THE INTER-TIER SPREAD OF HOUSING BUBBLES: ARE LUXURY MARKETS TO BLAME?

Understanding the spread of asset bubbles is pivotal to the effectiveness of risk management. This study thus estimates housing bubbles and investigates how and to what extent price bubbles spread between the tiers of luxury and mass housing in Hong Kong. The results show that price bubbles spread between housing tiers, the spreading of bubbles is not uni-directional from luxury to mass tiers, and more than 60% of bubbles come from inter-tier spreading. Moreover, bubble shocks from the luxury tier have stronger spreading influences on the movements of bubbles in the mass housing tier than the other way around during the period before the end of the global financial crisis (GFC), whereas the opposite is true for the period after GFC. The findings are important for policy makers attempting to tackle soaring housing bubbles, financial institutions seeking to managing lending risk, and housing investors wanting to time the submarkets.

Are There Any Housing Bubbles in Turkey?

It is very important that the housing market, which meets the most basic need of people is needed for shelter from the past to the present, has a stable structure. The instability structure of the housing market is generally associated with the presence of housing bubbles. The deviation of housing prices from their basic value and not being able to be explained by economic fundamentals leads to the formation of housing bubbles. Housing bubbles can lead to permanent losses, as it may take a long time to return to normal prices. For Turkey as a developing country, it is important to identify an unstable structure in house prices discuss the basic economic factors related to this. After the global increases in housing prices, inflation, and depreciation in the Turkish lira, Turkey has become the country with the highest housing price increases globally in 2020. In the study, the presence of bubbles in the housing market for Ankara, Izmir, Istanbul, and Turkey in general, was investigated by SADF and GSADF unit root tests for the period 2010:01-2021:02. In this context, the study examines the presence of bubbles in housing prices for Ankara, Izmir, Istanbul, and Turkey in general, which are the three cities with the highest price increases. As a result of the study, the presence of bubbles in the housing market has been determined for Ankara, Istanbul, Izmir, and Turkey in general.

High-speed Urbanization and Housing Bubbles

With China's high-speed urbanization, the housing demands and housing prices have increased rapidly in major cities. By combining the classical bubble theory with investors’ short-term decisions, we propose a method to simulate bubbles' rising and bursting process in a multi-sector economy. We find that when urbanization goes too fast, the housing price growth rate will exceed the industrial interest rate, causing enterprises to buy houses. Enterprises’ housing investment further increases the expected returns of housing investment, attracting more investment and leads to housing bubbles. The faster the speed of urbanization, the higher the housing price grows, the longer the bubble cycle, and the greater the impact on the economy when bubbles burst. Continued urbanization cannot prevent bubbles from bursting. To ensure economic stability, the pace of urbanization needs to be limited.

Tax Policy and Toxic Housing Bubbles in China

This paper explores the effects of a government tax policy in a growth model with economic transition and toxic housing bubbles applied to China. Such a policy combines taxing entrepreneurs with a one-time redistribution to workers in the same period. Under the tax policy, we find that the welfare improvement for workers is non-monotonic. In particular, there exists an optimal tax at which social welfare is maximized. Moreover, we consider the welfare effects of setting the tax at its optimum. We show that the tax policy can be welfare-enhancing, comparing to the case without active policies. The optimal tax may also yield a higher level of welfare than the case even without housing bubbles. In addition, our simple numerical exercise shows that the optimal tax rate is about 23%;, and social welfare is significantly improved with such a tax policy. Finally, we extend the benchmark economy to a multi-period setting and calibrate the model to China. Our results show that a 20%; tax rate can speed up economic transition and increase output growth. Between 1998 and 2012, aggregate consumption is 4.86%; higher under active tax policies.

A research paper of Hossein Sabzian (2019), Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners, ArXiv, 54p

Nowadays, we are surrounded by a large number of complex phenomena such as virus epidemic, rumor spreading, social norms formation, emergence of new technologies, rise of new economic trends and disruption of traditional businesses. To deal with such phenomena, social scientists often apply reductionism approach where they reduce such phenomena to some lower-lever variables and model the relationships among them through a scheme of equations (e.g. Partial differential equations and ordinary differential equations). This reductionism approach which is often called equation based modeling (EBM) has some fundamental weaknesses in dealing with real world complex systems, for example in modeling how a housing bubble arises from a housing market, the whole market is reduced into some factors (i.e. economic agents) with unbounded rationality and often perfect information, and the model built from the relationships among such factors is used to explain the housing bubble while adaptability and the evolutionary nature of all engaged economic agents along with network effects go unaddressed. In tackling deficiencies of reductionism approach, in the past two decades, the Complex Adaptive System (CAS) framework has been found very influential. In contrast to reductionism approach, under this framework, the socio-economic phenomena such as housing bubbles are studied in an organic manner where the economic agents are supposed to be both boundedly rational and adaptive. According to CAS framework, the socio-economic aggregates such as housing bubbles emerge out of the ways agents of a socio-economic system interact and decide. As the most powerful methodology of CAS modeling, Agent-based modeling (ABM) has gained a growing application among academicians and practitioners. ABMs show how simple behavioral rules of agents and local interactions among them at micro-scale can generate surprisingly complex patterns at macro-scale. Despite a growing number of ABM publications, those researchers unfamiliar with this methodology have to study a number of works to understand (1) the why and what of ABMs and (2) the ways they are rigorously developed. Therefore, the major focus of this paper is to help social sciences researchers get a big picture of ABMs and know how to develop them both systematically and rigorously.