Inflation, GDP and Causality for European Countries

This study investigates, through panel univariate GARCH models for 14 European countries the causality between inflation and GDP and finds that inflation causes GDP at the 5% level of significance and GDP cause inflation at the 10% significance level. Thus, there is a bidirectional effect between the above two cases which is significant at the 10% level.     

Robust monetary policy with imperfect knowledge

We examine the performance and robustness properties of monetary policy rules in an estimated macroeconomic model in which the economy undergoes structural change and where private agents and the central bank possess imperfect knowledge about the true structure of the economy. Policymakers follow an interest rate rule aiming to maintain price stability and to minimize fluctuations of unemployment around its natural rate but are uncertain about the economy's natural rates of interest and unemployment and how private agents form expectations. In particular, we consider two models of expectations formation: rational expectations (RE) and learning. We show that in this environment the ability to stabilize the real side of the economy is significantly reduced relative to an economy under RE with perfect knowledge. Furthermore, policies that would be optimal under perfect knowledge can perform very poorly if knowledge is imperfect. Efficient policies that take account of private learning and misperceptions of natural rates call for greater policy inertia, a more aggressive response to inflation, and a smaller response to the perceived unemployment gap than would be optimal if everyone had perfect knowledge of the economy. We show that such policies are quite robust to potential misspecification of private sector learning and the magnitude of variation in natural rates.     

Administrative Costs and Instrument Choice for Stochastic Non-point Source Pollutants

This paper extends the empiricalanalysis of non-point source pollution to thecase where the pollutant is stochastic andalternative regulatory instruments havedifferent administrative costs. It also appliesa method of stochastic programming whereemissions are log-normally distributed. Forthe Kennet catchment in South West England werank a range of policies in terms of abatementcosts alone, and total costs (abatement andadministrative costs). On the basis ofabatement costs alone, a uniform emission taxis the cost minimising policy, but on the basisof total cost a nitrogen input tax is theleast-cost policy. Furthermore, the policyranking, based on total costs, changes as thereliability standard increases.     

Modeling Frost Losses: Application to Pricing Frost Insurance

The main objective of this article is to model the losses caused by frost events and use it to price frost insurance. Since the data on frost events are either unavailable or rarely available, we have chosen to obtain a model for frost losses based on temperature by using some fundamental agricultural engineering findings on frost damage. The main challenges in modeling frost loss variables are, first, the nonlinearity of the frost losses with respect to the temperature and, second, the fruit resistance to the first few hours of low temperature. We address both issues when introducing our frost loss variable. Then after finding the loss model, we use it to price frost insurance for a general family of insurance contracts that do not generate any risk of moral hazard. In particular, we will find the premiums of stop-loss policies for losses to citrus fruits using Value at Risk, Conditional Value at Risk, and Wang's premium based on temperature data from San Joaquin Drainage in California.     

Forecasting and trading high frequency volatility on large indices

The present paper analyses the forecastability and tradability of volatility on the large S&P500 index and the liquid SPY ETF, VIX index and VXX ETN. Even though there is already a huge array of literature on forecasting high frequency volatility, most publications only evaluate the forecast in terms of statistical errors. In practice, this kind of analysis is only a minor indication of the actual economic significance of the forecast that has been developed. For this reason, in our approach, we also include a test of our forecast through trading an appropriate volatility derivative. As a method we use parametric and artificial intelligence models. We also combine these models in order to achieve a hybrid forecast. We report that the results of all three model types are of similar quality. However, we observe that artificial intelligence models are able to achieve these results with a shorter input time frame and the errors are uniformly lower comparing with the parametric one. Similarly, the chosen models do not appear to differ much while the analysis of trading efficiency is performed. Finally, we notice that Sharpe ratios tend to improve for longer forecast horizons.     

Financial Stability,Monetary Stability and Growth: a PVAR Analysis

Open Economies Review - This paper employs a panel vector autoregressive (PVAR) model to investigate the relationship among financial stress, inflation and growth in 19 advanced economies over the...     

DIRECTED SEARCH AND THE BERTRAND PARADOX

I study a directed search model of oligopolistic competition, extended to incorporate general capacity constraints, congestion effects, and pricing based on ex post demand. In the presence of any one of these ingredients, the Bertrand paradox fails to hold. Hence, despite the emphasis that has been placed by the literature on sellers' capacity constraints as a resolution to the paradox, the existence of such constraints is only a subcase of a general class of environments where the paradox fails. Specifically, Bertrand's paradox will not arise whenever the buyers' expected utility from visiting a seller is decreasing in that seller's realized demand.     

A case study investigating the impact of the London 2012 Olympic and Paralympic Games on participation in two non-traditional English sports,Judo and Fencing

The hosting of the London 2012 Olympic and Paralympic Games (LOPG) brought with it detailed legacy plans aiming to ‘Inspire a Generation’. The idea that hosting a sports mega-event will encourage the host population to engage in more physical activity is commonly used by governments to justify the large investments they make. The aim of this research paper was to investigate the impact that hosting the 2012 Games had on grass-root sports participation within the host nation. This paper focuses on two non-traditional English sports, Fencing and Judo and investigated the changes in mass sports participation. The membership rate analysis of our sample highlighted an overall increase in participation between 2007 and 2013, in both Judo and Fencing. The data gathered from the interviews with the head office staff at the National Governing Bodies (NGBs) and local club coaches suggested that the grass-root participation programmes were the most effective way of increasing participation, rather than the reliance, solely on the inspiration effect from hosting the LOPG itself. The study highlighted the importance of strengthening communication between local voluntary clubs and the NGB, to ensure sports could promote themselves and capitalise on this global sporting phenomenon, which provided unprecedented media coverage and opportunities for these non-traditional sports. This case study provides initial results relating to the effect that a major international multi-sport event can have in the development of non-traditional sports in the host population, in terms of membership variations, participation programmes and organisational dynamics.