Search Results
Working Paper
We Are All Behavioral, More or Less: Measuring and Using Consumer-Level Behavioral Sufficient Statistics
Can a behavioral sufficient statistic empirically capture cross-consumer variation in behavioral tendencies and help identify whether behavioral biases, taken together, are linked to material consumer welfare losses? Our answer is yes. We construct simple consumer-level behavioral sufficient statistics??B-counts??by eliciting seventeen potential sources of behavioral biases per person, in a nationally representative panel, in two separate rounds nearly three years apart. B-counts aggregate information on behavioral biases within-person. Nearly all consumers exhibit multiple biases, in ...
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders to anonymized cell phone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay home: County-level measures of mobility declined 8% by the day after the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: small businesses and large retail stores. However, consumers sharply increased spending on food delivery services after orders went into effect. Third, responses to stay-at-home orders were ...
Discussion Paper
Discretionary Services Spending Has Finally Made It Back (to 2007)
The current economic expansion is now the third-longest expansion in U.S. history (based on National Bureau of Economic Research [NBER] dating of U.S. business cycles). Even so, average growth in this expansion—a 2.1 percent annual rate—has been extraordinarily weak. In this post, I return to previous analysis on a specific portion of consumer spending—household discretionary services expenditures—that has displayed unusual weakness in the current expansion (see this post for the definition of discretionary versus nondiscretionary services expenditures, and these posts from 2012 and ...
Briefing
Estimating Aggregate Fiscal Multipliers from Local Data
Variations among regions in their responses to economic policies can be used to estimate the effects of those policies at the national level while minimizing or eliminating issues of reverse causation. Recent research has employed county-level data to look at the effects of federal government spending ? in particular, the 2009?12 stimulus ? on aggregate consumption.
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders to anonymized cellphone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay at home: county-level measures of mobility declined by between 9% and 13% by the day after the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: restaurants and retail stores. However, food delivery sharply increased after orders went into effect. Third, there is substantial county-level heterogeneity in consumer ...
Discussion Paper
Are Customers Pulling Back on Spending? Evidence From the Richmond Fed Business Surveys
In the last few years, consumer spending in the United States has been remarkably resilient. In our August business survey, we sought to understand if Fifth District firms have recently experienced softening demand for their goods or services. A majority of firms reported that over the past three months, customers decreased the amount of goods and services purchased — both in quantity and in dollar amount. The survey also found that demand has softened more for manufacturers and retailers than firms in other industries. Additionally, firms reported that lower-income customers pulled back on ...
Discussion Paper
Did State Reopenings Increase Consumer Spending?
The spread of COVID-19 in the United States has had a profound impact on economic activity. Beginning in March, most states imposed severe restrictions on households and businesses to slow the spread of the virus. This was followed by a gradual loosening of restrictions (“reopening”) starting in April. As the virus has re-emerged, a number of states have taken steps to reverse the reopening of their economies. For example, Texas and Florida closed bars again in June, and Arizona additionally paused operations of gyms and movie theatres. Taken together, these measures raise the question of ...
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders during the Covid-19 pandemic to anonymized cell phone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay home: county-level measures of mobility declined 7–8% within two days of when the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: small businesses and large retail chains. Third, we estimate fairly uniform responses to stay-at-home orders across the country; effects do not vary by ...
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders to anonymized cellphone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay at home: county-level measures of mobility declined by between 9% and 13% by the day after the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: restaurants and retail stores. However, food delivery sharply increased after orders went into effect. Third, there is substantial county-level heterogeneity in consumer ...
Discussion Paper
Racial and Income Gaps in Consumer Spending following COVID-19
This post is the first in a two-part series that seeks to understand whether consumer spending patterns during the COVID-19 pandemic evolved differentially across counties by race and income. As the pandemic hit and social distancing restrictions were put into place in March 2020, consumer spending plummeted. Subsequently, as social distancing restrictions began to be relaxed later in spring 2020, consumer spending started to rebound. We find that higher-income counties had a considerably steeper decline and a shallower recovery than low-income counties did. The differences by race were also ...