Data and Methodology

2.1 ASEAN's Labor-Intensive Manufacturing Exports

Figure 1 [ PDF 29KB | 1 page ] shows the value of ASEAN's labor-intensive exports over time. Labor- intensive exports include carpets, clothing, fabrics, furniture, knitwear, leather, and yarns. Exports of these goods increased very rapidly during the ten years preceding the 1997–1998 Asian financial crisis. Beginning in 2002, exports from Indonesia, Malaysia, and Thailand began increasing rapidly again. The figure also indicates that labor-intensive exports are especially important in Indonesia.

These findings are confirmed in Figure 2 [ PDF 49.7KB | 1 page ]. The figure shows Indonesia's exports in 2007 broken down by product category. The data come from the Centre D'Etudes Prospectives et D'Information Internationales-Comptes Harmonisés sur les Echanges et l'Economie Mondiale (CEPII)-CHELEM database. Labor-intensive manufactures (LIM) were the third largest export category. 12% of Indonesia's exports were in this category.

Figure 3 [ PDF 49.7KB | 1 page ] shows exports disaggregated by product category for Malaysia, Philippines, and Thailand. LIM make up only 5% of exports from these three countries. For Malaysia alone they make up 3% of exports, for the Philippines alone 5%, and for Thailand alone 7%.

Figure 3 indicates that electronics goods are especially important for Malaysia, Philippines, and Thailand. Electronic goods include computer equipment, consumer electronics, telecommunication equipment, electronic components, optics, clockmaking, and precision instruments. 41% of exports from these countries are electronic goods. For Malaysia alone they make up 46% of exports, for the Philippines alone 58%, and for Thailand alone 28%.

Electronic goods are produced largely within East Asian production and distribution networks. Japan; Korea; Taipei,China; and multinational companies located in ASEAN countries export sophisticated technology-intensive intermediate goods to ASEAN countries for assembly and re-export. Agarwalla (2005) reports that the Philippines' value-added in the electronics industry is small. In a comprehensive study, he finds that the local value-added is less than 15%. Austria (2008) similarly concludes, based on a detailed analysis of import and export data, that ASEAN's electronics exports are highly import-dependent and that the domestic content is minimal. Labor-intensive exports, on the other hand, have much higher domestic value-added.

Figure 4 [ PDF 38.5KB | 1 page ] shows the countries and regions that purchased ASEAN's labor-intensive exports. In 2006, 32% went to the US, 27% went to the European Union (EU)-15,¹ 7% went to Japan, and the remainder went to the rest of the world.

Figure 5 [ PDF 66.8KB | 1 page ] shows the leading exporters of labor-intensive goods in 2007, excluding the ASEAN countries. The PRC is the leader, exporting more than 30% of the total. Next come Italy, Germany, and France. Together, the eurozone countries export about 28% of total world exports. Viet Nam exports about 2% of the world total.

ASEAN thus produces LIM largely using domestic inputs and sells these products throughout the world. Key regional competitors include the PRC and Viet Nam.

2.2 The Imperfect Substitutes Model

This paper investigates how exchange rate changes affect ASEAN's exports of labor-intensive manufacturing goods. To do this it uses data on ASEAN's real exports of these goods to 25 countries. There has been substantial variation, both cross-sectionally and over time, in ASEAN exchange rates relative to these countries. This approach should thus help to identify in an econometric sense how exchange rate changes affect the export of LIM.

According to the imperfect substitutes model of Goldstein and Khan (1985), exports can be represented as:

where ex_t represents real exports, rer_t represents the real exchange rate, represents rgdp_t foreign real income, and the variables are measured in natural logs. Equation (1) can be obtained by assuming that the quantity of ASEAN's exports demanded by other countries depends on income in the other countries and the price of ASEAN's exports relative to the price of domestically produced goods in those countries and that the quantity of exports supplied by ASEAN depends on the export price relative to ASEAN's price level. By equating demand and supply one can derive equation (1).

2.3 Dependent and Independent Variables

The dependent variable is the log of labor-intensive manufacturing exports. These goods come from six product categories: clothing, furniture, leather, carpets, yarns and fabrics, and knitwear.² Data for exports of these goods measured in US dollars are obtained from the CEPII-CHELEM database and are deflated using the US Bureau of Labor Statistics price deflators for these six categories.

The panel data set includes exports from Indonesia, Malaysia, Philippines, and Thailand to 25 countries over the 1983–2007 period. These countries are Australia; Austria; Belgium; Bangladesh; Canada; PRC; Denmark; Finland; France; Germany; India; Italy; Japan; Netherlands; New Zealand; Norway; Poland; Saudi Arabia; Korea; Spain; Sweden; Switzerland; Taipei,China; United Kingdom; and US.

The independent variables include the bilateral real exchange rate (rer) between ASEAN and the importing country and real income in the importing country (rgdp), both obtained from the CEPII-CHELEM database. A weighted exchange rate (wrer) of the 27 other leading exports of LIM relative to the importing country is also included.

To calculate the weighted exchange rate for the countries that compete with ASEAN, the share of exports from the 27 leading exporters of LIM is employed. For every year between 1983 and 2007, weights are calculated based on the percentage of LIM coming from the 27 leading exporters to the world. For instance, if in 2007 the PRC provided 30% of the LIM exports from the 27 leading exporters, then the PRC would have a weight of 0.30. When trying to explain exports to Germany in 2007, the bilateral real exchange rate between the PRC and Germany in 2007 would be multiplied by 0.30 (i.e., 0.30*rer_{PRC, Germany, 2007}). The same approach can then be used for the other 26 leading exporters, giving a weighted exchange rate for Germany in 2007 that can be written:

In the same way, weighted exchange rates can be calculated for the other 24 importers in 2007. The procedure can then be repeated for every year going back to 1983, yielding new values of w_i and wrer for each year.

To calculate weighted exchange rates in this way, it is necessary to measure exchange rates using a common numeraire. This can be done by employing the real exchange rate variables constructed by CEPII. The CEPII real exchange rate between countries i and j is calculated by first dividing gross domestic product in US dollars for country i by gross domestic product in purchasing power parity for country i and doing the same for country j. The resulting ratio for country i is then divided by the ratio for country j. This variable measures the units of consumer goods in country i needed to buy a unit of consumer goods in country j. It can be compared across countries as well as across time. Because it is comparable across countries, it can be used in equation (2) to calculate wrer. Higher values of wrer represent stronger exchange rates among countries competing with ASEAN countries and higher values of rer represent stronger exchange rates in ASEAN countries.

2.4 Econometric Methodology

The model is estimated using DOLS. DOLS involves regressing the left-hand side variable on a constant, the explanatory variables, and lags and leads of the first difference of the explanatory variables. The individual export equations have the form:

Here ex_j,t represents real exports from Indonesia, Malaysia, Philippines, and Thailand to country j; rer_j,t represents the bilateral real exchange rate between the ASEAN country and importing country j; wrer_j,t represents the weighted exchange rate between the 27 leading exporters of LIM and country j; and rgdp_j,t equals real income in country j.

The data set extends from 1983 to 2007. One lead and lag is used in the DOLS estimation.

Download this Paper [ PDF 173.9KB| 17 pages ].

Comment(s)

There are [0] comment(s) for this entry. Post a comment.