Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

Financial development,economic growth and convergence clubs

To study the role of financial development in economic growth, we apply an array of convergence tests designed to capture nonlinear transitional dynamics to real outputs per capita. Strong evidence of multiple convergence clubs is observed, implying that the clubs are formed based on the initial level of real output per capita and average growth rate. Our empirical results show that the stage of economic growth of each country plays an important role for the composition of the convergence clubs. Furthermore, financial development emerges to be a significant determinant, albeit plays differently in the economic growth of each convergence club.     

辐射迁移方程--一个K-辛空间上的正则方程

说明了均匀、轴对称、无源介质是一个K-辛空间上的Hamilton系统，Hamilton函数是系统的守恒量；数值计算辐射强度角分布的合理途径是将辐射迁移方程离散成以离散Hamilton函数为守恒量的有限维K-辛空间上的正则方程，并采用保离散Hamilton函数守恒的K-辛算法数值求解．     

The effect of exchange rate changes on trade balances in the short and long run

Using generalized impulse response functions, this study tests for the trade J‐curve for three transitional central European countries – the Czech Republic, Hungary, and Poland – in their bilateral trade with respect to Germany. Our findings suggest that for each country there are some characteristics associated with a J‐curve effect: after a (real or nominal) depreciation the export‐to‐import ratio briefly drops to below its initial value within a few months and then rises to a long run equilibrium value higher than the initial one.     

Dynamic Panel Data Evidence on the Trade-Income Relation

This paper revisits the relationship between a country’s openness and its per capita income. Building on Frankel and Romer, it argues that a dynamic econometric specification similar to the ones used in empirical growth studies better fits the theoretical literature and also resolves some otherwise unresolved inconsistencies. The preferred econometric method is Blundell and Bond’s system-GMM estimator, which allows dealing with measurement error, weak instruments, and time-invariant country-specific effects. The findings confirm the existence of a strong effect of trade on income but fail to find evidence for trade as an independent factor of divergence. JEL no. F43, O40     

Inferential Causal Models: Integrating Quality & Quantity

In-depth data analysis plus statistical modeling can produce inferentialcausal models. Their creation thus combines aspects of analysis by close inspection,that is, reason analysis and cross-tabular analysis, with statistical analysis procedures,especially those that are special cases of the generalized linear model (McCullaghand Nelder, 1989; Agresti, 1996; Lindsey, 1997). This paper explores some of the roots of this combined method and suggests some new directions. An exercise clarifies some limitations of classic reason analysis by showing how the cross tabulation of variables with controls for test factors may produce better inferences. Then, given the cross tabulation of several variables, by explicating Coleman effect parameters, logistic regressions, and Poisson log-linear models, it shows how generalized linear models provide appropriate measures of effects and tests of statistical significance. Finally, to address a weakness of reason analysis, a case-control design is proposed and an example is developed.     

对计算企业经营活动现金流量的一点思考——从基本会计等式出发

本文旨在通过对基本会计等式的运用,揭示用间接法将净收益调节为经营活动现金流量的内在逻辑性。先对基本会计等式进行逐步的分析,推导出现金流量的计算步骤。在这一过程中,可以清楚的反映出会计报表之间的明晰性。     

A new bivariate distribution in natural exponential family

We propose a new bivariate distribution following a GLM form i.e., natural exponential family given the constantly correlated covariance matrix. The proposed distribution can represent an independent bivariate gamma distribution as a special case. In order to derive the distribution we utilize an integrating factor method to satisfy the integrability condition of the quasi-score function. The derived distribution becomes a mixture of discrete and absolute continuous distributions. The proposal of our new bivariate distribution will make it possible to develop some bivariate generalized linear models. Further the discrete correlated bivariate distribution will also arise from an independent bivariate Poisson mass function by compounding our proposed distribution (Iwasaki and Tsubaki, 2002).Received March 2003