Modelling conditional probability distributions for periodic variables

Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce two novel techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.

Modelling conditional probability distributions for periodic variables

Most conventional techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three related techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.

Estimating conditional probability densities for periodic variables

Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three novel techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.

Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.

Performance of small and medium enterprises and the impact of environmental variables: evidence from Vietnam

thesis is developed from a real life application of performance evaluation of small and medium-sized enterprises (SMEs) in Vietnam. The thesis presents two main methodological developments on evaluation of dichotomous environment variable impacts on technical efficiency. Taking into account the selection bias the thesis proposes a revised frontier separation approach for the seminal Data Envelopment Analysis (DEA) model which was developed by Charnes, Cooper, and Rhodes (1981). The revised frontier separation approach is based on a nearest neighbour propensity score matching pairing treated SMEs with their counterfactuals on the propensity score. The thesis develops order-m frontier conditioning on propensity score from the conditional order-m approach proposed by Cazals, Florens, and Simar (2002), advocated by Daraio and Simar (2005). By this development, the thesis allows the application of the conditional order-m approach with a dichotomous environment variable taking into account the existence of the self-selection problem of impact evaluation. Monte Carlo style simulations have been built to examine the effectiveness of the aforementioned developments. Methodological developments of the thesis are applied in empirical studies to evaluate the impact of training programmes on the performance of food processing SMEs and the impact of exporting on technical efficiency of textile and garment SMEs of Vietnam. The analysis shows that training programmes have no significant impact on the technical efficiency of food processing SMEs. Moreover, the analysis confirms the conclusion of the export literature that exporters are self selected into the sector. The thesis finds no significant impact from exporting activities on technical efficiency of textile and garment SMEs. However, large bias has been eliminated by the proposed approach. Results of empirical studies contribute to the understanding of the impact of different environmental variables on the performance of SMEs. It helps policy makers to design proper policy supporting the development of Vietnamese SMEs.

The determinants of export performance:evidence for manufacturing plants in Ireland and Northern Ireland

The dramatic GDP and export growth of Ireland over the last decade forms a marked contrast with that of its nearest neighbour Northern Ireland. In Ireland, export volume growth averaged 15.5% p.a. from 1991 to 1999 compared with 6.3% from Northern Ireland. Using data on individual manufacturing plants this paper considers the determinants of export performance in the two areas. Larger, externally owned plants with higher skill levels are found to have the highest export propensities in both areas. Other influences (plant age, R&D, etc.) prove more strongly conditional on location, plant size, and ownership. Structural factors (e.g. ownership, industry) explain almost all of the difference in export propensity between larger plants in Northern Ireland and Ireland but only around one-third of that between smaller plants. Significant differences are also evident between plants in terms of their sources of new technology. For indigenously owned plants, inhouse R&D is important. For externally owned plants, R&D conducted elsewhere in the group - typically outside Ireland and Northern Ireland - proves more significant. This external dependency and lower than expected export propensity on the part of small plants in Northern Ireland represent significant policy challenges for the future.© 2006 Scottish Economic Society. Published by Blackwell Publishing Ltd.

Can production subsidies explain China's export performance? Evidence from firm-level data

This paper analyses the relationship between production subsidies and firms’ export performance using a very comprehensive and recent firm-level database and controlling for the endogeneity of subsidies. It documents robust evidence that production subsidies stimulate export activity at the intensive margin, although this effect is conditional on firm characteristics. In particular, the positive relationship between subsidies and the intensive margin of exports is strongest among profit-making firms, firms in capital-intensive industries, and those located in non-coastal regions. Compared to firm characteristics, the extent of heterogeneity across ownership structure (SOEs, collectives, and privately owned firms) proves to be relatively less important.

Red capitalists:political connections and firm performance in China

Using a unique firm level data, this paper analyses the role of political connections in the post-entry performance of private start-up companies in China. It documents robust evidence that political affiliation enhances firms' survival and growth prospects. But interestingly politically neutral start-ups enjoy faster productivity improvements conditional on survival. In addition, the benefits of political connections are largely confined to firms associated with local or top level governments, and they are more pronounced in capital-intensive industries. We conclude that the close association between the state and a segment of the business community is leading to sub-optimal resource allocation in the economy by interfering with the process of market selection.

On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques.By combining two variants of the Free Disposal Hull (FDH) methods (order-m and order-?) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI.These results show the benefits of performing the analysis using quantile regression.

On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques. By combining two variants of the Free Disposal Hull (FDH) methods (order- m and order- α) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI. These results show the benefits of performing the analysis using quantile regression. © 2013 Elsevier B.V.