Housing Markets in Spain and the US: Some Lessons for India

2013 ◽  
Author(s):  
Amandeep Singh ◽  
Amrit Nanda ◽  
Charan Singh
Keyword(s):  
2007 ◽  
Vol 200 ◽  
pp. 7-30 ◽  

The global economy expanded by 5.3 per cent in 2006, one of the fastest rates of growth in the past 35 years. We project further expansions of 5 per cent this year and 4¾ per cent in 2008. The key risks to the forecast that we highlight in this Review relate to global housing markets and the current stance of monetary policy. The US economy is restrained by the recent correction in its housing market, which is expected to continue to weigh on the economy through 2008. There is some concern that the housing investment downturn may spread to other economies, and in this report we explore the areas most at risk to such a contagion. We also consider the recent volatility in the oil price, which makes it difficult for monetary authorities to distinguish signal from noise. If too much emphasis is placed on what subsequently turns out to be noise, policy settings could turn out to be overly lax or stringent.


2018 ◽  
Vol 61 (3) ◽  
pp. 505-547 ◽  
Author(s):  
Rose Neng Lai ◽  
Robert A. Van Order
Keyword(s):  

2018 ◽  
Vol 2 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Alper Ozun ◽  
Hasan Murat Ertugrul ◽  
Yener Coskun

Purpose The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies. Design/methodology/approach The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method. Findings The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach. Research limitations/implications One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets. Practical implications The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City. Social implications The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice. Originality/value The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.


2020 ◽  
Vol 38 (6) ◽  
pp. 1120-1137
Author(s):  
John W Elrick

This article traces the terms and practices underwriting emergent forms of urban government to technical efforts to simulate markets after the Second World War. With an eye toward contemporary techno-utopian schemes and city-building initiatives, I argue that the basis of technological approaches to urban rule today—a conception of cities as complex socio-economic systems amenable to market-driven optimization—was forged by postwar administrators and technicians in response to the vicissitudes of uneven development. To advance this claim, I examine the history of San Francisco’s Community Renewal Program, an early modeling initiative sponsored in the US by the federal government. After situating it in the context of racialized housing markets and policies, I probe the Community Renewal Program’s attempt to build a computer model capable of forecasting the effects of redevelopment on housing markets. Though the Community Renewal Program model ultimately proved unviable as a planning tool, expert appraisals of it at the time simultaneously confirmed the characterization of cities as systems of market signals and affirmed in principle the ability to model and thus manage them given an appropriate technological infrastructure. In this light, current municipal design and development projects premised on interactive and remote-sensing technologies express something of the technocratic politics and optimism of the mid-20th century.


2015 ◽  
Vol 56 (1) ◽  
pp. 55-82 ◽  
Author(s):  
Ming-Chu Chiang ◽  
I-Chun Tsai
Keyword(s):  

Author(s):  
Bilgi YILMAZ ◽  
Fatma YERLİKAYA ◽  
Sevtap KESTEL
Keyword(s):  
The Us ◽  

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