Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

A critical appraisal of the reporting quality of published randomized controlled trials in the fall injuries

To evaluate the quality of reporting in published randomized controlled trials (RTCs) in the field of fall injuries. The 188 RTCs published between 2001 and 2011, indexed in EMBASE and Medline databases were extracted through searching by appropriate keywords and EMTree classification terms. The evaluation trustworthiness was assured through parallel evaluations of two experts in epidemiology and biostatistics. About 40%–75% of papers had problems in reporting random allocation method, allocation concealment, random allocation implementation, blinding and similarity among groups, intention to treat and balancing benefits and harms. Moreover, at least 10% of papers inappropriately/not reported the design, protocol violations, sample size justification, subgroup/adjusted analyses, presenting flow diagram, drop outs, recruitment time, baseline data, suitable effect size on outcome, ancillary analyses, limitations and generalizability. Considering the shortcomings found and due to the importance of the RCTs for fall injury prevention programmes, their reporting quality should be improved.     

Empirical Bayes analysis of log-linear models for a generalized finite stationary Markov chain

This article presents the empirical Bayes method for estimation of the transition probabilities of a generalized finite stationary Markov chain whose ith state is a multi-way contingency table. We use a log-linear model to describe the relationship between factors in each state. The prior knowledge about the main effects and interactions will be described by a conjugate prior. Following the Bayesian paradigm, the Bayes and empirical Bayes estimators relative to various loss functions are obtained. These procedures are illustrated by a real example. Finally, asymptotic normality of the empirical Bayes estimators are established.     

Sustainable resource use,economic development,and public regulation

The role of production technology for sustainable economic growth and resource management in the multispecies renewable resources industries is a neglected issue, particularly in complex tropical ecosystems. Given the still rudimentary understanding of biological interactions among species, even in most temperate ecosystems, the importance of under-standing the technological and economic interactions is heightened for sustainable economic growth and public regulation. This paper evaluates these interactions for the multiproduct gill net fisheries of Peninsular Malaysia. Standard price and quantity controls may have little promise. Gear regulations, a policy of constant escapement, and managing the entire mix of species as a single stock for economic rather than biomass yield appear the most promising management tools given the limited regulatory options.     

Exchange Rate Regime and Demand for Reserves: Evidence from Kenya,Mexico and Philippines

This paper empirically investigates the demand for international reserves (and foreign exchange reserves) during fixed and floating exchange rates periods in three developing countries: Kenya, Mexico and Philippines. Based on theoretical models, three factors are identified as important for the demand of international reserves and foreign reserves: average propensity to import, volume of imports and variability of reserves. The paper employs the cointegration methodology and error correction method to investigate the relationships. Cointegration tests results indicate a reliable long-run stationary relationship between the international reserves (and foreign exchange reserves) and the stated explanatory variables across countries and sub-periods of fixed and clean float. The error correction results indicate causality from the explanatory variables to the reserves during both the short and long run. This is true during both the fixed and the floating periods.

Inference for the two-parameter bathtub-shaped distribution based on record data

Here we consider the record data from the two-parameter of bathtub-shaped distribution. First, we develop simplified forms for the single moments, variances and covariance of records. These distributional properties are quite useful in obtaining the best linear unbiased estimators of the location and scale parameters which can be included in the model. The estimation of the unknown shape parameters and prediction of the future unobserved records based on some observed ones are discussed. Frequentist and Bayesian analyses are adopted for conducting the estimation and prediction problems. The likelihood method, moment based method, bootstrap methods as well as the Bayesian sampling techniques are applied for the inference problems. The point predictors and credible intervals of future record values based on an informative set of records can be developed. Monte Carlo simulations are performed to compare the so developed methods and one real data set is analyzed for illustrative purposes.     

Natural resource rents and internal conflicts: Can decentralization lift the curse?

We study how natural resource rents affect the risk of internal conflict within countries and how the federal structure of countries influences this relationship. Natural resource abundance may induce excessive rent-seeking and thus increase the risk of internal conflict. Fiscal and political decentralization as an institutional arrangement for rent-sharing and political codetermination of regions within a country may limit the destructive effect of natural resource rents on internal stability. Using cross-country and panel data from more than 90 countries covering the period 1984–2004, we find evidence that natural resource rents indeed increase the risk of internal conflict, but this relationship is significantly mitigated by political decentralization.