In recent decades, technological progress in information and communication technology and falling trade barriers have led to the emergence of global value chains. Research and development, design, production of parts, assembly, marketing, and branding – previously performed in close proximity – are increasingly fragmented across firms and countries. As a result, trade in intermediate inputs now accounts for as much as two-thirds of international trade (Johnson and Noguera 2012).
A key organisational decision faced by firms is which segments of their production processes to own and which to outsource. Although the global fragmentation of production has featured prominently in the trade literature, much less attention has been placed on the importance of the position of a given production stage in the value chain for firm boundary choices. Recent studies have examined how the sequentiality of production affects firms' organisational decisions, but mostly from a theoretical perspective (e.g., Harms et al 2012, Baldwin and Venables 2013, Costinot et al 2013, Antràs and Chor 2013, Kikuchi et al 2014, Fally and Hillberry 2014). Testing these theories has been challenging due to the lack of comprehensive datasets tracking the flow of goods within value chains across borders and organisational forms.
In a recent paper, we take a first step to empirically examine firms’ organisational choices along value chains (Alfaro et al 2015). Building on Antràs and Chor (2013), we develop a rich theoretical framework of firm behaviour amenable to estimation using firm-level data. We describe an incomplete-contracts model in which the manufacturing of final goods entails a large number of production stages that need to be performed in a predetermined order. Suppliers provide the different stages by undertaking relationship-specific investments to make their components compatible with those of other suppliers in the value chain. We allow for heterogeneity in the importance of inputs for production, as well as in the marginal cost of production faced by suppliers at different points along the value chain.
To bring the model to the data, we use WorldBase, a comprehensive plant-level dataset that provides information on the activities of firms located in many countries and territories. Plants belonging to the same firm can be linked via information on domestic and global parents using a unique identification number. Our main sample consists of more than 300,000 manufacturing firms in 116 countries. For each plant, WorldBase provides information about its primary production activity and secondary activities. To distinguish between integrated and non-integrated inputs, we combine this information with Input-Output tables (see also Acemoglu et al 2009 and Alfaro et al 2013). We also use Input-Output tables to construct a new measure of the position of different industries along the value chain. This measure is industry-pair specific and captures the ‘upstreamness’ of each input i in the production of output in sector j. Figure 1 provides an illustration of the variation contained in this measure, when focusing on one particular input industry, Tires and Inner Tubes (SIC 3011). Notice that the upstreamness measure is smaller for industries that use tires almost exclusively as a direct input, such as Mobile Homes (2451), Lawn and Garden Equipment (3524), Industrial Trucks and Tractors (3537), Motorcycles, Bicycles, and Parts (3751), and Transportation Equipment (3799). This new measure is distinct and more informative than the one developed in Antràs et al (2012), which restricted attention to the distance of an input relative to final demand (see the horizontal line in Figure 1 for the case of Tires).
Figure 1. Upstreamness of tires (SIC 3011) in the production of all other manufacturing industries
The richness of our data allows us to exploit variation in the organisation of different firms, as well as within firms across their manufacturing stages. In line with the key prediction of our theoretical model, we find that a firm's propensity to integrate upstream (as opposed to downstream) inputs depends crucially on the relative size of the elasticity of demand for the firm's final good and the elasticity of substitution across its production stages. The higher the demand elasticity faced by the firm relative to the substitutability of its inputs, the more likely it is that the firm will outsource upstream suppliers rather than downstream ones. The intuition for this result is that, when the demand is elastic or inputs are not particularly substitutable, input investments are sequential complements; that is, the marginal incentive of a supplier to undertake relationship-specific investments is higher, the larger are the investments by upstream suppliers. In this case, the firm finds it optimal to contract at arm’s length with upstream suppliers in order to incentivise their investment effort, while integrating the most downstream stages to capture surplus. When demand is inelastic or inputs are sufficiently substitutable, input investments are instead sequential substitutes; that is, investments by upstream suppliers lower the investment incentives of downstream suppliers. When this is the case, the firm chooses to integrate relatively upstream stages, while engaging in outsourcing with downstream suppliers.
This result is illustrated in a simple (unconditional) form in Figure 2, which illustrates the average upstreamness of integrated inputs (left panel) and non-integrated inputs (right panel) for different quintiles of the parent firm's elasticity of demand. Notice that integrated inputs tend to be more upstream when the parent company belongs to an industry characterised by lower demand elasticity. Conversely, the upstreamness of non-integrated stages is greater the higher the elasticity of demand faced by the parent's final good. This pattern is robust in the regression analysis, even when controlling for a comprehensive list of parent firm characteristics (e.g. size, age, employment, sales), using different measures of the demand elasticity, as well as in different samples of firms (e.g., restricting to single-plant firms or multinationals). We also show that our results hold in specifications where the elasticity of demand is replaced by the difference between this same elasticity and a proxy for the degree of input substitutability associated with the firm's production process. We reach a similar conclusion when we exploit within-firm variation in integration patterns. In these specifications, we find that a firm's propensity to integrate is generally larger for downstream inputs, but disproportionately so for firms facing high demand elasticities.
Figure 2. Average upstreamness of integrated and non-integrated production stages, by quintile of parent's demand elasticity
We also construct a measure of input contractibility for each SIC industry (following Nunn 2007) and examine how firms' ownership decisions are shaped by the degree of contractibility of upstream versus downstream inputs. We find that a greater degree of contractibility of upstream inputs increases the likelihood that a firm integrates upstream inputs, when the firm faces a high elasticity of demand (both in absolute terms, as well as relative to our proxy for input substitutability). This result is also in line with the predictions of our theoretical model, according to which greater upstream contractibility reduces a firm's need to rely on organisational decisions and arrangements to elicit the right incentives from suppliers positioned at early stages in the value chain.
The firm-level empirical patterns that we uncover in our analysis provide strong evidence that considerations driven by contractual frictions are critical in shaping the integration choices of firms along their value chains.
Alfaro, L, P Antràs, D Chor and P Conconi (2015) “Internalizing global value chains: A firm-level analysis,” CEPR Discussion Paper 10837; NBER Working Paper 21582.
Alfaro, L, P Conconi, H Fadinger and A Newman (2013) “Do prices determine vertical integration?” Review of Economic Studies, forthcoming.
Antràs, P and D Chor (2013) “Organizing the global value chain”, Econometrica, 81(6): 2127-2204.
Antràs P, D Chor, T Fally and R Hillberry (2012) “Measuring the upstreamness of production and trade flows”, American Economic Review Papers & Proceedings, 102(3): 412-416.
Baldwin, R and A Venables (2013) “Spiders and snakes: Offshoring and agglomeration in the global economy”, Journal of International Economics, 90(2): 245-254.
Broda, C and D Weinstein (2006) “Globalization and the gains from variety”, Quarterly Journal of Economics, 121(2): 541-585.
Costinot, A, J Vogel and S Wang (2013) “An elementary theory of global supply chains”, Review of Economic Studies, 80(1): 109-144.
Fally, T and R Hillbery (2014) “A Coasian model of international production chains”, mimeo.
Johnson, R C and G Noguera (2012) “Accounting for intermediates: Production sharing and trade in value added”, Journal of International Economics, 86(2): 224-236.
Kikuchi, T, K Nishimura and J Stachurski (2014) “Transaction costs, span of control and competitive equilibrium”, mimeo.
Nunn, N (2007) “Relationship-specificity, incomplete contracts and the pattern of trade”, Quarterly Journal of Economics, 122(2): 569-600.