital from the housing sector due to recession and lack of purchasing power. Do not do unnecessary activities and even the outflow of capital from the country.
4- Injecting the necessary liquidity in different sectors of the economy Due to the consequences such as inflation, it should be noted that the necessary liquidity for the injection can be provided in various ways that must be used carefully in the use of these resources.
5- Prosperity and activation of financial and capital markets, so that in addition to preventing capital outflows abroad, it can be directed.
 

References:

References

• Akbari, N., Emadzadeh, M., & Razavi, Seyedali. (2004). A Study of Factors Affecting Housing Prices in Mashhad with the Approach of Spatial Econometrics in the Hadanik Method. Quarterly Journal of Economic Research, 4(11-12), 57-78. [In Persian]


• Askari, H., & Chegni, A. (2007). Determining the factors affecting housing prices in urban areas of the country by panel data method (1991-2006). Scientific Quarterly of Housing Economics, 40, 19-46. [In Persian]


• Baseri, B., Kiani, G., & Malekipour, M. (2021). An Analysis of Household Demand Absorption as a financial asset against Inflation volatility in IRAN. Financial Economics, 15(55), 79-106. https://dorl.net/dor/ 1001.1.25383833.1400.15.55.4.7 [In Persian]


• Chow, Sh- Ch., Cunado, J., Gupta, R.,& Wong, W- K. (2017). Causal relationships between economic policy uncertainty and housing market returns in China and India: evidence from linear and nonlinear panel and time series models. Studies in Nonlinear Dynamics & Econometrics, 22(2), 1-15. https://dorl.net/dor/1515/snde-2016-0121.


• Deng, L., & Chen, J. (2019). Market development, state intervention, and the dynamics of new housing investment in China. Journal of Urban Affairs, 41(2), 223 -247. https://dorl.net/dor/ 1080/07352166.2017.1422983.


• Ebrahimi, M., & Shokri, N. (2011). The Effect of Macroeconomic Variables on Stock Prices by Emphasizing the Role of Monetary Policy.Economic Modeling, 5(13), 23-45. [In Persian]


• Ghaderi, J., & Izady, B. (2016). Studying the Effects of Social and Economic Factors on the Housing Prices in Iran (1972-2013).Urban Economics, 1(1), 55-75. https://dorl.net/dor/ 22108/UE.2016.22104 [In Persian]


• Gholizade, A., & Mollavali, T. (2012). The Effects of Liquidity on Housing Price Fluctuations in Oil-Producing Countries VS other Countries, qjerp, 20(63), 83-104. [In Persian]


• Gholizade, A.,& Noroozonejad, M. (2019). Dynamics of Housing Prices and Economic Fluctuations in Iran with the Approach of Dynamic Stochastic General Equilibrium (DSGE), jemr, 9(36), 37-74. [In Persian]


• Gholizadeh, A., & Akbarian, H. (2010). Housing Investments and Economic Growth in Iran.Quarterly Journal of Quantitative Economics, 7(1), 105-133. [In Persian]


• Gholizadeh, A., & Kamyab, B. (2008). The effect of monetary policy on housing price bubble in periods of prosperity and recession in Iran. Quarterly Journal of Quantitative Economics, 5(3), 48-78. [In Persian]


• Golchini, S., Moradi, E., & Khezrnezhad, P. (2018). Comparative analysis of changing house indexes in urban places of Kurdistan province and Iran (1345-1390).Regional Planning, 8(30), 51-66. https://dorl.net/dor/ 1001.1.22516735.1397.8.30.4.4 [In Persian]


• Hajiheidari, A., Ezatpanah, B., & Meshkini, A. (2022). Spatial Analysis of the Affecting Factors on Housing Prices in Tehran Metropolis. Regional Planning, 12(48), 171-188. https://dorl.net/dor/30495/jzpm.2021.26895.3814 [In Persian]


• HasanGoodarzi, S., & Armanmehr, M. (2019). Market analysis and forecasting of housing prices in Tehran.Journal of Iranian Economic Issues, 5(2), 79-103. [In Persian]


• Hossain, B., & Latif, E. (2009). Determinants of Housing Price Volatility in Canada: A Dynamic Analysis. Applied Economics, 41(27), 3521-3531. https://dorl.net/dor/ 1080/00036840701522861.


• Kaghazian, S., Naghdi, Y., & H. (2015). An Analysis of the Effects of Exchange Rate Fluctuations on Housing Investment in Iran. Economic Strategy, 4(12), 181-196. [In Persian]


• Karimi, F., & Zahedi Keyvan, M. (2011). Feasibility and Determination of Investment Priorities of Housing Sector Under Risk and Uncertain Conditions. qjerp, 19(57), 31-56. [In Persian]


• King, P., & Aldershot, A. (2005). A social philosophy ofhousing. Habitat international, 29(2), 603-611.


• Kochduck, V., & Varnock, A.F. (2010). Market and House Financial Provision, Translator: Arbani Dana A. Journal of City Economy, 1(4), 32- 55.


• Kondybayeva, S. K., & Ishuov, Z. S. (2013). The effect of monetary policy on real house price growth in the Republic of Kazakhstan: a vector autoregression analysis. World Applied Sciences Journal, 22(10), 1384 -1394. https://dorl.net/dor/ 5829/idosi.wasj.2013.22.10.557.


• Mehrgan, N., & Tartar, M. (2014). Short-term and long-term effects of costs on housing prices in Tehran. Quarterly Journal of Urban Housing Economics, 50, 45-61. [In Persian]


• Mousavi, S., salmanpour, A., & shokouhifard, S. (2018). Investigating the Impact of Macroeconomic Instability on Private Investment in Iran.Quarterly Journal of The Macro and Strategic Policies, 6(22), 81-100. [In Persian]


• Nahidi Amirkhiz, M., ShokouhiFard, S., & Rahimzadeh, F. (2019). The Effect of Liquidity Growth on Business Cycle in Iran Economy. Journal of Iranian Economic Issues, 5(2),125-143. [In Persian]


• Nemati, G., Alizadeh, Mohammad., & Fetros, M. (2020). Identifying the factors affecting private sector investment in housing with emphasis on fiscal and monetary policies: Bayesian approach. Journal of Economics and Urban Management, 8(29), 87-110. [In Persian]


• Nneji, O., Brooks, C., & Ward, Ch. (2013). House Price Dynamics and Their Reaction to Macroeconomic Changes.Economic Modelling, 32(c), 172-178.


• Ott, H. (2014). Will euro area house prices sharply decrease?. Economic modeling, 42(c), 116-127.


• Panahi, H., Aghayari hir, T., & Aleemran, S. A. (2018). Studying the Instability Trend of Urban Housing Prices in Iran.Urban Economics, 2(2), 55-70. https://dorl.net/dor/22108/UE.2018.107545.1035 [In Persian]


• Robstad, Ø. (2018). House prices, credit and the effect of monetary policy in Norway: evidence from structural VAR models. Empirical Economics, 54(2), 461- 483. https://dorl.net/dor/ 1007/s00181-016-1222-1.


• Salmanpour, A., Jahandideh, F., & Bohlouli, P. (2011). The Relationship Between Investment in Housing Sector and Business Cycles During 1959-2006 in Iran.Economic Modeling, 5(13), 125-144. [In Persian]


• Shahabadi, A., & Ganji, M. (2014). Analysis of the Factors Affecting Investment In Housing and Construction in Iran. Bi-Quarterly Journal of Development Economics, Research and Planning, 3(1): 1-23. https://dorl.net/dor/ 1001.1.22516263.1393.3.1.1.2 [In Persian]


• Shi, S., Jou, J- B., & Tripe, David. (2014). Can Interest Rates Really Control House Prices? Effectiveness and Implications for Macroprudential Policy. Journal of Banking & Finance, 47(1), 15- 28. https://dorl.net/dor/ 1016/j.jbankfin.2014.06.012.


• Soheili, K., Fattahi, Sh., & Oveysi, B. (2014). A Study of Factors Affecting Urban Housing Price Fluctuations in Kermanshah. Quarterly Journal of Economic Research (Sustainable Growth and Development), 14(2), 41-67. [In Persian]