User Beware: Concerning Findings from the Post 2011–2012 U.S. Internal Revenue Service Migration Data

DeWaard, Jack; Hauer, Mathew; Fussell, Elizabeth; Curtis, Katherine; Whitaker, Stephan D.; McConnell, Kathryn; Price, Kobie; Egan-Robertson, David; Soto, Michael; Castro, Catalina Anampa

doi:10.1007/s11113-021-09663-6

Cited by 16 publications

(13 citation statements)

References 25 publications

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“…First, going beyond a one-size-fits-all approach (Fussell et al 2017;Gray and Wise 2016;Hunter et al 2015;McLeman 2013), we took a case-specific approach and focused our analysis on 23 disaster-affected areas in the contiguous United States and Puerto Rico that have experienced some of the most destructive and costly hurricanes, tornadoes, and wildfires in recent years. Second, because research on climate and environmental migration can be and often is constrained by the availability and quality of publicly available migration data (DeWaard et al 2019(DeWaard et al , 2021, we used the non-public CCP to study economic losses via migration from disaster-affected areas and, in the process, demonstrated some of the utility of these data for studying [climate and environmental] migration that extends prior research (DeWaard et al 2019(DeWaard et al , 2021Ding et al 2016;Molloy and Shan 2013). Third, in addition to describing levels of and changes in economic losses via migration from disaster-affected areas, we dug below the surface and used the tools of demographic standardization and decomposition to show that these losses primarily, but not exclusively, reflect underlying changes in outmigration from disaster-affected areas.…”

Section: Discussionmentioning

confidence: 99%

“…Second, publicly available migration data such as those provided by the IRS are not up-to-date enough to be useful in studying the three counties and three municipios that experienced Hurricanes Harvey and Maria, respectively, as well as the five counties that experienced the Carr, Camp, and Nuns wildfires. Finally, several recent papers have raised questions and concerns about the quality and accuracy of publicly available migration data, particularly the CPS and the IRS data (DeWaard et al 2021;Kaplan and Schulhofer-Wohl 2012).…”

Section: Datamentioning

confidence: 99%

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Migration as a Vector of Economic Losses from Disaster-Affected Areas in the United States

DeWaard

Fussell

Curtis

et al. 2021

Working Paper (Federal Reserve Bank of Cleveland)

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In this paper, we infuse consideration of migration into research on economic losses from extreme weather disasters. Taking a comparative case study approach and using data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel, we document the size of economic losses via migration from 23 disaster-affected areas in the United States after the most damaging hurricanes, tornadoes, and wildfires on record. We then employ demographic standardization and decomposition to determine if these losses primarily reflect changes in outmigration or changes in the economic resources that migrants take with them (greater economic losses per migrant). Finally, we consider the implications of these losses for changing spatial inequality in the United States. While disaster-affected areas and those living in them differ in their experiences of and responses to extreme weather disasters, we generally find that, relative to the year before an extreme weather disaster, economic losses via migration from disasteraffected areas increase the year of and after the disaster, that these changes primarily reflect changes in out-migration (vs. the economic resources that migrants take with them), and that these losses briefly disrupt the status quo by temporarily reducing spatial inequality.

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Section: Discussionmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Migration as a Vector of Economic Losses from Disaster-Affected Areas in the United States

DeWaard

Fussell

Curtis

et al. 2021

Working Paper (Federal Reserve Bank of Cleveland)

Self Cite

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“…Excluding the IRSdata,thesmallsam plesizesoftheCPSand,toalesserextent,oftheACSpro hibit pro duc ing accu rate esti ma tes of migra tion at finer spa tial scales (e.g., for an indi vid ual county). Second, pub licly avail able migra tion data such as those pro vided by the IRS are not up to date enough to be use ful to study the three counties and three municipios that expe ri enced Hurricanes Harvey and Maria, respec tively, as well as thefivecountiesthatexpe ri encedtheCarr,Camp,andNunsWildfires.Finally,sev eral recent papers have raised ques tions and con cerns about the qual ity and accu racy ofpub liclyavail ablemigra tiondata,par tic u larlytheCPSandtheIRSdata (DeWaard, Hauer et al 2022;Kaplan and SchulhoferWohl 2012).…”

Section: Datamentioning

confidence: 99%

“…data (DeWaardetal.2019;DeWaard, Hauer et al 2022;Fussell, Hunter, and Gray 2014), we used the non pub lic CCP to study eco nomic losses via migra tion from disas teraffected areas and, in the pro cess, dem on strated the util ity of these data for study ingcli mateandenvi ron men talmigra tionthatextendspriorresearch (DeWaard et al 2019;DeWaard, Johnson, and Whitaker 2020;Ding et al 2016;Molloy and Shan 2013). Third, in addi tion to sum ma riz ing lev els of and changes in eco nomic losses via migra tion from disas teraffected areas, we used the tools of demo graphic stan dard i za tion and decom po si tion to show that these losses pri mar ily, but not exclu sively, reflect under ly ing changes in outmigra tion from disas teraffected areas.…”

Section: Corrected Proofsmentioning

confidence: 99%

Migration as a Vector of Economic Losses From Disaster-Affected Areas in the United States

et al. 2023

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We introduce the consideration of human migration into research on economic losses from extreme weather disasters. Taking a comparative case study approach and using data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel, we document the size of economic losses attributable to migration from 23 disaster-affected areas in the United States before, during, and after some of the most costly hurricanes, tornadoes, and wildfires on record. We then employ demographic standardization and decomposition to determine if these losses primarily reflect changes in out-migration or the economic resources that migrants take with them. Finally, we consider the implications of these losses for changing spatial inequality in the United States. While disaster-affected areas and their populations differ in their experiences of and responses to extreme weather disasters, we generally find that, relative to the year before an extreme weather disaster, economic losses via migration from disaster-affected areas increase the year of and after the disaster, these changes primarily reflect changes in out-migration (vs. the economic resources that migrants take with them), and these losses briefly disrupt the status quo by temporarily reducing spatial inequality.

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“…To control for changes in population size that are not due to migration flows, we also use information from the IRS on non-migrant residents. Based on the IRS county data, non-migrant residents refer to tax filers (and their dependents) who have not changed their county of residence between two tax years (DeWaard et al 2020). The values of this variable are calculated by computing the natural logarithm of the number of non-migrants at the beginning and at the end of the five-year interval.…”

Section: Land Development: Independent Variablesmentioning

confidence: 99%

The Lagged Environmental Consequences of Demographic and Economic Change

Clement¹,

Pino²,

York³

et al. 2021

Sociological Inquiry

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Quantitative sociologists conducting environmental research often use temporally lagged variables to estimate the social drivers of ecological change. To highlight the relevance of temporal lags for this scholarship, we specifically look at the longitudinal relationship between demographic and economic change and two different environmental outcomes: land development and carbon emissions. For land development, we run longitudinal spatial regression models to assess whether increasing the lag time changes the slope estimates for in‐migration and out‐migration at the county level across the contiguous United States (n = 3,026). For carbon emissions, we use cross‐national data in Prais–Winsten models to assess changes in the lagged estimates for GDP, urbanization, and age structure (n = 146). Results from these analyses indicate that the slope estimates continue to be statistically significant, but the magnitudes of these coefficients change with increased lag time. We propose that scholars use a more systematic approach when assessing the temporal duration of socio‐ecological change.

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User Beware: Concerning Findings from the Post 2011–2012 U.S. Internal Revenue Service Migration Data

Cited by 16 publications

References 25 publications

Migration as a Vector of Economic Losses from Disaster-Affected Areas in the United States

Migration as a Vector of Economic Losses from Disaster-Affected Areas in the United States

Migration as a Vector of Economic Losses From Disaster-Affected Areas in the United States

The Lagged Environmental Consequences of Demographic and Economic Change

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