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production. The question is, whether the application the ITF that cause lower interest rates improve comparative advantage and trade balance for capital-intensive products in Indonesia.
Source: Bank Indonesia
Figure 2. Interest rate of investment loans and SBI after ITF (%)
Conference Papers the backward-bending function from interest rate. Peng &
Thibodeau (2016) empirically analyze non-monotic of changes in the interest rate on irreversible investment used dataset 1416 individual capital improvement of big firm like apartment, industrial and retail properties, for period 1978-2009 found that the effect non-monotonic is capture from interactions between interest rate with capitalization level from property firm. In contrast to studies which found that interest rate gives negative effect on capital and investment, Capozza and Li (2001) ware used data of 56 metropolitan housing for period 1980-1989 found that investment level gives positive effect to interest rate.
Furthermore, companies need input or factors of production, which in simply term is capital and labor. Heckscher–
Ohlin model explain that each countries have the difference in proportion of factor of production cause the difference in the good price. It makes country specialize produce goods that used intensively abundant factor of production and competitive advantage.
The increase of capital will rise output and net export of capital-intensive products. Rybczynski theorm express that the increase in the supply on one factor of production factor will increase output but can decrease other output (Akay & Dogan, 2013, Hanson & Slaughter, 1999). However Bernstein &
Weinstein (2002) found other conclusion. Akay and Dogan (2013) was used US data for 1979-2001, found that the increase on labor supply rise output in all industry but the magnitude is depend on elasticity on each industry. The same with Akay and Dogan (2001), Hanson and Slaughter (1999) was used OLS method, and 40 sectors in US period 1980-1990, found that there are linear relationship between labor supply and the change of output mix in US.
There are previous research which found the effect of interest rate on competitive advantage. Bergin and Corsetti (2014) used New Keynesian model prove that monetary policy can increase comparative advantage firm. Bergin and Corsetti (2008) express that the decrease on interest rate will increase expected
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discounted profit by create new firm, so that encourages new firm entry. Bergin and Corsetti (2014) were used US data as home country and aggregate of 10 EURO country to foreign country from 1972-2004, found that with stabilizing markup, monetary policy can foster competitiveness of firm, encourages investment and differentiation from the production of goods, increase output, and export. In contrast Ridhwan et al. 2010 found monetary policy influences output but insignificantly effect export.
3. METHODOLOGY
This paper use data of exports and imports published by the United Nations Commodity Trade Statistics Database (UN- COMTRADE). We use three-digit the standard international trade classification (SITC) Revision 2 and focuses on group of product classified by Empirical Trade Analysis (ETA). We use data of export and import for 2004 and 2014. ETA distinguished the following five products or industries: primary-industries (83 SITC), natural resource-intensive industries (21 SITC), unskilled labor-intensive industries (26 SITC), technology-intensive industries (62 SITC), and human capital-intensive industries (43 SITC). The classification table is available upon request.
The research use technology-intensive product and human capital products as capital intensive products. However, unskilled labor-intensive products used as control group that is compared to classification 5 and 6. The procedure comparing the group discuss later.
We use Revealed Symmetric Comparative Advantage (RSCA) by Laursen (1998) and Trade Balace Index by Lafay (1992) to measure comparative advantage and trade balance. RCA index is formulated as follows:
( ) ( ) (2)
The values of index has value between minus one to one.
greater than zero implies that country i has comparative advantage in group of products j. However, less than zero
Conference Papers means that country i has comparative disadvantage in group of
products j.
Furthermore, RCA in equation (2) is Revealed Comparative Advantage index or Balassa index (Balassa, 1965).
RCA index is formulated as follows:
( ⁄ )( ⁄ ) (3)
where represents revealed comparative advantage of country i for group of products (SITC) j; and Xij denotes total exports of country i in group of products (SITC) j. Subscript w refers to all countries and subscript n refers to all groups of products (SITC).
The other indicator analyze trade balance index (Lafay, 1992) to analyze whether a country has specialization in export (as net-exporter) or import (as net-importer) for specific group of product (SITC). TBI is formulated as
(4)
where TBIij denotes trade balance index of country i for group of products (SITC) j; xij and mij represents exports and imports of group of products j by country i, respectively. Furthermore, this index ranges from minus one to one. When TBI equals to minus one means a country only imports, in contrast, the TBI equals to one means a country only exports.
Tri Widodo (2008) use the RSCA and TBI indexes to constructed the ‗‗products mapping‘‘. He categorized product into four groups A, B, C and D as depicted in Figure 3. Group A consists of products which have both comparative advantage and export-specialization; Group B consists of products which have comparative advantage but no export-specialization; Group C consists of products which have export-specialization but no comparative advantage; and Group D consists of products which have neither comparative advantages nor export-specialization. In region A, there are potential products.
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Sources: Tri Widodo (2008)
Figure 3. Products Mapping
Furthermore, Widodo (2008) explain the industries in the first round of the FG pattern are unskilled labor-intensive
industries followed by human capital-intensive industries in the second round and technology-intensive industries in the third round.
Furthermore, the impact of the ITF influencing the comparative advantage index and trade balance index is estimated using difference in the difference model or double different (DD).
This model is used to see the effects the government policies on society. In the DD models, the data comes from two groups of units of analysis that have the same characteristics. Example, A group that impacted by policy (of participants) and group B who does not impacted by policy (control). In this study a group of products affected by the ITF are capital intensive products and control group that is not effected is unskilled labor intensive products.
Sources: Khandker, et al. (2010)
Figure 4. Reason for DD Model
Conference Papers Figure 3 shows the researchers assumed that the distance
between the groups of products, B and A at the time before the ITF or t0 is(Y1-Y0), where Y is RSCA or TBI index. The distance of RSCA and TBI will be the same at the next measurement t1 when there is no ITF. The model shows without ITF policy which tends ITF the distance is (Y3-Y2). The distance between Y3 to Y4 is impact of the ITF policy. Khandker et. al. (2010) also state the advantage of DD is relaxes the assumption of conditional selection only on observed characteristics. It also provides a tractable, intuitive way to account for selection on unobserved characteristics.
Based DD, this study use Ordinary Least Square (OLS) to investigate the causality relationship between ITF and capital intensive products. In the model, 2000 used as time before the policy and 2014 used as the time in policy. Furthermore, unskilled labor-intensive product is used as control variable. White heteroskedasticity-consistent standard errors & covariance apply and model can be formulated as:
(5) where d14 is dummy 2014 (period of policy) and dtech is dummy technology-intensive products. The equation 5 use to estimate ITF effect to technology-intensive products. Furthermore, the DD for human capital-intensive products estimated using the following equation:
(6) Where is dummy human capital-intensive products. In DD, coefficient is important because it measures the real effect of ITF on RSCA and TBI. The coefficient exclude the other effect that influence RSCA and TBI that assume effected treatment group, technology-intensive or human capital-intensive products, and control group, unskilled-labor intensive products.
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4. RESULT AND DISCUSSION