我国东北地区野生玫瑰种质资源状况调查

对我国东北野生玫瑰（Rosa rugosa）种质资源仅存的吉林珲春和辽宁营口地区进行调查，发现我国野生玫瑰资源遭到了严重破坏，处于濒危状态。其原因主要是沙漠化使其生长环境日益恶化，人类过度采摘和破坏等。应采取当地保护、迁移保护和栽培利用的保护对策。     

Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life

Using a three-stage data envelopment analysis approach, this paper explores efficiency in the provision of social care for older people in 148 English Councils in 2009/10. Departing from D'Amico and Fernández (2012) [31] our measure of efficiency is inscribed within the production of welfare framework and based on self-reported quality of life of recipients of the services. Our results indicate a high level of efficiency, but once we control for the effects of a number of environmental variables, we found that more stringent eligibility criteria and higher assessment costs are negatively associated with the efficiency in the provision of social services.     

Is real per capita state personal income stationary? New nonlinear,asymmetric panel-data evidence

This paper re-examines the stochastic properties of U.S. state real per capita personal income, using new panel unit-root procedures. The new developments incorporate non-linearity, asymmetry, and cross-sectional correlation within panel-data estimation. Including nonlinearity and asymmetry finds that 43 states exhibit stationary real per capita personal income whereas including only nonlinearity produces 42 states that exhibit stationarity. Stated differently, we find that two states exhibit nonstationary real per capita personal income when considering nonlinearity, asymmetry, and cross-sectional dependence.     

Optimal rebalance rules for the constant proportion portfolio insurance strategy – Evidence from China

The constant proportion portfolio insurance (CPPI) strategy is one of the most popular asset allocation strategies employed by guaranteed-return financial products investors. Rebalance disciplines play an important role in determining the CPPI performance in practice. This paper examines whether the selection of rebalance rules affects CPPI strategy performance in the context of Chinese equity markets and, if so, in what pattern, and whether an optimal parameter of rebalance exists. We find that, (1) the three alternative rebalance disciplines – time discipline, market move discipline and lag discipline – are indifferent in affecting the performance of CPPI strategy; (2) in terms of optimal parameters of each rebalance rule, the optimal rebalancing period for the time discipline is 3 trading days, the optimal trading threshold of the market move discipline 4%, and the optimal lag factor of the lag discipline 6%. These optimal parameters are not influenced by the length of investment.     

Efficiency Determinants and Capacity Issues in Angolan Insurance Companies

This paper describes a variety of approaches used to assess the efficiency of a sample of major insurance companies in Angola between 2003 and 2012. Starting out with the bootstrapping technique, several data envelopment analysis (DEA) estimates were generated, allowing the use of confidence intervals and bias correction in central estimates to test for significant differences in efficiency levels and input‐decreasing/output‐increasing potentials. Previous studies have focused on the measurement and explanation of the factors affecting the performance rather than the prediction. The use of neural networks combined with DEA results as part of an attempt to produce a model for insurance companies’ performance with effective predictive ability is investigated. The findings indicate that older insurance companies with Portuguese origin tend to be more efficient. Results also suggest that opportunities for accommodating future demand appear to be scarce.     

OUTPUT FLUCTUATIONS PERSISTENCE: DO CYCLICAL SHOCKS MATTER?

The aim of this paper is to identify the different sources of persistence of output fluctuations. We propose an unobserved components model that allows us to decompose GDP series into a trend component and a cyclical component. We let the drift of the trend component switch between different regimes according to a first‐order Markov process. To calculate an appropriate p‐value for a test of linearity we propose a bootstrap procedure, which allows for general forms of heteroscedasticity. The performance of the bootstrap is checked by means of a Monte Carlo simulation. Our study concerns the USA. We find that cyclical shocks appear to play an important role on the observed persistence of output.     

Aspects of statistical analysis in DEA-type frontier models

In Grosskopf (1995) and Banker (1995) different approaches and problems of statistical inference in DEA frontier models are presented. This paper focuses on the basic characteristics of DEA models from a statistical point of view. It arose from comments and discussions on both papers above. The framework of DEA models is deterministic (all the observed points lie on the same side of the frontier), nevertheless a stochastic model can be constructed once a data generating process is defined. So statistical analysis may be performed and sampling properties of DEA estimators can be established. However, practical statistical inference (such as test of hypothesis, confidence intervals) still needs artifacts like the bootstrap to be performed. A consistent bootstrap relies also on a clear definition of the data generating proces and on a consistent estimator of it: The approach of Simar and Wilson (1995) is described. Finally, some trails are proposed for introducing stochastic noise in DEA models, in the spirit of the Kneip-Simar (1995) approach.     

What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables

Efficiency estimations which do not account for the operational environment where production units are operating in may have only a limited value. This article presents a fully nonparametric framework to estimate relative performance of production units when accounting for continuous and discrete background variables. Using insights from recent developments in nonparametric econometrics, we show how conditional efficiency scores can be estimated using a tailored mixed kernel function with a data-driven bandwidth selection. The methodology is applied to the sample of Dutch pupils from the Organization for Economic Co-operation and Development's Programme for International Student Assessment (OECD PISA) data set. We estimate students' performance and the influence of its background characteristics. The results of our application show that several family- and student-specific characteristics have a statistically significant effect on the educational efficiency, while school-level variables do not have impact on performance.