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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 ...
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
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 ...
Working Paper
Government Transfers and Consumer Spending among Households with Children during COVID-19
Leveraging novel data on consumer credit and debit card spending by Zip code, this study examines how the impact of government transfers on economic well-being varied by household type during the COVID-19 pandemic. Our findings indicate that pandemic transfers disproportionately benefited households with children, buffering them from earnings losses at the pandemic’s start and sustaining spending growth over time. Household essential spending increased proportionally with the delivery of cash transfers, while discretionary spending was influenced more by pandemic-specific factors beyond ...
Tracking the Economic Impact of the Pandemic Using High-Frequency Data
High-frequency data can provide a quicker snapshot of economic conditions than data that take weeks or months to become available.
Newsletter
Consumer Spending and the COVID-19 Pandemic
The onset of the COVID-19 pandemic changed consumer spending habits. The January 2021 issue of Page One Economics reviews how people substituted meals purchased at restaurants with meals cooked at home. Also, people traveled less and the demand for hotel services decreased. As a result, both employment and prices declined in the leisure and hospitality industry.