This paper analyzes a general equilibrium economy featuring input‐output connections, imperfect competition, and external economies of scale owing to entry and exit. The interaction of input‐output networks with industry‐level market structure affects the amplification of shocks and the pattern of diffusion in the model, generating cascades of firm entry and exit across the economy. In this model, sales provide a poor measure of the systemic importance of industries. Unlike the relevant notions of centrality in competitive constant‐returns‐to‐scale models, systemic importance depends on the industry's role as both a supplier and a consumer of inputs, as well as the market structure of industries. A basic calibration of the model suggests that aggregate output is three times more volatile in response to labor productivity shocks when compared to a perfectly competitive model.

Abstract This paper develops a general theory of aggregation in inefficient economies. We provide nonparametric formulas for aggregating microeconomic shocks in economies with distortions such as taxes, markups, frictions to resource reallocation, financial frictions, and nominal rigidities. We allow for arbitrary elasticities of substitution, returns to scale, factor mobility, and input-output network linkages. We show how to separately measure changes in technical and allocative efficiency. We also show how to compute the social cost of distortions. We pursue applications focusing on firm-level markups in the United States. We find that improvement in allocative efficiency, due to the reallocation over time of market share to high-markup firms, accounts for about half of aggregate TFP growth over the period 1997–2015. We also find that eliminating the misallocation resulting from the large and dispersed markups estimated in the data would raise aggregate TFP by about 15%, increasing the economy-wide cost of monopoly distortions by two orders of magnitude compared with the famous 0.1% estimate by Harberger (1954). These exact numbers should be interpreted with care because the data are imperfect and require substantial imputation.

We study a flexible class of trade models with international production networks and arbitrary wedge‐like distortions like markups, tariffs, or nominal rigidities. We characterize the general equilibrium response of variables to shocks in terms of microeconomic statistics. Our results are useful for decomposing the sources of real GDP and welfare growth, and for computing counterfactuals. Using the same set of microeconomic sufficient statistics, we also characterize societal losses from increases in tariffs and iceberg trade costs and dissect the qualitative and quantitative importance of accounting for disaggregated details. Our results, which can be used to compute approximate and exact counterfactuals, provide an analytical toolbox for studying large‐scale trade models and help to bridge the gap between computation and theory.

We provide a nonlinear characterization of the macroeconomic impact of microeconomic productivity shocks in terms of reduced‐form nonparametric elasticities for efficient economies. We also show how microeconomic parameters are mapped to these reduced‐form general equilibrium elasticities. In this sense, we extend the foundational theorem of Hulten (1978) beyond the first order to capture nonlinearities. Key features ignored by first‐order approximations that play a crucial role are: structural microeconomic elasticities of substitution, network linkages, structural microeconomic returns to scale, and the extent of factor reallocation. In a business‐cycle calibration with sectoral shocks, nonlinearities magnify negative shocks and attenuate positive shocks, resulting in an aggregate output distribution that is asymmetric (negative skewness), fat‐tailed (excess kurtosis), and has a negative mean, even when shocks are symmetric and thin‐tailed. Average output losses due to short‐run sectoral shocks are an order of magnitude larger than the welfare cost of business cycles calculated by Lucas (1987). Nonlinearities can also cause shocks to critical sectors to have disproportionate macroeconomic effects, almost tripling the estimated impact of the 1970s oil shocks on world aggregate output. Finally, in a long‐run growth context, nonlinearities, which underpin Baumol's cost disease via the increase over time in the sales shares of low‐growth bottleneck sectors, account for a 20 percentage point reduction in aggregate TFP growth over the period 1948–2014 in the United States.

Abstract How does an increase in market size, say due to globalization, affect welfare? We study this question using a model with monopolistic competition, heterogeneous markups, and fixed costs. We characterize changes in welfare and decompose changes in allocative efficiency into three different effects: (1) reallocations across firms with heterogeneous price elasticities due to intensifying competition, (2) reallocations due to the exit of marginally profitable firms, and (3) reallocations due to changes in firms’ markups. Whereas the second and third effects have ambiguous implications for welfare, the first effect, which we call the Darwinian effect, always increases welfare regardless of the shape of demand curves. We nonparametrically calibrate demand curves with data from Belgian manufacturing firms and quantify our results. We find that mild increasing returns at the microlevel can catalyze large increasing returns at the macrolevel. Between 70 and 90% of increasing returns to scale come from improvements in how a larger market allocates resources. The lion’s share of these gains are due to the Darwinian effect, which increases the aggregate markup and concentrates sales and employment in high-markup firms. This has implications for policy: an entry subsidy, which harnesses Darwinian reallocations, can improve welfare even when there is more entry than in the first best.