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Empirical evidence demonstrates that credit standards, including lending margins and collateral requirements, move in a countercyclical direction. In this study, we construct a small open economy model with financial frictions to generate the countercyclical movement in credit standards. Our analysis demonstrates that countercyclical fluctuations in credit standards work as an amplifier of shocks to the economy. In particular, the existence of endogenous credit standards increases output volatility by 21%. We also suggest three alternative tools for policymakers to dampen the effects of endogenous credit standards on macroeconomic volatility. First, the introduction of credit growth to the monetary policy succeeds in counteracting the fluctuation of lending, and thus decreasing the additional volatility considerably. Second, the exchange rate augmented monetary policy, if well-constructed, is considered an efficient tool to eliminate most of the additional fluctuations caused by deep habits in the banking sector. Finally, the introduction of the foreign interest augmented policy also proves successful in dampening the effect of endogenous movements in lending standards.

In the context of a dynamic, stochastic, general equilibrium model, we perform classical maximum likelihood and Bayesian estimations of the contribution of anticipated shocks to business cycles in the postwar United States. Our identification approach relies on the fact that forward-looking agents react to anticipated changes in exogenous fundamentals before such changes materialize. It further allows us to distinguish changes in fundamentals by their anticipation horizon. We find that anticipated shocks account for about half of predicted aggregate fluctuations in output, consumption, investment, and employment.

This article reviews the literature on production networks in macroeconomics. It presents the theoretical foundations for the role of input-output linkages as a shock propagation channel and as a mechanism for transforming microeconomic shocks into macroeconomic fluctuations. The article also provides a brief guide to the growing literature that explores these themes empirically and quantitatively.

To counteract the adverse effects of shocks, such as the global pandemic, on the economy, governments have discussed policies to improve the resilience of supply chains by reducing dependence on foreign suppliers. In this paper, we develop and quantify an adaptive production network model to study network resilience and the consequences of reshoring of supply chains. In our model, firms exit due to exogenous shocks or the propagation of shocks through the network, while firms can replace suppliers they have lost due to exit subject to switching costs and search frictions. Applying our model to a large international firm-level production network dataset, we find that restricting buyer–supplier links via reshoring policies reduces output and increases volatility and that volatility can be amplified through network adaptivity.

We propose an aggregate growth index that explicitly accounts for fat tails in the firm size distribution and for the negative scaling relation between the size of the firm and the volatility of its growth rates. Using Compustat data on US publicly traded company, we show that the new index tracks aggregate fluctuations much better than simpler measures of central tendency of the dynamics of firms, like the growth rates sample average, confirming that the statistical properties characterizing the micro-economic dynamics of firms are relevant for the dynamics of the aggregate. To better characterize the origins of aggregate fluctuations, we decompose the index in two parts, describing, respectively, the modal (typical) value of log growth rates and the tilt (asymmetry) of their distribution. Regression analysis shows that models based on this decomposition, despite their simplicity, possess a remarkable explanatory and predictive power with respect to the aggregate growth.

We develop a theoretical model with labour market frictions, incomplete financial markets, and with households which have two members. Households face unemployment risks, but their members adjust their labour supplies to insure against unemployment. We use the model to explain the cyclical properties of aggregate employment and participation. As in the U.S. data, the model predicts that the participation rate (the fraction of individuals that want jobs) is not strongly correlated with aggregate economic activity. This property is in sharp contrast to the strongly procyclical participation predicted by both neoclassical models and models with search frictions, when we assume bachelor households or households with infinitely many members (complete markets). In the two-member household model and in the data, primary earners are always in the labour force, secondary earners have a mildly countercyclical participation rate, and a mildly procyclical employment rate. Their behaviour insures the household against unemployment risks.

Based on a multisector general equilibrium framework, we show that the sectoral elasticity of substitution plays the key role in the evolution of asymmetric tails of macroeconomic fluctuations and the establishment of robustness against productivity shocks. A non-unitary elasticity of substitution renders a nonlinear Domar aggregation, where normal sectoral productivity shocks translate into non-normal aggregated shocks with variable expected output growth. We empirically estimate 100 sectoral elasticities of substitution, using the time-series linked input-output tables for Japan and find that the production economy is elastic overall, relative to a Cobb-Douglas economy with unitary elasticity. In addition to the previous assessment of an inelastic production economy for the USA, the contrasting tail asymmetry of the distribution of aggregated shocks between the USA and Japan is explained. Moreover, the robustness of an economy is assessed by expected output growth, the level of which is led by the sectoral elasticities of substitution under zero-mean productivity shocks.

This paper studies the importance of shocks to the largest firms on the aggregate output. Using firm-level data on eight European countries (2006-2019), we find that shocks to the largest firms explain an important part of aggregate fluctuations. Our paper brings several novelties. Firstly, in addition to the aggregate level, we extend the analysis of the transmission of firm-level shocks to study the shocks at the sectoral level. Secondly, we provide a novel measurement for demand-side shocks within granularity. We show that idiosyncratic shocks affecting the largest 20 firms can explain almost half of the output volatility, which is consistent with Gabaix (2011). Moreover, demand-side shocks contribute a greater share to this volatility compared to supply-side shocks. Finally, we show that the smaller the sample of the largest firms, the larger the propagation effect of the shocks to GDP. This suggests that a few large firms drive a large part of the aggregate volatility, while volatility of other larger firms balances out on average.

This paper uses a data base covering the universe of French firms for the period 1990–2007 to provide a forensic account of the role of individual firms in generating aggregate fluctuations. We set up a simple multisector model of heterogeneous firms selling to multiple markets to motivate a theoretically founded decomposition of firms' annual sales growth rate into different components. We find that the firm-specific component contributes substantially to aggregate sales volatility, mattering about as much as the components capturing shocks that are common across firms within a sector or country. We then decompose the firm-specific component to provide evidence on two mechanisms that generate aggregate fluctuations from microeconomic shocks highlighted in the recent literature: (i) when the firm size distribution is fat-tailed, idiosyncratic shocks to large firms directly contribute to aggregate fluctuations, and (ii) aggregate fluctuations can arise from idiosyncratic shocks due to input—output linkages across the economy. Firm linkages are approximately three times as important as the direct effect of firm shocks in driving aggregate fluctuations.

We estimate a dynamic stochastic general equilibrium (DSGE) model with several frictions and both unanticipated and news shocks, using quarterly U.S. data from 1954 to 2004 and Bayesian methods. We find that unanticipated shocks dominate news shocks in accounting for the unconditional variance of output, consumption, and investment growth, interest rate, and the relative price of investment. The unanticipated shock to the marginal efficiency of investment is the dominant shock, accounting for over 45% of the variance in output growth. News shocks account for less than 15% of the variance in output growth. Within the set of news shocks, nontechnology sources of news dominate technology news, with wage markup news shocks accounting for about 60% of the variance share of both hours and inflation. We find that in the estimated DSGE model (i) the presence of endogenous countercyclical price and wage markups due to nominal frictions substantially diminishes the importance of news shocks relative to a model without these frictions, and (ii) while there is little change in the estimated contributions of technology news when we restrict wealth effects on labor supply, the contributions of nontechnology news shocks are relatively more sensitive.