Investigation of the evolutionary origin and history of a newly identified transposable element in rodents

The retroviral-like transposable element mys has been identified in a limited group of new-world rodents, providing a unique opportunity to assess its evolutionary origin and activity within various rodent genomes. In the course of this investigation we identified an element that appears to represent a distinct, but related, group of elements in the Mexican volcano mouse that we refer to as mys-like. We have determined the presence of this mys-like element in related species of rodents, suggesting that it likely dates back to a common ancestor of the Reithrodontomyini rodent tribe. The mys-like element predates the previously identified mys element and presumably gave rise to mys. Continued molecular investigations will provide insights into the evolutionary origin and history of transposable elements and their potential impacts on the mammalian genome

Diffusion and Risks of House Prices in the Netherlands

The rate of home-ownership has increased significantly in many countries over the past decades. One motivating factor for this increase has been the creation of wealth through the accumulation of housing equity, which also forms the basic tenet of the asset-based welfare system. In generating the home equity, house price developments play an important role. Generally, house prices show an increasing trend over long time period, however, there are short-term negative appreciations that may have inherent risks for the housing equity. Following the 2007-08 Global Financial Crisis (GFC), for example, the collapse of house prices has caused many recent home buyers to run into negative equity. Some housing researchers and experts have suggested that a better understanding of the spatial diffusion mechanisms of house prices will aid resuscitating the housing market after the GFC. Others also advocated adopting insurance schemes to protect the home equity that yields the welfare benefits. Unfortunately, however, little research insight exists on the Dutch house price diffusion process, although there are empirical results for countries such as the UK, US and China, where the contexts differ from the Netherlands. Furthermore, the current existing home-value insurance scheme in the literature is found to be less efficient and eliminates only up to 50% of the house price risks. This dissertation covers important aspects of house price diffusion and risks in the Netherlands. The aim is to better understand the diffusion mechanism and the risks of house prices, while it also contributes to the measurement of these housing risks. More specifically, there are three objectives: first, to discover the diffusion mechanism of house prices in the Netherlands and the pattern particularly from the capital Amsterdam; second, to examine the spatial distribution of the house price risk; and third, to investigate the efficiency of the index-based home-value insurance for reducing the house price risk in the Dutch context. The diffusion mechanism relates to the so-called ripple or spillover effect, for which movements of house prices in one location temporarily or permanently spread over their influence to other regions. The risks analyses capture the probability of selling the residential property below the purchase price. The index-based home-value insurance scheme is concerned with the reduction of the house price risk, while its efficiency and loss coverage are analysed. The contributions of the dissertation are specifically elaborated in five chapters. The chapters are self-contained, four of them having been published separately in international journals and the other being currently under review. Chapter 2 is a literature study that presents the general trend and an overview of the risks in home-ownership. It particularly discusses the government mortgage guarantee and tax deduction, among other factors, which contribute to home-ownership in the Netherlands. Mortgage default risk and house price risk, which are the two important risks from the perspective of the home-owners are also discussed in the context of the Dutch market. Chapter 3 investigates the house price diffusion mechanism between the twelve provinces in the Netherlands. The methodology adopts a new Bayesian graphical approach which enables a data-driven identification of the important regions where the diffusion may predominantly emerge. Using quarterly house price indexes, the findings suggest that house price diffusion exists in the Netherlands with a pattern varying over the period of time. Focusing specifically on the period prior to the 2007-2008 Global Financial Crisis (GFC), the house price diffusion predominantly originated from Noord-Holland. House prices in Amsterdam – the capital and an important economic hub of the Netherlands, are more likely to diffuse to other parts of the country. Thus in Chapter 4, attention is paid to the house price diffusion pattern from the capital Amsterdam to the other Dutch regional housing markets. The Granger causality and cointegration techniques are used, while controlling for the important house price fundamentals. The results suggest a possible house price diffusion existing from Amsterdam to all regions in the Netherlands except for Zeeland. The strongest long-run impact of Amsterdam house price diffusion potentially occur in Utrecht. As one of the largest and most dynamic in the Netherlands, the Amsterdam housing market is itself an interesting case study. One part of Chapter 5, therefore, deals with the diffusion pattern by studying the spatial interrelationships between house prices in Amsterdam. The other part of the chapter studies the house price risks. Using the Granger causality test, a general causal flow of house prices is observed from the central business districts to the peripherals. Simple statistics similarly reveal that house prices grow faster and are more risky in the central business districts than those on the peripherals of the city. Chapter 6 is concerned with the efficiency and loss coverage of the index-based home-value insurance scheme. It proposes a modification of the index-based home-value insurances policy, which seeks to reduce the large idiosyncratic residual house price risks. The modification uses aggregate measures of the reference index. Using the hedonic and repeated sales indexes, the empirical analysis suggests the proposed modified scheme is highly efficient and may eliminate up to 70% of the residual risks. In general, the dissertation adopts innovative empirical methodological approach that combines standard statistical analyses and more recent and complex econometric modelling techniques in the study of the diffusion and risks of house prices in the Netherlands. The application of the graphical approach to the study of diffusions particularly in Chapter 3, is the first of its kind in the context of the housing market. Furthermore, this dissertation is among the first to entirely provide a comprehensive analysis and the much needed body of knowledge regarding the house price diffusion and risks for the highly regulated Dutch housing market. The results have important policy implications and applications for households, commercial investors and financial institutions in the Netherlands. The results may also generally apply and replicable in other countries and economies with similar housing market conditions

Introduction

The rate of home-ownership across Europe and in many countries has increased significantly in recent decades. This is partly because most governments have promoted home-ownership as part of an asset-based welfare system with the notion that home-ownership will generate wealth for households through the accumulation of housing equity. Changes in house prices play an important role in the generation of the housing equity and the wealth inherent in home-ownership. In general, house prices change in cycles of upward and downward trends. Each of these cycles may be driven by different sets of fundamental determinants and by the prevailing conditions in the wider economy. Over the long term, home-owners usually accumulate significant housing equity, yielding welfare benefits. However, even periods of brief house price decline can erode the value of housing equity accrued over several years. Following the 2007-08 Global Financial Crisis (GFC), for example, the severe decline in house prices caused many recent home-owners to run into negative equity. Figures from Statistics Netherlands show that following the GFC, in the Netherlands alone the total wealth in residential properties declined from e738,449 million in 2009 to e721,018 million by the end of 2012. In effect, home-ownership involves significant financial risk, which can adversely affect the balance sheets of households. These risks require a better understanding and proper measurements. However, it is also important to first understand house price dynamics, which significantly affect the process of equity generation. A thorough understanding of house price dynamics is necessary if we are to identify innovative ways of insuring against the risks associated with home-ownership

Home-value insurance and idiosyncratic risks of residential property prices

The recent Global Financial Crisis has reawakened home-owners to the need for protecting their home-equities from possible future house price decline. This paper re-examines the Shiller and Weiss (1999) home-value insurance scheme and proposes a modification that eliminates a large proportion of the idiosyncratic sale price risks of residential properties. Using data between 1995 and 2014 for Amsterdam, the proposed insurance policy shows a higher pay-out efficiency, a higher loss coverage and a greater pay-out probability than the original Shiller and Weiss (1999) scheme. The new home-value insurance policy thus provides better protection for the property sale price risks

Diffusion and Risks of House Prices in the Netherlands

The rate of home-ownership has increased significantly in many countries over the past decades. One motivating factor for this increase has been the creation of wealth through the accumulation of housing equity, which also forms the basic tenet of the asset-based welfare system. In generating the home equity, house price developments play an important role. Generally, house prices show an increasing trend over long time period, however, there are short-term negative appreciations that may have inherent risks for the housing equity. Following the 2007-08 Global Financial Crisis (GFC), for example, the collapse of house prices has caused many recent home buyers to run into negative equity. Some housing researchers and experts have suggested that a better understanding of the spatial diffusion mechanisms of house prices will aid resuscitating the housing market after the GFC. Others also advocated adopting insurance schemes to protect the home equity that yields the welfare benefits. Unfortunately, however, little research insight exists on the Dutch house price diffusion process, although there are empirical results for countries such as the UK, US and China, where the contexts differ from the Netherlands. Furthermore, the current existing home-value insurance scheme in the literature is found to be less efficient and eliminates only up to 50% of the house price risks. This dissertation covers important aspects of house price diffusion and risks in the Netherlands. The aim is to better understand the diffusion mechanism and the risks of house prices, while it also contributes to the measurement of these housing risks. More specifically, there are three objectives: first, to discover the diffusion mechanism of house prices in the Netherlands and the pattern particularly from the capital Amsterdam; second, to examine the spatial distribution of the house price risk; and third, to investigate the efficiency of the index-based home-value insurance for reducing the house price risk in the Dutch context. The diffusion mechanism relates to the so-called ripple or spillover effect, for which movements of house prices in one location temporarily or permanently spread over their influence to other regions. The risks analyses capture the probability of selling the residential property below the purchase price. The index-based home-value insurance scheme is concerned with the reduction of the house price risk, while its efficiency and loss coverage are analysed. The contributions of the dissertation are specifically elaborated in five chapters. The chapters are self-contained, four of them having been published separately in international journals and the other being currently under review. Chapter 2 is a literature study that presents the general trend and an overview of the risks in home-ownership. It particularly discusses the government mortgage guarantee and tax deduction, among other factors, which contribute to home-ownership in the Netherlands. Mortgage default risk and house price risk, which are the two important risks from the perspective of the home-owners are also discussed in the context of the Dutch market. Chapter 3 investigates the house price diffusion mechanism between the twelve provinces in the Netherlands. The methodology adopts a new Bayesian graphical approach which enables a data-driven identification of the important regions where the diffusion may predominantly emerge. Using quarterly house price indexes, the findings suggest that house price diffusion exists in the Netherlands with a pattern varying over the period of time. Focusing specifically on the period prior to the 2007-2008 Global Financial Crisis (GFC), the house price diffusion predominantly originated from Noord-Holland. House prices in Amsterdam – the capital and an important economic hub of the Netherlands, are more likely to diffuse to other parts of the country. Thus in Chapter 4, attention is paid to the house price diffusion pattern from the capital Amsterdam to the other Dutch regional housing markets. The Granger causality and cointegration techniques are used, while controlling for the important house price fundamentals. The results suggest a possible house price diffusion existing from Amsterdam to all regions in the Netherlands except for Zeeland. The strongest long-run impact of Amsterdam house price diffusion potentially occur in Utrecht. As one of the largest and most dynamic in the Netherlands, the Amsterdam housing market is itself an interesting case study. One part of Chapter 5, therefore, deals with the diffusion pattern by studying the spatial interrelationships between house prices in Amsterdam. The other part of the chapter studies the house price risks. Using the Granger causality test, a general causal flow of house prices is observed from the central business districts to the peripherals. Simple statistics similarly reveal that house prices grow faster and are more risky in the central business districts than those on the peripherals of the city. Chapter 6 is concerned with the efficiency and loss coverage of the index-based home-value insurance scheme. It proposes a modification of the index-based home-value insurances policy, which seeks to reduce the large idiosyncratic residual house price risks. The modification uses aggregate measures of the reference index. Using the hedonic and repeated sales indexes, the empirical analysis suggests the proposed modified scheme is highly efficient and may eliminate up to 70% of the residual risks. In general, the dissertation adopts innovative empirical methodological approach that combines standard statistical analyses and more recent and complex econometric modelling techniques in the study of the diffusion and risks of house prices in the Netherlands. The application of the graphical approach to the study of diffusions particularly in Chapter 3, is the first of its kind in the context of the housing market. Furthermore, this dissertation is among the first to entirely provide a comprehensive analysis and the much needed body of knowledge regarding the house price diffusion and risks for the highly regulated Dutch housing market. The results have important policy implications and applications for households, commercial investors and financial institutions in the Netherlands. The results may also generally apply and replicable in other countries and economies with similar housing market conditions

General conclusions

Since the 2007-2008 Global Financial Crisis (GFC), a great deal of research has been conducted in various countries into the dynamics and risks associated with house prices in an attempt to find innovative ways of reducing these risks and resuscitating a depressed housing market. This dissertation contributes to that literature by providing comprehensive analyses of the spatial diffusion and risks associated with house prices in the Netherlands. It also studies the efficiency and loss coverage of home-value insurance in the context of the Dutch housing market and suggests modifications to the index-based insurance scheme that would minimise the residual idiosyncratic risks for home-owners. The dissertation innovatively adopts empirical methods that combine standard statistical analyses with more complex and recent econometric models. The contributions of the dissertation are presented in five main chapters. Four of these chapters have already been published separately in international journals and one is under review. Chapter 2 provided a general overview of the Dutch housing market and the risks involved in home-ownership. Chapters 3, 4 and 5 were devoted to the diffusion mechanism of house prices in the Netherlands. Chapter 5 also dealt in part with house price risks, while Chapter 6 focused on the house price risks and home-value insurance. Each chapter has provided a detailed conclusion on each aspect of the research questions addressed in this dissertation. This concluding chapter summarises the main findings of the dissertation as a whole. The limitations of the analyses are discussed, together with potential applications for its findings and directions for further research

Polyionic nanoclays as tailorable hybrid organic-inorganic platforms

We disclose the synthesis, characterization, and application of an imidazolium-based hybrid inorganic-organic layered magnesium phyllo(organo)silicate nanosheets, coined polyionic nanoclays (PINCs), as an emergent class of supported ionic liquids which boast extremely high ionic density (3.8 mmol g-1 for the 1-methyl-3-propylimidazolium chloride PINC, or roughly two-thirds the ion loading in the analogous free-flowing ionic liquid) and exchangeability (i.e., tailorability) of the associated cation and counteranion. The aqueously dispersing imidazolium PINCs are employed as nanocatalyst supports for monometallic gold and silver nanoparticles (PINC@Au- and AgNPs) and their bimetallic intermediates using sodium borohydride as a reducing agent, and the resulting heterogeneous catalysts are applied for the model reduction of 4-nitrophenol to 4-aminophenol to achieve the highest reaction turnover frequency yet reported in the literature (over 33,000 h-1 for nanoparticles comprising a 70:30 molar ratio of Au:Ag). Remarkably, the turnover for PINC@AuNPs is a 4000 percent increase over the corresponding unsupported borohydride-stabilized AuNPs (600 h-1), indicating an intense synergistic effect imparted by the PINC support. Additionally, aqueous anionic dye sequestration is demonstrated using Congo Red as a model dye system, accomplishing a maximum adsorption capacity of over 2,600 mg dye per g of PINC when maintained at 50 degreesC. The exceptional performance of these PINCs for the herein applications suggest an auspicious future for PINCs in catalysis, ion exchange, energy storage, separations, (bio)sensing, imaging, and the construction of nanoscale assemblies.Includes bibliographical references

Detecting spatial and temporal house price diffusion in the Netherlands

Following the 2007-08 Global Financial Crisis, there have been a growing research interest on the spatial interrelationships between house prices in many countries. This paper examines the spatio-temporal relationship between house prices in the twelve provinces of the Netherlands using a recently proposed econometric modelling technique called Bayesian graphical vector autoregression (BG-VAR). This network approach enables a data driven identification of the most dominant provinces where house price shocks may largely diffuse through the housing market and it is suitable for analysing the complex spatial interactions between house prices. Using temporal house price volatilities for owner-occupied dwellings, the results show evidence of house price diffusion pattern in distinct sub-periods from different provincial housing sub-markets in the Netherlands. We observed particularly prior to the crisis, diffusion of temporal house price volatilities from Noord-Holland