This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units can have different cointegration ranks and...

A stationary bilinear (SB) model can be used to describe processes with a time-varying degree of persistence that depends on past shocks. An example of such a process is inflation. This study develops methods for Bayesian inference, model comparison, and forecasting in the SB model. Using...

This paper explores the economic performance of rural-urban migrant households in the recently flourishing urban areas of Nepal. Using nationally representative primary survey data, we find that upon their arrival, these migrant households have 24 percent less income and 13 percent less...

Factor models are used in a wide range of areas. Two issues with Bayesian versions of these models are a lack of invariance to ordering of the variables and computational inefficiency. This paper develops invariant and efficient Bayesian methods for estimating static factor models. This approach...

This paper investigates the determinants of growth in the Asian developing economies. We use Bayesian model averaging (BMA) in the context of a dynamic panel data growth regression to overcome the uncertainty over the choice of control variables. In addition, we use a Bayesian algorithm to...

This paper investigates the determinants of growth in the Asian developing economies. We use Bayesian model averaging (BMA) in the context of a dynamic panel data growth regression to overcome the uncertainty over the choice of control variables. In addition, we use a Bayesian algorithm to...

We estimate a household consumption function using two rounds of the nationally representative panel of living standard measurement survey (LSMS) of Nepal and simulate the impacts of remittance on poverty and inequality. We study how these impacts vary with the regional ‘incidence’ and...

Bayesian model averaging (BMA) has been successfully applied in the empirical growth literature as a way to overcome the sensitivity of results to different model specifications. In this paper, we develop a BMA technique to analyze models that differ in the set of instruments, exogeneity...

This paper applies a time-varying cointegration (TVC) model to study regional financial integration, measured by the drifting cointegration coefficient of the long-term interest rates between Singapore and Malaysia. Conditioned on long-run exchange rate equilibrium, the evolving relation can be...

This paper develops a novel and efficient algorithm for Bayesian inference in inverse Gamma Stochastic Volatility models. It is shown that by conditioning on auxiliary variables, it is possible to sample all the volatilities jointly directly from their posterior conditional density, using simple...