Selection of Nonnested Demand Models

This paper applies the likelihood dominance criterion (LDC), a new method of model selection developed by Pollak and Wales (1991), to four popular demand equation systems, using a set of seasonally adjusted quarterly Canadian data series. the results indicate that the almost ideal demand system (AIDS) dominates various alternative demand systems. the LDC method is useful in assisting demand analysts in selecting the proper demand specification. the paper also includes tests for unit roots and cointegration and, based on these tests, an error corrections model is estimated and tested against the popular but not theoretically plausible linear approximate almost ideal demand system.     

Factors affecting the breadth and depth of e-procurement use in small and medium enterprises

Organizations differ in the range of e-procurement functionalities they use (breadth of use) and in how much they rely on e-procurement (depth of use). Nonetheless, factors affecting the breadth and the depth of e-procurement use have never been studied in a single context. Therefore, it is unclear whether the differences between the effects discovered in past studies are due to the difference between the breadth and the depth of use, or to the difference between contexts. We test the effects of factors potentially affecting the breadth and the depth of e-procurement use in a single context, using data from 151 small and medium enterprises (SMEs) in the manufacturing sector in New Zealand. The results indicate that the breadth and the depth of use of e-procurement in business organizations are influenced by different factors. Perceived relative advantage of using e-procurement, plus external pressure from suppliers and competitors to use e-procurement, result in the use of a broader range of e-procurement functionalities – in a greater breadth of e-procurement use. However, the extent of an organization’s reliance on e-procurement in organizational purchasing (i.e., depth of e-procurement use) is driven by compatibility of e-procurement with organizational values, practices, technology infrastructure, and strategy. Arguing that in order to benefit fully from e-procurement, an organization needs to integrate it deeply into its operations, we conclude that managers evaluating new e-procurement technologies should consider their compatibility with organizational norms and practices.     

Investigating Software Piracy in Jordan: An Extension of the Theory of Reasoned Action

Software piracy, the illegal and unauthorized duplication, sale, or distribution of software, is a widespread and costly phenomenon. According to Business Software Alliance (2008), over 41% of the PC software packages installed worldwide were unauthorized copies. Software piracy behavior has been investigated for more than 30 years. However, after a review of the relevant literature, there appears to be two voids in this literature: a lack of studies in non-Western countries and a scarcity of process studies. This study contributes to literature by developing a software piracy model to better understand the decision-making process that underlies this unethical behavior. The model was tested using data collected from a sample of 323 undergraduate business students. Consistent with the Theory of Reasoned Action (TRA), attitudes toward software piracy and subjective norms were significant predictors of intention to pirate software. Also, the results suggested that ethical ideology, public self-consciousness, and low self-control moderated the effect of these variables on intention to pirate software. The results have important practical implications for the software industry and governments hoping to curtail software piracy. Limitations of the study and recommendations for future studies are discussed as well.     

Will African Agriculture Survive Climate Change?

Measurement of the likely magnitude of the economic impact ofclimate change on African agriculture has been a challenge.Using data from a survey of more than 9,000 farmers across 11African countries, a cross-sectional approach estimates howfarm net revenues are affected by climate change compared withcurrent mean temperature. Revenues fall with warming for drylandcrops (temperature elasticity of –1.9) and livestock (–5.4),whereas revenues rise for irrigated crops (elasticity of 0.5),which are located in relatively cool parts of Africa and arebuffered by irrigation from the effects of warming. At first,warming has little net aggregate effect as the gains for irrigatedcrops offset the losses for dryland crops and livestock. Warming,however, will likely reduce dryland farm income immedia-tely.The final effects will also depend on changes in precipitation,because revenues from all farm types increase with precipitation.Because irrigated farms are less sensitive to climate, wherewater is available, irrigation is a practical adaptation toclimate change in Africa.     

Environmental policy and stable collusion: The case of a dynamic polluting oligopoly

We show that the imposition of a Markovian tax on emissions, that is, a tax rate which depends on the pollution stock, can induce stable cartelization in an oligopolistic polluting industry. This does not hold for a uniform tax. Thus, accounting for the feedback effect that exists within a dynamic framework, where pollution is allowed to accumulate into a stock over time, changes the result obtained within a static framework. Moreover, the cartel formation can diminish the welfare gain from environmental regulation such that welfare under environmental regulation and collusion of firms lies below that under a laissez-faire policy.     

How effective is central bank communication in emerging economies? An empirical analysis of the chinese money markets responses to the people’s bank of China’s policy communications

Review of Quantitative Finance and Accounting - Central banks, in both developed and developing economies, are responding to the increased demand for transparency in monetary policy formulation and...     

Big data tools for Islamic financial analysis

Behavioural science states that emotions, principles and the manner of thinking can affect the behaviour of individuals and even investors in their decision making on financial markets. In this paper, we have tried to measure the investor sentiment by three means of big data. The first is based on a search query of a list of words related to Islamic context. The second is inferred from the engagement degree on social media. The last measure of sentiment is built, based on the Twitter API classified into positive and negative directions by a machine learning algorithm based on the naive Bayes method. Then, we investigate whether these sensations and emotions have an impact on the market sentiment and the price fluctuations by means of a vector autoregression model and Granger causality analysis. In the final step, we apply the agent‐based simulation by means of the sequential Monte Carlo method with the control of our Twitter measure on Islamic index returns. We show, then, that the three social media sentiment measures present a remarkable impact on the contemporaneous and lagged returns of the different Islamic assets studied. We also give an estimation of the parameters of the latent variables relative to the agent model studied.     

Implication studies: a methodological framework

Quality & Quantity - This article introduces a new label, “a methodological framework for studying implications of a philosophy, a framework, a theory, a model, or an idea for other...