We use Geographic Information System tools to develop estimates of the economic impact of disaster events such as Hurricane Katrina. Our methodology relies on mapping establishments from the Census Bureau's Business Register into damage zones defined by remote sensing information provided by FEMA. The identification of damaged establishments by precisely locating them on a map provides a far more accurate characterization of affected businesses than those typically reported from readily available county level data. The need for prompt estimates is critical since they are more valuable the sooner they are released after a catastrophic event. Our methodology is based on pre-storm data. Therefore, estimates can be made available very quickly to inform the public as well as policy makers. Robustness tests using data from after the storms indicate our GIS estimates, while much smaller than those based on publicly available county-level data, still overstate actual observed losses. We discuss ways to refine and augment the GIS approach to provide even more accurate estimates of the impact of disasters on businesses.
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Storms and Jobs: The Effect of Hurricanes on Individuals' Employment and Earnings over the Long Term*
January 2015
Working Paper Number:
CES-15-21R
Hurricanes Katrina and Rita devastated the U.S. Gulf Coast in 2005, destroying homes and businesses and causing mass evacuations. The economic effects of disasters are often studied at a regional level, but little is known about the responsiveness of individuals' employment and earnings to the damages, disruption, and rebuilding'particularly in the longer run. Our analysis is based on data that tracks workers over nine years, including seven years after the storms. We estimate models that compare the evolution of earnings for workers who resided in a storm-affected area with those who resided in a suitable control counties. We find that, on average, the storms reduced the earnings of affected individuals during the first year after the storm. These losses reflect various aspects of the short-run disruption caused by the hurricanes, including job separations, migration to other areas, and business contractions. Starting in the third year after the storms, however, we find that the earnings of affected individuals outpaced the earnings of individuals in the control sample. We provide evidence that the long-term earnings gains were the result of wage growth in the affected areas relative to the control areas, due to reduced labor supply and increased labor demand, especially in sectors related to rebuilding. Despite the short-term earnings losses, we find a net increase in average quarterly earnings among affected individuals over the entire post-storm period. However, those who worked in sectors closely tied to tourism or the size of the local population experienced net earnings losses.
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A Shore Thing: Post-Hurricane Outcomes for Businesses in Coastal Areas
September 2020
Working Paper Number:
CES-20-27
During the twenty-first century, hurricanes, heavy storms, and flooding have affected many areas in the United States. Natural disasters and climate change can cause property damage and could have an impact on a variety of business outcomes. This paper builds upon existing research and literature that analyzes the impact of natural disasters on businesses. Specifically, we look at the differential effect of eight hurricanes during the period 2000-2009 on establishments in coastal counties relative to establishments in coastal-adjacent or inland counties. Our outcomes of interest include establishment employment and death. We find that following a hurricane event, establishments located in a coastal county have lower employment and increased probability of death relative to establishments in non-coastal counties.
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TAKEN BY STORM: BUSINESS SURVIVAL IN THE AFTERMATH OF HURRICANE KATRINA
April 2014
Working Paper Number:
CES-14-20
We use Hurricane Katrina's damage to the Mississippi coast in 2005 as a natural experiment to study business survival in the aftermath of a cost shock. We find that damaged establishments that returned to operation were more resilient than those that had never been damaged. This effect is particularly strong for establishments belonging to younger and smaller rms. The effect of damage on establishments in older and larger chains was more limited, and they were subsequently less resilient having survived the damage. These selection effects persist up to five years after the initial shock. We interpret these findings as evidence that the effect of the shock is tied to the presence of financial and other constraints.
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Measuring the Effect of COVID-19 on U.S. Small Businesses: The Small Business Pulse Survey
May 2020
Working Paper Number:
CES-20-16
In response to the novel coronavirus (COVID-19) pandemic, the Census Bureau developed and fielded an entirely new survey intended to measure the effect on small businesses. The Small Business Pulse Survey (SBPS) will run weekly from April 26 to June 27, 2020. Results from the SBPS will be published weekly through a visualization tool with downloadable data. We describe the motivation for SBPS, summarize how the content for the survey was developed, and discuss some of the initial results from the survey. We also describe future plans for the SBPS collections and for our research using the SBPS data. Estimates from the first week of the SBPS indicate large to moderate negative effects of COVID-19 on small businesses, and yet the majority expect to return to usual level of operations within the next six months. Reflecting the Census Bureau's commitment to scientific inquiry and transparency, the micro data from the SBPS will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.
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Who Creates Jobs? Small vs. Large vs. Young
August 2010
Working Paper Number:
CES-10-17
There's been a long, sometimes heated, debate on the role of firm size in employment growth. Despite skepticism in the academic community, the notion that growth is negatively related to firm size remains appealing to policymakers and small business advocates. The widespread and repeated claim from this community is that most new jobs are created by small businesses. Using data from the Census Bureau Business Dynamics Statistics and Longitudinal Business Database, we explore the many issues regarding the role of firm size and growth that have been at the core of this ongoing debate (such as the role of regression to the mean). We find that the relationship between firm size and employment growth is sensitive to these issues. However, our main finding is that once we control for firm age there is no systematic relationship between firm size and growth. Our findings highlight the important role of business startups and young businesses in U.S. job creation. Business startups contribute substantially to both gross and net job creation. In addition, we find an 'up or out' dynamic of young firms. These findings imply that it is critical to control for and understand the role of firm age in explaining U.S. job creation.
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High Frequency Business Dynamics in the United States During the COVID-19 Pandemic
March 2021
Working Paper Number:
CES-21-06
Existing small businesses experienced very sharp declines in activity, business sentiment, and expectations early in the pandemic. While there has been some recovery since the early days of the pandemic, small businesses continued to exhibit indicators of negative growth, business sentiment, and expectations through the first week of January 2021. These findings are from a unique high frequency, real time survey of small employer businesses, the Census Bureau's Small Business Pulse Survey (SBPS). Findings from the SBPS show substantial variation across sectors in the outcomes for small businesses. Small businesses in Accommodation and Food Services have been hit especially hard relative to those Finance and Insurance. However, even in Finance and Insurance small businesses exhibit indicators of negative growth, business sentiment, and expectations for all weeks from late April 2020 through the first week of 2021. While existing small businesses have fared poorly, after an initial decline, there has been a surge in new business applications based on the high frequency, real time Business Formation Statistics (BFS). Most of these applications are for likely nonemployers that are out of scope for the SBPS. However, there has also been a surge in new applications for likely employers. The surge in applications has been especially apparent in Retail Trade (and especially Non-store Retailers). We compare and contrast the patterns from these two new high frequency data products that provide novel insights into the distinct patterns of dynamics for existing small businesses relative to new business formations.
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An Analysis of Key Differences in Micro Data: Results from the Business List Comparison Project
September 2008
Working Paper Number:
CES-08-28
The Bureau of Labor Statistics and the Bureau of the Census each maintain a business register, a universe of all U.S. business establishments and their characteristics, created from independent sources. Both registers serve critical functions such as supplying aggregate data inputs for certain national statistics generated by the Bureau of Economic Analysis. This paper examines key micro-level differences across these two business registers.
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NEW DATA FOR DYNAMIC ANALYSIS: THE LONGITUDINAL ESTABLISHMENT AND ENTERPRISE MICRODATA (LEEM) FILE
December 1999
Working Paper Number:
CES-99-18
Until now, research on U.S. business activities over time has been hindered by the lack of accurate and comprehensive longitudinal data. The new Longitudinal Establishment and Enterprise Microdata (LEEM) are tremendously rich data that open up numerous possibilities for dynamic analyses of businesses in the U.S. economy. It is the first nationwide high-quality longitudinal database that covers the majority of employer businesses from all sectors of the economy. Due to the confidential nature of these data, the file is located at the Center for Economic Studies in the U.S. Bureau of the Census. To access the data, researchers must submit an acceptable proposal to CES and become sworn Census researchers. This paper describes the LEEM file, the variables contained on the file, and current uses of the data.
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The Impacts of Opportunity Zones on Zone Residents
June 2021
Working Paper Number:
CES-21-12
Created by the Tax Cuts and Jobs Act in 2017, the Opportunity Zone program was designed to encourage investment in distressed communities across the U.S. We examine the early impacts of the Opportunity Zone program on residents of targeted areas. We leverage restricted-access microdata from the American Community Survey and employ difference-in-differences and matching approaches to estimate causal reduced-form effects of the program. Our results point to modest, if any, positive effects of the Opportunity Zone program on the employment, earnings, or poverty of zone residents.
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Do SBA Loans Create Jobs? Estimates from Universal Panel Data and Longitudinal Matching Methods
September 2012
Working Paper Number:
CES-12-27
This pape reports estimates of the effects of the Small Business Administration (SBA) 7(a) and 504 loan programs on employment. The database links a complete list of all SBA loans in these programs to universal data on all employers in the U.S. economy from 1976 to 2010. Our method is to estimate firm fixed effect regressions using matched control groups for the SBA loan recipients we have constructed by matching exactly on firm age, industry, year, and pre-loan size, plus kernel-based matching on propensity scores estimated as a function of four years of employment history and other variables. The results imply positive average effects on loan recipient employment of about 25 percent or 3 jobs at the mean. Including loan amount, we find little or no impact of loan receipt per se, but an increase of about 5.4 jobs for each million dollars of loans. When focusing on loan recipients and control firms located in high-growth counties (average growth of 22 percent), places where most small firms should have excellent growth potential, we find similar effects, implying that the estimates are not driven by differential demand conditions across firms. Results are also similar regardless of distance of control from recipient firms, suggesting only a very small role for displacement effects. In all these cases, the results pass a "pre-program" specification test, where controls and treated firms look similar in the pre-loan period. Other specifications, such as those using only matching or only regression imply somewhat higher effects, but they fail the pre-program test.
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