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Keywords:consumer spending OR Consumer spending OR Consumer Spending 

Working Paper
Regional Consumption Responses and the Aggregate Fiscal Multiplier

We use regional variation in the American Recovery and Reinvestment Act (2009-2012) to analyze the effect of government spending on consumer spending. Our consumption data come from household-level retail purchases in Nielsen and auto purchases from Equifax credit balances. We estimate that a $1 increase in county-level government spending increases consumer spending by $0.29. We translate the regional consumption responses to an aggregate fiscal multiplier using a multi-region, New Keynesian model with heterogeneous agents and incomplete markets. Our model successfully generates the ...
Working Papers , Paper 2018-4

Working Paper
Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade

We create a new weekly index of retail trade that accurately predicts the U.S. Census Bureau's Monthly Retail Trade Survey (MRTS). The index's weekly frequency provides an early snapshot of the MRTS and allows for a more granular analysis of the aggregate consumer response to fast-moving events such as the Covid-19 pandemic. To construct the index, we extract the co-movement in weekly data series capturing credit and debit card transactions, foot traffic, gasoline sales, and consumer sentiment. To ensure that the index is representative of aggregate retail spending, we implementa novel ...
Working Paper Series , Paper WP-2021-05

Speech
Important choices for the Federal Reserve in the years ahead: remarks at Lehman College, Bronx, New York

Remarks at Lehman College, Bronx, New York.
Speech

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 ...
Working Paper Series , Paper WP-2020-12

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 ...
Working Paper Series , Paper WP-2020-12

Does Spending Slide When COVID-19 Surges?

In this District Data Brief, we show that state-level data suggest that economic implications from the latest wave have been less than those from the fall 2020 wave. While there has been some consumer response to the delta-variant-driven COVID-19 surge, it has been weaker than the response to the fall 2020 COVID-19 surge.
Cleveland Fed District Data Brief , Paper 20211007

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 ...
Liberty Street Economics , Paper 20171016

Working Paper
Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade

We create a new weekly index of retail trade that accurately predicts the U.S. Census Bureau’s Monthly Retail Trade Survey (MRTS). The index’s weekly frequency provides an early snapshot of the MRTS and allows for a more granular analysis of the aggregate implications of policies implemented during the Covid-19 pandemic. To construct the index, we extract the co-movement in several weekly data series capturing credit & debit card transactions and revenues, mobility, and consumer sentiment as well as monthly retail and food services sales excluding automotive spending (ex. autos) from the ...
Working Paper Series , Paper WP-2021-05

Working Paper
From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending

Access to timely information on consumer spending is important to economic policymakers. The Census Bureau's monthly retail trade survey is a primary source for monitoring consumer spending nationally, but it is not well suited to study localized or short-lived economic shocks. Moreover, lags in the publication of the Census estimates and subsequent, sometimes large, revisions diminish its usefulness for real-time analysis. Expanding the Census survey to include higher frequencies and subnational detail would be costly and would add substantially to respondent burden. We take an alternative ...
Finance and Economics Discussion Series , Paper 2019-057

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 Series , Paper WP-2020-12

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