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The purpose of this paper is to explore the risk factors in homeowners from the individual household’s perspectives within the owner-occupied housing sector of The Netherlands. Risk in home ownership from mortgage providers’ perspectives has received tremendous attention than individual home owner’s perspectives in existing literature following the financial crisis in 2007/2008 within the euro zone.

The paper adopted a broader review of extent literature on the different concepts and views on risk in homeownership. These concepts are unified into a framework that enhances our understanding of the perceived sophisticated risk in owner-occupier with focus on The Netherlands.

From the perspective of the homeowner, two main types of risks were identified: default payment and property price risk. The paper has unearthed a quantum number of factors which underline the above risks. These factors relate to the initial amount of mortgage loan taken out, the future housing expenses and the income development of the owner-occupier. Family disintegration is identified, as one of the main causes of mortgage default and that of property price risk are mainly influenced by income levels, interest rates and conditions in the social and private rental sectors.

Findings of the paper are based on review of the extant literature in the context of the Dutch housing market. Possible rigorous situational analysis using other tools are recommended for further research.

This paper contributes to the much needed body of knowledge in the owner-occupied sector and provides a better understanding of risk in home ownership from the individual perspectives.

This paper aims to examine the existence of the ripple effect from Amsterdam to the housing markets of other regions in The Netherlands. It identifies which regional housing markets are influenced by house price movements in Amsterdam.

The paper considers the ripple effect as a lead-lag effect and a long-run convergence between the Amsterdam and regional house prices. Using the real house prices for second-hand owner-occupied dwellings from 1995q1 to 2016q2, the paper adopts the Toda–Yamamoto Granger Causality approach to study the lead-lag effects. It uses the autoregressive distributed lags (ARDL)-Bounds cointegration techniques to examine the long-run convergence between the regional and the Amsterdam house prices. The paper controls for house price fundamentals to eliminate possible confounding effects of common shocks.

The cumulative evidence suggests that Amsterdam house prices have influence on (or ripple to) all the Dutch regions, except one. In particular, the Granger Causality test concludes that a lead-lag effect of house prices exists from Amsterdam to all the regions, apart from Zeeland. The cointegration test shows evidence of a long-convergence between Amsterdam house prices and six regions: Friesland, Groningen, Limburg, Overijssel, Utrecht and Zuid-Holland.

The paper adopts an econometric approach to examine the Amsterdam ripple effect. More sophisticated economic models that consider the asymmetric properties of house prices and the patterns of interregional socio-economic activities into the modelling approach are recommended for further investigation.

This paper focuses on The Netherlands for which the ripple effect has not yet been researched to the authors’ knowledge. Given the substantial wealth effects associated with house price changes that may shape economic activity through consumption, evidence for ripples may be helpful to policy makers for uncovering trends that have implications for the entire economy. Moreover, the analysis controls for common house price fundamentals which most previous papers ignored.

Commercial real estate (CRE) indicators typically include asset deals and exclude share deals. This study aims to explore the phenomenon of real estate share deals and assess whether omitting these transactions results in indicators that do not accurately reflect the market.

Various registers in the Netherlands were used to estimate transaction volumes, total values and price developments of both share and asset deals. Share deals are company transfers and its transactions cover more than real estate. To estimate the contribution of real estate in share deals, valuations were used.

In the Netherlands, share deals are most prominent for rental dwellings. Adding share deals to volume and value indicators seems required. In price development estimates, significant differences were found for dwellings between share and asset deals. Price indices should, therefore, also include share deals, but in practice this is difficult and has little impact on the outcomes due to the low weight of share deals.

Legislation has a major impact on choosing a share or asset deal. The significance of share deals is expected to vary amongst countries. Performing similar research in other countries will contribute in harmonising real estate indicators.

Statistical agencies face many challenges in the construction of CRE indicators. This study provides statisticians knowledge that can be used to evaluate possible data gaps.

This is the first study to estimate indicators of real estate share deals and compare these to asset deal indicators.

This paper aims to develop a methodology to accurately and timely measure movements in housing markets by constructing a continuously estimated house price index.

The continuous index, which is extracted from an additive model that includes the temporal and the locational effects as smooth functions, can be interpreted as an extension of the classical hedonic time-dummy method. The methodology is applied to housing sales from Sydney, Australia, between 2001 and 2011, and compared to three types of discrete indexes.

Discrete indexes turn out to approach the continuously estimated index with decreasing period lengths but eventually become wiggly and unreliable because of fewer observations per period. The continuous index, in contrast, is stable, has favourable robustness properties and is more objective in several ways.

The resulting index tracks movements in the housing market precisely and in “real-time” and is hence suited for monitoring and assessing housing markets. Because turbulence in housing markets is often a harbinger of financial crises, such monitoring tools support policymakers and investors in tailoring their decisions and reactions. Additionally, the index can be evaluated arbitrarily frequently and therefore is well suited for use in property derivatives.

Attitudes, perceptions, and intentions of a firm's customers, which can be captured via customer feedback metrics (CFMs), provide valuable information about the state of a firm's customer base. CFMs can help capture the impact of marketing actions on future customer behavior and future firm performance, and thus can help make marketing become more accountable. CFMs have received much attention in marketing research and business practice since the 1970s. In this chapter, we provide a short historical overview of the development of, and research about, CFMs, we classify the different types of CFMs, we highlight the empirical findings of the drivers and consequences of CFMs, and we explore how CFMs can be integrated in a firm's customer dashboard in order to make marketing more accountable. We furthermore explore some of the challenges in accurately measuring CFMs, and in the end of this chapter, we provide information on how to capture CFMs in the age of social listening via modern tools involving text-, voice-, and video-mining.

Examines the valuation of a real estate leasing certificate in Belgium. Develops a detailed model, which derives from the valuation theory concerning participating, redeemable bonds. Permits a user to generate valuations of real estate certificates for any number of assumptions. Concludes that a real estate valuer could also use the model to test the reasonableness of their expert valuations against the tables.

Computer corpus linguistics (CCL) is a scientific innovation that has facilitated the creation and analysis of large corpora in a systematic way by means of computer technology since the 1950s. This article provides an account of the CCL pioneers in general but particularly of those in Germany, the Netherlands, Sweden, and Switzerland. It is found that Germany and Sweden, due to more advantageous financing and weaker communities of generativists, had a faster adoption of CCL than the other two countries. A particular late adopter among the four was Switzerland, which did not take up CCL until foreign professors had been recruited.

The unique characteristic of Islamic bank leads in governance and disclosure. Using stakeholder, signaling, and market discipline theory, governance and adequate disclosure may increase bank soundness. This study aims to investigate the relationship of sharia disclosure and Sharia Supervisory Board in influencing Islamic bank soundness in the different regulatory framework of the country. Using purposive sampling, the research covered 84 Islamic banks in 16 countries during the period 2013–2015 with lag data of Islamic bank soundness. The result shows sharia disclosure influences on Islamic bank soundness for management efficiency, capital adequacy ratio, asset quality, and liquidity. The results also show that sharia disclosure mediates the indirect effect of SSB on Islamic bank soundness. The regulatory framework (sharia accounting standard and SSB regulation) shows moderating effect of regulation framework proved on the association of sharia disclosure with management efficiency, capital, and liquidity. The effect is indirectly depending on the regulatory framework for proxy management efficiency, capital, and liquidity. The implication of the research suggests that sharia disclosure could increase the market discipline mechanism of Islamic bank stream. The Islamic bank can increase the transparency using sharia disclosure as a branding for increasing public trust, even though in the deficient Islamic bank regulation countries.

This study examines problems that may occur when conventional Value‐at‐Risk (VaR) estimators are used to quantify market risks in an agricultural context. For example, standard VaR methods, such as the variance‐covariance method or historical simulation, can fail when the return distribution is fat tailed. This problem is aggravated when long‐term VaR forecasts are desired. Extreme Value Theory (EVT) is proposed to overcome these problems. The application of EVT is illustrated by an example from the German hog market. Multi‐period VaR forecasts derived by EVT are found to deviate considerably from standard forecasts. We conclude that EVT is a useful complement to traditional VaR methods.