Analysing Housing Market Affordability in Northern Ireland: towards a better understanding

Purpose The purpose of this research is to examine the nature of housing market affordability. Although the problem of housing affordability has been widely discussed, the theoretical underpinnings of the concept have received less attention. It has become increasingly evident that more holistic insights and integrated approaches are needed to provide a platform to define affordability to influence research and policy discourse. Design/methodology/approach Given the increasing importance of affordability within housing policy reform, this paper seeks to “unearth” the most important prognosticators of affordability. The paper uses principal component analysis to determine how affordability, as a key policy tool, should be analysed. In addition, co integration techniques, Granger causality and impulse response analysis are applied to test the movement and shocks of the key affordability indicators and the two common affordability metrics. Findings The principal conclusions stemming from this paper demonstrate that affordability is a multifaceted policy concept influenced by financial access (purchase) costs and the repayment costs of housing services which are correlated and interchangeable but significantly were found not to be co integrated. Originality/value Understanding the nature of housing market affordability remains problem for policy-makers. This paper adds to the debate and empirical understanding of the cyclic nature of affordability and how it is defined. It shows that there are intricate causal short-term relationships between the key affordability indicators. This is problematic for contemporary housing policy and the key directions in which policy must turn. </jats:sec

Commercial leases in the UK regions: business as usual?

PurposeThe purpose of this paper is to analyse the changing nature of commercial leases with specific reference to the landlord and tenant relationship, lease lengths and incentivisation in the post-recessionary UK property market.Design/methodology/approachThe research applies data analysis utilising the Estates Gazette Interactive database coupled with survey analysis conducted across three UK cities to investigate and compare the changing nature of the commercial property leasing market and the landlord and tenant relationship.FindingsThe empirical analysis highlights that recessionary conditions prevalent in the market from the 2007 global crisis has caused a reassessment of lease structures, leading to shorter lease terms and increased use of incentives, as tenants have been empowered to negotiate more flexible leases due to their stronger market position.Originality/valueThis paper builds upon previous research conducted back in 2005, investigating commercial leases in the market up-cycle. The recent volatility in the commercial property sector requires fresh insights and in-depth analysis of lease patterns, length and covenant strength, which is fundamental for investor decision-making. In addition, past research has tended to consider solely landlord or occupier perspectives, whereas this research offers new insight into the landlord–tenant lease negotiation process.</jats:sec

Accounting for locational, temporal, and physical similarity of residential sales in mass appraisal modeling: the development and application of geographically, temporally, and characteristically weighted regression

Geographically weighted regression (GWR) has been recognized in the assessment community as a viable automated valuation model (AVM) to help overcome, at least in part, modeling hurdles associated with location, such as spatial heterogeneity and spatial autocorrelation of error terms. Although previous researchers have adjusted the GWR weights matrix to also weight by time of sale or by structural similarity of properties in AVMs, the research described in this paper is the first that has done so by all three dimensions (i.e., location, structural similarity, and time of sale) simultaneously. Using 24 years of single-family residential sales in Fairfax, Virginia, we created a new locally weighted regression (LWR) AVM called geographically, temporally, and characteristically weighted regression (GTCWR) and compared it with GWR-based models with fewer weighting dimensions