In this article, we present the problem of selecting a good stochastic system with high probability and minimum total simulation cost when the number of alternatives is very large. We propose a sequential approach that starts with the Ordinal Optimization procedure to select a subset that overlaps with the set of the actual best m% systems with high probability. Then we use Optimal Computing Budget Allocation to allocate the available computing budget in a way that maximizes the Probability of Correct Selection. This is followed by a Subset Selection procedure to get a smaller subset that contains the best system among the subset that is selected before. Finally, the Indifference-Zone procedure is used to select the best system among the survivors in the previous stage. The numerical test involved with all these procedures shows the results for selecting a good stochastic system with high probability and a minimum number of simulation samples, when the number of alternatives is large. The results also show that the proposed approach is able to identify a good system in a very short simulation time.

The house price issue has become an issue that is enthusiastically discussed, especially when the occurrence of rising toward house price. Thus, the main objective of this study is to identify macroeconomic determinant which influences house price. The macroeconomic determinants that involved in this study are gross domestic product, real interest rate, inflation rate, money supply and household consumption and expenditure. This study also investigates the existence of long-run relationship between house price and the macroeconomic determinants. This study covers a period of seventeen years that starts from year 1998 to the year 2014. There are nine Asia countries that include in this study namely Hong Kong, Japan, South Korea, Singapore, China, Indonesia, Malaysia, Taiwan and Thailand. The results of this study showed that three from five macroeconomic determinants which is significant based on dynamic ordinary least squares estimation and fully modified ordinary least square estimation. The three macroeconomic determinants that are significant are real interest rate, inflation rate and household consumption and expenditure. In addition, panel cointegration test indicates the existence of long-run relationship between house price and macroeconomic determinants.

The present study investigates the causal relationship between ASEAN seven member countries electricity consumption (EC) and some determinants such as gross domestic product (GDP), exports (EXP) and carbon dioxide emission (CO2) using vector autoregressive (VAR) framework via vector error correction (VEC) model for the period from 1980-2015. The findings show that the effect of the chosen determinants is different among the seven countries. Within the sample period, by utilizing Granger causality test, out of the seven countries, only four revealed either unidirectional or bidirectional causality running from EC to the three determinants, GDP, EXP and CO2. Whereas, thru forecast error variance decomposition (FEVD), forecasting beyond the sample period uncovered a shock to EC will also spread to GDP, EXP and CO2. The present study suggests that ASEAN should take note in designing their electricity policy, since electricity affect and be affected by other factors. In addition, ASEAN also should find solutions on how to control CO2 emission through EC.