Berna Keskin

Hedonic analysis of price in the istanbul housing market

The purpose of this paper is to explore the factors that affect housing prices in Istanbul. A hedonic price model is employed in order to examine housing price determinants with respect to property characteristics, socio‐economic characteristics, neighbourhood quality characteristics, and locational factors. The results reveal that housing prices are affected by these factors: living area size, being in a low storey building, being in a secured site (with swimming pool and garage), and age of the building. In addition to these determinants, the length of time the inhabitants have lived in Istanbul, the average income of the household, neighbour satisfaction and earthquake risk of the area have effects on the residential prices in Istanbul. Further research is suggested by constructing a second model that includes neighbourhood dummy variables as a proxy for submarkets, and a multi‐level modelling framework will be employed in order to analyse the urban housing submarket system.

Defining spatial housing submarkets: Exploring the case for expert delineated boundaries

Although there are numerous reasons for real estate analysts to construct spatial housing submarkets, there is little clarity about how this might best be done in practice. The existing literature offers a variety of techniques including those based on principal components analysis, cluster analysis and a range of other statistical procedures. This paper asks whether, given their market expertise and their role in disseminating information, shaping search patterns and informing bid formation, real estate agents might offer an effective but less data intensive method of submarket construction. The empirical research is based on an experiment that compares the predictive of different sets of submarket boundaries constructed by using either standard statistical methods or through consultation with real estate agents and other market analysts. The analysis draws on housing transactions data from Istanbul, Turkey. While the results do not demonstrate the outright superiority of any single method, they do suggest that expert-defined boundaries tend to perform at least as well as alternative construction techniques. Importantly, the results suggest that agent-based methods for delineating submarket boundaries might be used with a degree of confidence by real estate analysts and planners in market contexts where rich micro-datasets are not readily available. This has been one of the constraints internationally on wider adoption of submarket boundaries as an analytical tool.

Using Multi Level Modeling Techniques as an AVM Tool: Isolating the Effects of Earthquake Risk from Other Price Determinants

Automated valuation methods employ diverse methodologies. The appropriateness of the individual model is contingent upon the characteristics of the housing market in question. In circumstances where the housing market is spatially variegated and data is sparse, distinguishing impacts of an environmental event or externality on different spatial segments of the market is challenging. A multi-level model provides one possible approach. Here we apply the model to explore the impact of a natural disaster on the housing market in Istanbul, a city located in a region with relatively frequent seismic activity. The Chapter provides a relatively simple exemplar of the method and its utility. Two levels of influence emerge. We distinguish between the citywide and segmented neighbourhood impact of earthquakes on house prices. Appraisers working in segmented markets where the potential for natural disasters occur might consider the methodological advantages of using multi-level modeling to help isolate both the effects of the risk of damage and also to discern the spatial variations in such effects. Furthermore we contend that there is considerable scope to expand the modelling approach to take account of different levels.

Modelling the impact of earthquake activity on real estate values: a multi-level approach

Purpose This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market. Design/methodology/approach The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region. Findings The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values. Research limitations/implications The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets. Practical implications The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments. Social implications The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk. Originality/value The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

Explaining Spatial Variation in Real Estate Development Activity in Turkey

There is a strong policy discourse at local and national level in Turkey that ascribes considerable economic benefits to new construction activity. Critics, however, argue that this policy discourse has led to a mismatch between public policy and market fundamentals in many cities. It has been suggested that policy intentions might be driving construction levels above demand levels and could be contributing to uneven spatial development between regions. This paper seeks to shed light on this argument by systematically exploring the relationship between planning policy and development activity in 81 Turkish cities. The analytical framework draws on research undertaken by Bramley and Leishman (2005) and Henneberry et al (2005) on the relationship between public policy and market outcomes and has been adapted to take account of the institutional arrangements and policy instruments operating in Turkey. Drawing on data on economic activity, local social indicators, planning permissions and applications, and demographic change, the paper develops a cross-sectional econometric model that helps isolate the effects of planning policy from other drivers of construction activity. The second stage analysis uses to GIS methods and spatial statistics to develop an understanding of spatial variations in the drivers of development activity. The paper offers some tentative conclusions about the relationship between policy imperatives, market fundamentals and development activity.