log_RER 37 -6.99 0.11 -7.25 -6.83 GDP_growth 37 3.91 2.24 -1.90 7.40 GDP_growth_season 37 0.91 0.93 -3.30 2.80 inflation 37 0.74 0.53 -0.32 2.06 M2_growth 37 1.97 0.89 -0.08 4.42 cd 37 3.82 0.99 2.41 5.69 Libor 37 2.21 1.98 0.26 5.44 interest_differential 37 1.60 1.40 -0.83 3.29 soveriegn_credit_rating 37 14.89 0.46 14.00 16.00 commodity_price_growth 37 1.46 11.40 -50.99 13.70 Figure 1. Plot of variables Table 2. Correlation capital_flow inflow_measures log_VIX commodity_ price_growth capital_flow 1 inflow_measures 0.1838 1 log_VIX -0.5692 -0.0775 1 commodity_ price_growth 0.665 0.2075 -0.4929 1 Figure 1 is plot of time series of capital flow, CFMs, and global push factors. It is hard to see association between capital inflow and inflow policy through the plot. Also correlation analysis shows that they have positive correlation (0.1838). It is conflicting to the expectation that CFMs reduces capital inflow. International commodity price growth and capital inflow to Korea show similar dynamics as shown in correlation analysis in Table 2 where they are positively correlated (coefficient is 0.665). Also, log of VIX index have negative correlation. VIX is high during stop” period of end-2008 and end-2010. “sudden 4. Empirical analysis We employ following OLS regression model to analyze role of capital flow management policies (CFMs) in terms of reducing impact of push factor on capital inflow. X denotes global push factors and Z denotes domestic pull factors. We expect to be opposed-sign of which indicates that CFMs reduce impact β* β,
log_RER 37 -6.99 0.11 -7.25 -6.83 GDP_growth 37 3.91 2.24 -1.90 7.40 GDP_growth_season 37 0.91 0.93 -3.30 2.80 inflation 37 0.74 0.53 -0.32 2.06 M2_growth 37 1.97 0.89 -0.08 4.42 cd 37 3.82 0.99 2.41 5.69 Libor 37 2.21 1.98 0.26 5.44 interest_differential 37 1.60 1.40 -0.83 3.29 soveriegn_credit_rating 37 14.89 0.46 14.00 16.00 commodity_price_growth 37 1.46 11.40 -50.99 13.70 Figure 1. Plot of variables Table 2. Correlation capital_flow inflow_measures log_VIX commodity_ price_growth capital_flow 1 inflow_measures 0.1838 1 log_VIX -0.5692 -0.0775 1 commodity_ price_growth 0.665 0.2075 -0.4929 1 Figure 1 is plot of time series of capital flow, CFMs, and global push factors. It is hard to see association between capital inflow and inflow policy through the plot. Also correlation analysis shows that they have positive correlation (0.1838). It is conflicting to the expectation that CFMs reduces capital inflow. International commodity price growth and capital inflow to Korea show similar dynamics as shown in correlation analysis in Table 2 where they are positively correlated (coefficient is 0.665). Also, log of VIX index have negative correlation. VIX is high during “sudden stop” period of end-2008 and end-2010. 4. Empirical analysis We employ following OLS regression model to analyze role of capital flow management policies (CFMs) in terms of reducing impact of push factor on capital inflow. X denotes global push factors and Z denotes domestic pull factors. We expect β* to be opposed-sign of β, which indicates that CFMs reduce impact
20150628_0600441.docx