A new concept of ‘low-carbon towns’ (LCTs) has emerged in the urban planning and development of China in recent years to face the challenge of global climate change. This manuscript presents the current status, basic concepts, and town practices for the development of LCTs in China. First,...

In finance and economics, there is a great deal of work on the theoretical modeling and statistical estimation of the yield curve (defined as the relation between $-\frac{1}{\tau }\log p_{t}(\tau )$ and $\tau$, where $p_{t}(\tau )$ is the time $t$ price of the zero-coupon bond with payoff 1 at...

Kim, Shephard and Chib (1998) provided a Bayesian analysis of stochastic volatility models based on a fast and reliable Markov chain Monte Carlo (MCMC) algorithm. Their method ruled out the leverage effect, which is known to be important in applications. Despite this, their basic method has been...

This paper deals with Dynamic Stochastic General Equilibrium (DSGE) models under a multivariate student-<italic>t</italic> distribution for the structural shocks. Based on the solution algorithm of Klein (2000) and the gamma-normal representation of the <italic>t</italic>-distribution, the TaRB-MH algorithm of Chib and...

In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating...

This paper provides methods for carrying out likelihood based inference for diffusion driven models, for example discretely observed multivariate diffusions, continuous time stochastic volatility models and counting process models. The diffusions can potentially be non-stationary. Although our...

The method of Bayesian model selection for join point regression models is developed. Given a set of "K"&plus;1 join point models "M"₀, "M"₁, …, "M"_{" K"} with 0, 1, …, "K" join points respec-tively, the posterior distributions of the parameters and competing models "M"_"k" are computed...