Recent literature has shown that the fraction of liquidity-constrained households in the population critically determines the mix of transmission channels of monetary policy. In this paper, we bring a different but important dimension of heterogeneity to the forefront: stock market participation. We show that the stock market participation rate not only shapes the mix of policy channels, but also heavily affects the aggregate responses. This happens as direct rebalancing effects and indirect equilibrium effects into investment are both increasing in the number of stock market participants, reinforcing each other. We show this in a quantitative New Keynesian model designed to account for the population share of stock market participants, their position in the income and wealth distribution and their saving rates. The model implies that, as stock market participation has increased since the 1980s, the power of monetary policy on the real economy has strengthened considerably.

Can the macroeconomic effects of credit supply shocks be large even when a small share of firms is credit-constrained? I use UK firm-level accounting data to discipline a heterogeneous-firm model where the interaction between real and financial frictions induces precautionary cash holdings. In the data, firms increased their cash ratios during the Great Recession, and cash-intensive firms displayed higher employment growth. A tightening of firms' credit conditions generates the same dynamics in the model. Unconstrained firms pre-emptively respond to credit supply shocks; this precautionary channel, when appropriately quantified, crucially matters for the aggregate dynamics and firm-level patterns.

We study the early stages of firm creation under imperfect information. Because startups make error-prone decisions due to rational inattention, the model generates both inefficient entry and labor misallocation. Ex-ante active learning of prospective entrepreneurs alters the effects of lump-sum transfers to startups: the total employment gain is amplified due to an unintended increase in inefficient entry, most entrants hire fewer workers, and misallocation goes up. The transfer makes low-size, previously dominated, actions profitable, affecting the entire endogenous learning problem and making even productive startups lean towards more conservative hiring. We show that this novel information channel works against well-known mechanisms (e.g., financial frictions), and thus can help reconcile recent empirical evidence on startup policies.

We propose a new, computationally efficient way to approximate the “grouped fixed-effects” (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the regularization parameter m approaches 1, the fuzzy clustering objective converges to the GFE objective; moreover, we recast this objective as a standard Generalized Method of Moments problem. We replicate the empirical results of Bonhomme and Manresa (2015) and show that our estimator delivers almost identical estimates. In simulations, we show that our approach delivers improvements in terms of bias, classification accuracy and computational speed.

We estimate the unconditional distribution of the marginal propensity to consume (MPC) using clustering regression and the 2008 stimulus payments. By deviating from the standard approach of estimating MPC heterogeneity using interactions with observables, we can recover the full distribution of MPCs. We find households spent between 4 and 133% of the rebate within a quarter, and individual households used rebates for different goods. While many observable characteristics correlate individually with our estimated MPCs, these relationships disappear when tested jointly, except for income and the average propensity to consume. Household observables explain only 8% of MPC variation, highlighting the role of latent heterogeneity.

When financial constraints bind, firms adjust employment in response to cash flow shocks. A 2010 revaluation of business rates, a UK tax levied on business-occupied properties, implied that similar firms, occupying similar properties in narrow geographical locations, experienced different tax changes. I find that, on average, for every £1 of additional cash flow triggered by the tax change, 39 pence were spent on employment, with small and leveraged firms responding the most. A general equilibrium model with firm heterogeneity and financial frictions rationalizes these findings, and quantitatively determines the aggregate effects of a fiscal transfer to firms.

Using detailed micro data, we document that households often use "stimulus'' checks to pay down debt, especially those with low net wealth-to-income ratios. To rationalize these facts, we introduce a borrowing price schedule into an otherwise standard incomplete markets model. Because interest rates rise with debt, borrowers have increasingly larger incentives to use an additional dollar to reduce debt service payments rather than consume. Using our calibrated model, we then study whether and how this marginal propensity to repay debt (MPRD) alters the aggregate implications of fiscal transfers. We uncover a trade-off between stimulus and insurance, as high--debt individuals gain considerably from transfers, but consume relatively little immediately. We show how this mechanism can lower short-run fiscal multipliers, but sustain aggregate consumption for longer.

We extend time-series models that have so far been used to study price inflation (Stock and Watson (2016)) and apply them to a micro-level dataset containing worker-level information on hourly wages. We construct a measure of aggregate nominal wage growth that (i) filters out noise and very transitory movements, (ii) quantifies the importance of idiosyncratic factors for aggregate wage dynamics, and (iii) strongly co-moves with labor market tightness, unlike existing indicators of wage inflation. We show that our measure is a reliable real-time indicator of wage pressures and a good predictor of future wage growth. 

This paper presents empirical evidence on the nature of idiosyncratic shocks to firms and discusses its role for firm behavior and aggregate fluctuations. We document that firm-level sales and productivity are hit by heavy-tailed shocks and follow a nonlinear stochastic process, thus departing from the canonical linear AR(1). We estimate a state-of-the-art model to flexibly capture the rich dynamics uncovered in the data and characterize the drivers of nonlinear persistence and non-Gaussian shocks. We show that these features are crucial to get empirically plausible volatility and persistence of micro-originated (granular) aggregate fluctuations.