Understanding differences in economic performance across countries has always been one of the great challenges in economics. Until recently, efforts to address this question relied mostly on aggregate data, often computing productivity as country residuals. The availability of firm-level data revolutionised the field by showing that productivity varies enormously even across firms within countries, and that this rich heterogeneity at the micro level has important consequences for aggregate statistics (see Baqaee and Farhi 2017 for a recent example). Yet, due to the lack of comprehensive and comparable data, existing studies have been confined to just a handful of countries (e.g. Bartelsman et al. 2013). As a result, there is still little systematic evidence to date on the role of firms in explaining country performance. In a recent work (Bonfiglioli et al. 2018c), we fill this gap by using detailed import data to compare firms from virtually all countries in the world competing in the US market, and show how the distribution of their characteristics shapes the observed aggregate sales. We then study, for the first time, how the distribution of firm-level characteristics varies across countries and explore some of its determinants.
Decomposing sales: Firms, attributes, and heterogeneity
Following recent methodological contributions, we show that data on unit values and volumes of imports in a single destination market, together with a few commonly-used assumptions, are sufficient to decompose the market shares captured by each country into the characteristics of the underlying firms (Hottman et al. 2016, Redding and Weinstein 2018a). In particular, CES preferences together with estimates of the elasticities of substitution across varieties in an industry provide a mapping from sales to two firm-level attributes: unit prices, which are observed; and a residual demand shifter, often interpreted as ‘quality’. We apply this methodology to a unique transaction-level dataset on US imports in 2002 and 2012 containing information on quantities, values, and the identity of exporting firms for 3500 (six-digit) products from 104 countries. We then perform a number of decompositions aimed at understanding how firms shape trade flows.
As a first step, we compute the variation in imports explained by an extensive margin (the number of firm-products per country) and an intensive margin (the average sales per firm-product in a given country). This decomposition, which we implement across 366 (four-digit) industries, shows that each margin accounts on average for half of the overall variation in market shares.
In a second step, we decompose average sales per firm-product in a country-industry-year triplet into two parts: the average ‘appeal’ of the firm-product, defined as quality relative to price; and a ‘heterogeneity’ term, capturing the dispersion of appeal around its mean. Intuitively, countries with more appealing firm-products capture larger market shares. However, dispersion also affects the total value of sales because consumers can substitute low-appeal products for high-appeal products. We show that when the elasticity of substitution between products is higher than two (as our structural estimates confirm for most sectors), more dispersion, such as having few superstar firms, implies larger sales than a more uniform distribution. We find that the heterogeneity term explains roughly half of the cross-country variation in average sales per firm-product.
In a third step, we decompose appeal into its two components: prices and quality. We find that quality explains between 75% and 100% of the variation in appeal across firm-products, while prices matter little. In sum, our exercise shows that countries capturing larger US market shares have more exporters, producing higher-quality products with a more dispersed distribution. These results are broadly consistent with recent findings by Redding and Weinstein (2018b), who perform a complementary decomposition of trade flows using different import data for the US and Chile.
Understanding firm heterogeneity
Our findings suggest that heterogeneity in firm attributes plays an important role in explaining economic performance, a role which is, however, masked in aggregate statistics. Given that this term is often neglected and poorly understood, we take further steps towards studying its determinants.
We start by presenting a number of novel facts about the cross-country and cross-industry variation in the dispersion of sales and other firm-level variables, computed separately for each country-industry-year triplet. We find that sales dispersion, measured by the variance of log sales, varies markedly across countries and industries, and has increased on average by 10% between 2002 and 2012. Quality dispersion shows similar patterns, while price dispersion is relatively small, exhibits a low cross-sectional variation, and has remained stable over time. We then study how heterogeneity varies with country characteristics. We find that measures of market size – namely, GDP per capita, population, and distance from the US – are on average associated with a higher dispersion of sales and firm attributes, especially due to heterogeneity in quality. Hence, contrary to a widespread belief, our results show that firms from richer countries are more unequal.
Next, we ask whether these results are driven by superstar firms, which are known to dominate trade volumes. We do find that the incidence of such firms is also positively correlated with measures of market size. Yet, the correlation between the heterogeneity term and market size is not driven by superstar firms, as it holds even when they are removed from the sample. To further explore the role of exceptional firms, we impose additional theoretical restrictions. Assuming that attributes follow log-normal distributions, with parameters that can differ across countries and sectors, we develop a novel decomposition that separates the role of heterogeneity (i.e. smooth variation in attributes across a large number of firms), from that of granularity (i.e. exceptional performance in a small sample). Surprisingly, we find once again that although top firms are quantitatively important, granularity explains only about 5% of the observed variation in sales across countries and sectors.
Quantitative implications and conclusions
Besides playing an important role in explaining sales, does firm heterogeneity also matter for welfare? To address this question, we show that when attributes are log-normally distributed, the effect of firm heterogeneity on prices and welfare is a function of the variance of log sales. We then use this simple and easy-to-measure statistic to quantify the effect of changes in heterogeneity on price indexes. In particular, we show that lowering the variance of log sales by one standard deviation below the observed average implies a 40% increase in the price index of exporting firms. Moreover, the average increase in heterogeneity observed between 2002 and 2012 implies a 3% reduction in the price index in the average sector and country of origin.
Our results have important implications. From a policy perspective, they point towards an underexplored benefit of market size – larger markets host more diverse firms and seem to be a more fertile ground for superstars. From a theoretical perspective, our results confirm that product differentiation, varieties, and heterogeneity in quality are essential features to explain the data. Besides confirming the importance of firm heterogeneity, as in Melitz (2003), our results underscore the need for modelling differences in the distribution of attributes. They also beg the question of what mechanism might be generating them. Some possibilities include differences in the process of innovation (e.g. Bonfiglioli et al. 2018a, 2018b) and imitation (e.g. König et al. 2016), or in sorting patterns between firms, suppliers, and workers (e.g. Bonfiglioli and Gancia 2018, Sampson 2014). While identifying the exact mechanism that explains the distribution of attributes across firms is still an open challenge, our work has identified a set of empirical observations that successful theories should match.
Baqaee, David Rezza and Emmanuel Farhi (2017). "Productivity and Misallocation in General Equilibrium," NBER Working Paper No. 24007.
Bartelsman, Eric, John Haltiwanger and Stefano Scarpetta (2009). "Measuring and Analyzing Cross Country Differences in Firm Dynamics," in Dunne, Jensen and Roberts (eds), Producer Dynamics: New Evidence from Micro Data, University of Chicago Press, 15-76.
Bonfiglioli, A, R Crinò and G Gancia (2018a), "Betting on exports: Trade and endogenous heterogeneity", Economic Journal 128: 612--651.
Bonfiglioli, A, R Crinò and G Gancia (2018b), "Trade, finance and endogenous heterogeneity", Journal of the European Economic Association, forthcoming.
Bonfiglioli, A, R Crinò and G Gancia (2018c), "Firms and economic performance: A view from trade", CEPR, Discussion Paper 12829.
Bonfiglioli, A and G Gancia (2018), "Heterogeneity, selection and labor market disparities", Review of Economic Dynamics, conditionally accepted.
Hottman, C, S Redding and D Weinstein (2016), "Quantifying the sources of firm heterogeneity", Quarterly Journal of Economics 131: 1291–1364.
König, M D, J Lorenz and F Zilibotti (2016), "Innovation vs imitation and the evolution of productivity distributions", Theoretical Economics 11: 1053–1102.
Melitz, M J (2003), "The impact of trade on intra-industry reallocations and aggregate industry productivity", Econometrica 71: 1695–1725.
Redding, S and D Weinstein (2018a), "A unified approach to aggregate price and welfare measurement", NBER Working paper 22479.
Redding, S and D Weinstein (2018b), "Accounting for trade patterns", Working paper.
Sampson, T (2014), "Selection into trade and wage inequality", American Economic Journal: Microeconomics 6: 157–202.