Inter-Sector and Inter-Country Linkages in Indonesian Economy: World Input-Output Analysis

Results of analysis on inter-sector and inter-country linkages in Indonesian economy using world inputoutput data are presented in this paper. The model was aggregated from 56 sectors and 43 countries into 30 sectors and 8 countries. Inter-sector linkages are analyzed using forward and backward effect indices. Meanwhile inter-county linkage is analyzed by spill-over and feed-back effects. The results showed thatfirstly, number of sectors include in Group-1, namely key sectors with strong forward and backward linkages: two sectors in year 2000, one sector in year 2005, 8 sectors in year 2010 and 2014. Secondly, spill-over effects were significantly importance in Indonesia economy, as around 20 per cent of multipliers occurred in other countries. Only small feed-back effects are in Indonesian economy. Finally, ignoring inter-country feed-back could be misleading as error created was significant.


Introduction
Assessment of sectoral and spatial economic performance is very important issues in forming development policies. In a competitive economy, sectoral and spatial interdependences are of the most important sources of economic expansion. Sectoral linkages, comprising backward (BL) and forward linkages (FL), reflect the interconnectedness between the sectors of an economy. The idea of linkages grew out of Hirschman's theory of unbalanced growth and describes the relationships that exist between parties involved along the supply chain. BL describes the process of how a company in a given sector purchases its goods, products, or supplies from a company in a different sector; these are called inputs. FL describes the process of how a company in a given sector sells its goods, products, or supplies to a company in a different sector; these are called outputs. BL and FL analysis have been used to determine key sectors in development planning. Several studies have been conducted on sectoral linkages by many researchers (Rueda-Cantuche, Neuwahl, & Delgado, 2012;Midmore et al., 2006;Cai & Leung, 2004;Cai, Leung, Pan, & Pooley, 2005;Rashid, 2004 ;Hoen, 2002;Andreosso-Callaghan & Yue, 2004;Sonis, Hewings, & Guo, 2000;Hewings & Fonseca, 1989;Hewings, 1982;Beyers, 1976) Inter-country or spatial linkages consist of spill-over effect (SOE) and inter-country feed-back effect (FBE). Measures of inter-regional feed-back and spill-over linkages have been developed by among others (Miller, 1986;Miller & Blair, 2009;Miller, 1966;Guccione, Gillen, Blair, & Millert, 1988;Cochrane, 1990;Dietzenbacher, 2002;Dietzenbacher & Linden, 1997). The importance of inter-country connection for a country could be shown by calculating output forthcoming from sectors in a country in response to a change in that county's final demands under two alternative assumptions, firstly that the country is a fully-connected part of an inter-country input-output system, and secondlythat the country is totally isolated from the remaining regions. Using Inter-Country Feed-Back Index (ICFBI) and Feed-Back and Spill-Over Index (FBSOI), the importance of inter-country linkages among country could also be clearly indicated.
The purpose of this paper aims to analyze inter-sector linkage through FLand BL and intercountry linkage through spill-over effectand feedback effectin Indonesian economy using world inputoutput analysis for year 2000,2005,2010 and 2014.

Research Method
The World Input-Output Database (WIOD) that provides annual time-series of world inputoutput tables from 1995 onwards. These tables have been constructed in a clear conceptual framework based on the system of national account (United Nation, 2018). They are based on officially published input-output tables merged with national accounts data and international trade statistics. In addition, the WIOD provides data on factor inputs enlarging the scope of potential applications considerably. Since its public inception on April 2012, WIOD has proved very useful in analyses of international trade. It has been used to describe trends in global supply chain trade and research into the formation of regional production clusters in the world economy (Baldwin & Lopez-gonzalez, 2014;Los, Timmer, & Vries, 2014;Timmer, Los, Stehrer, & de Vries, 2013)as well as analysing the domestic value-added content of gross exports (Wang, Zhu, &Wei, 2018initially proposed by Koopman, Wang, andWei (2014;Koopman, Wang, & Wei, 2014;Johnson, 2014). The data also proved suitable for calibrating general equilibrium models to evaluate the effects of trade policies (Costinot & Rodríguez-clare, 2018;Dhingra, Huang, Ottaviano, Sampson, & April, 2016). The cross-section panel dimensions of the data allowed a revisit of the debate on the effects of off shoring on labour demand (Fostermcgregor, Stehrer, & de Vries, 2013). WIOD also found its way into numerous policy-oriented studies on the effects of globalization (Mauro & Plamper, 2013;Saito, Ruta, & Turunen, 2013). Basically, a world input-output table (WIOT) is an extension of national input output table. The difference with the national tables is that the use of products is broken down according to their origin and destination countries (Timmer, Los, Stehrer, & De Vries, 2016;Dhehibi, Bahri, & Annabi, 2012). A world input-output table (WIOT) can be regarded as a set of national input-output tables that are connected with each other by bilateral international trade flows. This is illustrated in Table 1.
WIOT provides a comprehensive summary of all transactions in the global economy between industries and final users across countries. The columns in the WIOT contain information on production processes. When expressed as ratios to gross output, the cells in a column provide information on the shares of inputs in total costs. Such a vector of cost shares is often referred to as a production technology. Products can be used as intermediates by other industries or as final products by households and governments (consumption) or firms (stocks and gross fixed capital formation).The distribution of the output of industries over user categories is indicated in the rows of the table. An important accounting identity in the WIOT is that gross output of each industry (given in the last element of each column) is equal to the sum of all uses of the output from that industry (given in the last element of each row). In addition to a national input-output table, imports are broken down according to the country and industry of origin in a WIOT. This allows one, for example, to trace the country of origin of the chemicals used in the food industry of country A.
The columns of Table 1 provide information on the input composition of the total supply of each product j (X j ), this is comprised by the national production and also by imported products. The value of domestic production consists of intermediate consumption of several industrial inputs i plus value added. The inter-industry transactions table is a nuclear part of this table, in the sense that it provides a detailed portrait of how the different economic activities are interrelated. Since intermediate consumption is of the total-flow type, this implies that true technological relationships are being considered. In fact, each column of the intermediate consumption table describes the total amount of each input i consumed in the production of output j, regardless of the geographical origin of that input.
The second release of the WIOD in November 2013 provides a time-series of world input-output tables (WIOTs) from 1995 to 2011. It covers 40 countries, including all 27 members of the EU and 13 other major economies: Australia, Brazil, Canada, China, India, Indonesia, Japan, Mexico, Russia, South Korea, Taiwan, Turkey and the USA (Timmer et al., 2016). WIOD 2016 release covers all trade between 43 countries as well as with a "rest-of-the world" region (Timmer, Dietzenbacher, Los, & Stehrer, 2015). For the purpose of this study, model is aggregated into 6 Asian countries: China, Indonesia, India, Japan, Korea, and Taiwan, plus Australia and the United States. Sectors are aggregated from 56 sectors to 30 sectors as provided in Appendix-1. Data processed are data for year 2000, 2005, 2010 and 2014.
Inter-sector linkages, comprising backward (BL) and forward linkages (FL), reflect the interconnectedness between the sectors of an economy. FL describes the process of how a company in a given sector sells its goods, products, or supplies to a company in a different sector. BL describes the process of how a company in a given sector purchases its goods, products, or supplies from a company in a different sector and different country. In the literature on interindustry linkages, BL and FL are widely accepted concepts, but there remains discussion over how best to measure them (Jones, 1976;Hewings, 1982;Cella, 1984;Sonis & Hewings, 2009;Miller & Lahr, 2001;Cai & Leung, 2004). In this paper, the suggestion byCai et al., (2005) is employed; the Leontief supply-driven multiplier (LSD) as a backward-linkage measure and the Ghosh supplydriven multiplier (GSD) as the corresponding forward-linkage measured by Cai & Leung (2004) and Leung & Pooley (2002)for similar applications of these supply-driven multipliers.
In brief, the LSD multiplier provides information about an industry's existing relationships with its upstream suppliers; specifically, it measures the dollar amount of production needed directly and indirectly by the industry from its (upstream) suppliers to generate one dollar of sales. The GSD multiplier describes numerically an industry's relationship, directly and indirectly, with its downstream buyers.FL index is calculated by dividing its GSD multiplier by the average GSD multipliers for all the industries. FL i = GSD multiplier for sector-i/Average GSD multiplier for all industries (1) BL index for i is simply the industry's LSD multiplier divided by the average LSD for all the industries.
The spatial spill-over effects are calculated as the difference between the total multiplier in single-country model and the multiplier effects that occurred in own-region, in inter-country model. SOE is the multiplier effects that occur in other country due to the change of final demand of own country. Spatial feed-back effects of multipliers can easily be shown by the difference between the single-region multipliers and the intra-country multipliers, those multipliers that occur in own-country of the inter-country model. FBE is calculated as differences between intra-country multipliers in inter-country model and total multipliers in single-country model. Percentage error of ignoring the inter-country linkages is measured using ICFBI (Inter-Country Feed-Back Index) and FBSOI (Feed-Back and Spill-Over Index). ICFBI is ratio of feed-back effect multipliers to total multipliers in single-country model. FBSOI is ratio of feed-back and spill-over multipliers to total multipliers in inter-country model.  During the years of study, more sectors with strong BL than sectors with strong FL in Indonesian economy. BL are more strength than FL. Development priorities should be given to the sectors that have both strong BL and FL as well.  Group-1: strong FL (FL>1) and strong BL (BL>1); Group-2: strong FL (FL>1) but weak BL (BL<1); Group-3: weak FL (FL <1) but strong BL (BL > 1) and Group-4: weak FL (FL< 1) and weak BL (BL <1). In year 2000, only two sectors were in Group-1, namely Sector-8 and Sector-15. One sector was in Group-2 (Sector-2). Fourteen sectors were in Group-3, namely Sector-5, Sector-6, Sector-7, Sector-11, Sector-12, Sector-13, Sector-16, Sector-17, Sector-18, Sector-19, Sector-21, Sector-22, Sector-24, Sector-25, and 12 sectors were in Group-4, namely: Sector-1, Sector-3, Sector-4, Sector-9, Sector-10, Sector-14, Sector-20, Sector-26, Sector-27, Sector-28, Sector-29, and Sector-30.
Sectors included in Group-1 should be prioritized in development planning as the sectors had strong FL and strong BL. These sectors are known as the key sectors. Second priorities in sectoral development depended on either FL or BL. Sectors in Group-2, if strong FL is the main concern, however, sectors in Group-3, if strong BL is the main concern. Sectors in Group-4 were sectors that classified as non-priority sectors in development as these sectors had weak FL as well as weak BL. Figure 3 presents spill-over and feed-back effects in Indonesian economy for year 2000,2005,2010  In this year, multiplier occurred in China was increased to 2.11 per cent, multiplier occurred in India was also increased to 0.48 per cent. However, multipliers occurred in (spill-over effects to) Japan, Korea, Taiwan, Australia and the United States was decreased consecutively to 2.39 per cent, 0.96 per cent, 0.36 per cent, 0.92 per cent and 0.91 per cent. Three important countries received highest spill-over effect from Indonesia, namely: Japan (2.39%), China (2.11 %), and Korea (0.96 %). Meanwhile, feed-back effect to Indonesian economy was only 0.14 per cent.

Intercountry-Linkages: Spill-over and Feedback Effects
Panel-C presents Spill-Over and Feed-Back linkages in Indonesian economy for year 2010. In year 2010, total output multiplier in Indonesian economy was 2.1136; 81.81 per cent occurred in own country and 18.19 per cent occurred in other countries. This means that 18.19 per cent of total output multipliers spilled-over to other countries.
In this year, multiplier occurred in (spill-over to) China was increased to 2.88 per cent, and multiplier occurred in Taiwan was also increased to 0.41 per cent. However, multipliers occurred in India, Japan, Korea, Australia and the United States was decreased consecutively to 0.37 per cent, 1.87 per cent, 0.94 per cent, 0.52 per cent, and 0.84 per cent. Three important countries received highest spill-over effect from Indonesia, namely: China (2.88 %), Japan (1.87 %), and Korea (0.94 %). Meanwhile, feed-back effect to Indonesian economy was only 0.15 per cent. Panel-D presents Spill-Over and Feed-Back linkages in Indonesian economy for year 2014. In year 2014, total output multiplier in Indonesian economy was 2.1447; 79.36 per cent occurred in own country and 20.64 per cent occurred in other countries. This means that 20.64 per cent of total output multipliers spilled-over to other countries.
In this year, multiplier occurred in (spill-over to) China was increased to 4.35 per cent, multiplier occurred in India increased to 0.39 per cent, in Korea increased to 1.15 per cent, in Taiwan increased to 0.43 per cent, and the United States increased to 0.54 per cent. However, multipliers occurred in Japan, and Australia was decreased consecutively to 1.61 and 0.45 per cent. Three important countries received highest spill-over effect from Indonesia, namely: China (4.35 %), Japan (1.61 %), and Korea (1.15 %). Meanwhile, feed-back effect to Indonesian economy was only 0.15 per cent.
Inter-Country Feed-back (ICFB) index and Feed-back and Spill-over (FBSO) indices indicate the importance of inter-country connection for a country could be shown by calculating output forthcoming from sectors in a country in response to a change in that county's final demands. The overall percentage error of ignoring inter-country linkages is measured by ICFB and FBSO indices. Table 5

Discussion
This section highlights some important findings. Firstly, in Indonesian economy BL was stronger than FL. There were more sectors with BL > 1 (Group-3) than sector with FL > 1 ( .

Conclusions
From results and discussion it could be concluded that firstly sectoral-linkages through forward and backward analysis were important method in determining key sectors, but ignoring spill-over and feed-back effects could be misleading. It is suggested that sectors included in Group-1 be prioritized in economic development because they havestrong BL and FL as well. Secondly, spatial or inter-country spill-over and feed-back effects were significantly important in Indonesian economy. Ignoringinter-country input-output model will be resulting significant As the spill-over from Indonesia to China tend to increase the year of study, a trade policy between Indonesia and China should be formulated carefully.

Acknowledgement
Authors thank to the Editors and two anonymous reviewers for their valuable comments on earlier versions of the paper.