Modeling regional house prices

We develop a parsimonious panel model for quarterly regional house prices, for which both the cross-section and the time series dimension is large. The model allows for stochastic trends, cointegration, cross-equation correlations and, most importantly, latent-class clustering of regions. Class membership is fully data-driven and based on (i) average growth rates of house prices, (ii) the propagation of shocks to house prices across regions, also known as the ripple effect, and (iii) the relationship of house prices with economic growth and other variables. Applying the model to quarterly data for the Netherlands, we find convincing evidence for the existence of two distinct clusters of regions, with pronounced differences in house price dynamics.cointegration;ripple effect;cross-section dependence

Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income

Stylized facts show that average growth rates of US per capita consumption and income differ in recession and expansion periods. Since a linear combination of such series does not have to be a constant mean process, standard cointegration analysis between the variables to examine the permanent income hypothesis may not be valid. To model the changing growth rates in both series, we introduce a multivariate Markov trend model, which accounts for different growth rates in consumption and income during expansions and recessions and across variables within both regimes. The deviations from the multivariate Markov trend are modeled by a vector autoregressive model. Bayes estimates of this model are obtained using Markov chain Monte Carlo methods. The empirical results suggest the existence of a cointegration relation between US per capita disposable income and consumption, after correction for a multivariate Markov trend. This results is also obtained when per capita investment is added to the vector autoregression.Cointegration;MCMC;Permanent income hypothesis;Multivariate Markov trend

Surface Modification of a PCB Substrate for Better Adhesion of Inkjet Printed Circuit Structures

The robustness and service life of inkjet printed electronic circuit structures are highly influenced by the state of the interface between these structures and the substrate. In the case of polymeric substrate materials, surface modification is necessary to realise a favourable interface, as these materials are generally not very receptive to chemical bond formation with the deposited ink. This paper deals with the surface modification of a high frequency laminate (substrate) using two different techniques to improve interfacial adhesion. The techniques deployed are CF4/O2 based plasma treatment and micro structuring using pulsed laser. The plasma treatment parameters were varied systematically using a statistical design of experiments. Substrates with varying surface characteristics, resulting from different plasma treatment parameters, were subjected to post-processing steps including surface energy and surface roughness measurements. Similarly, the influence of laser treatment parameters on surface characteristics of the substrate was also studied in detail. The outcomes of these two surface modification techniques are discussed in this paper

A comparative study of two conductive inkjet inks for fabrication of RF circuit structures

Two commercially available silver inks were inkjet printed to fabricate the seed tracks (seed layers) of radio frequency (RF) circuit structures on a high frequency substrate material. One of them is a nanoparticle based ink, and the other, a non-particle based organic silver complex ink. Subsequent to printing, these seed layers were copper plated using an electroless copper plating process, to impart the desired thickness to the circuit structures. The inkjet printing-electroless plating process combination was validated with the example of an S-band filter and an RF transmission line. Prior to the fabrication of the circuit structures, the substrates were plasma treated, in order to modify their surface and promote mechanical interlocking with the printed structures.\ud Finally, experiments were conducted to determine the solderability\ud of inkjet printed as well as printed-plated structures. Conclusions on\ud the suitability of the two inks for RF circuit fabrication have been\ud drawn based on experimental results

Magnetostriction of a Superconductor: -Results from the Critical-State Model

In many cases, the critical-state theory can be treated as a suffi ciently accurate approximation for the modelling of the magnetic properties of superconductors. In the present work, the magnetostrictive hysteresis is computed for a quite general case of the modified Kim-Anderson model. The results obtained reproduce many features of the giant magnetostriction (butterfly-shaped curves) reported in the literature for measurements made on single-crystal samples of the high-temperature superconductor $Bi_2Sr_2CaCu_2O_8$. It is shown that addition of a contribution to the magnetostriction in the superconducting state which is of similar origin as in the normal state, offers a broader phenomenological interpretation of the complex magnetostriction hysteresis found in such heavy-fermion compounds as $UPt_3$, $URu_2Si_2$ or $UBe_{13}$.Comment: 9 LaTeX pages, 4 Postscript figures, WWW version available at http://is.dal.ca/~zkoziol/super.htm

Does Africa grow slower than Asia and Latin America?

In this paper we address the question whether countries on the African continent have lower average growth rates in real GDP per capita than countries in Asia and Latin America. In contrast to previous studies, we do not aggregate the data, nor do we a priori assign countries to clusters. Instead, we put forward a so-called latent class panel time series model, which allows a data-based classification of countries to clusters with growth levels that differ across the clusters. Our empirical results suggest that twenty-six African countries can be assigned to the low growth cluster, but that eleven African countries show growth levels which are comparable with many countries in Asia and Latin America. We also present results for sub-periods, which demonstrate that the relative performance of African countries has improved considerably over time.economic growth;latent class models;panel time series

Financial Development and Convergence Clubs

This paper studies the economic development process, measured by Gross Domestic Product (GDP), for a large panel of countries. We propose a methodology that identifies groups of countries (convergence clubs) that show similar GDP structures, while allowing for changes in club memberships over time. As a second step we analyze the short-run and long-run effects of financial development (measured by financial intermediary development and stock market development) on the GDP process, and the composition of the convergence clubs. We find that the club memberships are quite persistent, but still their compositions change substantially over time. In particular, several EU member countries and East Asian countries are found to belong to a higher GDP club in recent times compared to the beginning of the 1970s. In terms of the effects of financial development indicators on the GDP process, our results partially confirm the theoretical basis for different effects of financial development indicators in the short-run and the long-run. In the long-run, financial development is found to affect the countries’ GDP level positively. The short-run effects of financial development indicators however are found to be less clear, in the sense that we do not find a negative short-run effect of financial intermediary development on GDP levels, while the short-run effect of stock market development is found to be negative.economic growth;Markov chain models;convergence clubs;financial developments

A unified approach to nonlinearity, structural change and outliers

This paper demonstrates that the class of conditionally linear and Gaussianstate-space models offers a general and convenient framework for simultaneouslyhandling nonlinearity, structural change and outliers in time series. Manypopular nonlinear time series models, including threshold, smooth transitionand Markov-Switching models, can be written in state-space form. It is thenstraightforward to add components that capture parameter instability andintervention effects. We advocate a Bayesian approach to estimation andinference, using an efficient implementation of Markov Chain Monte Carlosampling schemes for such linear dynamic mixture models. The general modellingframework and the Bayesian methodology are illustrated by means of severalexamples. An application to quarterly industrial production growth rates forthe G7 countries demonstrates the empirical usefulness of the approach.Bayesian inference;threshold models;Markov-switching models;business cycle asymmetry;state-space models

Assessment of the development of aquifer management councils (COTAS) for sustainable groundwater management in Guanajuato, Mexico

Collective groundwater management by water users—self-regulation—is increasingly advocated as a complement to state regulation. This article analyzes the attempts by the Guanajuato State Water Commission (CEAG) in central Mexico to promote user self-regulation through the establishment and development of 14 Consejos Técnicos de Aguas (COTAS; Technical Water Councils). Based on a joint assessment by a former senior CEAG policy-maker and two researchers, Guanajuato’s groundwater-management policy is reviewed to understand why user self-regulation was less successful than expected. It concludes that increasing awareness and improving the knowledge base on groundwater is not enough to trigger self-regulation by groundwater users. A wider delegation of responsibilities to the COTAS is necessary, combined with: (1) functioning mechanisms for enforcing groundwater legislation, especially concerning well permits and pumped volumes, and (2) mechanisms that ensure the legitimacy and accountability of users’ representatives to both users and state agencie