The economic effects of oil prices shocks on the UK manufacturing and services sector

This paper investigates the relationship between changes in oil prices and the UK’s manufacturing and services sector performances. Only a few studies have been conducted at the sector level: the goal of this paper is to contribute in that direction. After presenting review of existing literature about oil effects on the UK’s sectors of manufacturing and services, an econometric analysis is carried out. In a more detailed analysis, three sets of vector autoregressive (VAR) models are employed using linear and non-linear oil price specifications among several key macroeconomic variables. From the linear oil price specification VAR model, the impulse response function reveals that oil price movement causes positive effects in both the output of manufacturing and services sectors. The variance decomposition shows that oil prices are quite important as a cause of the variance of the UK services sector output, while they do not have such a large role in the variance of the UK’s manufacturing output. From the asymmetric specification, it has been found that positive oil price changes determine a consistent contraction in manufacturing output, while the services sector does not seem to be affected by increases. Alternatively, negative oil price changes, show that manufacturing output does not increase so much despite a decrease in oil prices. The services sector is much more affected by oil prices decreases than increases. Finally considering the net oil price increase (NOPI) specification, it has been found that the manufacturing sector is much more affected by oil price changes than the services sector.Oil shock; VAR; impulse response function; variance decomposition;

Volatility and Long Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK

The aim of this paper is twofold. First it aims to compare several GARCH family models in order to model and forecast the conditional variance of German, Swiss, and UK stock market indexes. The main result is that all GARCH family models show evidence of asymmetric effects. Based on the “out of sample” forecasts I can say that for each market considered there is a model that will lead to better volatility forecasts. Secondly a long run relation between these markets was investigated using the cointegration methodology. Cointegration tests show that DAX30, FTSE100, and SMI indexes move together in the long term. The VECM model indicates a positive long run relation among these indexes, while the error correction terms indicate that the Swiss market is the initial receptor of external shocks. One of the main findings of this analysis is that although the UK, Switzerland and Germany do not share a common currency, the diversification benefits of investing in these countries could be very low given that their stock markets seem to move together in the lung term.Stock Returns; Volatility; GARCH models; Cointegration

Abstract approach to non homogeneous Harnack inequality in doubling quasi metric spaces

We develop an abstract theory to obtain Harnack inequality for non homogeneous PDEs in the setting of quasi metric spaces. The main idea is to adapt the notion of double ball and critical density property given by Di Fazio, Guti\'errez, Lanconelli, taking into account the right hand side of the equation. Then we apply the abstract procedure to the case of subelliptic equations in non divergence form involving Grushin vector fields and to the case of X-elliptic operators in divergence form

A genetic algorithm to design Laue lenses with optimal performance for focusing hard X- and gamma-rays

In order to focus hard X- and gamma-rays it is possible to make use of a Laue lens as a concentrator. With this optical tool it would be possible to improve the detection of radiation for several applications, spanning from the observation of the most violent phenomena in the sky to nuclear medicine applications, for diagnostic and therapeutic purposes. A code named LaueGen, based on a genetic algorithm and aimed to designing optimized Laue lenses, has been implemented. The genetic algorithm was selected because the optimization of a Laue lens is a complex and discretized problem. The output of the code consists in the design of a Laue lens composed of diffracting crystals selected and arranged in such a way to maximize the performance of the lens. The code allows one to manage crystals of any material and crystallographic orientation. The program is structured in such a way that the user can control all the initial parameters of the lens. As a result, LaueGen is highly versatile and can be used for the design of very small lens, e.g. for nuclear medicine, to very large lens, e.g. for satellite-borne astrophysical missions.Comment: 18 pages, 4 figure

Microfinance institutions: financial sustainability and efficiency

The main objective of this research is to analyse the relationship between financial sustainability and efficiency of Microfinance Institutions (MFIs) in terms of outreach to the poor as well as the relation between gender and repayment in microfinance. The sample used is composed of all MFIs in the globe as reported to MixMarket. Our study covers the period 2000-2010. The study also investigates whether the current global financial crisis has had any effects on the issues we study. Our dataset is organised as a panel dataset given that we have multiple observations on the same economic units and a number of periods over time. The estimation techniques are based on the fixed-effects (FE) and random-effects (RE) models. However we use the Hausman test in order to make a choice between FE and RE approaches. Our results show that FE models perform better that RE models through all the period of analysis. For the whole period of analysis results show that MFIs focusing on female clients, are characterized by a greater size of loans provided. On the other hand, we also find that the credit risk in microfinance institutions increases as the number of female clients raise

Cointegration and conditional correlations among German and Eastern Europe equity markets

This paper aims to examine the long term relationship between German and three Central and Eastern Europe (CEE) equity markets. Application of Johansen as well as Engle-Granger cointegration tests show that there is no long-term relationship among these markets while the Gregory-Hansen cointegration test rejects the null hypothesis of no cointegration with structural break. An additional objective is to capture the time-varying correlation among these markets through the dynamic conditional correlation models. Empirical results suggest that correlations increased after the accession of the CEE countries into the European Union.Equity markets; Cointegration; Dynamic conditional correlation models.