The Cost of Monopoly in Australian Manufacturing

This article looks at the deadweight loss arising from monopoly elements in Australian manufacturing under various assumptions and its relationship with the level of concentration.     

Corporate mergers and union wage premiums

Corporate mergers possibly enhance the labor negotiation advantage of employers. This study investigates the association between wage levels and merger activity to test the employer bargaining strength hypothesis. The results indicate significantly lower union wages as a consequence of merging. Merger activity, however, does not influence wage levels of non-union workers. These findings are supportive of the employer bargaining strength hypothesis.     

The Information Content of Dividend Initiations and Firm Size: An Analysis Using Bid-Ask Spreads

The bid-ask spread of stock prices is examined for a sample of dividend initiating firms. The average percentage and dollar bid-ask spreads increase significantly on the day preceding the Wall Street Journal Index announcement date, possibly reflecting, on average, the market maker's anticipatory uncertainty. The day -1 increase in spread is inversely associated with firm size, an information environment proxy, after considering the simultaneous effects of dividend yield, returns variance, dollar trading volume and share price. The average percentage spread declines significantly on day 0 from its day -1 level and remains lower, on average, over a 365 day post-announcement period than 90 day pre-announcement levels. Similar results are obtained for dollar spread averages. The post-announcement percentage spread decline suggests a resolution of uncertainty, and is positively associated with the dividend yield. Dividend initiation announcements appear to reduce informational asymmetry.     

A Multiple and Partial Wavelet Analysis of the Oil Price,Inflation, Exchange Rate,and Economic Growth Nexus in Saudi Arabia

This article provides a fresh insight into the dynamic nexus between oil prices, the Saudi/US dollar exchange rate, inflation, and output growth rate in Saudi Arabia’ economy, using novel Morlet’ wavelet methods. Specifically, it implements various tools of methodology: the continuous wavelet power spectrum, the cross-wavelet power spectrum, the wavelet coherency, the multiple and the partial wavelet coherence to the annual sample period 1969–2014. Our results unveil that the relationships among the variables evolve through time and frequency. From the time-domain view, we show strong but non-homogenous linkages between the four variables. From the frequency-domain view, we uncover significant wavelet coherences and strong lead-lag relationships. From an economic view, the wavelet analysis shows that Saudi economy is still exposed to several global risk factors, which are mainly related to the oil market volatility, and the pegging of the local currency to the US dollar. Such risk factors strongly and negatively affect the real economic growth, exert more pressure on inflation, and substantially limit the freedom to pursue an independent monetary policy.     

Mean–variance and mean–semivariance portfolio selection: a multivariate nonparametric approach

While univariate nonparametric estimation methods have been developed for estimating returns in mean-downside risk portfolio optimization, the problem of handling possible cross-correlations in a vector of asset returns has not been addressed in portfolio selection. We present a novel multivariate nonparametric portfolio optimization procedure using kernel-based estimators of the conditional mean and the conditional median. The method accounts for the covariance structure information from the full set of returns. We also provide two computational algorithms to implement the estimators. Via the analysis of 24 French stock market returns, we evaluate the in-sample and out-of-sample performance of both portfolio selection algorithms against optimal portfolios selected by classical and univariate nonparametric methods for three highly different time periods and different levels of expected return. By allowing for cross-correlations among returns, our results suggest that the proposed multivariate nonparametric method is a useful extension of standard univariate nonparametric portfolio selection approaches.     

An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

Forecasting technology diffusion: a new generalisation of the logistic model

The present research proposes a new generalisation of the logistic model aiming at technology diffusion forecasting. Regarding criticisms and failures reported in the literature to apply logistic function for long-term forecasting, in our work we focused on short-term accuracy of forecast. To formulate the model, based on mathematical approximation, at first the differential equation governing the diffusion process is found and then by solving the derived differential equation, the forecast function is obtained. In all steps, mathematical tools from numerical analysis are used. We compared the New Generalized Logistic Model with eight of the most renowned models in the literature. The model led to more accurate fits and forecasts than those obtained from other models we applied for comparison.     

Competitive strategies,innovation, and firm performance: an empirical study in a developing economy environment

This paper studies the relationships between competitive strategies, innovation, and firm performance within the context of Turkish manufacturing companies. The data were collected from top management of the firms via Computer Assistant Telephone Interviewing method. One hundred and forty manufacturing firms operating in various sectors including textile, automotive supply, computer and electronics provide the basis for this empirical research. In order to test our model, we employ structural equation modelling using partial least squares. The results show that competitive strategies such as cost-leadership and differentiation can lead to innovation, which, in turn, increase firm performance. Managers implement cost-leadership and differentiation strategies to take part in competitive market conditions; however, they should put additional importance on innovation that plays a significant role as a bridge between competitive strategies and firm performance.     

A Pyramid of Hate Perspective on Religious Bias,Discrimination and Violence

Journal of Business Ethics - This study provides a ‘pyramid of hate’ perspective on issues and challenges facing minority religious communities in social and political climates that...