Estimating money demand functions for South Asian countries

In this paper, we estimate a money demand function for a panel of five South Asian countries. We find that the money demand and its determinants, namely real income, real exchange rate and short-term domestic and foreign interest rates are cointegrated both for individual countries as well as for the panel, and panel long-run elasticities provide robust evidence of statistically significant relationships between money demand and its determinants. Our test for panel Granger causality suggests short-run causality running from all variables, except foreign interest rate, to money demand, and we find evidence that except for Nepal money demand functions are stable.

Have US external imbalances been determined at home or abroad?

This paper examines the relationship between the United States saving–investment imbalance and long-term real interest rates using a new international borrowing and lending framework. It first establishes how domestic or international factors may primarily influence the US external imbalance and interest rates over any given time before showing that the current account and real long term interest rate share a positive and statistically significant co-integrating relationship based on data from the mid-1980's. The results suggest that while in the pre-Asian financial crisis period (1985:01–1996:04) US external deficits and long term interest rates were mainly determined by domestic factors, external factors beyond the control of domestic policymakers dominated from 1997:01–2004:04.

True and apparent scaling : the proximity of the Markov-switching multifractal model to long-range dependence

In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal (MSM) model. In order to see how well the estimated model captures the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q=1,2) for both empirical data and simulated data of the MSM model. In most cases the multifractal model appears to generate ‘apparent’ long memory in agreement with the empirical scaling laws.

Understanding residential house prices : examining the contribution of social area analysis

A complete understanding of residential housing markets, particularly in relation to variations in house prices both within and between suburbs, continues to present challenges to property researchers and forecasters. Factors affecting changes in housing demand are not yet completely understood, and accordingly market changes cannot always be confidently predicted. Most urban cities contain precincts that have high or low house values at the same time, regardless of characteristics such as distance to the city centre, location of transport or topography. Exactly why these variations in suburb values occur is often unclear, although local residents are able to easily identify differences between the status of each suburb, especially when one area is clearly perceived as superior to another. Consequently, houses in premium suburbs are sold for substantially more than houses in other areas, primarily due to this perceived higher demand. An understanding of reasons behind varying levels of buyer demand has always been difficult to fully encapsulate in housing studies, even though clear links have been observed between housing affordability and the type of inhabitant that would live in a particular area. This study confirms that traditional economic indicators can not always observe the degree of purchaser and vendor willingness in the residential property market, as per the International Valuation Standards Committee definition of market value, and substantial consideration must also be given to characteristics of individual buyers and sellers within the marketplace. No longer can the focus be narrowly focussed just on endogenous factors such as interest rates and inflation levels.
Accordingly, this research draws the disciplines of demography and housing research closer together and looks to social indicators for an insight into the level of house prices. To establish this link, a two-stage process is adopted where social area analysis initially identifies the characteristics of suburbs within an urban area. This information is then used to examine variations in suburb values, resulting in a clearer understanding of the relationship between demographic variables and house prices. This research analysed changes in the value of established residential house prices in Melbourne, Australia as well as the relationship with social structure. The added dimension of time highlighted change, with data drawn from 1996 and 2001. The results confirmed the existence of strong linkages between social constructs and established house prices. Whilst acknowledging that the overall level of house values is influenced by external economic and political factors, differences between suburb values can be explained by demographic variables. The results confirm that increased emphasis must be placed upon demography when seeking to understand variations in residential property values between urban areas.

Physical theory of organisation and consequent neural model of spatio-temporal pattern acquisition

A neurone model (the FORMON) is proposed which provides a mathematical explanation for a range of psychological phenomena and has potential in Artificial Intelligence applications. A general definition of organisation in terms of entropy and information is formulated. The concept of microcodes is introduced to describe the physical nature of organisation. Spatio-temporal pattern acquisition and processing functions attributable to individual neurones are reviewed. The criterion for self-organisation in a neurone is determined as the maximisation of mutual organisation. A feedback control system is proposed to satisfy this criterion and provide an integrated long-term memory of spatio-temporal pattern. This pattern acquisition system is shown to be applicable to dendritic pattern recognition and axonal pattern generation. Provision is also made for adaptation, short-term memory and operant learning. An electro-chemical model of transmission and processing of neural signals is outlined to provide the pattern acquisition functions of the Formon model. A transverse magnetic mode of electrotonic propagation is postulated in addition to the transverse electromagnetic mode. Configurations of the Formon are categorised in terms of possible pattern processing functions. Connective architectures are proposed as self-organising models of acquisitive semantic and syntactic networks.

In situ stabilisation of pavements using cementitious binders

An extensive study was made of the physical properties of a range of cementitiously stabilised materials to determine their suitability for use in in situ pavement construction. This process for recycling existing pavements has considerable environmental and cost benefits. Pavement models incorporating these materials were analysed to determine their structural behaviour.

Analysis of springback variation in sheet metal forming

This thesis investigated how the variation in inputs, such as material and processing conditions affected the shape defect phenomenon (springback) for sheet metal forming processes. Using a stochastic Finite Element modelling tool, it was found that the material type and fluctuations in material properties significantly influenced the variation in springback.

Process-based modelling of mass transport in the subsurface

Modern societies rely on natural water pathways that include subsurface flow of water and dissolved chemicals. The thesis presents a range of numerical and analytical models for simulating physical, chemical and biological processes in the subsurface, including coastal aquifers, the near-surface vadose zone, and solute transport in biogeochemically active aquifers.