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...

Using nationally representative panel data from Nepal, we estimate a household consumption function and simulate the impacts of remittance on poverty and inequality. We study how these impacts vary with regional maturity of migration process and country-source of remittance. The results show...

This article explores the heterogeneous effects of the migration-remittance process on the educational attainment of Nepalese children. The results suggest that when controlling for remittances, the children of more educated or informed parents suffer from parental absence, while the children of...

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...

Bereavement is a grieved and inevitable event in our life. For an aging society, the incidence of spousal bereavement and parental bereavement is higher than the other kinds of bereavement events. This study employs the difference-in-differences (DiD) strategy and the Taiwanese panel Survey of...

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...

A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the...

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...

Panel datasets provide a rich source of information for health economists, offering the scope to control for individual heterogeneity and to model the dynamics of individual behaviour. However the qualitative or categorical measures of outcome often used in health economics create special...

This paper proposes a scheme that speeds up the convergence of Markov Chain Monte Carlo (MCMC) algorithms in the context of limited-dependent variable models. The algorithm reduces autocorrelations more than the recently proposed Parameter Expansion Data Augumentation (PX-DA) algorithm. In...