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Estimates are developed of the major macroeconomic aggregates – wages, land rents, interest rates, prices, factor shares, sectoral shares in output and employment, and real wages – for England by decade between 1209 and 2008. The efficiency of the economy in the years 1209–2008 is also estimated. One finding is that the growth of real wages in the Industrial Revolution era and beyond was faster than the growth of output per person. Indeed until recently the greatest recipient of modern growth in England has been unskilled workers. The data also create a number of puzzles, the principal one being the very high levels of output and efficiency estimated for England in the medieval era. These data are thus inconsistent with the general notion that there was a period of Smithian growth between 1300 and 1800 which preceded the Industrial Revolution, as expressed in such recent works as De Vries (2008).

The authors provide a way to represent spatial and temporal equilibria in terms of error correction models in a panel setting. This requires potentially two different processes for spatial or network dynamics, both of which can be expressed in terms of spatial weights matrices. The first captures strong cross-sectional dependence, so that a spatial difference, suitably defined, is weakly cross-section dependent (granular) but can be non-stationary. The second is a conventional weights matrix that captures short-run spatio-temporal dynamics as stationary and granular processes. In large samples, cross-section averages serve the first purpose and the authors propose the mean group, common correlated effects estimator together with multiple testing of cross-correlations to provide the short-run spatial weights. The authors apply this model to the 324 local authorities of England, and show that our approach is useful for modeling weak and strong cross-section dependence, together with partial adjustments to two long-run equilibrium relationships and short-run spatio-temporal dynamics. This exercise provides new insights on the (spatial) long-run relationship between house prices and income in the UK.

This study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels.

Data for eight Australian states on a quarterly basis from 2004–2017 is used. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction model (PVECM) is adopted.

Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed between the two variables. From the regional breakdown and analysis, it is discerned that in some states there is a significant and positive effect of immigration on residential real estate prices in the long run. Causality analysis confirms that the direction of causation is from immigration to housing prices.

The study illustrates that immigration and interstate migration, as well as high salaries, have been causing a rise in housing demand and subsequently housing prices. To monitor exceedingly high housing prices, local authorities should be controlling migration and salary levels.

Past research studies had highlighted the importance of native interstate migration in explaining the nexus between immigration – housing prices. In this study, it has been empirically verified how immigration has been affecting the locational decisions of natives and subsequently how this has been affecting housing prices.

Increasing regional wealth disparities have been explained by the role of agglomeration economies and the concentration of skilled mobile human capital. This paper aims to draw out the role of the housing market by considering the differential experience of Germany and the UK.

The empirical analysis is based on the comparison of regional house price trends in Germany and UK-based annual data from 1991 to 2015.

Regional house price inequality is found to have increased in both countries with the spatial concentration of skilled human capital. However, the main conclusion is that there are differential paths to regional house price inequality explained by the parameters of each country’s housing market.

The research is the first to compare and explain differential regional house price trends across countries.

This study aims to address the gap by empirically exploring how residential construction-production progress, which includes project commencement, under-construction and project completion, responds dynamically to fluctuations in house prices.

A vector autoregressive model and an impulse response function are applied to simulate and analyse the circle of the stage-responsiveness of residential construction to residential property price dynamics in the state of Victoria, Australia. The quarterly numbers of dwelling units commenced, under-construction and completed are used as the proxy for the residential construction activities at three stages over the construction progress.

The analysis indicates that the dynamics are essentially transmitted throughout the construction process and can substantially impact the pace of production progress. The findings from this study provide an empirical base that should be useful in developing price-elasticity and production theories applicable to the context of residential property construction.

The findings described above have been generated basically by examining the case of Victoria, Australia at a macro level. The generalisation of the research output needs to be verified further by future researchers using data collected from other regions/countries. Nevertheless, the reliability of the conclusions with particular practical implications can be substantially improved by future researchers by analysing more markets and production proxies at the activity level.

Based on new empirical findings, this research argues that building activity (i.e. under construction) played as a gateway between the construction and housing sectors, via which the inter-responsiveness of the housing supply in terms of construction activities and housing prices are transmitted.

This research firstly attempts to explore the inter-responsiveness between the real estate and construction sectors. A simulated circle of the stage-responsiveness of residential construction to residential property price dynamics is proposed, which can serve as a significant foundation for developing the theory of construction production.

Buildings contribute significantly to CO₂ production. They are also subject to considerable taxation based on value. Analysis shows that while similar attributes contribute to both value and CO₂ production, there is only a loose relationship between the two. If we wish to use taxation to affect policy change (drive energy efficiency behaviour), we are unlikely to achieve this using only the current tax base (value), or by increasing the tax take off this current tax base (unlike extra taxation of cigarettes to discourage smoking, for example). Taxation of buildings on the basis of energy efficiency is hampered by the lack of current evidence of performance. This paper aims to model the now-obligatory (at sale or letting) energy performance certificate (EPC) data to derive an acceptable appraisal model (marked to market, being the EPC scores) and deploys this to the entire population of properties. This provides an alternative tax base with which to model the effects of a tax base switch to energy efficiency and to understand the tax incidence effects of such a policy.

The research uses a multiplicative hedonic approach to model energy efficiency utilising EPC holding properties in a UK jurisdiction [Northern Ireland (NI)] as the sample. This model is then used to estimate discrete energy assessments for each property in the wider population, using attributes held in the domestic rating (property tax) database for NI (700,000+ properties). This produces a robust estimate of the EPC for every property in its current condition and its cost-effective improved condition. This energy assessment based tax base is further used to estimate a new millage rate and property tax bill (green property tax) which is compared against the existing property tax based on value to allow tax incidence changes to be analysed.

The findings show that such a policy would significantly redistribute the tax burden and would have a variety of expected and some unexpected effects. The results indicate that while assessing the energy performance of houses can be a complex process involving many parameters, much of the explanatory power can be achieved via a relatively small number of input variables, often already held by property tax jurisdictions. This offers the opportunity for useful housing stock modelling – such as the savings possible from power switching. The research also identifies that whilst urban areas display the expected “heat island” effect in terms of energy consumption, urban properties are on average more efficient than suburban/rural properties. This facilitates spatial targeting of policy messages and initiatives.

Analogous with other studies, data deficiencies introduce the risk of omitted variable bias. Modelling of the energy efficiency in the sample is limited to property attributes that are available for the wider population of properties. While this limits the modelling exercise, it is a perennial issue facing mass appraisal worldwide (where knowledge of the transacted sample attributes generally exceeds knowledge of the unsold properties). That said, the research demonstrates the benefits of sharing data and improving knowledge of the housing stock, as taxation databases would be stronger, augmented with EPC-derived property attributes for example.

The EPC lead in time for wide residential coverage is likely to be considerable. The paper contributes to emerging literature and policy debate surrounding the effect, performance measurement and implementation of energy efficiency certification, through a greater understanding of the sectorial and geographical dispersion of energy efficiency. It provides high level research to help guide policy and decision-making, identifying key locales where there is more of a physical problem and locations where there is more to gain in terms of targeting energy improvement and/or encouraging behavioural change. The paper also allows a glimpse of the implications of a change towards a taxation regime based on energy efficiency, which contributes to the debate surrounding the “greening” of property based taxes.

Human beings need shelter as the beginning of their existence. Same holds true for people who live in Turkey as it is a cultural and traditional reason to be the host and endeavor to buy a home even if one has to pay the debt for years. Another factor that is important for individuals and even for countries is the inflation rate. In this context, the purpose of this study is to investigate whether the 26 regions of Turkey are affected by the inflationary pressure, specifically in the housing price index (HPI).

For this purpose, data from 2010:01 to 2019:01 and the consumer price index (CPI), as well as HPI have been used. The causal relationship between the variables is analyzed by Konya Causality (2006) test.

The key results suggest that HPI causes inflationary pressures in some regions.

The study has some limitations in terms of data set and scope. These are as follows: although there are many variables affecting housing prices, this study aims to investigate the causal link between inflation and housing prices. In addition, only the CPI and HPI variables were provided on a monthly basis in the 2010-2019 period for 26 regions due to the aim of making regional propositions in the investigation of this relationship. For these reasons, different macroeconomic variables could not be studied.

This study makes the following contribution to the literature. While the majority of existing literature investigates the relationship between housing prices and inflation from an empirical perspective for country, very few studies have been for the sub-regions and also these studies have focused on only some sub-regions. In other words, in the literature review, a study has observed that Turkey has to examine the relationship between the housing price and inflation variables for all sub-regions in particular. To overcome this deficiency in the literature, this study aims to investigate the relationship between housing price and inflation for 26 regions.

The purpose of this paper is to examine the house market in Malaysia from 2002 to 2015. Specifically, the macroeconomic determinants on the house price and house demand are investigated.

Structural Vector Autoregressive Regression was adopted to estimate the unexpected changes in both house demand (residential transaction volume) and prices based on economic theoretical reasoning that consider shock from macroeconomic determinants.

The transaction volume and real house prices respond to most of the macroeconomic shocks. While the impact of real gross domestic product (GDP) on house prices appears to be stronger and longer in comparison to other macroeconomic shocks, a 60 per cent change in house prices can be explained by real GDP regardless of whether it is in the short run or the long run. The studies also reveal that a positive effective exchange rate plays an important role when demonstrating the transaction volume. Moreover, monetary liquidity plays a major role in justifying the transaction volume. This implies that mortgage lending may have an impact on housing demand. Meanwhile, movements of house prices cannot be explained by the demand in quantity. This signifies that supply has a strong influence in determining the price.

This study has implications on policymakers of which the interest rate as a cooling measure might not be effective in the short run. The interest rate has very little impact on housing prices. Furthermore, policymakers should address the concerns on speculations, as the results reveal that monetary liquidity and the exchange rate have a strong impact on the housing demand.

This study seeks to provide answers regarding the recent upsurge of Malaysian housing prices. Besides focusing on the house price changes, this study addresses the role of transaction volume while evaluating the house market, as housing prices are usually downwards rigid. Since the price and transaction volume are both related to the transaction activity, this study is significant and could be a good reflection on the actual demand behaviour in the residential market.

A number of studies have investigated the relationship between energy performance certificates (EPCs) and house prices. A majority of studies have tended to model energy performance pricing effects within a traditional hedonic conditional mean estimate model. There has been limited analysis that has accounted for the relationship between EPCs and the effects across the pricing distribution. Moreover, there has been limited research examining the “standard cost improvements EPC score”, or “potential score”. Therefore, this paper aims to quantify and measure the dynamic effects of EPCs on house prices across the price spectrum and account for standardised cost-effective retrofit improvements.

Existing EPC studies produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price effect. The approach within this study applies a quantile regression approach to empirically estimate how quantiles of house prices respond differently to unitary changes in the proximal effects of EPCs and structural property characteristics across the conditional distribution of house prices. Using a data set of 1,476 achieved transaction prices, the quantile regression models apply both assessed EPC score and bands and further examine the potential EPC rating for improved energy performance based on an average energy cost improvement.

The findings show that EPCs are valued differently across the quantiles and that conditional quantiles are asymmetrical. Only property prices in the upper quantiles of the price distribution show significant capitalisation effects with energy performance, and only properties with higher EPC scores display positive significant effects at the higher end of the price distribution. There are also brown discount effects evident for lower-rated properties within F- and G-rated EPC properties at the higher end of the pricing distribution. Moreover, the potential energy efficiency rating (score) also shows increased effects with sales prices and appears to minimise any brown discount effects. The findings imply that energy performance is a complex feature that is not easily “averaged” for valuation effect purposes.

While numerous studies have investigated the pricing effects of EPCs, they have tended to provide a single estimate to determine the relationship with price. This paper extends the traditional analytical insights beyond the conditional mean estimate by examining the quantiles of the relationship between EPCs and house prices to enhance the understanding of this esoteric and complex issue. In addition, this research applies the assessed energy efficiency potential to establish whether effective cost improvements enhance the relationship with sales price and capitalisation effects.

This study aims to examine the impact of lending liquidity on house prices especially during black swan events such as the Global Financial Crisis of 2007–08 and COVID-19. Homeownership is an important goal for many, and house prices are a significant driver of household wealth and the wider economy. This study argues that excessive liquidity from central banks may be driving house price increases, despite negative changes to fundamental drivers. This study contributes to the literature by examining lending liquidity as a driver of house prices and evaluating the efficacy of fiscal policies aimed at boosting liquidity during black swan events.

This study aims to examine the impact of quantitative easing on Australian house prices during back swan events using data from 2004 to 2021. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation's Central Bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration among some of the I(1) variables, the auto-regressive distributed lag model was selected given its flexibility and relative lack of assumptions.

The Australian housing market continued to perform well during the COVID-19 pandemic, with the house price index reaching an unprecedented high towards the end of 2021. Research using data from 2004 to 2021 found a consistent positive relationship between house prices and housing finance, as well as population growth and the value of work commenced on residential properties. Other traditional drivers such as the unemployment rate, economic activity, stock prices and income levels were found to be less significant. This study suggests that quantitative easing implemented during the pandemic played a significant role in the housing market's performance.

Given the severity of COVID-19, policymakers have responded with fiscal and monetary measures that are unprecedented in scale and scope. The full implications of these responses are yet to be completely understood. In Australia, the policy interest rate was reduced to a historic low of 0.1%. In the following periods house prices appreciated by over 20%. The efficacy of quantitative easing and associated fiscal policies aimed at boosting liquidity to mitigate the impact of black swan events such as the pandemic has yet to be tested empirically. This study aims to address that paucity in literature by providing such evidence.