From 5590d330518d1b84a73df4fa1655e479a50497c7 Mon Sep 17 00:00:00 2001 From: Mingli Zhong Date: Wed, 11 Dec 2024 09:33:17 -0500 Subject: [PATCH 1/2] 2023 county-level delinquent debt data by overall, auto loan, medical debt, and student loan debt were added to subfolder output. 2022 county-level and 2021 city-level data were created previously and in the same output subfolder. Note that county and state names in 2022 county-level csv file are numeric but are string variables with the actual state and county names in 2023 files. Further guidance is needed on whether actual state and county names are needed. Code to generate 2023 county-level data is county-debt-coll-shares-2023.do --- .../county-debt-coll-shares-2022-2023.do | 160 + ...s_all_autoretail_county_2023_1Jul2024.xlsx | Bin 0 -> 461041 bytes ...lbls_all_medical_county_2023_1Jul2024.xlsx | Bin 0 -> 402851 bytes ...lbls_all_overall_county_2023_1Jul2024.xlsx | Bin 0 -> 560858 bytes ...lbls_all_student_county_2023_1Jul2024.xlsx | Bin 0 -> 485500 bytes .../city-debt-coll-shares-2021.csv | 0 .../county-debt-coll-shares-2022.csv | 0 ...ounty-debt-coll-shares-2023-autoretail.csv | 9430 +++++++++++++++++ .../county-debt-coll-shares-2023-medical.csv | 9430 +++++++++++++++++ .../county-debt-coll-shares-2023-overall.csv | 9430 +++++++++++++++++ .../county-debt-coll-shares-2023-student.csv | 9430 +++++++++++++++++ 11 files changed, 37880 insertions(+) create mode 100644 01_financial-well-being/county-debt-coll-shares-2022-2023.do create mode 100644 01_financial-well-being/dia-2023/dia_lbls_all_autoretail_county_2023_1Jul2024.xlsx create mode 100644 01_financial-well-being/dia-2023/dia_lbls_all_medical_county_2023_1Jul2024.xlsx create mode 100644 01_financial-well-being/dia-2023/dia_lbls_all_overall_county_2023_1Jul2024.xlsx create mode 100644 01_financial-well-being/dia-2023/dia_lbls_all_student_county_2023_1Jul2024.xlsx rename 01_financial-well-being/{ => output}/city-debt-coll-shares-2021.csv (100%) rename 01_financial-well-being/{ => output}/county-debt-coll-shares-2022.csv (100%) create mode 100644 01_financial-well-being/output/county-debt-coll-shares-2023-autoretail.csv create mode 100644 01_financial-well-being/output/county-debt-coll-shares-2023-medical.csv create mode 100644 01_financial-well-being/output/county-debt-coll-shares-2023-overall.csv create mode 100644 01_financial-well-being/output/county-debt-coll-shares-2023-student.csv diff --git a/01_financial-well-being/county-debt-coll-shares-2022-2023.do b/01_financial-well-being/county-debt-coll-shares-2022-2023.do new file mode 100644 index 00000000..76e136ab --- /dev/null +++ b/01_financial-well-being/county-debt-coll-shares-2022-2023.do @@ -0,0 +1,160 @@ + +/************************************************ +Created by Mingli Zhong (mzhong@urban.org) +12-10-2023 +* This do file is based on Jen Andre's do file county-debt-coll-shares-2022 in the same folder (C:\GitHub\mobility-from-poverty\01_financial-well-being). It generates county-level debt in collection results based on Debt in America data. +* Debt in Collections County-Level Shares 2022 and 2023* +* Data & Program Source: Debt in America +* Description: Process county-level debt in collections shares, overall and by race subgroups +[1] Import and process Urban Data Catalog file +[2] Export +************************************************/ + +global output "C:\GitHub\mobility-from-poverty\01_financial-well-being\output" // USER: must set output path here +assert !mi("$output") + +**# [1] Import and process Urban Data Catalog file ----------------------------------- +******************************************************************************* +** Delinquent debt by debt category: overall, medical, auto, studnet loan debt +******************************************************************************* +* source: Debt in America +* import excel using "https://urban-data-catalog.s3.amazonaws.com/drupal-root-live/2022/06/16/county_dia_delinquency_%207%20Jun%202022.xlsx", clear +foreach x in overall medical { + import excel using "C:\GitHub\mobility-from-poverty\01_financial-well-being\dia-2023\dia_lbls_all_`x'_county_2023_1Jul2024.xlsx", clear firstrow + +/* +* keep only debt in collections metrics +gen state = substr(B, 1, 2) +gen county = substr(B, 3, 3) +ren (D E F) /// + (share_debt_coll_all share_debt_coll_majnonwhite share_debt_coll_majwhite) +*/ + +keep CountyName - F +rename CountyName county +rename StateName state +ren (Sharewith E F) (share_debt_coll_all share_debt_coll_majnonwhite share_debt_coll_majwhite) + +keep state county share_debt_coll* + +drop if county == "OID" + +* format long and adjust subgroups to match standard +reshape long share_debt_coll, i(county state) j(subgroup) string + +replace subgroup = "All" if subgroup == "_all" +replace subgroup = "Majority Non-White" if subgroup == "_majnonwhite" +replace subgroup = "Majority White" if subgroup == "_majwhite" + +gen subgroup_type = "race-ethnicity" + +* create data quality fields - most 1, some 3 for missing/suppression +replace share_debt_coll = "" if inlist(share_debt_coll, "n/a*", "n/a**", "NA") +destring share_debt_coll, replace +gen share_debt_coll_quality = . + replace share_debt_coll_quality = 1 if !mi(share_debt_coll) + replace share_debt_coll_quality = 3 if mi(share_debt_coll) // suppressed or no subgroup + +**# [2] Export ----------------------------------- +gen year = 2023 + +compress +order year state county share_debt_coll share_debt_coll_quality subgroup_type subgroup +gsort year state county subgroup + +export delimited using "$output\county-debt-coll-shares-2023-`x'.csv", datafmt replace +* save "output\county-debt-coll-shares-2023-`x'.dta", replace +} + +******************** +** student loan debt +** variable names are different in these spreadsheets so will need to process them individually +import excel using "C:\GitHub\mobility-from-poverty\01_financial-well-being\dia-2023\dia_lbls_all_student_county_2023_1Jul2024.xlsx", clear firstrow + +keep CountyName - SharewithstudentloandebtWh +rename CountyName county +rename StateName state +ren (SharewithstudentloandebtAl SharewithstudentloandebtCo SharewithstudentloandebtWh) (share_debt_coll_all share_debt_coll_majnonwhite share_debt_coll_majwhite) + +keep state county share_debt_coll* + +drop if county == "OID" + +* format long and adjust subgroups to match standard +reshape long share_debt_coll, i(county state) j(subgroup) string + +replace subgroup = "All" if subgroup == "_all" +replace subgroup = "Majority Non-White" if subgroup == "_majnonwhite" +replace subgroup = "Majority White" if subgroup == "_majwhite" + +gen subgroup_type = "race-ethnicity" + +* create data quality fields - most 1, some 3 for missing/suppression +replace share_debt_coll = "" if inlist(share_debt_coll, "n/a*", "n/a**", "NA") +destring share_debt_coll, replace +gen share_debt_coll_quality = . + replace share_debt_coll_quality = 1 if !mi(share_debt_coll) + replace share_debt_coll_quality = 3 if mi(share_debt_coll) // suppressed or no subgroup + +**# [2] Export ----------------------------------- +gen year = 2023 + +compress +order year state county share_debt_coll share_debt_coll_quality subgroup_type subgroup +gsort year state county subgroup + +export delimited using "$output\county-debt-coll-shares-2023-student.csv", datafmt replace + + +******************** +** Autoretail +** variable names are different in these spreadsheets so will need to process them individually +import excel using "C:\GitHub\mobility-from-poverty\01_financial-well-being\dia-2023\dia_lbls_all_autoretail_county_2023_1Jul2024.xlsx", clear firstrow + +keep CountyName - F +rename CountyName county +rename StateName state +ren (Autoretailloandelinquencyrat E F) (share_debt_coll_all share_debt_coll_majnonwhite share_debt_coll_majwhite) + +keep state county share_debt_coll* + +drop if county == "OID" + +* format long and adjust subgroups to match standard +reshape long share_debt_coll, i(county state) j(subgroup) string + +replace subgroup = "All" if subgroup == "_all" +replace subgroup = "Majority Non-White" if subgroup == "_majnonwhite" +replace subgroup = "Majority White" if subgroup == "_majwhite" + +gen subgroup_type = "race-ethnicity" + +* create data quality fields - most 1, some 3 for missing/suppression +replace share_debt_coll = "" if inlist(share_debt_coll, "n/a*", "n/a**", "NA") +destring share_debt_coll, replace +gen share_debt_coll_quality = . + replace share_debt_coll_quality = 1 if !mi(share_debt_coll) + replace share_debt_coll_quality = 3 if mi(share_debt_coll) // suppressed or no subgroup + +**# [2] Export ----------------------------------- +gen year = 2023 + +compress +order year state county share_debt_coll share_debt_coll_quality subgroup_type subgroup +gsort year state county subgroup + +export delimited using "$output\county-debt-coll-shares-2023-autoretail.csv", datafmt replace + + +/* +**** +** DID NOT COMBINE AS COUNTY AND STATE NAMES IN 2022 FILES ARE NUMERIC BUT STRING WITH NAMES IN 2023 +** DON'T KNOW WHAT 2022 NUMERIC COUNTY AND STATE NAMES STAND FOR +*********************************************************** +** Combine 2022 and 2023 county-level data in one csv file +*********************************************************** +import delimited using "$output\county-debt-coll-shares-2022.csv", clear +save "$output\county-debt-coll-shares-2022.dta", replace + +append using "$output\county-debt-coll-shares-2023.dta" +*/ diff --git a/01_financial-well-being/dia-2023/dia_lbls_all_autoretail_county_2023_1Jul2024.xlsx b/01_financial-well-being/dia-2023/dia_lbls_all_autoretail_county_2023_1Jul2024.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..0885d175ed183c586d87020d509cc5e2a81e517e GIT binary patch literal 461041 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