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Balke et al. (2017)'s model integrates financial frictions-arising from asymmetric information and costly monitoring-and time-varying uncertainty into a medium-scale Dynamic New Keynesian model. The model includes monetary policy uncertainty, financial risks (micro-uncertainty), and aggregate macro-uncertainty in stochastic volatility form. In this paper, we provide the key derivations of the model as well as detailed information on the simulation and estimation approach employed. We use this modeling framework to thoroughly explore how uncertainty propagates and its interplay with financial frictions. We also investigate further how uncertainty affects the propagation of first-moment shocks (TFP and monetary policy shocks) and second-moment shocks with first-order effects (micro-uncertainty).

We examine the interaction of uncertainty and credit frictions in a New Keynesian framework. To do so, uncertainty is modeled as time-varying stochastic volatility-the product of monetary policy uncertainty, financial risk (micro-uncertainty), and macrouncertainty. The model is solved using a pruned third-order approximation and estimated by the Simulated Method of Moments. We find that: 1) Micro-uncertainty aggravates the information asymmetry between lenders and borrowers, worsens credit conditions, and has first-order effects on real economic activity. 2) When credit conditions are poor, as indicated by elevated credit spreads, additional micro-uncertainty shocks produce even larger real effects. 3) Poor credit conditions notably affect the transmission mechanism of monetary policy amplifying the real effects of monetary shocks while mitigating the economic boost from TFP shocks. 4) While macro-uncertainty and policy uncertainty exert relatively little direct impact on aggregate economic activity, policy uncertainty accounts for around 40% of the business cycle volatility by affecting the size of monetary policy shocks in the presence of nominal rigidities.

Balke et al. (2017)'s model integrates financial frictions-arising from asymmetric information and costly monitoring-and time-varying uncertainty into a medium-scale Dynamic New Keynesian model. The model includes monetary policy uncertainty, financial risks (micro uncertainty), and aggregate macro-uncertainty in stochastic volatility form. In this paper, we provide the key derivations of the model as well as detailed information on our simulation and estimation approach. We use this framework to identify how uncertainty propagates and its interplay with financial frictions. We also investigate how uncertainty affects the propagation of other shocks (in particular, the propagation of TFP and monetary policy shocks).

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This paper integrates a financial accelerator mechanism à la Bernanke et al. (1999) and timevarying uncertainty into a Dynamic New Keynesian model. We examine the extent to which uncertainty and credit conditions interact with one another. The idea is that uncertainty aggravates the information asymmetry between lenders and borrowers, and worsens credit conditions. Already poor credit conditions amplify the effect of shocks (to both the mean and variance) on the aggregate economy. In our model, uncertainty modelled as time-varying stochastic volatility emerges from monetary policy (policy uncertainty), financial risks (microuncertainty), and the aggregate state of the economy (macro-uncertainty). Using a third order approximation, we find that micro-uncertainty has first order effects on economic activity through its direct impact on credit conditions. We also find that if credit conditions (as measured by the endogenous risk spread) are already poor, then additional micro-uncertainty shocks have even larger real effects. In turn, shocks to aggregate uncertainty (macro-and policy-uncertainty) have relatively small direct effects on aggregate economic activity.

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In this paper I develop a dynamic stochastic general equilibrium model of credit frictions in which the production technology provides a U-shaped average cost curve, enabling endogenous solutions for firm size and quantity. Firms weigh the present value of future net revenues against the opportunity cost of staying in business in their entry or exit decisions. I find that credit frictions increase variable investment costs and result in a larger firm size and a smaller number of firms in the steady state. As the economy deviates from the steady state, however, the presence of credit frictions increases fluctuation in the number of firms, raising market entry during an economic upturn and market exit during a downturn. Also, I find that allowing free entry mitigates some of the effects of credit frictions due to macroeconomic fluctuations. In addition to the homogeneous-firm model, I examine the model when firms have heterogeneous access to credit and find that different credit access gives rise to different firm sizes in the steady state. Firms with easier access to credit become larger than those with less access to credit. Heterogeneous credit access also means that these two types of firms will respond differently to a common technology shock.