Estimation Model

This research uses regression model based on Keynesian and Monetary approach in which balance of payment is selected as the dependent variable and exchange rate, GDP, domestic credit, interest rate and price level are the independent economic variables. This model is adopted from Tijani (2014). In his work, Tijani develops a simple OLS regression model at level value and takes into account variables of exchange rate, inflation rate, trade balance, domestic credit, and GDP. This study also uses level value but only takes into account, variables of exchange rate, GDP, interest rate, domestic credit, price level, political stability and government’s

consumption expenditure, using panel data analysis technique. Furthermore, this research is conducted as follows: First, we examine the influence of relevant economic variables balance of payment. Second, we test the robustness of the economic variables with the two control variables, political stability and the size of government by government’s consumption expenditure. Then, the empirical model can be written as;

NFA it= β1 Exch it + β2 GDP it + β3 DC it + β4 i it + β5 CPI it + β6 Polstab it +β7 GSit

+ μt ··· (3.3) Where:

NFA = net foreign asset Exch = exchange rate

GDP = gross domestic product DC = domestic credit

i = interest rate

CPI = consumer price index Polstab = political stability

GS = government’s consumption expenditure μt = error term

Chapter 4

The Background of Research Variables

4.1. Balance of Payment in Six ASEAN Countries

Balance of payment performance in six ASEAN countries shows an increasing trend in almost all of those countries during 2002 to 2012. According to Figure 4.1, Singapore has the biggest balance of payment position in those periods, followed by Thailand in the second position, Malaysia in the third position, Indonesia in the fourth position, the Philippines in the fifth position and Brunei Darussalam in the sixth position. Overall, the trend of balance of payment shows the resiliency of the domestic economy to external fluctuation, especially the impact of the global crisis economy in 2008. Improvement in the performance of trade balance and capital account is the main factor. High export growth and diversified export destination markets to some Asian countries as well as the characteristics of the export products and the value of the exchange rate in ASEAN region which remains competitive contribute to balance of payment improvement. In addition, the global economic fluctuation directly affects the dynamics of capital and financial transactions, particularly foreign portfolio investments that records surpluses in some countries such as Malaysia and Singapore (see Figure 1.2). However, starting from 2013 to 2014, balance of payments in some countries was decreasing such as in Thailand, Indonesia, the Philippines and Brunei Darussalam. In Indonesia, a decrease in balance of payment is due to an increase in import that leads to trade balance deficit and an increase in capital outflow due to improvement of economic condition in European and American countries after the crisis. In Thailand, a decrease in balance of payments is because the flooding in 2012 disturbed the domestic economics and hence led to a decrease in export. In Malaysia, a decrease in balance of payment is due to an increase in capital outflow as the reaction to uncertainty to the rate of US Federal Reserve bond purchases program. In Brunei Darussalam, a decrease in balance of payments is due to a decrease in the number of oil exports. In 2015, balance of payment in those six countries have increased again because of improvement in domestic economic condition.

Figure 4.1. Balance of payment in six ASEAN countries Data source: World Bank website (2017)

4.2. Exchange Rate in Six ASEAN Countries

Generally, an increase or decrease in exchange rate in ASEAN countries is influenced by the international trade of each country. In addition, the exchange rate of Brunei Darussalam and Singapore has equality of value. Both Brunei Darussalam and Singapore have signed a Currency Interchangeability Agreement since 1967 in which Brunei dollar is accepted in Singapore as "customary tender" and, likewise, Singapore dollar is accepted for payments in Brunei Darussalam.¹ As a result, the exchange rate of Singapore and Brunei increased as much as US$ 0.00691 from 2008 to 2009, while in Malaysia, it increased as much as US$ 0.00750 from 2008 to 2009. In Thailand, the exchange rate increased as much as US$ 0.000691 from 2008 to 2009, and in Indonesia it increased as much as US$ 0.000009 from 2008 to 2009. Then, in the Philippines, the exchange rate increased as much as US$ 0.000513 from 2008 to 2009.

1 Monetary Authority of Singapore. "The Currency Interchangeability Agreement". Retrieved July 8, 2017.

Figure 4.3. Exchange rate in six ASEAN countries Data source: IMF website, World Bank website (2017)

4.3. GDP in Six ASEAN Countries

According to Figure 4.3, the GDP in six ASEAN countries has shown a positive trend during the period of 2002 to 2015, in which Indonesia’s GDP is on the first position and Thailand’s GDP is on the second position. However, in 2009, there were a decrease in GDP of some countries such as Singapore, Thailand, Malaysia, and Brunei Darussalam due to the impact of global economy crisis. In Singapore, the GDP decreased to US$ 1.245 million from 2008 to 2009 and in Thailand it decreased as many as US$ 2.358 million. In Malaysia, the GDP decreased to the point of US$ 6.176 million and in Brunei Darussalam it decreased to US$ 329 thousand. A different situation was undergoing in Indonesia and the Philippines, in which the GDP in these two countries were increasing. In Indonesia, the GDP increased to US$ 31.448 million, and in the Philippines, it increased to US$ 2.105 million. In 2015, the GDP of Brunei Darussalam decreased to the point of US$ 77,000 as the impact of the decrease in oil export.

Export is the one of the sectors that produces GDP. In some countries, such as Singapore, Malaysia, Thailand, and Brunei Darussalam, export is the crux of their economy. In Singapore, manufacturing export is the most important factor in determining their GDP, while in Malaysia, the GDP is crutched by manufacturing export and agricultural export. In Thailand, the GDP is crutched by agricultural export, while in Brunei Darussalam oil export is the most important factors to determine GDP.

However, the GDP in Indonesia and the Philippines is crutched more by consumption sector.

$0.000000

$0.100000

$0.200000

$0.300000

$0.400000

$0.500000

$0.600000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

EXCHANGE RATE

Singapore Thailand Malaysia Indonesia Philippine Brunei

Figure 4.3: GDP in six ASEAN countries Data source: World Bank website (2017)

4.4. Domestic Credit in Six ASEAN Countries

Figure 4.4 shows that domestic credit shares in almost all countries under studies have positive trend during the period of 2002-2015. The domestic credit of Thailand increased on an average of US$ 21.776 million from 2004 to 2014 and was distributed in service sectors, particularly in professional services industry as working capital credit. In Malaysia, the domestic credit increased on an average of US$ 20.248 million from 2004 to 2014 and was distributed to agricultural sector, particularly in the crude and palm oil industry as working capital credit. In Singapore, the domestic credit increased on an average of US$ 20.290 million from 2004 to 2014 and was distributed to the real estate sector as investment credit. Then, in Indonesia the domestic credit increased on an average of US$ 16.996 million from 2004 to 2014 and was distributed to trade sector, particularly on thesmall and medium-sized micro industries as working capital credit. In the Philippines, the domestic credit increased on an average of US$

5.982 million from 2004 to 2014 and was distributed among real estate, manufacturing, information and communication sectors as investment credit. In Brunei Darussalam, the domestic credit increased on average as much as US$ 201.206 thousand.

Figure 4.4. Domestic credit in six ASEAN countries Data source: World Bank (2017)

4.5. Interest Rate in Six ASEAN Countries

In some ASEAN countries, the lending interest rate is still high. The reason is due to banking inefficiency and a high fund cost, high inflation, high risk of legal uncertainty, legal compliance costs and corporate governance, high concentration in banking industry structure, and high concentration in the deposit market.² Figure 4.5 shows the interest rate in six ASEAN countries during the period 2002 to 2015.

According to Table 4.5, Indonesian interest rate was the highest in comparison with other ASEAN countries during the period 2002 to 2015. From 2002 to 2015, the average of Indonesian interest rate was 14.02 percent, in which on 2002 recorded the highest interest rate as many as 18.95 percent and in 2013 recorded the lowest interest rate as many as 11.66 percent. The interest rate of Philippines is at the second position.

The average of the Philippines interest rate from 2002 to 2015 was 7.96 percent, in which in 2005 recorded the highest interest rate as many as 10.18 percent and in 2013 recorded the lowest interest rate as many as 11.8 percent. Thai interest rate is at the third position. The average of Thai interest rate from 2002 to 2015 was 6.55 percent, in which in 2006 recorded the highest interest rate as many as 7.35 percent and in 2004 recorded the lowest interest rate as many as 5.5 percent.

2 Asosiasi Pengusaha Indonesia. “Policy brief apindo: Tingginya suku bunga kredit perbankan  Indonesia”. (2016). http://apindo.or.id/id/press/read/policy‐brief‐apindo‐tingginya‐suku‐bunga‐

kredit‐perbankan‐indonesia Retrieved July 10, 2017. 

Figure 4.5. Interest rate in six ASEAN countries Data source: World Bank website (2017)

4.6. Price Level in Six ASEAN Countries

According to Asian Development Bank, an increase in the price level in some ASEAN countries is mainly due to the increase in fuel price and an increase in staple food price.³ According to Figure 4.5, Indonesia had the highest increase in price level during 2013 to 2015. The consumer price index is increasing as many as 15.39 index during the period of 2013 to 2015. The reason was due to the revocation of fuel subsidies by Indonesian government which brought an impact over the increase in staple food price. In the Philippines, the consumer price index was increasing as many as 6.23 index during the period of 2013 to 2015 because of an increase in fuel price. In Singapore, the consumer price index was increasing as to the 0.57 index during the period of 2013 to 2015 because of an increase in price in energy, food, and commodity sectors. Consumer price index of Thailand increased as many as 2.34 index during 2013 to 2014 due to the flood they suffered in 2012 that led to an increase in staple food price.

In Malaysia, the consumer price index increased as many as 5.7 index during 2013 to 2015 because of an increase in staple food price.

3 BBC Indonesia. com.” Laju inflasi ancam Asia”. (2008).

http://www.bbc.co.uk/indonesian/news/story/2008/06/printable/080615_asia_inflation.shtml Retrieved July 10, 2017.

0 2 4 6 8 10 12 14 16 18 20

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Interest Rate

Singapore Thailand Malaysia Indonesia Philippine Brunei

Figure 4.6: Price in six ASEAN countries Data source: World Bank website (2017) 0

20 40 60 80 100 120 140

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Price Level

Singapore Thailand Malaysia Indonesia Philippine Brunei

Chapter 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

Government’s consumption expenditure variable on column (4) has a positive coefficient, while on column (5) has a negative coefficient. However, those coefficients