exports)/GDP. Imports and exports data come from the IFS 2008. Government final consumption expenditure (FCE) as percentage of GDP and terms of trade (TOT) obtained from World Development Indicators (online version 2008). The series for excess money growth (EXMGR) is constructed as the difference between growth rate of M2 and GDP, both of which are derived from WDI database. The variable excess money growth is used for future inflation to observe the macroeconomic consistency among the countries of analysis. 2) Methodology and Model SpecificationThe static as well as dynamic panel models for fixed effects of the real exchange rate using panel data for six selected Asian countries are examined. The static analysis refers to some kind of movement in which speed is constantly maintained i.e. studies focused on particular period of time. It is similar to taking a photo when you press the button for a shot then the photo is just at a particular point of time. Does that situation will remain there for long? Is there any force that can push the movement towards equilibrium or disequilibrium one? This question cannot be answer by static analysis. In dynamic economic the study of time path of variable is to see whether the variable will converge to a point which we call stable or steady state or will it diverge. Dynamic
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58Dutch Disease Investigated: Empirical Evidence from Selected South-East Asian Economies analysis allows us to see the path of variable how the variables change with time. It helps us to see whether the equilibrium will be reached or not. Different techniques have been used to estimate equation for different forms of foreign inflows which influence the real exchange rate. The objective is to analyze the “Dutch Disease” effects. The econometric analysis suggest various problems while using Static panel model fixed effects (within) estimator and dynamic panel using generalized method of moments (GMM) estimator to analyze the impact of foreign inflows on real exchange rate as a first step. Endogeneity and hetroskedasticity and identification are important in this regard. The problem of endogeneity occurs when the independent variable is correlated with the error term in a regression model. This implies that the regression coefficient in an OLS regression is biased. It is more worthy to mention that GMM and Two stages least squares (TSLS) are better techniques in the presence of endogeneity. This implies that the regression coefficient in an OLS regression is biased. There are many methods of overcoming this, including instrumental variable regression and Heckman selection correction. Hetroskedasticity is in fact about differing variances; its presence does not lead to inconsistency problems. Standard instrumental variable may be preferable in the presence of hetroskedasticity (Baum et al 2002).An identification problem may arise if some of the explanatory variables are correlated with the error term. For example, in the presence of risk-sharing strategies among distant family members, a drought will
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