# **1 Introduction**

A large literature in macroeconomics and development explores the ‘misallocation’ of resources across firms, i.e., dispersion in static marginal products of inputs, and the implications for crosscountry differences in aggregate productivity and per capita income/output.<sup>1</sup> Because marginal products are not directly observed, the extent of such misallocation is typically inferred from dispersion in the _average_ product of these inputs (revenue or value-added/input ratios) – under standard assumptions, the dispersions in the two are identical (for example, with common production technologies and demand elasticities). Recently, attention has turned towards examining the role of particular factors in generating the observed misallocation. Examples include technological frictions such as adjustment costs or imperfect information, unobserved heterogeneity at the firm level, for example, in production technologies or markups, as well as firm-specific ‘distortions’ stemming from economic policies or other institutional features.<sup>2</sup> From a policy standpoint, disentangling the role of these forces is paramount – any prescription for economic reforms aimed at reducing misallocation must be based on a careful understanding of the underlying determinants and nature – e.g., efficient or inefficient – of the observed average product dispersion.

In a recent contribution, David and Venkateswaran (2017) develop an empirical methodology to disentangle a number of sources of _measured_ capital misallocation – dispersion in the average (revenue) product of capital ( _arpk_ ) – using observable data on firm revenues (or value-added) and inputs. This paper applies their method to a number of countries, with a particular focus on developing ones. Specifically, we use the Orbis database in conjunction with a number of country-specific firm-level censuses/surveys to compile data for 11 countries – nine developing and two developed (Japan and the US) – and implement that methodology on this set of countries. In addition to furthering our understanding of the sources of capital misallocation, our analysis also aims to provide a broader perspective on firm investment dynamics in these countries, which may help to guide future research.

The essence of the method in David and Venkateswaran (2017) is that by targeting an appropriately chosen set of moments, one can jointly estimate the contributions of capital adjustment costs, firm-level uncertainty and a broad class of other firm-specific factors to observed _arpk_ dispersion. This class includes factors that are correlated with firm fundamentals, e.g., productivity or demand, as well as those orthogonal to fundamentals. The latter can be further

> 1Seminal contributions include Hsieh and Klenow (2009) and Restuccia and Rogerson (2008). Restuccia and Rogerson (2017) and Hopenhayn (2014) provide excellent recent overviews of this line of work. 2See, e.g., work by Asker et al. (2014) on adjustment costs, Buera, Kaboski, and Shin (2011), Moll (2014), Gopinath et al. (2017) and Midrigan and Xu (2014) on financial frictions, David et al. (2016) on uncertainty and Peters (2016) on markup dispersion.  Following  Hsieh and Klenow (2009) and Restuccia and Rogerson (2008),    a large number of studies focus on the role of distortions along the lines that we model here.

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