Neuro‐fuzzy time‐series analysis of large‐volume data

This paper describes a framework that utilizes an adaptive‐network‐based fuzzy inference system to perform user‐constrained pattern recognition on time‐series data. Using a customizable fuzzy logic grammar, the architecture allows an analyst to capture domain expertise in a context‐relevant manner. Fuzzy logic rules constructed by the analyst are used to perform feature extraction and influence the training of a neural network to perform pattern recognition. We demonstrate that the architecture is capable of performing noise‐tolerant searches across multiple features on large volumes of time‐series data. The experiments presented here are from the domain of stock analysis. We are able to create simple rule sets automatically to search a data warehouse of stocks to select stocks that exhibit desirable behaviours. Copyright © 2011 John Wiley & Sons, Ltd.     

Quantifying Inefficient Expenditure in Local Government: A Free Disposable Hull Analysis of a Sample of South African Municipalities

Municipalities in South Africa play a pivotal role in the provision of basic services to communities. However, local government as a sphere in the country is notorious for its spending inefficiency, which is cited as a major factor in service delivery failure. This paper quantifies inefficient expenditure at the local government level by estimating efficiency scores for a sample of 129 municipalities in South Africa from the 2005/2006 to the 2009/2010 municipal financial years. In essence, this paper examines the technical efficiency of municipalities by using the nonparametric free disposable hull approach and finds that 10 municipalities are constantly efficient over the period. On average, input efficiency scores range from 42% to 46%, suggesting that, in general, municipalities can achieve the same output levels with over 50% less resources. Quantitatively for the 2009/2010 financial year, this amounts to a total of R80 billion being spent inefficiently, which equates to R220 million being “wasted” per day.     

Measuring product market efficiency: A new methodology

This paper proposes a new methodology to measure product market efficiency. Our approach is based on the economic theory of product market equilibrium where consumers have incomplete information, and it allows quality to be multidimensional. We illustrate the methodology and compare it with other methodologies including the data envelopment analysis (DEA)-based procedure of Kamakura, Ratchford, and Agrawal (1988). The empirical results show that our model is robust to the precise distributional form of the disturbance term. In addition, our efficiency estimates are always equal to or lower than the DEA estimates of efficiency.