This paper estimates the elasticity of labor productivity with respect to employment density, a widely used measure of the agglomeration effect, in the Yangtze River Delta, China. A spatial Durbin model is presented that makes explicit the influences of spatial dependence and endogeneity bias in...

We estabilsh the relationships between certain Bayesian and classical approaches to instrumental variables regression. We determine the form of priors that lead to posteriors for structural paameters that have similar properties as classical 2SLS and LIML and in doing so provide some new insight...

A key aim of economics is to set goals and investigate the relationship between various socio-economic indicators. By fitting time series data using a Bayesian dynamical systems approach we identify non-linear interactions between GDP, child mortality, fertility rate and female education. We...

Global emissions beyond 44 gigatonnes of carbondioxide equivalent (GtCO2e) in 2020 can potentially lead the world to an irreversible climate change. Employing a novel dynamical system modeling approach, we predict that in a business-asusual scenario, it will reach 61 GtCO2e by 2020. Testing...

This paper develops a small open economy (SOE) dynamic stochastic general equilibrium (DSGE) model that helps to explain business cycle synchronization between an emerging market and advanced economies. The model captures the specificities of both economies (e.g. primary commodity,...

This paper develops a small open economy (SOE) dynamic stochastic general equilibrium (DSGE) model that helps to explain business cycle synchronization between an emerging market and advanced economies. The model captures the specificities of both economies (e.g. primary commodity,...

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this...

The paper aims at systematic placement of identification concept within Bayesian approach. Pointing to some deficiencies of the standard Bayesian language to describe identification problem we propose several useful characterizations that seem to be intuitively sound and attractive given their...

Global emissions beyond 44 gigatonnes of carbondioxide equivalent (GtCO2e) in 2020 can potentially lead the world to an irreversible climate change. Employing a novel dynamical system modeling approach, we predict that in a business-asusual scenario, it will reach 61 GtCO2e by 2020. Testing...

A key aim of economics is to set goals and investigate the relationship between various socio-economic indicators. By tting time series data using a Bayesian dynamical systems approach we identify non-linear interactions between GDP, child mortality, fertility rate and female education. We show...