Indias Linkages into Global Value Chains: Role of Imported Services - PowerPoint PPT Presentation

India’s Linkages into Global Value Chains: Role of Imported Services Bishwanath Goldar, Rashmi Banga and Karishma Banga

Context and Structure of the Paper  Growing trade under GVCs  India is lagging behind in linking into GVCs - comparatively lower forward and backward linkages (Gupta 2015 and Goldar et al 2017).  While studies have examined the role of services in GVCs and in the context of India have estimated India’s linkages in GVCs, very few studies have focussed on the impact of imported services on export competitiveness.  This paper compares India’s services foreign value added (FVA) in its exports of manufactures with other developing countries; compares across industries and kinds of services imported; estimates the impact of imported services on export intensity of the firms; and derives policy implications.

Quick Review of Existing Studies on Role of Services in GVCs  Increasing “servicification” of manufacturing and rising product digitalisation  Services are involved in the establishment stage, pre-manufacturing stage, manufacturing stage as well as post-manufacturing stage; besides others such as after-sales service and back-office and recurrent services- ‘Glue ‘ to make GVCs work!  A case study of value chain for supply of construction machinery -5 services enter in the establishment stage, 10 in pre-manufacturing stage, 15 in manufacturing stage, and 7 in post-manufacturing stage. In addition, there is requirement for back-office and recurrent services, totalling 25 in number and after-sales services which add up to 10 services (Low and Pasadilla, 2015). –’smiley curve’  The incidence of services input is the largest for the back-office and recurrent services category followed by services used for the manufacturing stage- together account for more than 50% of the services used by manufactured products.  Out the 22 case studies - in-house provision was more than 50% in only three cases, and more than 60% in only one case. This shows that services used by manufacturing firms are mostly outsourced .

In 2011, the imported content of services in exports of manufactures in the world  amounted to around 31% (estimated using TiVA 2016). India’s imported content of services in its exports of manufactures has remained  comparatively much lower, amounting to around 13% in the same year. Table 1: Imports of Services in Exports of Manufactures: 2011 1995 2000 2005 2008 2009 2010 2011 Brazil 4 6 6 6 5 6 6 China (People's Republic of) 24 23 22 18 18 18 18 India 5 6 9 10 11 11 13 Indonesia 9 10 9 8 7 7 7 Malaysia 19 28 25 23 23 21 22 Philippines 19 17 20 16 15 14 11 Singapore 24 25 25 23 24 24 23 Thailand 15 18 19 20 19 19 20 Viet Nam 15 18 20 21 20 19 20

Table 2: Percentage of Foreign Value Added by Services in Exports of Manufactures: 2014 (Methodology- WIOD- using ‘ decompr ’ package in R, developed by Quast and Kummritz (2015), Brazil China Indonesia Russia India 8 8 8 4 11 Manufacture of basic metals 18 9 15 23 Manufacture of basic pharmaceutical products 11 8 10 7 10 Manufacture of chemicals and chemical products 14 10 5 4 21 Manufacture of coke and refined petroleum products 28 24 48 26 19 Manufacture of computer, electronic and optical products 17 15 26 14 Manufacture of electrical equipment 10 9 12 13 Manufacture of fabricated metal products 14 22 9 19 13 Manufacture of food products, beverages and tobacco 27 23 47 33 20 Manufacture of furniture; other manufacturing 22 16 32 19 20 Manufacture of machinery and equipment n.e.c. 20 10 14 51 24 Manufacture of motor vehicles, trailers and semi-trailers 6 6 8 4 7 Manufacture of other non-metallic mineral products 62 29 13 59 Manufacture of other transport equipment 7 9 9 6 8 Manufacture of paper and paper products 9 9 12 11 10 Manufacture of rubber and plastic products 8 22 51 26 13 Manufacture of textiles, wearing apparel and leather Manufacture of wood and of products of wood and cork, 5 9 5 5 5 except furniture; manufacture of articles of straw

 While, services FVA in exports of manufactures has been found to be comparatively low in the case of India, an important question that arises is whether lower services imports can adversely impact the export-intensity of Indian firms?

Firm-Level Analysis  The firm level analysis is based on Prowess database of CMIE. Data for manufacturing firms for the years 2000-01 to 2014-15 are used for the analysis. The number of firms in the dataset is mostly between 3000 to 5000 firms in different years.  The main question investigated : Is the extent of use of service input, particularly imported services, a significant factor determining export competitiveness of the Indian manufacturing firms?  A related question : does relatively low use of imported services adversely impact export intensity of Indian firms?  Two econometric models are estimated: one explains export intensity for firms (model- A), the other explains firms’ export status, i.e. exporting or not exporting (model-B).

Key explanatory variables in the estimated models  Total factor productivity (TFP) - measured by the Levinsohn- Petrin method  Services input to sales ratio, and the share of imported services in total services used  Lagged export status or lagged export intensity  Other explanatory variables include: firm size, imported raw materials and stores and spares (RMSS) intensity, and financial constraint faced by firms – leverage and liquidity. Extension of Melitz (2003) model by incorporating financial constraints faced by firms as an additional factor determining firms’ decision to enter export markets (Chaney, 2005; Muuls, 2008; Manova, 2013).

Model-A, explaining export intensity  𝐹𝑦𝑞𝑝𝑠𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧 𝑗𝑢 =  1 𝐹𝑦𝑞𝑝𝑠𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧 𝑗,𝑢−1 +  2 𝐹𝑦𝑞𝑝𝑠𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧 𝑗,𝑢−2 +  𝑚𝑝𝑕(𝑈𝐺𝑄) 𝑗,𝑢−1 +  𝑚𝑝𝑕(𝑇𝑓𝑠𝑤𝑗𝑑𝑓𝑡 𝑗𝑜𝑞𝑣𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧) 𝑗,𝑢−1 +  {𝑚𝑝𝑕 𝑇𝑓𝑠𝑤𝑗𝑑𝑓𝑡 𝑗𝑜𝑞𝑣𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧 ∗ 𝑚𝑝𝑕(𝐽𝑛𝑞𝑝𝑠𝑢𝑓𝑒 𝑡𝑓𝑠𝑤𝑗𝑑𝑓 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧) 𝑗,𝑢−1 } +  𝑎 𝑗,𝑢 +  𝑌 𝑗,𝑢−1 + 𝑏 𝑢 + 𝑣 𝑗𝑢 …(1) The System Generalised Method of Moments (GMM) estimator is applied for estimating the above empirical model. The estimation issues are: Unobserved firm characteristics can be correlated with both export intensity and services input intensity, leading to omitted variable bias. The results can also be biased if there are unobserved time- invariant firm effects correlated with the regressors in the model. The biases caused by persistency in the dependent variable and endogeneity in the model are both addressed by the System GMM estimator.

Model-B, explaining export status (export decision)  𝐹𝑦𝑞𝑝𝑠𝑢 𝑡𝑢𝑏𝑢𝑣𝑡 𝑗𝑢 =  1 𝐹𝑦𝑞𝑝𝑠𝑢 𝑡𝑢𝑏𝑣𝑢𝑡 𝑗,𝑢−1 +  2 𝐹𝑦𝑞𝑝𝑠𝑢 𝑡𝑢𝑏𝑢𝑣𝑡 𝑗,𝑢−2 +  𝑚𝑝𝑕(𝑈𝐺𝑄) 𝑗,𝑢−1 +  𝑚𝑝𝑕(𝑇𝑓𝑠𝑤𝑗𝑑𝑓𝑡 𝑗𝑜𝑞𝑣𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧) 𝑗,𝑢−1 +  {𝑚𝑝𝑕 𝑇𝑓𝑠𝑤𝑗𝑑𝑓𝑡 𝑗𝑜𝑞𝑣𝑢 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧 ∗ 𝑚𝑝𝑕(𝐽𝑛𝑞𝑝𝑠𝑢𝑓𝑒 𝑡𝑓𝑠𝑤𝑗𝑑𝑓 𝑗𝑜𝑢𝑓𝑜𝑡𝑗𝑢𝑧) 𝑗,𝑢−1 } +  𝑎 𝑗,𝑢 +  𝑌 𝑗,𝑢−1 + 𝑏 𝑢 + 𝑣 𝑗𝑢 …(2) The dependent variable is a zero-one variable reflecting the firms’ export status (taking value one if firm i exports in year t , and zero otherwise). With the dependent variable being taken as a dichotomous, the lagged dependent variable, lagged by one year and two years, has been defined accordingly. This model has been estimated by applying dynamic panel probit. 𝑎 𝑗,𝑢 is a vector of firm level control variables measured at time 𝑢, such as log(age), log(size) and log (capital/labour ratio) of the firm, 𝑌 𝑗,𝑢−1 is a vector of controls measured at time t -1 such as log (imported capital goods intensity), log(R&D intensity), and log(imported raw materials and stores and spares [RM&SS] intensity).

Framework of analysis  Many firm-level studies on export behaviour in India in the last 10 to 15 years have used variants of Model B for testing the “self - selection” hypothesis.  The self-selection hypothesis is essentially based on the idea that there is heterogeneity among firms in terms of productivity, and it is the better firms (in terms of productivity) which self-select themselves into export activity. [Melitz , 2003; Bernard et al., 2003; Barnard and Jenson,1999, 2006]. Wide empirical support to this hypothesis.  Typically, export status of a particular firm in a particular year is taken as a function of its export status in the previous year (reflecting sunk cost) and lagged productivity (reflecting firm heterogeneity) along with other controls.