5. Result of Estimation
5.1 Findings
In the first step, the Fixed Effect Model and Random Effect Model of the panel data are conducted to analyse the influence of economic variables such as exchange rate, GDP, domestic credit, interest rate, and price level to balance of payment. Table 5.1 shows the result of Fixed Effect Model, Random Effect Model, and Hausman test.
Table 5.1. Estimation results of balance of payment: Fixed Effect Model vs. Random Effect Model Balance of payment
Constant -108 41.10
(0.0006)*** (0.0167)**
Exchange rate 129 93.30
(0.0153)** (0.0000)***
GDP -0.10 0.051
(0.0510)* (0.0019)***
Domestic credit 0.19 0.324
(0.0000)*** (0.0000)***
Interest rate 3.29 -2.97
(0.0750)* (0.0049)***
Price level 1.24 -0.39
(0.0004)*** (0.0090)***
Observation 84 84
F statistic 99.91 23.67
(Prob) F statistic (0.0000)*** (0.0000)***
Adjusted R-square 0.92 0.58
Hausmant Test
Chi-square statistic 352.866384
Probability (0.0000)***
Chi-square df 5
Note:
* significance at 10% level
** significance at 5% level
*** significance at 1% level
According to Table 5.1, column (1) and (2) show the regression estimation of the relevant economic variables on balance of payment. The Hausman test result shows
that the number of chi-square statistic is 352.86 and the number of chi-square table is 15.09. The chi-square table result is based on the α = 5%, df = k= 5, and the total of observation number = 84. Hence, this research concludes that the number of chi-square statistic > chi-square table. It means that this research should reject H0 or, in other words, the best result is Fixed Effect Model.
Hausman test shows that H0 hypothesis of random effect model is rejected.
Moreover, the fixed effect model in column (1) has an adjustment R-square value of 0.92 which is greater than 0.58 in the random effect model. Both results show that the use of fixed effect model is more appropriate for the estimation of the six ASEAN countries.
From column (1) exchange rate variable has a positive and significant coefficient. It means that a decrease in exchange rate will lead to a decrease in balance of payment on the ceteris paribus assumption. Therefore, the positive effect of exchange rate variable on balance of payment is consistent with Keynesian approach.
Variable of GDP has a negative and significant coefficient. It means that an increase in GDP will lead to a decrease in balance of payment on the ceteris paribus assumption. Therefore, variable of GDP has a negative and significant influence on the balance of payment. This is consistent with Keynesian approach. Variable of domestic credit has a positive and significant coefficient. It means that an increase in domestic credit will lead to an increase in balance of payment on the ceteris paribus assumption.
This finding, however, is not consistent with both Keynesian approach and Monetary approach. Interest rate variable has a positive and significant coefficient. It means that an increase in interest rate leads to an increase in balance of payment on the ceteris paribus assumption. This finding is consistent with the Keynesian approach. Price variable has a positive and significant coefficient. It means that an increase in price leads to an increase in balance of payment on the ceteris paribus assumption. This finding, however, is consistent with the Monetary approach.
Table 5.2 shows the robustness test with other control variables in Fixed Effect Model. Column (3) shows the influence of economics variables and political stability to balance of payment in Fixed Effect Model. Column (4) shows the influence economics variables and government’s consumption expenditure to balance of payment in Fixed Effect Model. Then, column (5) shows the influence economics variables and two control variables to balance of payment in Fixed Effect Model.
According to regression result of Table 5.2, each of the exchange rate variable on the column (3), (4) and (5) has a positive coefficient and significant to influence balance of payment variable, and this finding is still consistent with Keynesian approach. This research finding is also similar to the finding of Duasa (2004). Her research suggested that exchange rate has a negative and significant influence on balance of payment. However, this finding is not similar to the finding of Ismalia (2005) who found that exchange rate has a positive and significant influence on balance of payment in both short and long terms, and Tijani (2014) found that exchange rate is insignificant to balance of payment.
Each variable of GDP on the column (3), (4) and (5) has a negative coefficient.
However, only coefficient of column (4) that deems significant to influence balance of payment and consistent to Keynesian approach, while the coefficient of column (3) and column (5) are not significant. The reason is because in the six ASEAN counties, almost every country has adopted budget deficit. Therefore, they are more focused to use their GDP for paying their state debts and the debts interest. In addition, some countries also use their GDP for paying their civil servant salary and use as the capital for building domestic infrastructures. This finding is similar to the finding of Duasa (2004) who found that GDP has a negative and significant influence on balance of payment.
However, this finding is not similar to the findings of Fleermuys (2005), of Adamu (2007) in both within-country result and cross-country effect, of Umer, et.al (2010) in the short term and of Tijani (2014). Their finding suggested that GDP has a positive and significant influence on balance of payment.
Each variable of domestic credit on column (3), (4) and (5) has a positive coefficient and significant. This finding is still not consistent with both Keynesian and Monetary approaches, because domestic credit almost in these six ASEAN countries is more distributed to production credit than consumption credit, particularly as investment credit and working capital credit. Hence, an increased domestic credit leads to an increase in capital of production sectors. In the assumption of fixed production cost, an increase in capital leads to an increase in quality of goods and services. Then, an increase in quality of goods and service will lead to an increase in competitive price, then it will lead to an increase in export. An increase in export leads to an increase in trade balance, hence balance of payment increases. This finding is not similar to the findings of Fleermuys (2005) in the long term, of Adamu (2007) in both within-country result and cross-country effect, and of Umer, et.al (2010) in the short term. Their
findings suggested that domestic credit has a negative and significant influence on balance of payment. Furthermore, this finding is also not similar to the finding of Tijani (2014) who found that domestic credit is insignificant to balance of payment.
Table 5.2. Robustness test with other control variables
Balance of payment
Domestic credit 0.163 0.19 0.16
(0.0001)*** (0.0000)*** (0.0003)***
Government’s consumption expenditure - 3.36 -47.08
- (0.9974) (0.962)
* significance at 10% level
** significance at 5% level
*** significance at 1% level
Each variable of interest rate on the column (3), (4) and (5) has a positive coefficient. However, only coefficient of column (4) that shows significant to influence balance of payment and consistent to Keynesian approach, while the coefficient of column (3) and column (5) are not significant. The reason is because high interest rate in some countries in those six in ASEAN countries leads to a decrease in real sector. A decrease in real sector leads to a decrease in import as the impact of a decrease in income. A decrease in real sector also will lead to a decrease in export as the impact of an increase in financing in production sector. Therefore, when the two effects of a
decrease in real sector offsetting each other as the impact of high interest rate, it will lead to an unchanged balance of payment. This finding is similar to the finding of Fleermuys (2005) in both short and long term and of Ismalia (2015). Their findings suggested that interest rate is insignificant to balance of payment. However, this is not similar to the findings of Duasa (2004), of Adamu (2007) and of Umer, et.al (2010) in the short term. Their findings suggested that interest rate has a negative and significant influence on balance of payment.
Each price level variable on column (3), (4) and (5) has a positive coefficient and significant. This finding is still consistent with Monetary approach. However, this finding is not similar to the finding of Duasa (2004) who found that price level has a negative and significant influence on balance of payment.
Each variable of political stability on column (3) and (5) has a negative coefficient and significance at 5 %. Therefore, this research concludes that the variable of political stability has a negative and significant influence on balance of payment variable. The reason is because political instability means that some countries in those six ASEAN are likely to improve strict capital control to safeguard them from external shock that can disturb their foreign reserves. This finding is not similar to the finding of Ali, et.al (2008) who found that an increase in political stability leads to an increase in balance of payment.
Government’s consumption expenditure variable on column (4) has a positive coefficient, while on column (5) has a negative coefficient. However, those coefficients are not significant. The reason is because the allocation of government expenditure in some ASEAN countries is allocating more for paying the prime of state foreign debts and its debt interest, subsidy, and domestic social assistance. Therefore, this condition leads to unchanged balance of payment situation. This finding is not similar to the research finding of Brown and Bidemi (2015) who found that government expenditure has a negative and significant influence on balance of payment.
Chapter 6
Conclusion and Policy Implication
This research examines the determinant factors of balance of payment in six ASEAN countries during the period of 2002 to 2005 using Keynesian and Monetary approach to balance of payment theory. The regression model is conducted by the use of economic variables and control variables as independent variable and balance of payment as a dependent variable. Hausman test is in favor of the Fixed Effect Model.
Then, the regression results of the fixed effect model shows that Keynesian approach is more appropriate in the case of ASEAN countries. The reason is because the financial sectors in ASEAN countries economies are inflexible and susceptible to pressure.
Besides, there is a strict capital control in some of those six ASEAN countries.
Therefore, the government and monetary authorities need a policy to maintain the equilibrium of balance of payment in the long run under flexible financial market and perfect capital mobility.
To conclude, this thesis identifies the policy implication for the government and monetary authorities in six ASEAN countries. To begin with, those respective countries should adopt combination policy among expansionary fiscal and contractionary monetary policy. Expansionary fiscal policy is a government policy to increase government spending or a tax cut. The aim of this policy is to push output and to recover the economy condition of a country, while, contractionary monetary policy is a government or central bank policy through monetary policy instruments to reduce money supply. The combination among expansionary fiscal and contractionary monetary policy is very efficient in generating adequate capital mobility in order to maintain the stability of balance of payments in the long run.
The combination policy among expansionary fiscal policy and contractionary monetary policy will lead to an increase in the interest rate and unchanged in income.
An increase in interest rate, then, will lead to an increase in capital inflow. An increase in capital inflow leads to an increase in international reserve then leads to an increase in balance of payment. The use of expansionary fiscal policy and contractionary monetary policy is supported by Duasa (2004) in the case of maintain balance of payment in Malaysia and Fleermuys (2005) in the case of maintain balance of payment in Namibia.
Bibliography
Adamu, Patricia A. (2007). Balance of payment adjustment: The west African monetary zone experience. Journal of Monetary and Economic Integration, 10(2), 100-116.
Akpansung, Aniekan O. (2013). A review of empirical literature on balance of payments as a monetary phenomenon. Journal of Emerging Trends in Economics and Management Sciences,4(2), 124-132.
Ali, Arfan, Shukui, Tan,Selvarathnam, Santhirasegaram, Xiaolin, Xu & Sabor, Abdul.
(2008). Political stability and balance of payment: An empirical study in Asia.
American Journal of Applied Sciences, 5(9), 1149-1157.
Bird, Graham. (1981). Balance of payment stabilisation in developing countries. Odi
Working paper, 5. Retrieved from:
https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/6831.pdf
Blanchard, Oliver & Johnson, David. (2013). Macroeconomics (6rd ed.) London:
Pearson.
Brown, Denis, & Bidemi, Joseph. (2015). Fiscal policy measures and balance of payments in Nigeria. Journal of Global Economics, 3(4), 1-6.
Daniels, Joseph & VanHose, David. (2005). International monetary and financial Economics (3rd ed.) New York: Mc Graw Hill.
Dornbusch, Rudiger & Standley Fischer. (1995). Macroeconomics (6th ed.) United States of America: Thomson Shouth-Western.
Duasa, Jarita. (2004). The Malaysian balance of payments: Keynesian Approach Versus
Monetary Approach. Retrieved from http://econpapers.repec.org/paper/scescecf4/26.htm
Dullien, Sebastian, Kotle, Detlef J., Marques, Alejandro, Priewe Jan. (2010). The financial and economic crisis of 2008-2009 and developing countries. New York: United Nations.
Fleermuys, FN (2005). The balance of payments as a monetary phenomenon: An econometric study of Namibia. Dea Research Discusion Paper, 72. Retrieved from: http://www.the-eis.com/data/RDPs/RDP72.pdf
Froyen, Richard T. (1996). Macroeconomics: Theory and policies (5th ed.). United States of America: Prentice-Hall.
Gujarati, Damodar. (2003). Basic econometrics (4th ed.). New York: Mc Graw Hill.
Ismalia, Mohammed, & Imoughele, Lawrence.E. (2015). Monetary policy and balance of payment stability in Nigeria. International Journal of Academic Research in Public Policy and Governance, 2(1), 1-15.
Iyoboyi, Martins. (2014). Impact of exchange rate depreciation on the balance of payments: Empirical evidence of Nigeria. Research Article, Cogent Economics
and Finance, 2. Retrieved from:
http://www.tandfonline.com/doi/full/10.1080/23322039.2014.923323
Keyle, John. F. (1976). The balance of payment in a monetary economy. United Kingdom: Princeton University Press.
Mankiw, N. Gregory., & David Romer. (eds). (1991). New Keynesian economics volume 1: Imperfect competition and sticky prices. London. England: The MIT Press.
Masdjojo, Gregorius, N. (2008). Study of Keynesian approach and Monetary approach to the international reserve dynamics: Empirical study in Indonesia during the period of 1983-2008. Dissertation. Semarang, Indonesia: Diponegoro University.
Nopirin. (1999). International economics. Yogyakarta, Indonesia: BPFE Yogyakarta.
Tijani, Julius. O. (2014). Monetary policy and balance of payment stability in Nigeria.
Medditeranean Journal of Social Science, 5(14). 67-76.
Umer, Muhammad, Muhammad, Sulaiman. D., Abro, Alif Asif, Sheikh, Qurrra-Tul-Ain Ali., & Ghazali,Ahmad. (2010). The balance of payments as a monetary phenomenon: Econometric evidence from Pakistan. International Research Journal of Finance and Economics, 32, 210-219.
Widarjono, Agus. (2007). Econometrics: Theory and application (3rd ed.). Yogyakarta, Indonesia: Ekanesia.
Wright, David McCords. (1961). The Keynessian system. New York City: Fordham University Pers.
Appendix
Fixed Effcet Model (1)
Dependent Variable: NFA4 Method: Panel Least Squares Date: 07/12/17 Time: 10:21 Sample: 2002 2015
Periods included: 14 Cross-sections included: 6
Total panel (balanced) observations: 84
Variable Coefficient Std. Error t-Statistic Prob.
C -1.08E+11 3.01E+10 -3.577389 0.0006
EXC4 1.29E+11 5.21E+10 2.484501 0.0153
GDP2 -0.103725 0.052268 -1.984482 0.0510
DOM_CRED 0.191853 0.039687 4.834135 0.0000
INTER 3.29E+09 1.82E+09 1.806003 0.0750
CPI 1.24E+09 3.33E+08 3.715642 0.0004
Effects Specification
Cross-section fixed (dummy variables)
R-squared 0.931908 Mean dependent var 5.56E+10 Adjusted R-squared 0.922580 S.D. dependent var 4.24E+10 S.E. of regression 1.18E+10 Akaike info criterion 49.34197 Sum squared resid 1.02E+22 Schwarz criterion 49.66029 Log likelihood -2061.363 Hannan-Quinn criter. 49.46993 F-statistic 99.90777 Durbin-Watson stat 0.420742
Prob(F-statistic) 0.000000
Random Effect Model (2)
Dependent Variable: NFA4
Method: Panel EGLS (Cross-section random effects) Date: 07/12/17 Time: 11:27
Sample: 2002 2015 Periods included: 14 Cross-sections included: 6
Total panel (balanced) observations: 84
Swamy and Arora estimator of component variances
Variable Coefficient Std. Error t-Statistic Prob.
C 4.11E+10 1.68E+10 2.446912 0.0167
EXC4 9.33E+10 8.84E+09 10.55536 0.0000
GDP2 0.050962 0.015853 3.214775 0.0019
DOM_CRED 0.323819 0.023562 13.74325 0.0000
INTER -2.97E+09 1.03E+09 -2.894210 0.0049
CPI -3.85E+08 1.44E+08 -2.678331 0.0090
Effects Specification
S.D. Rho
Cross-section random 0.000000 0.0000
Idiosyncratic random 1.18E+10 1.0000
Weighted Statistics
R-squared 0.602765 Mean dependent var 5.56E+10 Adjusted R-squared 0.577302 S.D. dependent var 4.24E+10 S.E. of regression 2.76E+10 Sum squared resid 5.93E+22 F-statistic 23.67150 Durbin-Watson stat 0.078353
Prob(F-statistic) 0.000000
Unweighted Statistics
R-squared 0.602765 Mean dependent var 5.56E+10 Sum squared resid 5.93E+22 Durbin-Watson stat 0.078353
Hausman Test
Correlated Random Effects - Hausman Test Equation: EQ01
Test cross-section random effects
Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.
Cross-section random 352.866384 5 0.0000
** WARNING: estimated cross-section random effects variance is zero.
Cross-section random effects test comparisons:
Variable Fixed Random Var(Diff.) Prob.
GDP2 -0.103725 0.050962 0.002481 0.0019
DOM_CRED 0.191853 0.323819 0.001020 0.0000
INTER 3292640995.0
Cross-section random effects test equation:
Dependent Variable: NFA4 Method: Panel Least Squares Date: 07/12/17 Time: 11:27 Sample: 2002 2015
Periods included: 14 Cross-sections included: 6
Total panel (balanced) observations: 84
Variable Coefficient Std. Error t-Statistic Prob.
C -1.08E+11 3.01E+10 -3.577389 0.0006
EXC4 1.29E+11 5.21E+10 2.484501 0.0153
GDP2 -0.103725 0.052268 -1.984482 0.0510
DOM_CRED 0.191853 0.039687 4.834135 0.0000
INTER 3.29E+09 1.82E+09 1.806003 0.0750
CPI 1.24E+09 3.33E+08 3.715642 0.0004
Effects Specification
Cross-section fixed (dummy variables)
R-squared 0.931908 Mean dependent var 5.56E+10 Adjusted R-squared 0.922580 S.D. dependent var 4.24E+10 S.E. of regression 1.18E+10 Akaike info criterion 49.34197 Sum squared resid 1.02E+22 Schwarz criterion 49.66029 Log likelihood -2061.363 Hannan-Quinn criter. 49.46993 F-statistic 99.90777 Durbin-Watson stat 0.420742
Prob(F-statistic) 0.000000
Fixed Effect Model (3)
Dependent Variable: NFA4 Method: Panel Least Squares Date: 07/12/17 Time: 11:29 Sample: 2002 2015
Periods included: 14 Cross-sections included: 6
Total panel (balanced) observations: 84
Variable Coefficient Std. Error t-Statistic Prob.
C -1.03E+11 2.94E+10 -3.518907 0.0008
EXC4 1.40E+11 5.10E+10 2.746142 0.0076
GDP2 -0.056241 0.055296 -1.017080 0.3125
DOM_CRED 0.163413 0.040767 4.008418 0.0001
INTER 2.31E+09 1.83E+09 1.260778 0.2115
CPI 1.13E+09 3.28E+08 3.445875 0.0010
POLSTAB -1.04E+10 4.71E+09 -2.206281 0.0306
Effects Specification
Cross-section fixed (dummy variables)
R-squared 0.936220 Mean dependent var 5.56E+10 Adjusted R-squared 0.926476 S.D. dependent var 4.24E+10 S.E. of regression 1.15E+10 Akaike info criterion 49.30036 Sum squared resid 9.52E+21 Schwarz criterion 49.64762 Log likelihood -2058.615 Hannan-Quinn criter. 49.43995 F-statistic 96.07985 Durbin-Watson stat 0.412347
Prob(F-statistic) 0.000000
Fixed Effect Model (4)
Dependent Variable: NFA4 Method: Panel Least Squares Date: 07/12/17 Time: 11:31 Sample: 2002 2015
Periods included: 14 Cross-sections included: 6
Total panel (balanced) observations: 84
Variable Coefficient Std. Error t-Statistic Prob.
C -1.08E+11 3.44E+10 -3.128147 0.0025
EXC4 1.29E+11 5.55E+10 2.330694 0.0226
GDP2 -0.103706 0.052918 -1.959745 0.0539
DOM_CRED 0.191809 0.042059 4.560482 0.0000
INTER 3.29E+09 1.84E+09 1.789487 0.0777
CPI 1.24E+09 3.36E+08 3.687622 0.0004
GS 3360694. 1.01E+09 0.003330 0.9974
Effects Specification
Cross-section fixed (dummy variables)
R-squared 0.931908 Mean dependent var 5.56E+10 Adjusted R-squared 0.921505 S.D. dependent var 4.24E+10 S.E. of regression 1.19E+10 Akaike info criterion 49.36578 Sum squared resid 1.02E+22 Schwarz criterion 49.71304 Log likelihood -2061.363 Hannan-Quinn criter. 49.50537 F-statistic 89.58108 Durbin-Watson stat 0.420721
Prob(F-statistic) 0.000000
Fixed Effect Model (5)
Dependent Variable: NFA4 Method: Panel Least Squares Date: 07/12/17 Time: 11:32 Sample: 2002 2015
Periods included: 14 Cross-sections included: 6
Total panel (balanced) observations: 84
Variable Coefficient Std. Error t-Statistic Prob.
C -1.03E+11 3.36E+10 -3.051786 0.0032
EXC4 1.39E+11 5.43E+10 2.562021 0.0125
GDP2 -0.056474 0.055896 -1.010335 0.3158
DOM_CRED 0.164010 0.042908 3.822329 0.0003
INTER 2.30E+09 1.85E+09 1.245168 0.2172
CPI 1.13E+09 3.31E+08 3.421698 0.0010
POLSTAB -1.04E+10 4.74E+09 -2.191461 0.0317
GS -47083730 9.84E+08 -0.047860 0.9620
Effects Specification
Cross-section fixed (dummy variables)
R-squared 0.936222 Mean dependent var 5.56E+10 Adjusted R-squared 0.925443 S.D. dependent var 4.24E+10 S.E. of regression 1.16E+10 Akaike info criterion 49.32413 Sum squared resid 9.52E+21 Schwarz criterion 49.70033 Log likelihood -2058.614 Hannan-Quinn criter. 49.47536 F-statistic 86.85295 Durbin-Watson stat 0.412925
Prob(F-statistic) 0.000000
Data
Countries Years Net Foreign Asset Exchange
Rate GDP Domestic Credit Interest
Rate (%) Price Political Stability
Government's Consumption Expenditure (%) SINGAPORE 2002 $76,513,218,390.80 $0.57471 $138,821,048,771.54 $51,625,683,915.00 5.35 85.77 1.20 11.96 SINGAPORE 2003 $88,211,176,470.59 $0.58824 $144,978,217,821.78 $53,199,603,009.00 5.31 86.21 0.90 11.56 SINGAPORE 2004 $107,322,085,889.57 $0.61350 $158,822,442,244.22 $54,419,956,653.10 5.30 87.64 1.10 10.51 SINGAPORE 2005 $117,433,734,939.76 $0.60241 $170,716,905,023.84 $54,531,031,400.60 5.30 88.01 1.10 10.18 SINGAPORE 2006 $147,554,248,366.01 $0.65359 $185,842,757,609.09 $62,659,097,340.00 5.31 88.91 1.20 10.30 SINGAPORE 2007 $165,731,944,444.44 $0.69444 $202,775,870,920.43 $81,388,438,465.20 5.33 90.78 1.10 9.51 SINGAPORE 2008 $184,847,916,666.67 $0.69444 $206,400,733,406.67 $92,581,482,222.00 5.38 96.69 1.30 10.55 SINGAPORE 2009 $212,598,571,428.57 $0.71429 $205,155,335,533.55 $109,917,826,202.50 5.38 97.28 1.10 10.29 SINGAPORE 2010 $238,934,108,527.13 $0.77519 $236,421,782,178.22 $130,828,929,715.20 5.38 100.00 1.10 10.19 SINGAPORE 2011 $230,668,461,538.46 $0.76923 $251,097,543,087.64 $153,175,783,402.90 5.38 105.25 1.20 9.56 SINGAPORE 2012 $248,276,229,508.20 $0.81967 $260,313,164,649.80 $182,891,132,311.20 5.38 110.02 1.30 9.06 SINGAPORE 2013 $228,092,125,984.25 $0.78740 $272,484,048,404.84 $223,314,222,581.60 5.38 112.64 1.30 9.94 SINGAPORE 2014 $219,678,030,303.03 $0.75758 $281,367,070,040.34 $257,321,791,212.60 5.35 113.77 1.20 9.86 SINGAPORE 2015 $214,330,496,453.90 $0.70922 $287,017,968,463.51 $248,652,769,941.00 5.35 113.21 1.20 10.40 THAILAND 2002 $37,734,414,831.98 $0.02317 $239,061,299,460.76 $119,694,487,629.06 6.88 79.16 0.40 13.17 THAILAND 2003 $46,766,607,729.22 $0.02526 $256,248,205,097.28 $131,921,671,759.59 5.94 80.59 -0.20 12.93 THAILAND 2004 $53,752,176,139.27 $0.02560 $272,364,394,116.51 $133,645,927,724.43 5.50 82.81 -0.70 13.11 THAILAND 2005 $58,222,032,659.03 $0.02437 $283,770,565,333.11 $144,006,314,538.75 5.79 86.57 -0.90 13.65 THAILAND 2006 $81,750,624,133.15 $0.02774 $297,868,050,989.68 $155,841,051,197.94 7.35 90.59 -1.10 13.50 THAILAND 2007 $106,594,306,049.82 $0.02966 $314,057,455,297.12 $166,404,470,863.54 7.05 92.62 -1.20 13.93 THAILAND 2008 $118,412,320,916.91 $0.02865 $319,477,044,016.93 $176,359,821,336.16 7.04 97.68 -1.30 14.34 THAILAND 2009 $137,154,861,944.78 $0.03001 $317,118,409,570.78 $191,513,063,577.63 5.96 96.85 -1.40 15.97 THAILAND 2010 $161,989,054,726.37 $0.03317 $340,923,571,200.89 $237,258,344,513.74 5.94 100.00 -1.40 15.85 THAILAND 2011 $171,233,196,591.99 $0.03156 $343,765,791,175.47 $262,561,574,773.59 6.91 103.81 -1.10 16.14 THAILAND 2012 $161,377,734,247.47 $0.03265 $368,623,355,242.12 $312,716,098,712.79 7.10 106.94 -1.20 16.30 THAILAND 2013 $152,688,814,385.86 $0.03048 $378,583,990,657.96 $337,571,198,096.20 6.96 109.28 -1.30 16.46 THAILAND 2014 $151,427,487,864.08 $0.03034 $381,679,418,683.63 $351,410,927,041.16 6.77 111.35 -0.90 17.02 THAILAND 2015 $162,823,773,898.59 $0.02771 $392,474,592,367.69 $350,039,338,585.21 6.56 110.35 -1.00 17.25 MALAYSIA 2002 $31,622,368,421.05 $0.26316 $172,170,105,616.09 $106,937,971,024.72 6.53 83.08 0.50 12.96 MALAYSIA 2003 $38,617,105,263.16 $0.26316 $182,136,170,935.40 $104,088,702,501.69 6.30 83.90 0.50 12.97 MALAYSIA 2004 $57,350,526,315.79 $0.26316 $194,491,264,661.14 $102,746,962,942.63 6.05 85.18 0.30 12.58 MALAYSIA 2005 $58,096,825,396.83 $0.26455 $204,861,809,506.07 $118,377,550,875.85 5.95 87.70 0.50 11.47 MALAYSIA 2006 $74,537,960,339.94 $0.28329 $216,303,028,282.26 $128,853,690,557.16 6.49 90.86 0.30 11.17 MALAYSIA 2007 $87,634,441,087.61 $0.30211 $236,695,353,388.59 $138,741,287,976.07 6.41 92.70 0.20 11.57 MALAYSIA 2008 $74,324,566,473.99 $0.28902 $244,552,678,743.29 $158,337,046,865.92 6.08 97.75 0.10 11.50 MALAYSIA 2009 $84,260,233,918.13 $0.29240 $238,375,704,355.66 $174,018,035,830.98 5.08 98.32 -0.10 13.05 MALAYSIA 2010 $92,269,480,519.48 $0.32468 $255,016,609,232.87 $213,270,288,383.08 5.00 100.00 0.10 12.58 MALAYSIA 2011 $112,254,088,050.31 $0.31447 $268,516,655,800.81 $232,549,717,004.39 4.92 103.20 0.10 13.27 MALAYSIA 2012 $113,523,202,614.38 $0.32680 $283,216,292,570.86 $268,115,717,162.71 4.79 104.90 0.00 13.84 MALAYSIA 2013 $102,852,743,902.44 $0.30488 $296,507,404,302.88 $299,625,136,751.63 4.61 107.10 0.10 13.72 MALAYSIA 2014 $93,135,428,571.43 $0.28571 $314,333,923,193.94 $307,030,488,153.52 4.59 110.50 0.20 13.32 MALAYSIA 2015 $83,855,710,955.71 $0.23310 $329,952,500,698.52 $281,718,474,580.45 4.59 112.80 0.20 13.13
Countries Years Net Foreign Asset Exchange
Rate GDP Domestic Credit Interest
Rate (%) Price Political Stability
Government's Consumption Expenditure (%) INDONESIA 2002 $25,820,134,228.19 $0.00011 $491,078,136,159.83 $78,997,902,628.39 18.95 54.91 -1.60 7.26 INDONESIA 2003 $29,688,718,251.62 $0.00012 $514,553,483,744.12 $79,221,762,419.81 16.94 58.53 -2.10 8.13 INDONESIA 2004 $26,001,076,426.26 $0.00011 $540,440,020,890.98 $78,678,313,236.39 14.12 62.18 -1.90 8.32 INDONESIA 2005 $30,930,213,631.74 $0.00010 $571,204,954,434.66 $91,237,260,820.33 14.05 68.68 -1.50 8.11 INDONESIA 2006 $44,565,742,793.79 $0.00011 $602,626,663,572.80 $102,514,894,600.31 15.98 77.69 -1.40 8.63 INDONESIA 2007 $54,184,520,649.75 $0.00011 $640,863,459,320.35 $107,836,507,320.30 13.86 82.67 -1.20 8.35 INDONESIA 2008 $53,362,557,077.63 $0.00009 $679,403,088,245.17 $107,362,896,194.20 13.60 90.75 -1.10 8.42 INDONESIA 2009 $67,979,361,702.13 $0.00011 $710,851,782,010.38 $135,593,878,336.35 14.50 95.12 -0.80 9.59 INDONESIA 2010 $90,447,669,892.11 $0.00011 $755,094,160,363.07 $165,241,566,316.18 13.25 100.00 -0.90 9.01 INDONESIA 2011 $100,065,063,961.18 $0.00011 $801,681,840,622.49 $200,023,975,144.14 12.40 105.36 -0.80 9.06 INDONESIA 2012 $100,124,922,440.54 $0.00010 $850,023,661,688.38 $227,973,227,116.22 11.80 109.86 -0.60 9.25 INDONESIA 2013 $82,973,172,532.61 $0.00008 $897,261,717,986.53 $270,444,420,027.50 11.66 116.91 -0.50 9.52 INDONESIA 2014 $89,031,350,482.32 $0.00008 $942,339,151,204.16 $248,642,998,200.70 12.61 124.39 -0.40 9.43 INDONESIA 2015 $85,294,671,982.60 $0.00007 $987,514,148,527.99 $255,746,126,404.00 12.66 132.30 -0.60 9.75 PHILIPPINE 2002 $12,818,851,224.11 $0.01883 $133,678,066,448.09 $43,559,615,408.49 9.14 68.88 -0.90 10.57 PHILIPPINE 2003 $14,191,380,241.14 $0.01800 $140,322,352,579.61 $44,471,963,737.38 9.47 70.46 -1.60 10.20 PHILIPPINE 2004 $15,519,566,376.40 $0.01777 $149,720,633,578.56 $49,121,482,643.25 10.08 73.86 -1.70 9.38 PHILIPPINE 2005 $20,742,415,677.41 $0.01884 $156,873,781,583.38 $50,547,340,564.00 10.18 78.67 -1.20 9.04 PHILIPPINE 2006 $28,610,421,331.16 $0.02035 $165,098,600,285.16 $61,586,082,268.03 9.78 82.99 -1.70 9.18 PHILIPPINE 2007 $40,022,705,314.01 $0.02415 $176,022,627,371.78 $80,491,291,312.96 8.69 85.39 -1.60 9.28 PHILIPPINE 2008 $42,700,779,111.39 $0.02106 $183,332,419,607.65 $77,132,883,473.58 8.75 92.45 -1.80 8.83 PHILIPPINE 2009 $52,319,456,427.96 $0.02157 $185,437,681,530.08 $84,338,489,574.27 8.57 96.35 -1.70 9.86 PHILIPPINE 2010 $65,278,651,173.39 $0.02278 $199,590,774,784.58 $65,585,908,217.04 7.67 100.00 -1.60 9.72 PHILIPPINE 2011 $73,811,518,324.61 $0.02276 $206,895,308,421.49 $75,064,790,557.58 6.66 104.65 -1.40 9.70 PHILIPPINE 2012 $78,867,443,554.26 $0.02428 $220,723,798,225.41 $84,908,294,774.26 5.68 107.97 -1.20 10.84 PHILIPPINE 2013 $80,501,013,285.30 $0.02252 $236,315,800,036.30 $94,594,967,607.73 5.77 111.20 -1.10 10.84 PHILIPPINE 2014 $84,089,197,669.21 $0.02241 $251,010,922,600.73 $108,950,014,385.63 5.53 115.77 -0.70 10.55 PHILIPPINE 2015 $84,774,220,903.12 $0.02120 $265,833,154,133.29 $119,986,759,463.59 5.58 117.43 -0.80 10.96
BRUNEI 2002 $2,855,911,763.13 $0.55866 $12,775,897,725.92 $1,679,531,978.90 5.50 93.31 1.07 27.17
BRUNEI 2003 $3,519,871,600.57 $0.57471 $13,146,904,063.75 $1,335,049,380.15 5.50 93.59 1.14 24.07
BRUNEI 2004 $4,668,559,273.96 $0.59172 $13,213,206,317.91 $1,077,898,580.86 5.50 94.36 1.40 22.05
BRUNEI 2005 $5,194,814,083.13 $0.60241 $13,264,408,405.29 $692,477,915.53 5.50 95.53 1.25 18.41
BRUNEI 2006 $4,798,867,794.97 $0.62893 $13,847,739,967.73 $1,290,362,747.36 5.50 95.68 1.18 18.06
BRUNEI 2007 $5,391,989,431.13 $0.66225 $13,869,146,006.39 $1,499,529,933.08 5.50 96.61 1.17 22.62
BRUNEI 2008 $7,427,853,847.18 $0.70423 $13,600,124,169.25 $829,444,724.07 5.50 98.62 1.16 17.14
BRUNEI 2009 $5,915,481,133.10 $0.68966 $13,360,145,119.69 $2,273,650,505.85 5.50 99.64 1.36 23.29
BRUNEI 2010 $8,038,386,161.76 $0.73529 $13,707,370,737.07 $2,107,731,071.69 5.50 100.00 1.24 22.15
BRUNEI 2011 $12,375,384,901.59 $0.79365 $14,220,755,408.87 $866,207,967.65 5.50 102.02 1.09 18.73
BRUNEI 2012 $11,887,763,341.60 $0.80000 $14,350,568,390.17 $1,529,977,127.12 5.50 102.49 0.92 18.44 BRUNEI 2013 $11,238,017,992.00 $0.80000 $14,045,471,213.79 $2,330,458,524.26 5.50 102.88 1.08 20.16 BRUNEI 2014 $10,291,820,777.95 $0.78740 $13,715,438,210.49 $3,089,966,643.12 5.50 102.68 1.25 21.39
BRUNEI 2015 $8,183,892,260.58 $0.72993 $13,637,697,103.04 $3,841,344,040.69 5.50 102.25 1.21 25.06