Agricultural land-use dynamics: Assessing the relative importance of socioeconomic and biophysical drivers for more targeted policy

A detailed understanding of multiple human and environmental factors influencing land allocations among agricultural uses can facilitate more efficient and targeted land policy. To show this, we used a comprehensive dataset of socioeconomic, physiographic, and climatic indicators to investigate potential determinants of land-use in Australia’s intensive agricultural region during the period 1992–2010. We applied a seemingly unrelated regressions land-use shares spatial error model with random effects coupled with variance decomposition analysis to identify the statistical significance, direction and magnitude of observed associations between land-use and its drivers.Population: density, rainfall, equity ratio, and access to markets were the most influential policy-relevant land-use factors. Land allocations to cereals and livestock production were significantly influenced by spatiotemporal rainfall and temperature variability. Improved pastures, cereals, annual and perennial crops plantations were larger in regions with better access to markets. Increases in equity ratio (i.e., better financial position) were associated with larger land allocations to improved pastures and annual crops and smaller extensive grazing area. Marginal associations were detected between land-use and output prices, and higher population density was associated with lower shares for all high value agricultural land-uses. The results suggest that improved transportation infrastructure, zoning regulations, and mechanisms to reduce farm debt exposure and risks from climate variability could have significant impact on the configuration of the Australian agricultural landscape.     

Yearly,monthly and weekly seasonality of tourism demand: A decomposition analysis

Annual seasonal variations in tourism demand have been a central theme in literature. However, annual seasonality is not the only time-based inequality in tourism flows that has important implications on policy-making decisions at destinations. Within the context of tourism, this study aims to make an in-depth analysis of intra-monthly and intra-weekly tourism demand using the entropy and relative redundancy measures as alternative seasonality indicators to the Gini coefficient in order to provide new tools to manage tourism and propose new action policies at these frequencies. In comparison with the Gini coefficient, the entropy measure is simpler to compute and it is easily decomposable. Using the case study of air arrivals and departures to and from the Balearic Islands, results show the appropriateness of entropy and relative redundancy as seasonal indicators but also as a new information tools for tourism seasonality analysis.     

Internet Access and Farm Household Income – Empirical Evidence using a Semi‐parametric Assessment in Taiwan

There is considerable literature examining individuals’ behaviour with respect to Internet use, but less attention is paid to farm household use of the Internet. Among the few studies on farm households, the emphasis is on the correlation between socioeconomic factors and the adoption of the Internet. Thus, relatively little is known about the association between Internet use and farm household well‐being. In an effort to fill this void, this paper investigates Internet access among farm households and examines the effects of Internet access on farm household income. Given the observed income gap between Internet users and non‐users, we then investigate the extent to which socioeconomic factors may be associated with this income gap. Using a nationwide survey of farm households in Taiwan, a novel econometric model is proposed and estimated employing a semi‐parametric technique. Our results support the conclusion that Internet use improves farm household income. Most of the income gap between adopters and non‐adopters can be explained by the differences in the return of the socioeconomic factors.     

上海能源效率变动及其因素分析

本文首先就上海能源效率的发展现状进行了分析，结果显示，上海经济总量持续上升、产业结构变动显著，上海能源强度持续下降，但这一趋势近期有所减缓。为了能进一步分析上海能源效率的决定因素，本文构建了能源效率分析的因素分析模型，选用对数平均迪氏指数法（Log Mean Divisia Index）对上海的整体能源效率进行研究，并讨论上海整体能源效率变动的原因。结果表明，以部门强度效应为主、结构效应为辅的两大影响因素共同提高了上海的整体能源效率。最后，本文从优化产业结构、加大科研投资、促进能源结构多元化、加快新能源发展等方面提出了对提高上海能源效率的政策建议。     

Clustering financial time series with variance ratio statistics

This study introduces a new distance measure for clustering financial time series based on variance ratio test statistics. The proposed metric attempts to assess the level of interdependence of time series from the point of view of return predictability. Simulation results show that this metric aggregates time series according to their serial dependence structure better than a metric based on the sample autocorrelations. An empirical application of this approach to international stock market returns is presented. The results suggest that this metric discriminates stock markets reasonably well according to size and the level of development. Furthermore, despite the substantial evolution of individual variance ratio statistics, the clustering pattern remains fairly stable across different time periods.     

Modelling and Estimation for Bivariate Financial Returns

Maximum likelihood estimates are obtained for long data sets of bivariate financial returns using mixing representation of the bivariate (skew) Variance Gamma (VG) and two (skew) t distributions. By analysing simulated and real data, issues such as asymptotic lower tail dependence and competitiveness of the three models are illustrated. A brief review of the properties of the models is included. The present paper is a companion to papers in this journal by Demarta & McNeil and Finlay & Seneta.     

一种能源消耗强度影响因素分解的新方法

研究能源消费各影响因素对能源消费的影响程度是降低能耗节约能源的基础。能源消耗强度影响因素分解是测度能源消耗强度影响程度的一类方法,对这类方法的研究和应用有极其重要的现实意义。本文提出了一种能源消耗强度影响因素分解的新方法,该方法分别利用对数平均迪氏指数法和投入产出法的优势,在完全分解交互项的同时,充分考虑部门之间的消耗及产品结构变化等特点。通过将此方法用于中国能源强度影响因素分解的结果证明,该方法是一种行之有效的分解方法。     

Evaluating the Productivity Performance of Agricultural Enterprises in Ireland using a Multiple Output Distance Function Approach

This paper uses a distance function approach to measure and decompose productivity growth of Irish agriculture between 1984 and 2000 for four principal farming systems. The technology used by each system is found to be sufficiently different as to warrant a system‐by‐system approach. The overall rate of productivity growth in Irish agriculture is found to be just over 1% for this period, but there are significant differences between systems. Sheep systems had the highest rate of productivity growth followed by dairy and tillage. Productivity in cattle farms fell during this period although there is evidence that this trend has been reversed in more recent years.     

Impact of the Great Recession on unemployed and NEET individuals’ labour market transitions in Ireland

The impact that the Great Recession has had on countries’ labour markets has been well documented. In Ireland, the contraction in economic activity that took place resulted in the country's overall unemployment rate increasing from 4.6% in 2006 to 15% in 2012. The country's youth unemployment rate rose from 9.9% to 33% over the same time period, while the proportion of NEETs increased from 10.1% in 2006 to 18.7% in 2012. Policymakers are aware of the unemployment rates of young and prime-aged people as well as the NEETs rate. However, little is known about these groups’ profiles, whether their profiles have changed since the recession and also their labour market transition patterns pre and post the Great Recession. Given the importance of this information in the design of effective activation measures to assist unemployed and NEET individuals, this paper examines each of these issues in turn. Overall, the study found for all three groups examined that the rate of transition to employment fell dramatically between 2006 and 2011. The analysis showed that the drop in the groups’ transition rates was not due to changes in the underlying sub-group population structures but to changes in the external environment that resulted in the impact of possessing certain characteristics changing over the recession. For example, education and nationality have become more important in finding a job in Ireland over the course of the recession, while there has been a fall in the scarring impact of unemployment durations.     

Price reversals versus price continuations: the transitory price effects of futures trading extension on the underlying stock market

This paper examines the transitory price effects of index futures trading extension on the underlying stock market. Based on the model formulation of George and Hwang (1995) and Amihud and Mendelson (1987) and using the Hong Kong data, we find that the extension of futures trading hour helps to reduce the opening pricing errors and change the correlations between daytime and overnight stock returns. Our finding adds to the literature that the trading behavior of derivatives has a significant influence on the transitory price changes of the underlying cash products.