U.S.-Korea Free Trade Agreement: Potential Economy-wide ... - USITC

Results
variability, which is the variance of the quarterly interest rate over the preceding three years,
should also increase NIMs because banks must compensate for increased uncertainty.
Countries that had interest rate volatility of more than two standard deviations above the
mean were excluded. Cases of extreme interest rate volatility occurred in countries
experiencing hyperinflation over the period. The GATS score variable is described above.
Credit rating, which measures perceived credit worthiness, is a score assigned to a country
by the trade publication Institutional Investor and reported in the Global Competitiveness
Report. 19 It should have a negative relationship with NIMs because a higher score indicates
a less risky country. The tax rate is defined as the average taxes paid by banks divided by
pretax profits, and is expected to have a positive sign. As corporate tax rates rise, banks have
to adjust by increasing their NIMs. GDP per capita should have a negative effect on NIMs,
because as personal incomes rise, the supply of banking services provided should increase,
thereby reducing NIMs. In addition to Bankscope, data for these variables were obtained
from the Global Competitiveness Report, the IMF, and the World Bank.
In order to test for stability of the model across time, results for 2 years were estimated. For
the first stage reported in table H-1, all the prudential and firm-level measures were of the
expected sign and statistically significant with similar coefficients reported in both years.
The adjusted R 2 s for the first stage were 0.74 and 0.76 for 1999 and 2005, respectively,
meaning approximately three-quarters of the variation in NIMs between firms were
accounted for by prudential regulations and noninterest operating expenses. For the second
stage reported in table H-2, interest rate variability and tax rate were positive and statistically
significant, consistent with previous studies. Market share was found to have a negative
relationship with pure spreads, indicating the presence of economies of scale. This effect was
only significant in 2005, however. A number of other variables were also found to be
significant in one year and not the other. The GATS scores were positive and statistically
significant, signifying an increase in the GATS score will increase pure spreads. Critically,
however, the GATS scores between the two years were statistically close, 20 and the estimated
results of the model as a whole were quite similar. 21 From these results, TEs were generated
using equation (1). 22 As noted above, these TEs represent how much higher a given country’s
average NIM is versus what the NIM would be if no trade restrictions existed.
The TEs for Korea were estimated, first using the GATS scores for 1999 and 2005
respectively, and then by substituting the U.S.-Korea FTA score for the GATS score in the
TE equation. The estimated TE for Korea under the GATS was 76 percent for 1999 and
59 percent for 2005, whereas the TE estimated from the FTA was 29 percent, a decline of
19 World Economic Forum, “The Global Competitiveness Report,” 2000, 296; and World Economic
Forum, “The Global Competitiveness Report,” 2005, 498.
20 To test this, the data for the 2 years were pooled and the same model was run with the inclusion of a
year dummy variable and an interaction term between the year dummy variable and the GATS score. The
coefficient on this interaction term was not statistically significant, indicating that the GATS score was
relatively stable over time.
21 Pure spreads were estimated using 2005 data and the coefficients estimated from the second stage of the
1999 and 2005 models respectively. These pure spreads were found to have a correlation coefficient of 0.80,
indicating that the predictive power of the model is relatively strong.
22 In order to hold all other factors constant aside from changes in trade policy, the calculation of all the
TEs was performed using the 2005 GATS coefficient.
H-7