Assessment of the situation on the regional housing market in Russia - Курсовая работа

Introduction The majority of Russian citizens have some real estate in their propertyoneway or another - either for living or for investment purposes. Formany people their real estate is the most valuable asset they have, that is why housing defines and reflects quality of life and plays a significant role in the formation of public wealth.And at the same time the increase of personal income usually boost housing consumption, prices and construction activity (Aoki, Proudman, and Vlieghe 2004), which enhances GDP, additional job creation and finally redistribution of wealth. Moreover real estate is a separate class of investment assets that attracts more and more attention in the global investment community and in particular in Russia. There are several reasons for that. First of all, real estate is believed as a good inflation-hedging instrument due to the fact that in average the value of real estate in many countries increases at least as fast as inflation rate or even faster. Furthermore it is usually considered as an asset that has negative correlation with “bad times”: this feature relates to the belief of the investors that real estate is a “safe haven” during the crisis, because it is able to store the value even when financial markets crash. Finally real estate outperformed in comparison with other asset classes such as fixed-income, index, etc. in long run. (Ilmanen, 2012) This is also relevant regarding housing market in Russia(see figure1).Compared to real return of broad Russian equity index MICEX, the real return of housing was much smoother and experienced less considerable drawdown during numerous crises that occurred at that time. Besides real return remained positive for a really long period of time - at least 11 years, which means that housing prices outperformed inflation and allowed not only saving but multiplying capital of real estate owners. Fig. 1. Real return of residential housing vs. real return of financial market 1998-2015 However real estate market is highly opaque because of incredible amount of factors that influence the price, which are studied in hedonic models such as (Goodman 1978), (Malpezzi and others, 2003), etc. This aspect complicates research in this field, especially macroeconomic and regulatory aspects are currently underinvestigated. In particular, little had been done for understanding real estate market in Russia despite the fact that questions connected to pricing of such assets are urgent for Russian investors as well as for any other investors in the world. During past years housing prices in Russia were quite volatile (see figure 2). (Case and Shiller 1988)This result found implications in furtherdynamic models of housing market of different countries such as (Poterba, Weil and Shiller, 1991) and in particular in dynamic models of general equilibrium such as (M. Iacoviello 2010)(M. Iacoviello and Neri 2008), etc. This problem was solved on the New Zealand data in the study of(Grimes and Aitken 2010), who used an actual residential construction land cost. For other markets the issue is still underinvestigated due to unavailability of proper data. Furthermore the irrelevance of supply which was stated by Poterba had been challenged by a number of studies such as(Caldera and Johansson 2013)and (Glaeser, Gyourko, and Saiz 2008). Construction constrains were proved to explain instantaneous stickiness of the housing prices in dynamic models. Due to the fact that the amount of vacant land which is suitable for residential construction is highly restricted especially in metropolitan areas, it takes time and considerable amount of resources to pass through all the governmental procedures to obtain a building permit and start construction works. Table 1. Literature review on empirical estimation of housing market structural models Article attributes Sample Variables and Method Results Housing market spillovers : evidence from an estimated DSGE model (M. M. Iacoviello and Neri 2008)USA 1695-2006 quarterly dataDSGE model. The goal: to study core drivers of housing prices in the USA; to study the effect of housing market on external economic environment Results: prices are mostly driven by the availability of land and the difference in technological progress between housing and non-housing sectors; monetary factors explain only 20% of housing price variation; Wage rigidity increases the sensitivity of output to shifts in aggregate demand; collateral effect increases the elasticity of consumption to wealth. So spillovers of the housing market matter more and more Supply constraints and housing market dynamics (A. Paciorek, 2013) USA 1975-2008 yearly data Dynamic structural model The goal: to investigate the mechanism of interconnection between housing supply and housing prices Results: bureaucratic processes diminish developer’ reaction on demand shocks and create additional expenses for them; geographic limitations restrict opportunity for quick response for demand shoc