pment in the process of economic growth, a convincing theoretical framework was lacking until the recent publications of McKinnon [19] and Shaw [25]. Indeed, neoclassical growth theories provide, in the main, a negative role to the monetary process. Here, a reduction rather than an increase in...

Using data from Thailand's Labour Force Survey from 2012 to 2021, the differences over time were investigated for the likelihood of youths moving between employment states, such as unemployment, employment and out of the labour force. Additional transitions were calculated for groups moving...

This paper extends the analysis of bivariate seemingly unrelated (SUR) Tobit model by modeling its nonlinear dependence structure through copulas. The capability in coupling together the different marginal distributions allows the flexible modeling for the SUR Tobit. The ability in capturing...

This paper proposes a generalized class of univariate skew distributions that are constructed through mixture of two scaled normal distributions. The proposed skew distributions with the skewness parameter defined in the (0,1) interval allow us to have an application on parametric quantile...

Parallel computation is a fast growing computing environment in many areas including computational Bayesian statistics. However, most of the Bayesian parallel computing have been implemented through the sequential Monte Carlo method where model parameters are updated sequentially and it is...

This paper proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two...

COVID-19 pandemic is an extreme event that created a turmoil in stock markets around the world. This unexpected circumstance poses a critical question whether the prevailing models can help predict the plummets of indices, hence the returns. In this study, we model the stock returns using...

This paper aims to study the forecasting capabilities of several models under the Markov regime-switching (MRS) and the extreme value theory (EVT) frameworks applied to daily electricity prices in the New Zealand electricity market. The MRS models in this study include up to five regimes, with...

Macroeconomic data are an important piece of information in decision making for both the public and private sectors in Thailand. However, the release of key macroeconomic data, usually in a lower frequency such as quarterly, is not always in a timely manner. Using the higher frequency data such...

Feature selection becomes a prominent method in the big data era. The logistic regression model is a wrapper method that provides better classification or prediction accuracy but it is computationally expensive. In this study, we propose the random subspace logistic regression where features are...