Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.

Estimation of the Spatial Weights Matrix under Structural Constraints

While estimates of models with spatial interaction are very sensitive to the choice of spatial weights, considerable uncertainty surrounds de nition of spatial weights in most studies with cross-section dependence. We show that, in the spatial error model the spatial weights matrix is only partially identi ed, and is fully identifi ed under the structural constraint of symmetry. For the spatial error model, we propose a new methodology for estimation of spatial weights under the assumption of symmetric spatial weights, with extensions to other important spatial models. The methodology is applied to regional housing markets in the UK, providing an estimated spatial weights matrix that generates several new hypotheses about the economic and socio-cultural drivers of spatial di¤usion in housing demand.

A New Model Of Trend Inflation

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this interval can either be fixed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of inflation. The bounds placed on trend inflation mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend inflation model. In an empirical exercise with CPI inflation we find the model to work well, yielding more sensible measures of trend inflation and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.

Pareto or log-normal? A recursive-truncation approach to the distribution of (all) cities

Traditionally, it is assumed that the population size of cities in a country follows a Pareto distribution. This assumption is typically supported by nding evidence of Zipf's Law. Recent studies question this nding, highlighting that, while the Pareto distribution may t reasonably well when the data is truncated at the upper tail, i.e. for the largest cities of a country, the log-normal distribution may apply when all cities are considered. Moreover, conclusions may be sensitive to the choice of a particular truncation threshold, a yet overlooked issue in the literature. In this paper, then, we reassess the city size distribution in relation to its sensitivity to the choice of truncation point. In particular, we look at US Census data and apply a recursive-truncation approach to estimate Zipf's Law and a non-parametric alternative test where we consider each possible truncation point of the distribution of all cities. Results con rm the sensitivity of results to the truncation point. Moreover, repeating the analysis over simulated data con rms the di culty of distinguishing a Pareto tail from the tail of a log-normal and, in turn, identifying the city size distribution as a false or a weak Pareto law.

Joint estimates of automatic and discretionary fiscal policy: the OECD 1981-2003

Official calculations of automatic stabilizers are seriously flawed since they rest on the assumption that the only element of social spending that reacts automatically to the cycle is unemployment compensation. This puts into question many estimates of discretionary fiscal policy. In response, we propose a simultaneous estimate of automatic and discretionary fiscal policy. This leads us, quite naturally, to a tripartite decomposition of the budget balance between revenues, social spending and other spending as a bare minimum. Our headline results for a panel of 20 OECD countries in 1981-2003 are .59 automatic stabilization in percentage-points of primary surplus balances. All of this stabilization remains following discretionary responses during contractions, but arguably only about 3/5 of it remains so in expansions while discretionary behavior cancels the rest. We pay a lot of attention to the impact of the Maastricht Treaty and the SGP on the EU members of our sample and to real time data.

Joint estimates of automatic and discretionary fiscal policy: the OECD 1981-2003

Official calculations of automatic stabilizers are seriously flawed since they rest on the assumption that the only element of social spending that reacts automatically to the cycle is unemployment compensation. This puts into question many estimates of discretionary fiscal policy. In response, we propose a simultaneous estimate of automatic and discretionary fiscal policy. This leads us, quite naturally, to a tripartite decomposition of the budget balance between revenues, social spending and other spending as a bare minimum. Our headline results for a panel of 20 OECD countries in 1981-2003 are .59 automatic stabilization in percentage-points of primary surplus balances. All of this stabilization remains following discretionary responses during contractions, but arguably only about 3/5 of it remains so in expansions while discretionary behavior cancels the rest. We pay a lot of attention to the impact of the Maastricht Treaty and the SGP on the EU members of our sample and to real time data.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

Indexed versus nominal government debt under inflation and price-level targeting

This paper presents a DSGE model in which long run inflation risk matters for social welfare. Optimal indexation of long-term government debt is studied under two monetary policy regimes: inflation targeting (IT) and price-level targeting (PT). Under IT, full indexation is optimal because long run inflation risk is substantial due to base-level drift, making indexed bonds a much better store of value than nominal bonds. Under PT, where long run inflation risk is largely eliminated, optimal indexation is substantially lower because nominal bonds become a better store of value relative to indexed bonds. These results are robust to the PT target horizon, imperfect credibility of PT and model calibration, but the assumption that indexation is lagged is crucial. From a policy perspective, a key finding is that accounting for optimal indexation has important welfare implications for comparisons of IT and PT.

On Cobb-Douglas Preferences in Bilateral Oligopoly

Bilateral oligopoly is a simple model of exchange in which a finite set of sellers seek to exchange the goods they are endowed with for money with a finite set of buyers, and no price-taking assumptions are imposed. If trade takes place via a strategic market game bilateral oligopoly can be thought of as two linked proportional-sharing contests: in one the sellers share the aggregate bid from the buyers in proportion to their supply and in the other the buyers share the aggregate supply in proportion to their bids. The analysis can be separated into two ‘partial games’. First, fix the aggregate bid at B; in the first partial game the sellers contest this fixed prize in proportion to their supply and the aggregate supply in the equilibrium of this game is X˜ (B). Next, fix the aggregate supply at X; in the second partial game the buyers contest this fixed prize in proportion to their bids and the aggregate bid in the equilibrium of this game is ˜B (X). The analysis of these two partial games takes into account competition within each side of the market. Equilibrium in bilateral oligopoly must take into account competition between sellers and buyers and requires, for example, ˜B (X˜ (B)) = B. When all traders have Cobb-Douglas preferences ˜ X(B) does not depend on B and ˜B (X) does not depend on X: whilst there is competition within each side of the market there is no strategic interdependence between the sides of the market. The Cobb-Douglas assumption provides a tractable framework in which to explore the features of fully strategic trade but it misses perhaps the most interesting feature of bilateral oligopoly, the implications of which are investigated.

A Simple Characterization of Dynamic Completeness in Continuous Time

This paper investigates dynamic completeness of financial markets in which the underlying risk process is a multi-dimensional Brownian motion and the risky securities dividends geometric Brownian motions. A sufficient condition, that the instantaneous dispersion matrix of the relative dividends is non-degenerate, was established recently in the literature for single-commodity, pure-exchange economies with many heterogenous agents, under the assumption that the intermediate flows of all dividends, utilities, and endowments are analytic functions. For the current setting, a different mathematical argument in which analyticity is not needed shows that a slightly weaker condition suffices for general pricing kernels. That is, dynamic completeness obtains irrespectively of preferences, endowments, and other structural elements (such as whether or not the budget constraints include only pure exchange, whether or not the time horizon is finite with lump-sum dividends available on the terminal date, etc.)

Ecological-economic modelling of interactions between wild and commercial bees and pesticide use

The decline in extent of wild pollinators in recent years has been partly associated with changing farm practices and in particular with increase of pesticide use. In this paper we combine ecological modelling with economic analysis of a single farm output under the assumption that both pollination and pest control are essential inputs. We show that the drive to increase farm output can lead to a local decline in the wild bee population. Commercial bees are often considered an alternative to wild pollinators, but we show that their introduction can lead to further decline and finally local extinction of wild bees. The transitions between different outcomes are characterised by threshold behaviour and are potentially difficult to predict and detect in advance. Small changes in economic (input prices) and ecological (wild bees carrying capacity and effect of pesticides on bees) can move the economic-ecological system beyond the extinction threshold. We also show that increasing the pesticide price or decreasing the commercial bee price might lead to reestablishment of wild bees following their local extinction. Thus, we demonstrate the importance of combining ecological modelling with economics to study the provision of ecosystem services and to inform sustainable management of ecosystem service providers.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

Reading Ng Kim Chew: Malaysian-Chineseness and memory in contemporary Malaysian Chinese literature in taiwan

The idea of Chineseness as a geographic, cultural-specific and ethnically-charged concept, and the pivotal role assumed by memory linger throughout the writings of most authors hailing from Chinese community in Southeast Asia. Among these communities, being the Malaysian Chinese the more prolific in terms of number of writers and pieces of literature produced, this paper deals specifically with it. Its focus is put on the literature produced by Malaysian Chinese authors residing in Taiwan, which topic constitutes an important part of the first chapter, and on one of its main representatives, Ng Kim Chew, to whom chapter two and three are fully dedicated. A literary analysis of one of his short stories, Huo yu tu, will allow the reader to have a first-hand experience, through excerpts from the original text, of the importance of Chineseness and memory in the literary production of Ng and of many authors sharing with him similar life and literary experiences. I started this research from the assumption that these authors make large use of their own memories and memories from their own community in their writing as a way to re-tie themselves to the Chineseness they left in their places of origin. However in the case of Ng Kim Chew, the analysis of his works led be to theorizing that the identity he is imbued with, if there is one, is not Chinese, nor Malaysian, but purely and distinctively Malaysian-Chinese. This paper can also serve as an introduction for the general public to the field of Sinophone literature from Southeast Asia and to promote wider and innovative paths of research within the realm of Chinese studies that go beyond China proper.

Near-linear dynamics in KdV with periodic boundary conditions

Near linear evolution in Korteweg de Vries (KdV) equation with periodic boundary conditions is established under the assumption of high frequency initial data. This result is obtained by the method of normal form reduction.

Siliceous deep-sea sponge Monorhaphis chuni: A potential paleoclimate archive in ancient animals

The deep-sea sponge Monorhaphis chuni forms giant basal spicules, which can reach lengths of 3 m; they represent the largest biogenic silica structures on Earth that is formed from an individual metazoan. The spicules offer a unique opportunity to record environmental change of past oceanic and climatic conditions. A giant spicule collected in the East China Sea in a depth of 1110 m was investigated. The oxygen isotopic composition and Mg/Ca ratios determined along center-to-surface segments are used as geochemical proxies for the assessment of seawater paleotemperatures. Calculations are based on the assumption that the calculated temperature near the surface of the spicule is identical with the average ambient temperature of 4 degrees C. A seawater temperature of 1.9 degrees C is inferred for the beginning of the lifespan of the Monorhaphis specimen. The temperature increases smoothly to 2.3 degrees C, to be followed by sharply increased and variable temperatures up to 6-10 degrees C. In the outer part of the spicule, the inferred seawater temperature is about 4 degrees C. The lifespan of the spicule can be estimated to 11,000 +/- 3000 years using the long-term trend of the inferred temperatures fitted to the seawater temperature age relationships since the Last Glacial Maximum. Specimens of Monorhaphis therefore represents one the oldest living animals on Earth. The remarkable temperature spikes of the ambient seawater occurring 9500-3100 years B.P. are explained by discharges of hydrothermal fluids in the neighborhood of the spicule. The irregular lamellar organization of the spicule and the elevated Mn concentrations during the high-temperature growth are consistent with a hydrothermal fluid input. (C) 2012 Elsevier B.V. All rights reserved.