Document Type : Research Paper

Authors

1 Ph.D. in Monetary Economics, University of Tabriz, Tabriz, Iran

2 Professor of Economics, University of Tabriz, Tabriz, Iran

Abstract

Recent studies highlight an increasing focus on models that incorporate a wide range of economic data, which is made possible by enhancing traditional vector autoregression (VAR) models with one or more factors. The present study aimed to apply the self-explanatory model of the generalized factor vector autoregressive (FAVAR) to investigate macroeconomic and housing market shocks from 1991 to 2022, on a relatively small annual scale. It examined the effects of production shocks, inflation, exchange rates, oil revenues, and the money supply. Housing price levels were estimated using four indices: housing price, fuel and lighting, real estate, rent, and business activity. Additionally, the rental housing index in Tehran and the price index of construction services were used to estimate investment levels in the housing sector. The analysis also included data on new housing investment in major cities, total investment in new houses in Tehran, the number of permits issued by municipalities in urban areas, and the number of permits issued in Tehran. The results revealed that macroeconomic shocks (inflation, production, exchange rates, money supply, and oil revenues) create a wave-like effect in the housing sector, with this effect lasting approximately 6 to 8 years. Inflation, money supply, and exchange rates, compared to GDP and oil revenues, have a greater impact on the housing market. Given the varying effects of these macroeconomic shocks, the central bank and monetary authorities should consider the responses of all sectors to develop more accurate housing plans during monetary policy formulation.

Introduction

Playing a key role in intensifying economic booms and busts, the housing market is a crucial component of the Iranian economy, which can be influenced by macroeconomic shocks. A significant portion of housing demand stems from its function as an asset. When macroeconomic shocks occur, they impact the opportunity cost of holding durable goods (e.g., housing) by increasing inflation, money supply, exchange rates, and oil revenues. These shocks influence both the demand for housing as an asset and the demand for housing services, altering the relative returns on housing investments. As a result, individuals adjust their asset portfolios, including housing, in response to these economic shifts. Consequently, housing demand as an asset fluctuates accordingly. The current study highlighted the conflict between two economic objectives: fostering production and investment growth versus managing inflation, macroeconomic shocks, and their adverse social and distributional effects. The expansion of the housing market can mitigate macroeconomic shocks by improving housing availability for households, contributing to sectoral and national economic growth. However, it may also drive up housing prices. Using the self-explanatory model of the generalized factor vector autoregressive (FAVAR), this empirical research aimed to examine the impact of macroeconomic shocks on housing prices in Iran’s economy.

Materials and Methods

The present study used time series data on macroeconomic variables and bank stability from 1991 to 2022. The data selection followed the general classification outlined in Bernanke et al. (2005), which includes production, inflation, money supply, oil revenues, exchange rates, and the housing market. Since the estimation of factors using the FAVAR requires stationarity, tests such as the generalized Dickey-Fuller unit root test were conducted on the variables. The modeling of FAVAR was based on Bernanke et al. (2005), while the model estimation followed the expectation-maximization algorithm as proposed by Dempster et al. (1977) and Shumway and Stoffer (1982). All variables were obtained from the time series databases of the Central Bank and the Ministry of Housing and Urban Development. After estimating the FAVAR model using EViews and SPSS software, the study presented the instantaneous response analysis of the model variables concerning the key variables over ten periods. The variables were transformed into logarithmic form, and their growth rates were calculated.

Results and Discussion

The response of housing prices and investment in the housing sector to a one-standard-deviation shock was immediate and significant, indicating that the economy quickly adjusts to the shock’s influence in the initial years. As shown in Figure (1), shocks related to production, money supply, exchange rates, oil revenues, and inflation created a wave-like effect in the housing sector, with a duration of approximately 15 years (15 periods), reflecting a period fluctuation. A one-standard-deviation shock in the exchange rate initially caused both housing investment and prices to rise. However, the impact gradually diminished, with investment converging to zero after 9 periods and housing prices after 8 periods—which aligns with expectations. Similarly, a one-standard-deviation shock in money supply initially increased investment in the housing sector while causing housing prices to decline. After 4 periods, both investment and prices converged towards zero, as anticipated. In the case of inflation, a one-standard-deviation shock initially reduced investment in the housing sector, followed by an increase. At the same time, housing prices rose with the inflation shock but gradually declined, with both investment and prices converging towards zero after 8 periods. A shock to GDP led to an initial increase in housing investment and a decline in housing prices. Over time, these effects diminished, with investment and prices converging towards zero after 4 periods and 3 periods, respectively. A one-standard-deviation shock in oil prices resulted in an increase in both housing investment and prices. However, these effects waned, with investment converging to zero after 4 periods and housing prices after 3 periods. Overall, the impact of these shocks diminished over time and eventually converged to zero, as it was anticipated.
 
 
Figure 1. Macroeconomic shocks
 

Conclusion

According on the results of the FAVAR model, macroeconomic shocks have both direct and indirect effects on the housing sector and other markets. Macroeconomic shocks were found to increase demand in the housing sector, as housing is an asset that can absorb shocks over the long term and helps preserve the value of money to some extent. The housing channel also exhibited a consistent degree of price stickiness in response to these shocks. The analysis of macroeconomic shocks on housing prices and investment suggested that increasing demand for smaller housing units would drive future demand toward compact-sized homes. This shift is largely due to the declining purchasing power of the middle class, which has been severely impacted by recent shocks of inflation, monetary supply, exchange rates, and oil revenues. As a result, lower-income groups are left with little financial strength to afford housing. The growing gap between housing costs and household income further contributes to this trend. Moreover, the increasing share of housing costs in household expenditures—observed even during periods without economic sanctions—underscores this financial strain.

Keywords

Main Subjects

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