基于景观生态学的区域土地利用结构演变及优化分析——以北京市顺义区为例

从景观生态的角度对北京市顺义区1996-2006年的土地利用结构演变进行数量与空间特征变化分析,并借助马尔科夫模型进行用地预测,获得该区土地利用演变规律:顺义区地类的面积比例呈现出均一化的特点,耕地和未利用地的数量减少,建设用地、生态用地和廊道增加,且建设用地将在10a之内代替耕地成为该区域的优势景观类型,而生态用地、廊道与未利用地将维持一个相对稳态;空间层面上,研究区整体景观的破碎度增加,聚集度减少,景观形状呈现简单化,景观异质性和多样性增强。最后,以"斑块-廊道-基质"理论为依据,构建出顺义区土地利用结构优化框架:即集中耕地形成基质,斑块的布局应该特别注重生态节点的建设和生态敏感地带的保护及建设生态廊道。     

“Panelizing” Repeated Cross Sections

This paper considers the implementation of a non-stationary, heterogeneous Markov model for the analysis of binary dependent variables in a time series of repeated cross-sectional (RCS) surveys. The model offers the opportunity to estimate entry and exit transition probabilities and to examine the effects of time-constant and time-varying covariates on the hazards. We show how maximum likelihood estimates of the parameters can be obtained by Fishers method-of-scoring and how to estimate both fixed and time-varying covariate effects. The model is exemplified with an analysis of the labor force participation decision of Dutch and West German women using ISSP (and other) data from 10 annual Dutch surveys conducted between 1987 and 1996 and 7 annual West German surveys conducted between 1988 and 1994. Some open problems concerning the application of the model are discussed.     

Empirical Bayes analysis of log-linear models for a generalized finite stationary Markov chain

This article presents the empirical Bayes method for estimation of the transition probabilities of a generalized finite stationary Markov chain whose ith state is a multi-way contingency table. We use a log-linear model to describe the relationship between factors in each state. The prior knowledge about the main effects and interactions will be described by a conjugate prior. Following the Bayesian paradigm, the Bayes and empirical Bayes estimators relative to various loss functions are obtained. These procedures are illustrated by a real example. Finally, asymptotic normality of the empirical Bayes estimators are established.     

Testing time-homogeneity of rating transitions after origination of debt

When modelling rating transitions as continuous-time Markov processes, in practice, time-homogeneity is a common assumption, yet restrictive, in order to reduce the complexity of the model. This paper investigates whether rating transition probabilities change after the origination of debt. Accordingly, we develop a likelihood-ratio test for the hypothesis of time-homogeneity. The alternative is a step function of transition intensities. The test rejects time-homogeneity for rating transitions observed over 7 years in a real corporate portfolio. Especially 1-year transition probabilities increase over the first year after origination. This time effect suggests that banks should manage their credit portfolios with respect to the age of debt.      

Testing for negativity in a demand system: A Bayesian approach

The paper introduces Bayesian inference into a demand model. This allows us to test for the negativity condition of the substitution matrix which is difficult to handle directly in the traditional approach. To illustrate the Bayesian inference procedures, we estimate the Rotterdam model and test the demand properties using Japanese data. The empirical results show the importance of specifically considering negativity in demand analysis. First version received: September 1997/final version received: February 1998     

中国省际城镇职工工资收入分布演进的时空特征

运用Kernel密度估计方法和空间马尔科夫链分析方法,并将空间因素纳入分析框架中,对1978—2009年期间中国省际城镇职工工资收入分布演进的时空特征进行了分析。研究结果表明:从时间动态性看,中国省际城镇职工工资收入的差距正逐步固化和深化,多俱乐部收敛特征明显、贫困陷阱问题日益突出;从空间动态性看,近邻效应对省际城镇职工工资收入分布演进存在一定影响,多数省份的工资收入水平向邻区的平均工资收入水平演进。     

Do rice prices follow a random walk? Evidence from Markov switching unit root tests for Asian markets

This study revisits the issue of mean reversion in the import rice prices of six Asian countries over the period between 1995 and 2015. Augmented Dickey Fuller tests with a conventional linear regression model support the presence of a unit root in the levels of the price data. However, when regressions allow for Markov switching in coefficients and variances to capture periodic shifts in levels and volatilities, there is strong evidence against the unit‐root null hypothesis in favor of stationarity over much of the observation period.     

Product Patent Reform and its Impact on Korea's Pharmaceutical Industry

Our analysis focuses on the effect of U.S. government pressure on Korea to adopt product patents for chemical and pharmaceutical products. American pressure began in November 1985 and ended with the Korean Legislature's passage of a new patent law in December 1986. We conduct an event study of the effect of the new patent law on the value of Korean pharmaceutical firms listed on the Korea Stock Exchange. Regression analysis shows that the new law induced excess returns of-74 percent over the 14-month analysis period. The results suggest that adoption of stronger patent laws reduced Korea's wealth. [G14, O34]     

Asymptotic stability of a general equilibrium under perfect and monopolistic competition

This study examines the asymptotic stability of a general equilibrium for an economy under perfect and monopolistic competition in which delays in a production process arise. Crucially, we find that the sufficient conditions for the stability of the equilibrium in each model differ markedly. For the stability of the equilibrium under perfect (monopolistic) competition, it is favorable that the slope of every demand curve is gradual (steep).     

STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG‐RUN RESTRICTIONS VIA HETEROSKEDASTICITY

Long‐run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long‐run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.