Misallocation in the Market for Inputs: Enforcement and the Organization of Production

Abstract

The strength of contract enforcement determines how firms source inputs and organize production. Using microdata on Indian manufacturing plants, we show that production and sourcing decisions appear systematically distorted in states with weaker enforcement. Specifically, we document that in industries that tend to rely more heavily on relationship-specific intermediate inputs, plants in states with more congested courts shift their expenditures away from intermediate inputs and appear to be more vertically integrated. To quantify the impact of these distortions on aggregate productivity, we construct a model in which plants have several ways of producing, each with different bundles of inputs. Weak enforcement exacerbates a holdup problem that arises when using inputs that require customization, distorting both the intensive and extensive margins of input use. The equilibrium organization of production and the network structure of input-output linkages arise endogenously from the producers' simultaneous cost minimization decisions. We identify the structural parameters that govern enforcement frictions from cross-state variation in the first moments of producers' cost shares. A set of counterfactuals show that enforcement frictions lower aggregate productivity to an extent that is relevant on the macro scale. 2 These are also closely related to models of global value chains and global sourcing such as Costinot, Vogel and Wang (2012), Fally and Hillberry (2015), Antràs and de Gortari (2017), Antras, Fort and Tintelnot (2017). 2 the industry environment and the choices of other producers. Our paper is also closely related to the literature on misallocation in developing countries (see Hopenhayn (2014) for a survey). Several papers have extended the work of Hsieh and Klenow (2009) to settings in which distortions affect the use of intermediate inputs, e.g., Jones (2013), Bartelme and Gorodnichenko (2014), Fadinger, Ghiglino and Teteryatnikova (2016), Bigio and La'O (2016), Caprettini and Ciccone (2015), Liu (2017), Caliendo, Parro and Tsyvinski (2017), Osotimehin and Popov (2017), and Baqaee and Farhi (2017). These papers typically posit industry-level production functions and use industry-level data. Our approach of identifying wedges from factor shares (in our case, intermediate input expenditure shares) extends the work of Hsieh and Klenow (2009) along three key dimensions. First, we relate the estimated wedges to the quality of Indian statelevel institutions, which allows us draw policy conclusions from our exercise. Second, we confront the fact that firms produce in very different ways even in narrowly defined industries by explicitly modeling this heterogeneity; we allow firms to choose among several types of technologies (recipes) in the theory and identify these recipes in the data through the application of techniques from statistics/data mining. Third, we identify wedges from systematic differences in first moments, which helps to alleviate concerns about mismeasurement being interpreted as misallocation....

Endogenous Production Networks

“…Third, it is not a consequence of proportionately more products or innovations arriving over time (as is the case in Romer (1990), Jones (1995), Eaton and Kortum (2001), or Klette and Kortum (2004)). More closely related to our paper are the important prior work by Oberfield (2017), independent contemporaneous work by Taschereau-Dumouchel (2017), and more recent work by Boehm and Oberfield (2018). Finally, it is also not due to thick-tailed productivity draws that continuously improve technology and spreading in the economy via a diffusion process (as in Akcigit, Celik, and Greenwood (2016), Lucas (2009), Lucas and Moll (2014), or Perla and Tonetti (2014)).…”

“…This might be because of customer-specific taxes or because of contracting frictions that apply between some customer-supplier pairs (see Boehm and Oberfield (2018), for a model of such frictions). This might be because of customer-specific taxes or because of contracting frictions that apply between some customer-supplier pairs (see Boehm and Oberfield (2018), for a model of such frictions).…”

“…Atalay, Hortaçsu, and Syverson (2011) study the choice of suppliers at the firm level. More closely related to our paper are the important prior work by Oberfield (2017), independent contemporaneous work by Taschereau-Dumouchel (2017), and more recent work by Boehm and Oberfield (2018). Oberfield constructs an elegant model of the endogenous evolution of the input-output architecture, but with two notable differences from our work.…”

“…Fourth, it is not driven by proportional improvements in the productivity of all industries as in quality-ladder models (as in Aghion and Howitt (1992) or Grossman and Helpman (1991)). Subsequent work by Boehm and Oberfield (2018) constructs a firm-level model of input choices and estimated it on microdata. Crucially, even though the distribution of productivity across different input mixes is thick-tailed in our economy, this by itself does not lead to sustained growth.…”

“…Relatedly,Boehm and Oberfield (2018) documented large differences in firm supply chains across different states of India. 4 For example, in OECD data, the input-output matrices of more advanced economies such as the United States or Germany are denser than those of developing economies such as Mexico or Argentina (http://www.…”