Abu Hassan Shaari

The influence of junction formation process variables on diffusion sheet resistance using statistical design of experiment methodology

The statistical design of experiments technique was used to study the influence of junction formation process variables on the diffusion sheet resistance. A two-level screening experiment with 2/sup 3/ factorial design was used to evaluate three process variables in eight combination runs. The factors were BF/sub 2/ and Ar implantation dose, drive-in temperature and drive-in time. Variance analysis was used to analyze the data and we found that all of the main variables were important for arsenic implanted wafers but only the drive-in temperature factor was important for boron implanted wafers. We also discovered that there was no significant interaction between the factors. For arsenic implanted wafers, which were driven-in at 950/spl deg/C, the measured sheet resistances were at between 110 and 130 /spl Omega///spl square/ while for wafers which were driven-in at 850/spl deg/C, the sheet resistances were measured at between 60 and 90 /spl Omega///spl square/. For boron implanted wafers, the measured sheet resistance values were found to be constant at about 30 /spl Omega///spl square/, regardless of drive-in temperature. The experimental data were used in regression equations to model the sheet resistance. By this, we have illustrated how the statistical design of experiments methodology can be used effectively in order to control the process performance.

Income inequality and shadow economy: a nonparametric and semiparametric analysis

Purpose - The purpose of this paper is to investigate the nonlinear relationship between shadow economy and income inequality and determine whether the size of shadow economy can influence the level of income inequality. Design/methodology/approach - Both parametric (panel OLS) and nonparametric/semiparametric regression suggested by Robinson (1988) will be used to capture the dynamic nonlinear relationship between these variables using unbalanced panel data of 154 countries from 2000 to 2007. Additionally, the relationship between income inequality and shadow economy on both developed and developing countries will be analyzed and compared. Findings - First, semiparametric analysis and nonparametric analysis are significantly different than parametric analysis and better in nonlinear analysis between income inequality and shadow economy. Second, income inequality and shadow economy resemble an inverted-N relationship. Third, the relationship between income inequality and shadow economy is different in developed countries (OECD countries) and developing countries, where OECD countries have similar inverted-N relationship as before. However, for developing countries, income inequality and shadow economy show an inverted-U relationship, similar to the original Kuznets hypothesis. Practical implications - This study suggests that there is a possible trade-off between income inequality and shadow economy and helps policy makers in solving both problems effectively. Originality/value - Despite the growing importance of income inequality and shadow economy, literature linking the two variables is scarce. To the best of the authors’ knowledge, there is no literature that nonlinearly links these two variables. Furthermore, the dynamics of the relationship between these two variables in developed countries and developing countries will be explored as well.

Financial integration via panel cointegration approaches in ASEAN+5

Purpose - – The purpose of this paper is to identify whether any financial integration exists among ASEAN+5 members and some East Asian countries, including China, Japan, Korea, Hong Kong, and Taiwan, through interest rate, exchange rate, level of prices, and real output. Design/methodology/approach - – Therefore, the authors intend to identify any long-term relationship among these variables utilizing the data in the most efficient manner via panel cointegration and panel unit root tests. The study likewise uses a panel-based vector error correction (panel-vec) model for comparison and also short-run relationship analysis. The long-run relationship is estimated using dynamic ordinary least square technique and a panel multi-layer perceptron (MLP) neural network. Findings - – For the ten countries under consideration, the empirical result supports the long-run equilibrium relationship among real output, exchange rate, interest rate, and level of prices, and that the cointegration relationship implies unidirectional causality from exchange rate to real output. This result is favorable to a model that contains real output as a dependent variable and exchange rate, interest rate, and level of prices as explanatory variables. Panel-vec results indicate no evidence of short-run causality from exchange rate to real output. Furthermore, the comparison result of long-run equation estimation shows the superiority of neural networks over econometric models. Originality/value - – This paper adds to the literature by examining the financial cointegration using a panel model that contains real exchange rate, interest rate, real output, and inflation rate in ASEAN+5. Additionally this paper applied the MLP neural network to yield a robust estimation of the long-run equation obtained among the variables.