区域农业项目投资评价方法研究

文章根据农业项目投资的特征性,充分考虑农业区域的优势所在,在借鉴和总结前人研究成果的基础上,用D-S证据推理的原理和模糊数学的理论来研究区域农业项目的投资评价。这种方法避免了以往凭主观臆断来选择项目的麻木性,减少了不必要的损失,使农业项目的投资决策更为科学合理。     

Data features1

This article attempts to provide a formal framework for a data based inference which explicitly and consistently recognizes the approximate nature of probability models. It is based on the idea that a stochastic model is adequate if samples generated under the model are very much like the sample actually obtained. The formalization is based on the concept of data feature. Examples are given of applying the ideas to different areas of statistics including location-scale models, densities, non-parametric regression, interlaboratory test, auto-regressive processes and the analysis of variance. The four cornerstones of the approach are direct comparison, approximation, weak topologies and parsimony. The approach is contrasted to that of much of conventional statistics many of whose concepts are pathologically discontinuous with respect to the topology of data analysis and common sense.     

Bayesian Estimation of ARMA-GARCH Model of Weekly Foreign Exchange Rates

Three Bayesian methods (Markov chain Monte Carlo, Laplace approximation and quadrature formula) are developed to estimate the parameters of the ARMA-GARCH model. The ARMA-GARCH model is applied to weekly foreign exchange rate data of five major currencies, and their stochastic volatilities are judged by the posterior probabilities of stationarity and other conditions. This revised version was published online in August 2006 with corrections to the Cover Date.     

Robust bootstrap procedures for the chain-ladder method

Insurers are faced with the challenge of estimating the future reserves needed to handle historic and outstanding claims that are not fully settled. A well-known and widely used technique is the chain-ladder method, which is a deterministic algorithm. To include a stochastic component one may apply generalized linear models to the run-off triangles based on past claims data. Analytical expressions for the standard deviation of the resulting reserve estimates are typically difficult to derive. A popular alternative approach to obtain inference is to use the bootstrap technique. However, the standard procedures are very sensitive to the possible presence of outliers. These atypical observations, deviating from the pattern of the majority of the data, may both inflate or deflate traditional reserve estimates and corresponding inference such as their standard errors. Even when paired with a robust chain-ladder method, classical bootstrap inference may break down. Therefore, we discuss and implement several robust bootstrap procedures in the claims reserving framework and we investigate and compare their performance on both simulated and real data. We also illustrate their use for obtaining the distribution of one year risk measures.     

Financial Convergence in Transition Economies: EU Enlargement

This paper analyzes the financial effect of the enlargement of the European Union (EU) to include ten new Central and East European countries (CEECs) on firms' business and financial structures. We employ quantitative analytic techniques and financial ratios to discover whether firms in the new EU member states tend to converge with businesses in the EU-15 in terms of the structure of their financial statements. We examine the extent to which the increasing integration of the former may foster the convergence of productive structures. We analyze the evolution of twelve financial ratios in a sample of firms obtained from the AMADEUS database, performing a dynamic factor analysis that identifies the determining factors of the joint evolution of deviations in financial ratios from the average values of EU-15 firms. This allows us to analyze the convergence in each of the CEECs toward the EU-15.     

The impact of protected areas on the rural households’ incomes in Ethiopia

Protected areas are cornerstones for biodiversity conservation, yet they can be controversial because of their potential impact on the livelihoods of local people due to restrictions on agricultural land use and the extractive use of natural resources. This study evaluates the impact of PAs on households’ livelihoods, as measured by total household income (THI) and livestock income (LI). We use a survey and a quasi-experimental design to gather socioeconomic and biophysical data from households living within, adjacent to and outside three national parks (NPs) in Ethiopia and employ matching methods to isolate the impact of NPs. Our findings suggest that there is no evidence that the establishment of NPs adversely affects local livelihoods. Instead, we find that households within and in adjacent areas to NPs have higher incomes compared to those living outside. Understanding the heterogeneity of the effect of NPs on local livelihoods can help in designing well-targeted policy interventions that improve conservation goals while also addressing livelihood concerns of resource-dependent local communities.