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 We present a unified treatment of how welfare responds to changes in budget sets or technologies with taste shocks and nonhomothetic preferences. We propose a welfare metric that ranks production possibility frontiers that differs from one that ranks budget sets and characterize it using a general equilibrium generalization of Hicksian demand. This extends Hulten’s theorem, the basis for constructing aggregate quantity indices, to environments with nonhomothetic and unstable preferences. We illustrate our results using both long- and short-run applications. In the long run, we show that if structural transformation is caused by income effects or changes in tastes, rather than substitution effects, then Baumol’s cost disease is twice as important for our preferred measure of welfare. In the short run, we show that standard chain-weighted deflators understate welfare-relevant inflation for current tastes. Finally, using the COVID-19 recession, we illustrate that chain-weighted real consumption and real GDP are unreliable metrics for measuring welfare or production when there are taste shocks.

Consumer surplus, the area between the demand curve and the price, plays a key role in many models of trade and growth. Quantifying it typically requires estimating and extrapolating demand curves. This paper provides an alternative approach to measuring consumer surplus by focusing on firms as consumers of inputs. We show that the elasticity of a downstream firm's marginal cost to supplier additions and separations measures the downstream firm's consumer surplus relative to its input costs. Using Belgian data and instrumenting for changes in supplier access, we find that for every 1% of suppliers gained or lost, the marginal cost of downstream firms falls or rises by roughly 0.3%. Our estimates are directly informative about the strength of love‐of‐variety effects and the gains from movements along quality ladders. We use our microeconomic estimates of consumer surplus to assess the macroeconomic importance of supplier additions and separations in a growth accounting framework. We find that supplier churn plausibly accounts for about half of aggregate productivity growth.

Abstract The money metric utility function is an essential tool for calculating welfare-relevant growth and inflation. We show how to recover it from repeated cross-sectional data without making parametric assumptions about preferences. We do this by solving the following recursive problem. Given compensated demand, we construct money metric utility by integration. Given money metric utility, we construct compensated demand by matching households over time whose money metric utility value is the same. We illustrate our method using household consumption survey data from the United Kingdom from 1974 to 2017 and find that real consumption calculated using official aggregate inflation statistics overstates money metric utility in 1974 pounds for the poorest households by around 0.5% a year and understates it by around a third of a percentage point per year for the richest households. We extend our method to allow for missing or mismeasured prices, assuming preferences are separable between goods with well-measured prices and the rest. We discuss how our results change if the prices of some service sectors are mismeasured.

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.

We study supply and demand shocks in a disaggregated model with multiple sectors, multiple factors, input-output linkages, downward nominal wage rigidities, credit-constraints, and a zero lower bound. We use the model to understand how the COVID-19 crisis, an omnibus supply and demand shock, affects output, unemployment, and inflation, and leads to the coexistence of tight and slack labor markets. We show that negative sectoral supply shocks are stagflationary, whereas negative demand shocks are deflationary, even though both can cause Keynesian unemployment. Furthermore, complementarities in production amplify Keynesian spillovers from supply shocks but mitigate them for demand shocks. This means that complementarities reduce the effectiveness of aggregate demand stimulus. In a stylized quantitative model of the United States, we find supply and demand shocks each explain about one-half of the reduction in real GDP from February to May 2020. Although there was as much as 6 percent Keynesian unemployment, this was concentrated in certain markets. Hence, aggregate demand stimulus is one quarter as effective as in a typical recession where all labor markets are slack. (JEL E12, E23, E24, E31, E32, E62, I12)

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.

We propose a supply-side channel for the transmission of monetary policy. We show that when high-markup firms have lower pass-throughs than low-markup firms, then positive demand shocks, such as monetary expansions, alleviate cross-sectional misallocation by reallocating resources to high-markup firms. Consequently, positive ?demand shocks? are accompanied by endogenous positive ?supply shocks? that raise productivity and lower inflation. We derive a tractable, four-equation model where monetary shocks generate hump-shaped productivity responses. In our calibration, the supply-side effect amplifies the total impact of monetary shocks on output by about 70%. We provide empirical evidence validating our model?s predictions using identified monetary shocks.