Housing finance in transition economies : the early years in Eastern Europe and the former Soviet Union

The transition to markets dominates the development agenda of the 1990s. Financial sector reforms are central to a successful transition to a market economy. The author focuses on one dimension of these reforms: the development of housing finance institutions and services. He presents a progress report for the years since 1989, when the road to change opened with the collapse of communist regimes in most countries. Rather than a detailed account of reform in 25 countries, he offers a general framework for analyzing change and evaluating the prospects for rapid development of market-based housing finance systems. To understand why sound housing finance systems have not yet developed, one must consider factors in four key reform areas: the macroeconomic policies adopted to liberalize the economy and stabilize prices; privatization policies, in particular in housing and real estate; the strategies adopted - whether by design or by default - to reform the financial sector; the nature of the financial priorities and institutional constraints affecting housing finance reform strategies followed in different countries. Housing finance policy development has been somewhat haphazard in many countries. But the evidence suggests that the transition economiesthat have achieved low inflation, have adopted radical banking reforms, and seriously reformed and liberalized their real estate sector should be among the first to develop a modern system of housing finance.Non Bank Financial Institutions,Banks&Banking Reform,Payment Systems&Infrastructure,Housing Finance,Public Sector Economics&Finance,Banks&Banking Reform,Housing Finance,Public Sector Economics&Finance,Non Bank Financial Institutions,Municipal Financial Management

Vulnerability assessment and protective effects of coastal vegetation during the 2004 tsunami in Sri Lanka

The tsunami of December 2004 caused extensive human and economic losses along many parts of the Sri Lankan coastline. Thanks to extensive national and international solidarity and support in the aftermath of the event, most people managed to restore their livelihoods completely but some households did not manage to recover completely from the impacts of the event. The differential in recovery highlighted the various vulnerabilities and coping capacities of communities exposed to the tsunami. Understanding the elements causing different vulnerabilities is crucial to reducing the impact of future events, yet capturing them comprehensively at the local level is a complex task. This research was conducted in a tsunami-affected area in southwestern Sri Lanka to evaluate firstly the role of coastal vegetation in buffering communities against the tsunami and secondly to capture the elements of vulnerability of affected communities. The area was chosen because of its complex landscape, including the presence of an inlet connecting the Maduganga estuary with the sea, and because of the presence of remaining patches of coastal vegetation. The vulnerability assessment was based on a comprehensive vulnerability framework and on the Sustainable Livelihoods Framework in order to detect inherent vulnerabilities of different livelihood groups. Our study resulted in the identification of fishery and labour-led households as the most vulnerable groups. Unsurprisingly, analyses showed that damages to houses and assets decreased quickly with increasing distance from the sea. It could also be shown that the Maduganga inlet channelled the energy of the waves, so that severe damages were observed at relatively large distances from the sea. Some reports after the tsunami stated that mangroves and other coastal vegetation protected the people living behind them. Detailed mapping of the coastal vegetation in the study area and subsequent linear regression revealed significant differences between three vegetation classes present in the area with regard to water level and damages to houses. As our region showed homogeneity in some important factors such as coastal topography, our results should only be generalised to comparable regions

Permutation Inference for Canonical Correlation Analysis

Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements. As other variables are often a source of variability not of direct interest, previous work has used CCA on residuals from a model that removes these effects, then proceeded directly to permutation inference. We show that such a simple permutation test leads to inflated error rates. The reason is that residualisation introduces dependencies among the observations that violate the exchangeability assumption. Even in the absence of nuisance variables, however, a simple permutation test for CCA also leads to excess error rates for all canonical correlations other than the first. The reason is that a simple permutation scheme does not ignore the variability already explained by previous canonical variables. Here we propose solutions for both problems: in the case of nuisance variables, we show that transforming the residuals to a lower dimensional basis where exchangeability holds results in a valid permutation test; for more general cases, with or without nuisance variables, we propose estimating the canonical correlations in a stepwise manner, removing at each iteration the variance already explained, while dealing with different number of variables in both sides. We also discuss how to address the multiplicity of tests, proposing an admissible test that is not conservative, and provide a complete algorithm for permutation inference for CCA.Comment: 49 pages, 2 figures, 10 tables, 3 algorithms, 119 reference

Detection of TeV emission from the intriguing composite SNR G327.1-1.1

The shock wave of supernova remnants (SNRs) and the wind termination shock in pulsar wind nebula (PWNe) are considered as prime candidates to accelerate the bulk of Galactic cosmic ray (CR) ions and electrons. The SNRs hosting a PWN (known as composite SNRs) provide excellent laboratories to test these hypotheses. The SNR G327.1-1.1 belongs to this category and exhibits a shell and a bright central PWN, both seen in radio and X-rays. Interestingly, the radio observations of the PWN show an extended blob of emission and a curious narrow finger structure pointing towards the offset compact X-ray source indicating a possible fast moving pulsar in the SNR and/or an asymmetric passage of the reverse shock. We report here on the observations, for a total of 45 hours, of the SNR G327.1-1.1 with the H.E.S.S. telescope array which resulted in the detection of TeV gamma-ray emission in spatial coincidence with the PWN.Comment: Proceeding of the 32nd ICRC, August 11-18 2011, Beijing, Chin