The public R&D and productivity growth in Australia's broadacre agriculture: is there a link?

This paper investigates the dynamic relationships between research and development (R&D) expenditure and productivity growth in Australian broadacre agriculture using aggregate time series data for the period 1953 to 2009. The results show a cointegrating relationship between R&D and productivity growth and a unidirectional causality from R&D to TFP (total factor productivity) growth in Australian broadacre agriculture. Using the dynamic properties of the model, data from beyond the sample period are analysed by employing the variance decomposition and the impulse response function. The findings reveal that R&D can be readily linked to the variation in productivity growth beyond the sample period. Furthermore, the forecasting results indicate that a significant out‐of‐sample relationship exists between public R&D and productivity in broadacre agriculture.     

Venture Capitalists, Business Angels, and Performance of Entrepreneurial IPOs in the UK and France

Abstract:  Using a unique sample of 444 entrepreneurial IPOs in the UK and France, this paper analyses the investment patterns and the stock-market performance effects of two types of early stage investors: venture capitalists (VCs) and business angels (BAs). Extending existing research, we identify important endogeneity and institutional effects. Our findings indicate that UK IPOs have a higher retained ownership and lower participation ratio by BAs, but a lower retained ownership and participation ratio by VCs than in France. BA and VC investments are substitutes, and they are endogenously determined by a number of firm- and founder-related factors, such as founder ownership and external board 'interlocks', and underwriter reputation. UK VCs are effective third-party certifying agents who reduce underpricing in UK IPOs, whereas in French IPOs they increase it by appearing to engage in grandstanding. This certification effect is more significant in UK IPOs involving both high VC and BA ownership. Finally, underpricing increases with VC participation ratio, where the higher exit of VCs seems to increase the risk premium required by outside investors, in particular in the UK.     

The Worldwide Movement in Private Universities: Revolutionary Growth in Post-Secondary Higher Education

The end of the Cold War, which resulted from the collapse of communism and the spread of free market ideas in the former Soviet Union, China, and nations in Eastern Europe, has brought about many dramatic and momentous changes on the world scene. One remarkable development not widely recognized outside specialized academic circles is the emergence of new institutions of higher learning in the private sector of previously command economies and also in many developing countries that had been wedded to a culture of socialism for decades. The “privatization” of higher education is by all accounts a global phenomenon. Very few systematic studies of these new trends in private post‐secondary education exist to date, although the impact of this development could be far‐reaching not only for higher education but also for the social and economic development of many societies in the world. In this paper we attempt to analyze the phenomenon of new private universities in non‐Western nations, focusing on the developing world in general, and Asia in particular. What missions have these institutions chosen? Which models are these institutions following? What challenges do they face? How are they coping with their relationship to existing public universities? How are they dealing with tuition and budgetary issues? What sources of funding are they tapping into? How are they dealing with issues of equity, excellence, and access? In the composition of their faculty, student body, and curriculum, are these institutions sufficiently international? How are the funding institutions and universities in the West helping these fledgling universities? Are these trends expected to accelerate in the future? We attempt to answer these questions within the context of a few case studies that reflect the breadth and diversity of this revolutionary growth in post‐secondary higher education.     

Can medium-scale farms support smallholder commercialisation and improve welfare? Evidence from Nigeria

In spite of mounting evidence about the growth of medium-scale farms (MSFs) across Africa, there is limited empirical evidence on their impact on neighbouring small-scale farms (SSFs). We examine the relationships between MSFs and SSFs, with particular focus on the specific mechanisms driving potential spillover effects. First, we develop a theoretical model explaining two propagating mechanisms: learning effects (training) and cost effects (reduced transactions cost). An empirical application to data from Nigeria shows that SSFs with training from MSFs tend to use higher levels of modern inputs (have higher productivity), and receive higher prices and income. The results also show that purchasing inputs from MSFs reduces the costs of accessing modern inputs and is associated with higher inorganic fertiliser use by SSFs. Our results suggest that the benefits of receiving training and purchasing inputs from MSFs are particularly important for very small-scale producers, operating less than 1 hectare of land. This implies that policies which promote the efficient operation of MSFs and encourage their interaction with SSFs can be an effective mechanism for improving the productivity and welfare of smallholder farms, hence reducing their vulnerability to extreme poverty.     

Christian roots of capitalist civilization

A conceptual argument is offered for the centrality of religion to the structure of capitalist civilization. This centrality is documented by examples of the role of Christianity in European civilization.     

Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.     

Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia*

This article empirically examines the impact of R&D and climate change on the Western Australian Agricultural sector using standard time series econometrics. Based on historical data for the period of 1977–2005, the empirical results show that both R&D and climate change matter for long‐run productivity growth. The long‐run elasticity of total factor productivity (TFP) with respect to R&D expenditure is 0.497, while that of climate change is 0.506. There is a unidirectional causality running from R&D expenditure to TFP growth in both the short run and long run. Further, the variance decomposition and impulse response function confirm that a significant portion of output and productivity growth beyond the sample period is explained by R&D expenditure. These results justify the increase in R&D investment in the deteriorating climatic condition in the agricultural sector to improve the long‐run prospects of productivity growth.     

A two‐step system for direct bank telemarketing outcome classification

A two‐step system is presented to improve prediction of telemarketing outcomes and to help the marketing management team effectively manage customer relationships in the banking industry. In the first step, several neural networks are trained with different categories of information to make initial predictions. In the second step, all initial predictions are combined by a single neural network to make a final prediction. Particle swarm optimization is employed to optimize the initial weights of each neural network in the ensemble system. Empirical results indicate that the two‐step system presented performs better than all its individual components. In addition, the two‐step system outperforms a baseline one where all categories of marketing information are used to train a single neural network. As a neural networks ensemble model, the proposed two‐step system is robust to noisy and nonlinear data, easy to interpret, suitable for large and heterogeneous marketing databases, fast and easy to implement.     

Six Decades of Total Factor Productivity Change and Sources of Growth in Bangladesh Agriculture (1948–2008)

This study applies the Färe–Primont index to calculate total factor productivity (TFP) indices for agriculture in 17 regions of Bangladesh covering a 61‐year period (1948–2008). It decomposes the TFP index into six finer components (technical change, technical‐, scale‐ and mix‐efficiency changes, residual scale‐ and residual mix‐efficiency changes). Results reveal that TFP grew at an average rate of 0.57% p.a. led by the Chittagong, Rajshahi, Rangpur, Dinajpur and Noakhali regions. TFP growth is largely powered by technological progress estimated at 0.74% p.a. Technical efficiency improvement is negligible (0.01% p.a.) due to stagnant efficiency in most of the regions. Decline in scale efficiency is also negligible (0.01% p.a.), but the decline in mix efficiency is high at 0.19% p.a. Decomposition of the components of TFP changes into finer measures of efficiency corrects the existing literature’s blame of a decline in technical efficiency as the main cause of poor TFP growth in Bangladesh. Among the sources, farm size, R&D investment, extension expenditure and crop specialisation positively influenced TFP growth, whereas the literacy rate had a negative influence on growth. Policy implications include encouraging investment in R&D and extension, land reform measures to increase average farm size, promotion of Green Revolution technology and crop diversification.