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The Key Factors of in : Case of Indonesia, Malaysia, and Thailand

Kiki Verico University of Indonesia, Indonesia

Abstract

The major aim of economic integration in Southeast Asia is to shift economic integration from intra-regional to intra-regional before it achieves the common . This article attempts to analyze the two essential factors in Southeast Asia’s economic integration: intra-regional trade and an economic community. In the first analysis, this article observes three selected countries: Indonesia, Malaysia, and Thailand; while in the second analysis it focuses on Indonesia as a case study. Findings from this article showed that agreement is effective to increase intra-regional trade but not effective to attract investment; therefore suggesting that Southeast Asia needs to amplify its open-regionalism principle. This article also found that the private sector is ready for the economic community; therefore the ASEAN Economic Community (AEC) is fit for Southeast Asia’s economic integration exemplary.

Key words: economic integration, international investment (long-term -FDI inflows), ASEAN Free Trade Area (AFTA), Bilateral Free Trade Agreements (BFTA), Asian noodle bowl phenomenon

Introduction investment. Intra-regional trade is affected by its regional trade agreement known as The Association of Southeast Asian the ASEAN Free Trade Area (AFTA), Nations (ASEAN) is committed to while its impact is expected to attract transform Southeast Asia’s economic long-run investment inflows of Foreign integration in trade, which allows free Direct Investment (FDI). As intra-regional flows of to free flows of investment trade analysis is essential for Southeast and services. The latter is known as an Asia’s economic integration, this article economic community and has started attempts to observe both the impact of since the end of 2015. This agreement was free trade agreement to intra-regional implemented through the ASEAN trade and the impact of intra-regional 1 Economic Community (AEC). trade to FDI inflows. It is followed by a The key factor for this second observation on the economic transformation process is in its intra- community as this is the next stage to regional trade because it connects intra- intra-regional trade. regional trade and intra-regional Previous studies show that intra- regional trade is directly affected by the 1 For further detail, refer to implementation of AFTA through the http://www.aseansec.org/18757.htm.

Journal of ASEAN Studies, Vol. 4, No. 2 (2016), pp. 107-126 DOI: 10.21512/jas.v4i2.887.g1736 ©2016 by CBDS Bina Nusantara University and Indonesian Association for International Relations ISSN 2338-1361 print / ISSN 2338-1353 electronic 108 The Key Factors of Economic Integration in Southeast Asia reduction of barriers among its In addition, to analyze the impact members (Braga and Bannister, 1994; of AFTA on FDI inflows, this article Ravenhill, 1995; Menon, 1996; Bowles and adopts another type of agreements titled MacLean, 1996). A high intra-regional the direct Bilateral Free Trade Agreement trade indicates that the welfare-enhancing, (BFTA) as a factor to FDI inflows. BFTA trade-creating effects outweigh its directly connects ASEAN member states welfare-reducing, trade-diverting effects to non-member states. Some previous (Viner, 1950). An increasing intra-regional studies show that BFTA has been trade within members is expected to considered as a shortcut for member states attract long-run investment creation of to attract FDI inflows from non-member FDI inflows. states alongside regional trade agreements (Menon, 2006). BFTA is not prohibited in Theoretically, intra-regional trade ASEAN; therefore there is a potential risk affects FDI inflows in two ways: (1) an that BFTA can infringe the objectives of increase in horizontal FDI inflows from AFTA. In Asia, this glitch is known as the non-members which avoid trade ‘Asian noodle bowl phenomenon.’ impediments as a result of discrimination from regional trade policies (Markusen, In order to complete a model 1984), and (2) an increase in vertical FDI analysis of the factors and impacts of the inflows from members due to the Southeast Asia’s intra-regional trade, this increasing benefits from intra-regional article observes the economic community trade following the implementation of in Southeast Asia by finding the regional discriminative trade policies perceptions of firms, from both the (Helpman, 1984). manufacturing and service sectors, on the AEC. The analysis uses primary data Previous studies find that intra- based on a field survey of the upper- regional trade increases FDI inflows. middle level firms in Indonesia. The Applying Generalized Method of primary data is adopted from a survey Moments analysis to titled ‘Monitoring of Investment Climate,’ (EU) member states in 1989-2001, Baltagi, of which one of its coverage in 2014 was Egger, and Pfaffermayr (2005) find that the firms’ perceptions on the AEC 2015. the increase of intra-regional trade This method is necessary to evaluate the significantly increased FDI inflows. perceptions of firms on the economic Dunning (1990) finds that the acceleration community, the next stage factor for of the United States’ FDI inflows in economic integration in Southeast Asia Europe, which occurred in the late 1950s, after the intra-regional trade. was affected by the EU’s discriminative trade policy towards non-member states. Objective Using fixed effects panel data of gravity model on 55 Organisation for Economic Based on the background, this Co-operation and Development (OECD) article attempts to conduct three analyses. countries in 1982-1997, Mac Dermott First, the factors that affect intra-regional (2006) finds that intra-trade integration trade. This is a proxy for trade creation encourages total FDI inflows in North effect. This objective is achieved by America (North American Free Trade adopting and testing two time dummy Area). variables: (1) the AFTA that is expected to create positive impact on Southeast Asia’s intra-regional trade and (2) the direct Journal of ASEAN Studies 109

BFTA that is expected to do the opposite: Model, Variable, Hypothesis, and create negative impact on ASEAN’s intra- Method regional trade. This article uses BFTA as a proxy to prove the existence of the ‘Asian Secondary Data Analysis: Case of noodle bowl’ in Southeast Asia. This Indonesia, Malaysia, and Thailand phenomenon is a major problem for This article chooses the time enhancing intra-regional trade in dummy of AFTA of year 19992 and, with Southeast Asia. the purpose of sterilizing from global Second, the impact of intra- economic crises in 2008, this article limits regional trade on FDI inflows as a proxy the time series up to year 2008. In order to of investment creation in Southeast Asia. have a balanced time series span, this This article adopts two dummy variables article selects the first time dummy of year of AFTA and BFTA as they are the factors 1988. Therefore, finally this article has 21 for intra-regional trade of trade creation years (1988-2008) of time series analysis. and intra-regional trade is a factor of FDI In order to make a connection inflows of investment creation. For these between the factors and impact of intra- two objectives, given several regional trade, this article has formulated considerations, the observed countries in two equations as a system. The first this article are limited to the ASEAN’s equation uses intra-regional trade as a founding members, in particular dependent variable while the second one Indonesia, Malaysia, and Thailand. uses FDI inflows. This article has adopted Third, the perceptions of firms on trade arrangements (AFTA and BFTA) as the AEC 2015 from both the the factors affecting intra-regional trade of manufacturing and service sector. These Southeast Asia that is complemented by perceptions are obtained from the field other macroeconomic variables as control survey conducted in the biggest ASEAN variables given that trade arrangements member state in terms of Gross Domestic are not the sole factor affecting intra- Product (GDP) and population size, regional trade. These trade agreements are Indonesia. The field survey had been treated as time dummy variables. The conducted in six big cities around time dummy for BFTA is its first time of Indonesia in 2014. In order to achieve this agreement among the observed countries, objective, this article designs questions which was 2004. (Indonesia signed its first that are related to the theory of economic BFTA in 2006, Malaysia in 2005, and community for respondents from upper- Thailand in 2004.) middle level classification. This article assumes that AFTA directly affects intra-regional trade and intra-regional trade directly affects FDI inflows.3 This assumption is also based on

2 According to Nesadurai (2003), the AFTA processes have three stages of negotiations:

identification (1992-1995), expansion (1996- 1998), and implementation that began in 1999.

3 Indirect impact of AFTA to FDI inflows follows the preposition by Ravenhill (1995) and Bowles and MacLean (1996). 110 The Key Factors of Economic Integration in Southeast Asia the empirical facts that AFTA was in home of developed countries to invest.12 designed to boost Southeast Asia’s intra- Regarding that, this article uses nominal regional trade while, for attracting FDI exchange rate as local home currency per inflows, ASEAN offered ASEAN local host currency; therefore, the Investment Area (AIA) policy. increasing ER generates disincentive for the investors to invest FDI inflows in host As for the impact of intra-regional countries. trade to FDI inflows, this article adopts selected variables that hypothetically This article proposes a new affect FDI inflows from previous studies exogenous variable: FDI profit. This of nominal value of GDP, economic variable is adopted from the Global growth and number of population,4 value Financial Development data of the World of consumption,5 employment,6 electricity Bank.13 The data is part of Resource capacity,7 degree of openness,8 Flows, at which the data set form is on of labors and their level of yearly basis. This article adopts this data education,9 as well as exchange rate.10 as a proxy for the profit for the home county of FDI. Exchange Rate (ER) effects on FDI inflows in Southeast Asia are essential to Variables such as corruption index, be observed. During Southeast Asia’s political stability, distance, and English economic crises, exchange rates incurred proficiency however are not observed due unanticipated depreciation leading to to either limited data availability or devaluation.11 Exchange rate also irrelevance to the article’s hypothesis. represents the cost of service link. This means that countries with high exchange The selected variables, their rate volatility will be difficult to cooperate expected signs of hypothesis, and sources with other countries under a production of data are described in Table 1. The network as their exchange rate volatility methodology is built to find the most endangers the entire network. significant variables that explain the effect of trade agreements at the regional and According to the relative value of bilateral levels in Southeast Asia (AFTA wealth approach, the more depreciated and BFTA) on investment creation (FDI). the local currency of a developing country The trade agreements in question are host, the more incentive for the investors accompanied by other macroeconomic variables, because FDI flows are affected 4 For more details, see Sethi, Guisinger, not only by trade policies but also by Phelan, and Berg (2003). macroeconomic variables. 5 For more details, see Walz (1997). 6 For more details, see Hejazi and Pauly (2003). 12 Previous study shows that exchange rate 7 For more details, see Foster (2000). volatility has significant negative impact to 8 For more details, see Park and Park (2008). FDI inflows in East Asian countries (Kiyota 9 For more details, see Hejazi and Safarian and Urata, 2004). (1999). 13 The defines it as the form of 10 For more details, see Barrell and Pain (1996). value of Profit Remittance of FDI in US$ which 11 Hayakawa and Kimura (2008)’s study finds explained in details as ‚payments of direct that exchange rate is the most important investment income (debit side) which consist variable to describe economic uncertainty and of income on equity (dividends, branch competitiveness within production blocks in profits, and reinvested earnings) and income the regional production networks. on the intercompany debt (interest).‛ Journal of ASEAN Studies 111

Table 1. Selected Variables and Hypothesis

Dependent Variables Independent Variables Expected Sources of Data Sign Aggregate FDI Inflows for 1. Value of GDP (GDP) + 1. ADB Statistics testing the impact of AFTA 2. Value of Consumption + 2. ADB Statistics on Investment Creation (CONS) 3. Percentage of + 3. ADB Statistics (ADB Statistics and The World Bank Global (GR) Financial Development 4. Number of Population + 4. ADB Statistics data) (POP) 5. Number of Employed + 5. ADB Statistics Worker (EMPL) Intra-regional trade (IRT) 6. Government + 6. The World Bank World for testing the impact of Expenditure on Development Indicators (WDI) AFTA on Trade Creation Education (EDU) 7. Electricity + 7. The World Bank World (ARIC - ADB and Journal of Consumption Development Indicators (WDI) EFI, 2007) (ELECONS) 8. Degree of Openness + 8. WTO Statistics (DOO) 9. Real Wage (RW) + 9. ADB Statistics 10. Exchange Rate (ER) - 10. ADB Statistics and IMF Country Economic Outlook 11. FDI Profit + 11. The World Bank Global (FDIPROFIT) Financial Development: Profit Remittance on FDI in US$ 12. Intra-regional trade + 12. WTO Statistics 13. Dummy AFTA + 13. Year of Effectiveness of AFTA (1999) 14. Dummy BFTA + 14. Year of first signature of BFTA (Malaysia: 2004; Thailand: 2005, Indonesia: 2006). The first year was 2004 Source: Various articles in academic journals and author’s own proposed proxy and time dummy variables

FDI inflow is affected by intra- In order to provide a comparative regional trade (Motta and Norman, 1996). picture, this article presents both the intra- This article constructs this logical regional trade (%) of ASEAN from the framework as follows: Intra-regional trade Asia Regional Integration Center - Asian is directly affected by regional Free Trade Development Bank (ARIC - ADB) data of Areas (FTA), such as AFTA, and bilateral 2010 and the observed country’s share of FTA (BFTA), and simultaneously affects that intra-regional trade of Indonesia, FDI inflows. This simultaneous relation Malaysia, and Thailand, which is needs system equation of econometrics to calculated based on ADB statistical data. find the connections. These patterns are illustrated in Figure 1.

112 The Key Factors of Economic Integration in Southeast Asia

Figure 1. Intra-regional Trade in ASEAN and Observed Countries (Indonesia, Malaysia, and Thailand), 1988-2008

Intra Regional Trade ASEAN, IMT (%) 1988 - 2008

30% 25% 20% 15% 10% 5% 0%

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

IMT's Intra-regional Trade Share ASEAN's Intra-regional Trade Share (ARIC)

Source: ASEAN Intra-regional trade adopted from ARIC, ADB; Observed Countries Intra regional trade is own calculation based on WTO Statistic

This figure describes that the countries play an important role in patterns of aggregate intra-regional trade forming Southeast Asia’s intra-regional of Indonesia, Malaysia, and Thailand are trade. As mentioned in the background, similar to that of ASEAN as a whole. On the impact of intra-regional trade is average, in 1988 to 2008 the share of intra- limited to FDI inflows and, based on the regional trade of Indonesia, Malaysia, and models and previous studies, the impact Thailand to that of ASEAN was around of intra-regional trade on FDI inflows is 49.8 per cent. This shows that these three proposed as follows:

FDI r t  C   .1 GDPrt   .2 CONSrt   .3 GRrt   .4 ERrt   .5 POPrt   .6 EMPLrt   .7 EDU rt

  .8 ELECONSrt   .9 FDIPROFITrt  10.DOOrt

 11.RWrt  12.INTRArt  ert

…………(1)

This article adopts total value of from the World Bank’s Global Financial FDI inflows due to data limitation on both Development data. The pattern of country and sector levels. The data is aggregate FDI inflows of these three collected from ADB statistical data for observed countries is described in Figure Direct Investment Value, which originates 2.

Journal of ASEAN Studies 113

Figure 2. Aggregate FDI Inflows for Indonesia, Malaysia, and Thailand, 1988-2008

16,000

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 IMT

Source: Data based on Global Development Finance, World Bank

This figure shows that the trend of Model (SEM) estimator. These system FDI inflows at aggregate level of equations are explained below. Indonesia, Malaysia, and Thailand decreased during the Asian A. TSLS-IV Analysis from 1997 to 2001, but then increased after This estimator applies a 2002. This figure shows that the FDI flows Generalized Least Squares (GLS) system required a 5 year adjustment period due with instrumental variable (IV) estimators. to the Asian financial crisis. This method runs the equation without Based on the basic assumption of needing the first-step estimation for intra- this article that AFTA directly affects trade. The equation has been estimated intra- regional trade and intra-regional using the GLS estimator with the TSLS trade directly affects FDI inflows, option and the selected instrumental therefore this article implements a two- variables. Instrumental variables are step procedure. The first step estimates correlated with explanatory variables, but the factors of intra-regional trade, and independently distributed with then the second step estimates the impact disturbance terms. This means that the of intra-regional trade to FDI inflows. As instrumental variables are exogenous. explained in the basic equation above, this Instrumental variables can be adopted article implements system equation from existing exogenous variables with a models of Two-Stage Least Squares with lagged form (Vogelvang, 2005). This Instrumental Variable (TSLS-IV), estimator uses all of the exogenous Seemingly Unrelated Regressions (SUR) variables as instrumental variables; estimator, and Simultaneous Equations therefore the variables that are not utilized 114 The Key Factors of Economic Integration in Southeast Asia as instrumental variables are intra- one and two under one system that has regional trade and FDI inflows. unrelated errors (SUR).

B. Seemingly Unrelated Regressions (SUR) C. Simultaneous Equations Model (SEM) Estimator Estimator

This estimator is chosen due to the This estimator is chosen because possibility that the two equation errors are one of the exogenous variables in equation correlated. Error correlation occurs 1 can be affected by the endogenous because of their covariance (eFDI,eintra) ≠ 0 dependent variable. It opens up the 2 2 then FDI   intra . The two equations probability that FDI influences intra- need to be written in one system with a regional trade variable. It needs to put the SUR estimator. Correlation between FDI variable as an exogenous in equation disturbance terms of these two equations one. If the t-statistic of this parameter is can be affected by the identical smaller than the t-table, then hypothesis unsystematic factors like regional market (H0), which states that FDI affects intra- sentiment, regional production network, trade, is rejected. Similar to SUR, this etc. This estimator assumes that non-zero estimator requires two equations to be correlation exists among the two estimated in one system and follows disturbance errors. The system uses a GLS reduced form methods. It runs equation instead of the regular Ordinary Least one and two under one system that FDI Squares (OLS) because the GLS efficiently inflow is expected to affect intra-trade. estimates parameters and generates The relation between intra-trade and FDI smaller standard errors. It runs equation is reciprocal; therefore equation two has an additional variable (FDI).

INTRArt  C  1..AFTA  .2 BFTA  .3 FDI rt  ut ………… (2)

Primary Data Analysis: Field Survey in Manufacturing Statistics 2010 data Indonesia provided by Indonesian Central Bureau of Statistics (BPS) and 200 service sector This article adopts a survey firms, each of which has 25 or more findings conducted by the Institute for employees, adopted from Indonesia 2006 Economic and Social Research at the Economic Census data provided by the University of Indonesia (LPEM FEB UI) in BPS as well. The field survey was 2014. This survey covers the perceptions conducted from August to December and experiences of firms in relation to 2014. Beside its original panel investment climate factors and was questionnaires, this 2014 survey covers a conducted on manufacturing and services special subject of the AEC 2015 with sector firms in six big cities in Indonesia: specific questions. These questions are Medan, Greater Jakarta, Bandung, designed to figure out the perceptions of Semarang, Surabaya, and Makassar. The these firms on the AEC 2015. survey covers 500 manufacturing firms, each of which has 100 or more workers, adopted from the Indonesia Journal of ASEAN Studies 115

Analysis Based on Regression Results Based on the method used, this and Field Survey Findings article concludes the reduced form model for both the factors and the impact of The Factors and Impact of the Intra- intra-regional trade. Calculation of intra- regional Trade regional trade is customized from intra- The Factors of Intra-regional Trade (Trade regional trade model of Frankel (1997). Creation) This article constructs intra-regional trade as follows: Xr r Mr r in  rt , rt  rt , rt rt Xrwt ,wwt Mrwt ,wwt

; Xrt,rrt is the value of export (country-based) from region to region

; Mrt,rrt is the value of import (country-based) from region to region

; Xwt,wwt is the value of export from region to world

; Mwt,wwt is the value of import of region from the world

The regression result for the factors that affect intra-regional trade in Southeast Asia is presented in Model 1.

Dependent Variable: SUR SIMULTAN Intra-regional Trade TSLS (SYSTEM) (SYSTEM) (IMT) R-squared 0.74 0.69 0.74 Durbin-Watson 1.99 1.88 1.99 F-stat 11.36 Constant Constant Constant Coefficient 0.12*** 0.11*** 0.12*** t-stat 21.11 23.46 21.12

GDP GDP GDP *** *** *** Coefficient 5.85E-14 6.02E-14 5.85E-14 t-stat 3.78 4.13 4.34 AFTA AFTA AFTA Coefficient 0.01** 0.008* 0.01** t-stat 2.01 1.74 2.3

BFTA BFTA BFTA Coefficient -0.009 -0.01* -0.009* t-stat -1.43 -1.81 -1.64

FDI FDI

-8.00E-07* NONE -8.00E-07* Coefficient -1.69 -1.93 t-stat Source: Author’s own calculation, *p<0.1**p<0.05***p<0.01

116 The Key Factors of Economic Integration in Southeast Asia

All of the system estimators (TSLS, generates positive impact on intra- SUR, and SEM) show that GDP generates regional trade of aggregate of Indonesia, positive impact on intra-regional trade. Malaysia, and Thailand. SEM and TSLS GDP is significant at 1 per cent for all give 5 per cent significance level while regression methods. All the estimators SUR gives 10 per cent significance level. show that increasing the economic size of This confirms that AFTA positively affects member countries stimulates trade intra-regional trade in Southeast Asia, relations within ASEAN member states. proving that AFTA is effective for trade This confirms the ‘horizontal integration’ creation. Survey of Japanese-Affiliated Firms thesis that argues that the higher GDP size in Asia and Oceania (FY 2009) released in of member states, the higher incentive to March 2010 by the Overseas Research increase intra-regional trade (Helpman Department of Japan External Trade and Krugman, 1985). Yet, increasing intra- (JETRO) also confirms that regional trade could also occur between AFTA is effective for trade (export and high-income non-member states and low- import). JETRO’s survey respondents income member states, known as ‘vertical involve the manufacturing industry, integration.’ This includes the regional which conducts export and import in production network led by Japan; the Indonesia, Malaysia, and Thailand. flying geese model (Akamatsu, 1944). Empirical data below shows that Both horizontal and vertical integration ASEAN’s intra-trade share significantly have the same essential factor, which is increased over twofold from 12 per cent in the GDP. 1990 to 24.5 per cent in 2009 as described in Table 2. All of the system estimators (TSLS, SUR, and SEM) indicate that AFTA

Table 2. Intra-Regional Trade in Some Regional Integration Organization, 1990 and Latest Data

Per cent ASEAN EU NAFTA 1990 12 per cent 66 per cent 43 per cent 9 per cent Latest 24.5 per cent 67 per cent 55 per cent 17 per cent (2008-9) (2003) (2000) (2000) Source: EU, NAFTA, and MERCOSUR data sources are various, ASEAN: www.aseansec.org

This table shows that Southeast Both estimator systems (SUR and Asia’s intra-regional trade increased after SEM) show that BFTA with non-members the implementation of AFTA. SEM model give a negative effect on intra-regional indicates that FDI inflows affect intra- trade. Even as the obtained t-statistic is regional trade at a 10 per cent significance not relatively high at significance at 10 per level. This finding confirms that the SEM cent, the results have indicated that estimator is the most representative BFTAs weaken intra-regional trade. The models in describing the economic negative sign of BFTAs confirms that relations between ASEAN intra-regional BFTAs generate a leakage for Southeast trade and FDI inflows. Asia’s economic integration as it gives a Journal of ASEAN Studies 117 negative impact on intra-regional trade of economic gap among members as only Southeast Asia. This finding proves the advanced economic members can gain existence of the ‘Asian noodle bowl benefit from such direct BFTAs. phenomenon’ (Panagariya, 2000; Tumbarello, 2007; Kawai and Wignaraja, The Impact of Intra-regional trade on FDI 2009) in Southeast Asia. Inflows (Investment Creation)

In addition, BFTA creates a After running the reduced form prisoner’s dilemma for ASEAN member model from general to specific principle, states because BFTA forces other ASEAN this article finds that aside from intra- members who are actually inadequate for regional trade being the independent BFTA to enter such agreements, so that variable affecting FDI, there are four other they can minimize the cost of being significant variables: consumption, excluded from others’ BFTA benefits. This population, labor productivity (real wage effect is called ‘snowballing effect of as a proxy), and exchange rates. The final BFTA’ (Baldwin, 2006). In sum, BFTA result of the impact of intra-regional trade makes trade agreements in Southeast Asia on FDI inflows can be described in Model become complicated and this increases the 2.

Model 2. The Impacts of Intra-regional trade and Selected Macroeconomic Variables on

FDI Inflows (Investment Creation) in Southeast Asia (Observed Countries)

Dependent TSLS-IV SUR SIMULTANEOUS Variable: CONS(-1) ; (SYSTEM) (SYSTEM) FDI Inflows POP ; RW(-1); Aggregate Level ER(-1)

R-squared 0.67 0.66 0.67 Durbin-Watson 1.56 1.69 1.57 F-statistic 5.66 Constant Constant Constant Coefficient -55,403** -55,219* -55,403* t-stat -2.17 -1.84 -1.84 Consumption Consumption Consumption Coefficient -2.43E-08** -2.37E-08** -2.43E-08** t-stat -2.74 -1.99 -2.02 Population Population Population Coefficient 302*** 318** 302** t-stat 3.05 2.66 2.5 RW(-1) RW(-1) RW(-1) Coefficient 4.24*** 4.4*** 4.25*** t-stat 4.81 4.7 4.26 Intra-regional Intra-regional Intra-regional trade trade trade -178,100*** Coefficient -178,100*** -214,257*** -2.91 t-stat -3.16 -3.55 ER ER ER Coefficient -3.39** -3.58** -3.39** t-stat -2.6 -2.46 -2.31 Source: Author’s own calculation, *p<0.1 **p<0.05***p<0.01 118 The Key Factors of Economic Integration in Southeast Asia

All of the estimators (TSLS-IV, of significance for all estimators. In SUR, and SEM) show that consumption affecting investment creation, all the value has a negative relation to FDI. All equation systems show that the system models show that the independent labor productivity of real consumption affects FDI inflows at the 5 wages as a proxy requires a one-year lag. per cent level of significance with no time This shows that foreign investors make lag. The negative sign indicates that investment decisions in Southeast Asia increasing consumption will decrease based on last year Indonesia, Malaysia, regional FDI Inflows. This can be and Thailand’s labor productivity of real explained as follows: Increasing wage (RW). consumption means an increase in demand for products, including imports. In this model, intra-regional trade The absence of a due to generates negative impact on investment unregulated external tariff barriers creation. All the system models show that between member states and non-member intra-regional trade affects FDI inflows at states create a ‘trade deflection’ in 1 per cent significance level, while the Southeast Asia, at which, in order to fulfill TSLS is proven at 10 per cent significance total increasing demand, non-members level. The negative relation between intra- prefer to export through the lowest tariff regional trade and FDI inflows can be (Most Favored Nation) of member state interpreted as follows: (1) the increasing than to invest their FDI. Therefore, intra-regional trade does not increase regional economic cooperation such as investment creation in Southeast Asia; (2) AFTA faces the issue of Country of Origin trade diversion effect is not significant in due to possibilities of re-exportation from Southeast Asia, unlike found in EU and those low-tariff members in the region. In Mercosur. Similarly, Asian regional sum, the increasing consumption in economic integration has more ‘trade Southeast Asia encourages non-member creation effect’ than ‘trade diversion state investors (outside ASEAN) to do effect.’ trade rather than invest FDI. In terms of attracting long-run The estimators of TSLS, SUR, and investment at the regional level in SEM show a 5 per cent significance level, Southeast Asia, ASEAN formulated while TSLS-IV shows a 1 per cent several policies aside from AFTA, such as significance level for the effect of the ASEAN Industrial Projects (AIPs) that population size to FDI inflows. This supports each member state to build means that all estimators show that projects with all member states as population size significantly encourages stakeholders; ASEAN Industrial investors to invest as it reflects the size of Complementation Scheme (AICS) that demand for goods and supply of labor. provides preferential tariffs for trade of complementary goods in the same All of the estimators show that industrial sector within members; and labor productivity of MPL=RW has a ASEAN Industrial Joint Venture Scheme positive impact on FDI inflows. This (AIJVS) that provides preferential tariffs confirms that investors take production for trade of goods between joint venture efficiency as an essential factor. This firms with at least 51 per cent equity variable is significant at a 1 per cent level owned by the ASEAN member firm. Yet, Journal of ASEAN Studies 119 all of these policies have not effectively exchange rate (ER) has negative relation succeeded in achieving ASEAN’s with net value of FDI flows. objective to attract investment and enhance regional production networks All of the system equations (SUR, among its member states (Bowles and SEM, and TSLS-IV) indicate that ER shows MacLean, 1996). a 5 per cent significance level while the TSLS estimator shows ER at 1 per cent Furthermore, ASEAN also significance level. The negative relation established ASEAN Industrial between ER and FDI shows that Cooperation Scheme (AICO) and ASEAN depreciation or devaluation of a national Investment Area (AIA). These currency tends to lessen the incentive for establishments confirm that not only FDI inflows. This confirms the ‘J-curve ASEAN covers trade or demand-side phenomenon.’ Currency depreciation issues, but it also covers supply-side does not necessarily boost exports or issues. AICO was established after the reduce imports. At the beginning, it Japanese automotive company revealed generates the opposite effect: increasing their plan in 1996 to enlarge production imports and decreasing exports due to the networks and production volume in producer-consumer lag. It creates a Southeast Asia; while AIA was negative trade balance and serves as a established in 1999 to focus on investment ‘disincentive to invest.’ In contrast, the liberalization, human resources relative value of wealth finds that the development, information and more depreciated the local currency of communication technology (ICT), and host developing country, the more developments. However, incentive for the investor in home AICO received complaints from private developed country to invest; while other companies because of its unprepared studies find that the ‘volatility’ of administrative procedures (Yoshimatsu, exchange rate affects FDI inflows rather 2002), while the AIA’s impact on than ‘level’ of the exchange rate. For ASEAN’s long-run investment creation example, ‘exchange rate volatility’ has a remains unclear. In addition, most studies significant negative relation to Japanese on investment perception in Asia show FDI in East Asian countries (Kiyota and that investors take into regard the internal Urata, 2004). This article proves that factors of doing business than the AFTA has a positive effect only on trade existence of the regional free trade creation of Model 1, but intra-regional agreements. These internal factors include trade has a negative effect on investment required procedures to start a business, creation of Model 2. profit tax, number of documents to export and import, ease of doing business index, This shows the relation between a and others. value of FDI inflows of investment creation and intra-regional trade of trade During the 1998 Southeast and creation is negative. This means that East Asia economic crisis, the local ASEAN regional trade agreement of currencies of the observed countries were AFTA is only effective to increase intra- significantly depreciated. In this article, regional trade from trade creation, but exchange rate is described as the value of ineffective to attract FDI inflows of local currency to international currency of investment creation. This finding confirms US$. All of the estimators indicate that that Preferential Trading Area (PTA) such 120 The Key Factors of Economic Integration in Southeast Asia as AFTA practically generates trade firms, or around 75 per cent of realization creation; even basically its main objective rate. The firms consist of 343 is to attract FDI inflows from its trade manufacturing firms and 179 service diversion (Grossman and Helpman, 1995). firms. This survey finds that the dominant firms in the manufacturing and Field Survey on AEC 2015: Case of service sectors know about AEC 2015: Indonesia about 56 per cent of manufacturing firms This survey has succeeded to know about AEC 2015 and 60 per cent of interview 522 out of the targeted 700 service firms know it. (Details in Figure 3.)

Figure 3. Percentage of Firms that ‘Know’ AEC 2015

Source: LPEM FEB UI’s Field Survey on Manufacturing and Service Firms

Based on the ‘yes’ answer on ‘yes,’ this survey further finds that the whether the firms know about AEC 2015, manufacturing firms are more ‘ready’ for next question is whether they are ready AEC compared to those in the service for AEC 2015 and the answer options are sector; 84 per cent and 77 per cent ‘yes’ or ‘no’. Based on those who replied respectively. (Details in Figure 4.)

Journal of ASEAN Studies 121

Figure 4. Percentage of Firms that Reply ‘Ready’ towards AEC 2015

Source: LPEM FEB UI’s Field Survey on Manufacturing and Service Firms

The 2014 survey also asks the Figure 5.) The result in this pattern is perceptions of the firms on the potential interesting, even the firms have no initial impacts of AEC 2015 and identifies their academic information based on the theory perceived impact of the AEC of 2015. of economic community yet their There are six factors that this survey asks perceptions show that given their the firms: (1) whether intra-ASEAN empirical experiences on the trade and investment from ASEAN members will investment relations between countries in increase (yes or no), (2) whether extra- Southeast Asia under ASEAN economic ASEAN investment from non-ASEAN cooperation, most firm’s patterns of members will increase (yes or no), (3) knowledge on the AEC are close to theory whether non-competitive members will of which top three patterns are: one, intra- face the cost of AEC (yes or no), (4) investment is expected to increase; two, whether competitive non-member states extra investment is predicted to increase; will enjoy the benefit of AEC (yes or no), three, competitive non-member state (i.e. (5) whether service-related trade will be China) will enjoy more benefit while four, liberalized (yes or no), and (6) whether the non-competitive member states will face service sector in general will be liberalized the cost; and five, service sector will be (yes or no). The results provide detailed liberalized from trade related service information about the patterns of sector to service sector in general due to potential impacts of AEC 2015 from the the harmonization of service sector in perceptions of the firms on it. (Details in ASEAN.

122 The Key Factors of Economic Integration in Southeast Asia

Figure 5. Perceptions of the Expected Impacts of AEC 2015 as Percentage of Respondents Who Replied the Particular Question

Source: LPEM FEB UI’s Field Survey on Manufacturing and Service Firms

Conclusion effectiveness in trade creation. BFTA plays as a ‘stumbling block’ instead of a System equations are appropriate ‘building block’ towards intra-regional in making connection between the factors trade. All of the model estimators prove and impact of intra-regional trade. As for that BFTA generates a negative impact on the factors of intra-regional trade, a intra-regional trade. This confirms that reduced form model finds that intra- BFTA has the potential to weaken regional regional trade in Southeast Asia is affected trade policy of ASEAN due to its non- by the value of nominal GDP as a proxy discriminative tendency towards non- for economic size and time dummy ASEAN members. This result also variable of trade agreements of AFTA and confirms that ‘Asian noodle bowl BFTA. Nominal GDP gives a positive phenomenon’ exists in Southeast Asia impact on intra-regional trade. This since BFTA generated a ‘leakage’ to the proves that the higher the economic level intra-regional trade of ASEAN. of a member country (GDP), the higher its trade relation within Southeast Asian. As for the impact, intra-regional This confirms the ‘horizontal integration’: trade generates a negative impact on long- the higher the GDP, the higher the intra- run investment creation (FDI inflows). regional trade among countries. AFTA Furthermore, SEM estimator proves that generates positive impact on intra- FDI inflows also generate a negative regional trade (aggregate of Indonesia, impact on intra-regional trade. This Malaysia, and Thailand). This confirms indicates that, in Southeast Asia, intra- that AFTA positively affects intra-regional regional trade and long-run investment trade in Southeast Asia, thus proving its weaken each other. This article finds that Journal of ASEAN Studies 123

SEM is the most appropriate system member states, and liberalization of equation model to describe the relation service-related trade and service sector in between intra-regional trade and FDI general due to the harmonization process inflows because it proves interdependent at the regional level. relation between intra-regional trade and FDI inflows. In addition to intra-regional Policy Implication trade, FDI inflows are affected by the Currently, Southeast Asia is still value of consumption, the size of focusing on the first step of regional population, the marginal productivity of economic integration, which is trade labor (Real Wage), and the exchange rate. liberalization among its members. This For consumption, this article indicates the article finds that through ASEAN, the existence of ‘trade deflection’ as the higher three countries have not been effective in of consumption value, the lower the FDI enhancing its regional economic inflows. For the population, this article cooperation achievement from intra- finds that population size gives a positive regional trade to regional investment impact on FDI inflows. As for marginal integration. Southeast Asia needs more productivity of labor, this article finds that comprehensive and open regional the higher productivity (one-year lag), the economic cooperation scheme to enlarge higher the FDI inflows. While for the its regional economic integration from exchange rate, this article finds that local trade to investment. This needs currency depreciation gives a negative enlargement of Southeast Asia economic impact on FDI inflows. cooperation with non-member states. Each The field survey finds that the country in Southeast Asia is free to have perceptions of firms on AEC 2015 are direct bilateral agreements with non- positive and optimistic. They are positive member states (BFTA). Yet, if a country in as more than 50 per cent of the firms Southeast Asia opens bilateral trade with know that Southeast Asia enters an non-member states, sooner or later the economic community named AEC since other members will do the same early 2016; the proportions are 56 per cent regardless its readiness for the manufacturing firms and 60 per cent agreements. It is named the bandwagon service firms. From those who replied effect of BFTA. ‘yes’ on whether the firms know about Member states that are suitable for AEC 2015, more than 70 per cent say that direct bilateral agreements will get benefit they are ‘ready’ to compete in AEC; the from them, while those that are incapable proportions are 84 per cent manufacturing will only get cost from them. This will firms and 77 per cent service firms. increase the economic gap among Furthermore, this survey finds that both members and, at the end, harm Southeast manufacturing and service firms have Asia’s economic integration purpose. close knowledge patterns to the theory of economic community; in particular, its The best way for the Southeast major expected impacts. From the highest Asian region in enlarging the regional to the lowest impacts, they include economic integration from trade to increase of intra-investment from member investment creation is under the ‘ASEAN states, extra-investment from non-member umbrella.’ Given the divergence of states, benefit for competitive non- economic level among members, the most member states, cost for non-competitive advanced economic member should 124 The Key Factors of Economic Integration in Southeast Asia tolerate other weaker members. ASEAN’s University of Indonesia (LPEM FEB UI). soft decision-making process will make The author holds a Ph.D. degree in this enlargement take longer time than International Studies (Economics) from that of bilateral agreements; yet it is more the Graduate School of Asia-Pacific secure and fairer for all the members. Studies (GSAPS), Waseda University, Tokyo. Therefore, AEC 2015 is the best choice for ASEAN. In addition, given that Reference Southeast Asia does not have a Custom Union alongside AEC, Southeast Asia can Akamatsu, K. (1944). Keisei Shinchitujo no utilize its ‘open and soft regionalism Keisei Genli (The Theory of Formation of principle’ through the implementation of the New Economic Order). Tokyo: the ASEAN Plus frameworks, AFTA Plus Lisosha. One, and Regional Comprehensive ASEAN Secretariat. (1999). ASEAN Economic Partnership (RCEP). AEC can Investment Area: Temporary Exclusion be a substitute for the absence of a List and Sensitive List. 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