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Is monetary policy less effective at increasing real output during periods of high volatility than during normal times? In this article, I argue that greater volatility leads to an increase in aggregate price flexibility so that nominal stimulus mostly generates inflation rather than output growth. To do this, I construct price-setting models with “volatility shocks” and show these models match new facts in CPI micro data that standard price-setting models miss. I then show that these models imply that output responds less to nominal stimulus during times of high volatility. Furthermore, because volatility is countercyclical, this implies that nominal stimulus has smaller real effects during downturns. For example, the estimated output response to additional nominal stimulus in September 1995, a time of low volatility, is 55% larger than the response in October 2001, a time of high volatility.

We use US household-level bank account data to investigate the heterogeneous effects of the pandemic on spending and savings. Households across the income distribution all cut spending from March to early April. Since mid-April, spending has rebounded most rapidly for low-income households. We find large increases in liquid asset balances for households throughout the income distribution. However, lower-income households contribute disproportionately to the aggregate increase in balances, relative to their prepandemic shares. Taken together, our results suggest that spending declines in the initial months of the recession were primarily caused by direct effects of the pandemic, rather than resulting from labor market disruptions. The sizable growth in liquid assets we observe for low-income households suggests that stimulus and insurance programs during this period likely played an important role in limiting the effects of labor market disruptions on spending.

In this paper I discuss the increasingly prominent role of administrative micro data in macroeconomics research. This type of data proved important for interpreting the causes and consequences of the Great Recession, and it has played a crucial role in shaping economists' understanding of the COVID-19 pandemic in near real-time. I discuss a number of specific insights from this research while also illustrating some of the broader opportunities and challenges of working with administrative data.

We document a causal response of local retail prices to changes in local house prices, with elasticities of 15–20 percent across housing cycles. These price responses are largest in zip codes with many homeowners and are driven by changes in markups rather than local costs. We argue that markups rise with house prices because greater housing wealth reduces homeowners’ demand elasticity, and firms raise markups in response. Shopping data confirm that house price changes affect the price sensitivity of homeowners, but not that of renters. Our evidence suggests a new source of business cycle markup variation.

Are there times when durable spending is less responsive to economic stimulus? We argue that aggregate durable expenditures respond more sluggishly to economic shocks during recessions because microeconomic frictions lead to declines in the frequency of households' durable adjustment. We show this by first using indirect inference to estimate a heterogeneous agent incomplete markets model with fixed costs of durable adjustment to match consumption dynamics in PSID microdata. We then show that aggregating this model delivers an extremely procyclical Impulse Response Function (IRF) of durable spending to aggregate shocks. For example, the response of durable spending to an income shock in 1999 is estimated to be almost twice as large as if it occurred in 2009. This procyclical IRF holds in response to standard business cycle shocks as well as in response to various policy shocks, and it is robust to general equilibrium. After estimating this robust theoretical implication of micro frictions, we provide additional direct empirical evidence for its importance using both cross-sectional and time-series data.

We argue that the time-varying regional distribution of housing equity influences the aggregate consequences of monetary policy through its effects on mortgage refinancing. Using detailed loan-level data, we show that regional differences in housing equity affect refinancing and spending responses to interest rate cuts, but these effects vary over time with changes in the regional distribution of house price growth. We build a heterogeneous household model of refinancing with mortgage borrowers and lenders and use it to explore the monetary policy implications arising from our regional evidence. We find that the 2008 equity distribution made spending in depressed regions less responsive to interest rate cuts, thus dampening aggregate stimulus and increasing regional consumption inequality, whereas the opposite occurred in some earlier recessions. Taken together, our results strongly suggest that monetary policy makers should track the regional distribution of equity over time.

Recent empirical work shows large consumption responses to house price movements. This is at odds with a prominent theoretical view which, using the logic of the permanent income hypothesis, argues that consumption responses should be small. We show that, in contrast to this view, workhorse models of consumption with incomplete markets calibrated to rich cross-sectional micro facts actually predict large consumption responses, in line with the data. To explain this result, we show that consumption responses to permanent house price shocks can be approximated by a simple and robust rule-of-thumb formula: the marginal propensity to consume out of temporary income times the value of housing. In our model, consumption responses depend on a number of factors such as the level and distribution of debt, the size and history of house price shocks, and the level of credit supply. Each of these effects is naturally explained with our simple formula.

The dispersion of many economic variables is countercyclical. What drives this fact? Greater dispersion could arise from greater volatility of shocks or from agents responding more to shocks of constant size. Without data separately measuring exogenous shocks and endogenous responses, a theoretical debate between these explanations has emerged. In this paper, we provide novel identification using price data in the open-economy environment: using confidential BLS microdata, we document a robust positive relationship between exchange rate pass-through and the dispersion of item-level price changes. We then show that this relationship supports models with time-varying responsiveness.

How much ability does the Fed have to stimulate the economy by cutting interest rates? We argue that the presence of substantial debt in fixed-rate, prepayable mortgages means that the ability to stimulate the economy by cutting interest rates depends not just on their current level but also on their previous path. Using a household model of mortgage prepayment matched to detailed loan-level evidence on the relationship between prepayment and rate incentives, we argue that recent interest rate paths will generate substantial headwinds for future monetary stimuli.

We estimate how durable expenditures respond to government spending shocks at different points in the business cycle using a nonlinear VAR approach that allows for the durable multiplier to vary smoothly with the state of the economy. We find strong evidence that the aggregate durable spending response to fiscal shocks is substantially larger during expansions than during recessions, in contrast to what has been has been observed for the aggregate multiplier. We argue that these results are consistent with the theoretical predictions of the fixed cost model of durable demand in Berger and Vavra (2012).