File Overview

Project: Flood Risk and Property Values

Code

library(tidyverse)

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Code

library(glue)
library(kableExtra)


Attaching package: 'kableExtra'

The following object is masked from 'package:dplyr':

    group_rows

Code

library(stringr)

files <- readxl::read_xlsx("readme_file_information.xlsx")

Code

files |> 
  select(File, Purpose, Inputs, Outputs, `Analysis Step`) |>
  mutate(markdown = glue::glue("
### {row_number()}. `{File}`  
**Purpose:**  
{Purpose}  

**Inputs:**   

- {str_replace_all(Inputs, ', ', '\n- ')}  

**Outputs:**  

- {str_replace_all(Outputs, ', ', '\n- ')}  
")) |> 
  pull(markdown) |> 
  cat(sep = "\n\n")

1. `AssessedValues _andFIRMS.qmd`

Purpose:
Early exploration of AV trends in SFHA and flood-prone parcels using CCAO data

Inputs:

Parcel universe
AV data

Outputs:

Exploratory graphs and maps

2. `building_footprint_clips.R`

Purpose:
Identifies parcels that have a building in them where the building is within the SFHA. Specifically uses premade SFHA parcels and intersects it with building outlines to see which SFHA parcels to keep. (earlier SFHA parcel files were created from the land polygon intersecting with the SFHA and was over inclusive.)

Inputs:

cook_MS.shp (building outlines)
SFHA shapefiles

Outputs:

processed/buildings_in_sfha_w_parcelinfo.shp
processed/buildings_distinct_in_sfha.csv

3. `buyouts.R`

Purpose:
Identifies PINs that were bought out due to high flood risk

Inputs:

Illinois Buyout Database BuyoutPoints_Statewide.xlsx

Outputs:

none

4. `CC_Individual_ FEMA_Assistance.qmd`

Purpose:
Analyzes FEMA IA aid at ZIP level during recent flood events; descriptive stats on applicants and aid granted

Inputs:

data/raw/indiv_assistance_CookCounty.csv
data/processed/treated_zipcodes.csv

Outputs:

census block
tract
zip code
and muni level post-disaster aid data

5. `clean_damanged City_names`

Purpose:
Used to assign municipality names to individual aid data from FEMA that had typos in names. Join to IA data. Takes damagedCity variable from Open FEMA individual assistance, exports city names which had tons of typos. This was put in chatGPT to match with clean names.

Inputs:

Open FEMA API
City_Name_Mapping.csv

Outputs:

data/raw/ia_city_names.csv which becomes data/processed/City_Mapping_Names.csv
indiv_assistance_V2_CookCounty_wNames.csv

6. `Cook_flood_policies _and_claims.qmd`

Purpose:
Summarizes NFIP claims and policies across geographies (ZIP, block, tract, muni)

Inputs:

data/raw/nfipclaims_CookCounty.csv
data/raw/nfippolicies_CookCounty_all.csv

Outputs:

Aggregated claim/policy stats. Not used except to show that there are not many claims or insurance policies in cook county. But there are a lot of post-disaster FEMA aid.

7. `Cook_Sales_data.qmd`

Purpose:
Links sales data with flood risk indicators (SFHA, LOMR, Flood Factor); identifies multi-sale parcels and treatment status

Inputs:

data/raw/assessor_parcel_sales.csv, parcels_sfha_2018.gpkg, parcels_sfha_2024.gpkg
parcels_lomrs.gpkg, data/raw/pins_floodfactor_2019.csv

Outputs:

Counts of PINs by treatment status
sales trends

8. `CookCounty _ParcelMaps.qmd - ARCHIVED`

Purpose:
Early mapping of parcels marked SFHA in CCAO data; not currently used

Inputs:

CCAO parcel universe

Outputs:

Static SFHA parcel maps

9. `data_prep.R`

Purpose:
Takes sales data and joins FIRM variables and SFHA indicator variables to the sales. Makes the res_sales.RDS file that goes to 2_create_dataframes which creates the dataframes for files that run models (Question1, Question2, Question3)

Inputs:

raw/Assessor_Parcel_Sales_20250105.csv
processed/parcels_wFIRMS.csv, processed/sfha_indicator_pins.csv, processed/lomr_pins_2024.csv

Outputs:

sales_prepped.rds
res_sales.rds

10. `descriptive_stats _singlefam.qmd`

Purpose:
Naïve OLS and FE models using the “easy” PINs that were always residential

Inputs:

singlefamily_assessed_values.csv

Outputs:

11. `detect_flood_variable _change_in_CCAO`

Purpose:
Tries to identify if CCAO removed PINs that were in LOMRs from SFHA indicator or what year they stopped updating the LOMR data if removed

Inputs:

Open FEMA API

Outputs:

None

12. `Flood_Appeal_PINs.qmd - ARCHIVED`

Purpose:
Identifies and summarizes AV appeal activity for PINs affected by 2023 flood; compares AV changes for appeal vs. neighbor parcels

Inputs:

PTAX-245 appeal forms
assessed values

Outputs:

Graphs of average AV changes
summary stats

13. `Flood_factor_pins.qmd - ARCHIVED`

Purpose:
Filter for PINs with Flood Factor ≥ 5; analyze post-2023 PTAX-245 flood appeals; calculates AV changes in affected land blocks. Mapped berwyn and cicero

Inputs:

Parcel universe API
PTAX-245 appeal forms

Outputs:

Summary tables and figures

14. `make_panel_data.qmd - ARCHIVED`

Purpose:
Combine files created by scripts. Combine data necessary for creating variables in models. Code for combining files was rough draft for creating data_prep.R script

Inputs:

res_pins_ever.csv
sfha_indicator_pins.csv
Assessor_Parcel_Sales.csv
parcels_wFIRMs.csv
floodfactor_scores.csv

Outputs:

singlefamily_assessed_values.csv
treated.csv

15. `mcmillen_salescomparison.qmd`

Purpose:
reads in McMillens Sales Data

Inputs:

parquet file from McMillen
Assessor_sales file from CCAO

Outputs:

16. `pull_addresses_pins_wo_ffscores.R`

Purpose:
Takes PINs that didn’t have flood factor scores and pulls addresses to make searching flood factor score faster. Otherwise you have to search the PIN to get the address, and then search the address to get the Risk Score.

Inputs:

missing_floodfactor_scores.xlsx
API for Cook County parcel addresses

Outputs:

pins_with_some_addresses.csv

17. `pull_distinct_ resPINs.R`

Purpose:
Extract all parcels that were residential from 2006–2023 and pull assessed values

Inputs:

PTAXSIM database

Outputs:

data/raw/residential_pins_ever.csv, pin_muni_key.csv, muniname_taxcode_key.csv

18. `pull_floodfactor _pin_list.R`

Purpose:
Join Flood Factor risk scores (2019 snapshot) to Cook County parcel universe

Inputs:

Parcel universe with PINs
Flood Factor data

Outputs:

data/raw/floodfactor_scores.csv
data/processed/floodfactor_scores.csv

19. `pull_individual_ assistance_applicants.R`

Purpose:
Pull FEMA Individual Assistance (IA) application data for Cook County (accepted and denied)

Inputs:

FEMA IA API

Outputs:

data/raw/indiv_assistance_CookCounty.csv, data/processed/treated_zipcodes.csv

20. `pull_NFIP_ redactedclaims.R`

Purpose:
Pull NFIP policy and claims data for Cook County from FEMA API

Inputs:

NFIP Policies API
NFIP Claims API

Outputs:

data/raw/nfippolicies_CookCounty_all.csv, data/raw/nfipclaims_CookCounty.csv

21. `pull_parcel_sfs.R`

Purpose:
Download and convert Cook County parcel shapefiles for 2018 and 2023

Inputs:

ptaxsim parcel centroids

Outputs:

S_FIRM_PAN.csv, parcels_wFIRMS.csv

22. `shapefile_sfha_changes.R`

Purpose:
Compares CCAO flood variables to NFHL. Makes shapefiles and also CSV versions of PINs that are in each SFHA or LOMR

Inputs:

NFHL 2018 and NFHL 2024 (NFHL_17_20180129.gdb
Statewide_NFHL_17_20240628.gdb)

Outputs:

sfha_indicator_pins.csv
S_FIRM_PAN.csv
parcels_sfha_2018.csv(shp)
parcels_lomrs_2018.csv(shp)
sfha_pins_2024.csv
lomr_pins_2024.csv,

23. `waterbasins_map.R`

Purpose:
Makes visualization of cook county with rivers and water basins. Not actually used for dissertation.

Inputs:

Water Basins shapefiles online. River shapefiles

Outputs:

24. `2_create_datasets.qmd`

Purpose:
Creates df_prep and df_pairs for files that run the models. Reads in sales data and turns it into repeat sales data format

Inputs:

res_sales.rds
pin_muni_key.csv
muni_shortnames.xlsx

Outputs:

df_pairs.RDS
ff_pairs.RDS
df_prep.RDS

25. `3_check_assumptions`

Purpose:
Check for parallel trends for models

Inputs:

Outputs:

26. `Question1`

Purpose:
NA

Inputs:

Outputs:

27. `Question2`

Purpose:
NA

Inputs:

Outputs:

28. `Question3`

Purpose:
NA

Inputs:

city_name_mapping.csv
FEMA API for individual assistance

Outputs:

29. `data_prep_buildings.R`

Purpose:
NA

Inputs:

Outputs:

30. `didFF_test.R`

Purpose:
Implied density tests of distributional parallel trends. Saves model and plot output because it takes a long time to run.

Inputs:

df_prep_buildings.RDS

Outputs:

outputs/didFF_model_out.rds
outputs/didFF_plot_out.rds
outputs/didFF_model_out2.rds
outputs/didFF_plot_out2.rds

31. `q1_assumption_tests.qmd`

Purpose:
NOT USED 11/23/2025: use did packageto by Callaway & Sant’Anna but didn’t do treatment within the cohorts. Instead it just compared pre and post event trends of the cohorts, where it ran the models as if each cohort was treated.

Inputs:

Outputs:

32. `Question1_continued_staggered.qmd`

Purpose:
Compares Fixed Effects models for question 1 to fixest::sunab() estimates. Creates staggered treatment plots and staggered model estimates for Question 1.

Inputs:

df_prep_buildings.RDS

Outputs:

33. `comparison_2variables.R`

Purpose:
uses high_ff _post variable

Inputs:

df_prep_bldg_v2026_03.RDS

Outputs:

outputs/compared_by2variables.rds

34. `comparison_3variables.R`

Purpose:
splits high_ff_score & post variable

Inputs:

df_prep_bldg_v2026_03.RDS

Outputs:

outputs/compared_by3variables.rds

Code

#DT::datatable(files)


files |> kable(booktabs = TRUE) |> #kable_paper(full_width = F) |>
  column_spec(1, width = "1in") |>
  column_spec(2, width = "3in") |>
  column_spec(3, width = "1in") |>
  column_spec(4, width = "1in") |>
  column_spec(5, width = "1in")

File	Purpose	Inputs	Outputs	Analysis Step	DV Model Type	For dissertation	Became targets pipeline?
AssessedValues _andFIRMS.qmd	Early exploration of AV trends in SFHA and flood-prone parcels using CCAO data	Parcel universe, AV data	Exploratory graphs and maps	Exploratory & Descriptive Analysis	Assessed Value	No	NA
building_footprint_clips.R	Identifies parcels that have a building in them where the building is within the SFHA. Specifically uses premade SFHA parcels and intersects it with building outlines to see which SFHA parcels to keep. (earlier SFHA parcel files were created from the land polygon intersecting with the SFHA and was over inclusive.)	cook_MS.shp (building outlines), SFHA shapefiles	processed/buildings_in_sfha_w_parcelinfo.shp, processed/buildings_distinct_in_sfha.csv	Data Preparation Scripts	NA	Y	NA
buyouts.R	Identifies PINs that were bought out due to high flood risk	Illinois Buyout Database BuyoutPoints_Statewide.xlsx	none	Other External Data Exploration	NA	dropped - q3	NA
CC_Individual_ FEMA_Assistance.qmd	Analyzes FEMA IA aid at ZIP level during recent flood events; descriptive stats on applicants and aid granted	data/raw/indiv_assistance_CookCounty.csv, data/processed/treated_zipcodes.csv	census block, tract, zip code, and muni level post-disaster aid data	Exploratory & Descriptive Analysis	NA	dropped - q3	NA
clean_damanged City_names	Used to assign municipality names to individual aid data from FEMA that had typos in names. Join to IA data. Takes damagedCity variable from Open FEMA individual assistance, exports city names which had tons of typos. This was put in chatGPT to match with clean names.	Open FEMA API, City_Name_Mapping.csv	data/raw/ia_city_names.csv which becomes data/processed/City_Mapping_Names.csv, indiv_assistance_V2_CookCounty_wNames.csv	Data Preparation Scripts	NA	dropped - q3	NA
Cook_flood_policies _and_claims.qmd	Summarizes NFIP claims and policies across geographies (ZIP, block, tract, muni)	data/raw/nfipclaims_CookCounty.csv, data/raw/nfippolicies_CookCounty_all.csv	Aggregated claim/policy stats. Not used except to show that there are not many claims or insurance policies in cook county. But there are a lot of post-disaster FEMA aid.	Exploratory & Descriptive Analysis	NA	Background info / Intro	NA
Cook_Sales_data.qmd	Links sales data with flood risk indicators (SFHA, LOMR, Flood Factor); identifies multi-sale parcels and treatment status	data/raw/assessor_parcel_sales.csv, parcels_sfha_2018.gpkg, parcels_sfha_2024.gpkg, parcels_lomrs.gpkg, data/raw/pins_floodfactor_2019.csv	Counts of PINs by treatment status, sales trends	Exploratory & Descriptive Analysis	Sales	No	NA
CookCounty _ParcelMaps.qmd - ARCHIVED	Early mapping of parcels marked SFHA in CCAO data; not currently used	CCAO parcel universe	Static SFHA parcel maps	Exploratory & Descriptive Analysis	NA	No	NA
data_prep.R	Takes sales data and joins FIRM variables and SFHA indicator variables to the sales. Makes the res_sales.RDS file that goes to 2_create_dataframes which creates the dataframes for files that run models (Question1, Question2, Question3)	raw/Assessor_Parcel_Sales_20250105.csv, processed/parcels_wFIRMS.csv, processed/sfha_indicator_pins.csv, processed/lomr_pins_2024.csv	\|sales_prepped.rds, res_sales.rds	\|Data Preparation Scripts	\|NA	\|NA	\|Y
descriptive_stats _singlefam.qmd	Naïve OLS and FE models using the "easy" PINs that were always residential	singlefamily_assessed_values.csv	NA	Exploratory & Descriptive Analysis	NA	No	NA
detect_flood_variable _change_in_CCAO	Tries to identify if CCAO removed PINs that were in LOMRs from SFHA indicator or what year they stopped updating the LOMR data if removed	Open FEMA API	None	Data Preparation Scripts	NA	No	No
Flood_Appeal_PINs.qmd - ARCHIVED	Identifies and summarizes AV appeal activity for PINs affected by 2023 flood; compares AV changes for appeal vs. neighbor parcels	PTAX-245 appeal forms, assessed values	Graphs of average AV changes, summary stats	Exploratory & Descriptive Analysis	Assessed Value	dropped - q3	NA
Flood_factor_pins.qmd - ARCHIVED	Filter for PINs with Flood Factor ≥ 5; analyze post-2023 PTAX-245 flood appeals; calculates AV changes in affected land blocks. Mapped berwyn and cicero	Parcel universe API, PTAX-245 appeal forms	Summary tables and figures	Exploratory & Descriptive Analysis	Assessed Value	No	NA
make_panel_data.qmd - ARCHIVED	Combine files created by scripts. Combine data necessary for creating variables in models. Code for combining files was rough draft for creating data_prep.R script	res_pins_ever.csv, sfha_indicator_pins.csv, Assessor_Parcel_Sales.csv, parcels_wFIRMs.csv, floodfactor_scores.csv	singlefamily_assessed_values.csv, treated.csv	Data Preparation Scripts	Assessed Value	No	Y
mcmillen_salescomparison.qmd	reads in McMillens Sales Data	parquet file from McMillen, Assessor_sales file from CCAO	NA	Exploratory & Descriptive Analysis	Sales	No	NA
pull_addresses_pins_wo_ffscores.R	Takes PINs that didn't have flood factor scores and pulls addresses to make searching flood factor score faster. Otherwise you have to search the PIN to get the address, and then search the address to get the Risk Score.	missing_floodfactor_scores.xlsx, API for Cook County parcel addresses	pins_with_some_addresses.csv	Data Preparation Scripts	NA	Y - Q2 prep	NA
pull_distinct_ resPINs.R	Extract all parcels that were residential from 2006–2023 and pull assessed values	PTAXSIM database	data/raw/residential_pins_ever.csv, pin_muni_key.csv, muniname_taxcode_key.csv	Data Preparation Scripts	Assessed Value	Y	NA
pull_floodfactor _pin_list.R	Join Flood Factor risk scores (2019 snapshot) to Cook County parcel universe	Parcel universe with PINs, Flood Factor data	data/raw/floodfactor_scores.csv, data/processed/floodfactor_scores.csv	Data Preparation Scripts	NA	Y - Q2	NA
pull_individual_ assistance_applicants.R	Pull FEMA Individual Assistance (IA) application data for Cook County (accepted and denied)	FEMA IA API	data/raw/indiv_assistance_CookCounty.csv, data/processed/treated_zipcodes.csv	Other External Data Exploration	NA	dropped - q3	NA
pull_NFIP_ redactedclaims.R	Pull NFIP policy and claims data for Cook County from FEMA API	NFIP Policies API, NFIP Claims API	data/raw/nfippolicies_CookCounty_all.csv, data/raw/nfipclaims_CookCounty.csv	Other External Data Exploration	NA	dropped - q3	NA
pull_parcel_sfs.R	Download and convert Cook County parcel shapefiles for 2018 and 2023	ptaxsim parcel centroids	S_FIRM_PAN.csv, parcels_wFIRMS.csv	Data Preparation Scripts	NA	NA	Y
shapefile_sfha_changes.R	Compares CCAO flood variables to NFHL. Makes shapefiles and also CSV versions of PINs that are in each SFHA or LOMR	NFHL 2018 and NFHL 2024 (NFHL_17_20180129.gdb, Statewide_NFHL_17_20240628.gdb)	sfha_indicator_pins.csv, S_FIRM_PAN.csv, parcels_sfha_2018.csv(shp), parcels_lomrs_2018.csv(shp), sfha_pins_2024.csv, lomr_pins_2024.csv,	Data Preparation Scripts	NA	NA	Y
waterbasins_map.R	Makes visualization of cook county with rivers and water basins. Not actually used for dissertation.	Water Basins shapefiles online. River shapefiles	NA	Other External Data Exploration	NA	No	N
2_create_datasets.qmd	Creates df_prep and df_pairs for files that run the models. Reads in sales data and turns it into repeat sales data format	res_sales.rds, pin_muni_key.csv, muni_shortnames.xlsx	df_pairs.RDS, ff_pairs.RDS, df_prep.RDS	Data Preparation Scripts	Sales	NA	NA
3_check_assumptions	Check for parallel trends for models	NA	NA	Analysis	NA	NA	NA
Question1	NA	NA	NA	Analysis	NA	NA	NA
Question2	NA	NA	NA	NA	NA	NA	NA
Question3	NA	city_name_mapping.csv, FEMA API for individual assistance	NA	NA	NA	dropped - q3	NA
data_prep_buildings.R	NA	NA	NA	NA	NA	NA	NA
didFF_test.R	Implied density tests of distributional parallel trends. Saves model and plot output because it takes a long time to run.	df_prep_buildings.RDS	outputs/didFF_model_out.rds, outputs/didFF_plot_out.rds, outputs/didFF_model_out2.rds, outputs/didFF_plot_out2.rds	Data Preparation Scripts	Sales	NA	NA
q1_assumption_tests.qmd	NOT USED 11/23/2025: use `did` packageto by Callaway & Sant'Anna but didn't do treatment within the cohorts. Instead it just compared pre and post event trends of the cohorts, where it ran the models as if each cohort was treated.	NA	NA	Data Preparation Scripts	Sales	NA	NA
Question1_continued_staggered.qmd	Compares Fixed Effects models for question 1 to fixest::sunab() estimates. Creates staggered treatment plots and staggered model estimates for Question 1.	df_prep_buildings.RDS	NA	Analysis	NA	NA	NA
comparison_2variables.R	uses high_ff _post variable	df_prep_bldg_v2026_03.RDS	outputs/compared_by2variables.rds	NA	NA	Y - Q2	NA
comparison_3variables.R	splits high_ff_score & post variable	df_prep_bldg_v2026_03.RDS	outputs/compared_by3variables.rds	NA	NA	Y - Q2	NA

Output Files

Output	Created By
`data/raw/parcels_2018.gpkg`	`pull_parcel_sfs.R`
`data/raw/parcels_2023.gpkg`	`pull_parcel_sfs.R`

`data/raw/nfippolicies_CookCounty_all.csv`	`pull_NFIP_redactedclaims.R`
`data/raw/nfipclaims_CookCounty.csv`	`pull_NFIP_redactedclaims.R`
`data/raw/indiv_assistance_CookCounty.csv`	`pull_individual_assistance_applicants.R`
`data/raw/residential_pins_ever.csv`	`pull_distinct_resPINs.R`
`data/raw/pin_muni_key.csv`	`pull_distinct_resPINs.R`
`data/raw/muniname_taxcode_key.csv`	`pull_distinct_resPINs.R`
`data/raw/pins_floodfactor_2019.csv`	`pull_floodfactor_pin_list.R`
processed/ treated.csv	`make_panel_data.qmd`
raw/floodfactor_scores.csv	pull_floodfactor_pin_list.R
outputs/nbh_pins_parceluniversepull2022.csv	??
outputs/pins_in_Blocks_2006_2023_20241126.csv	??

Data Cleaning Notes

Do filtering steps last. Keep all property classes until creating the panel dataset for analysis.

Create a long-format dataset with:

Key Variables:

year: Matching the time of assessment or sale
in_sfha: 0/1 for floodplain presence that year
flood_factor_score: Ordinal flood risk score (e.g., 1–10)
in_lomr: 0/1 if parcel is in a LOMR revision area that year
av: Assessed value that year
sale_price: Sale price (if sold that year)
sold: 0/1 if there was a sale
treatment: 1 if the PIN was ever added to (or removed from) the SFHA (i.e., eligible for treatment)
post: 1 if observation is after the map change
added_to_sfha = (in_sfha_2024 == 1 & in_sfha_2018 == 0) removed_from_sfha = (in_sfha_2024 == 0 & in_sfha_2018 == 1)
treatment = 1 if added_to_sfha | removed_from_sfha

If you’re using multiple years of sales and assessed values, define:

post = 1 for all years after the map change
pre = 1 for years before

Optionally use event_time = year - treatment_year to do event study style DiD

Project: Flood Risk and Property Values

1. AssessedValues _andFIRMS.qmd

2. building_footprint_clips.R

3. buyouts.R

4. CC_Individual_ FEMA_Assistance.qmd

5. clean_damanged City_names

6. Cook_flood_policies _and_claims.qmd

7. Cook_Sales_data.qmd

8. CookCounty _ParcelMaps.qmd - ARCHIVED

9. data_prep.R

10. descriptive_stats _singlefam.qmd

11. detect_flood_variable _change_in_CCAO

12. Flood_Appeal_PINs.qmd - ARCHIVED

13. Flood_factor_pins.qmd - ARCHIVED

14. make_panel_data.qmd - ARCHIVED

15. mcmillen_salescomparison.qmd

16. pull_addresses_pins_wo_ffscores.R

17. pull_distinct_ resPINs.R

18. pull_floodfactor _pin_list.R

19. pull_individual_ assistance_applicants.R

20. pull_NFIP_ redactedclaims.R

21. pull_parcel_sfs.R

22. shapefile_sfha_changes.R

23. waterbasins_map.R

24. 2_create_datasets.qmd

25. 3_check_assumptions

26. Question1

27. Question2

28. Question3

29. data_prep_buildings.R

30. didFF_test.R

31. q1_assumption_tests.qmd

32. Question1_continued_staggered.qmd

33. comparison_2variables.R

34. comparison_3variables.R

Output Files

Data Cleaning Notes

1. `AssessedValues _andFIRMS.qmd`

2. `building_footprint_clips.R`

3. `buyouts.R`

4. `CC_Individual_ FEMA_Assistance.qmd`

5. `clean_damanged City_names`

6. `Cook_flood_policies _and_claims.qmd`

7. `Cook_Sales_data.qmd`

8. `CookCounty _ParcelMaps.qmd - ARCHIVED`

9. `data_prep.R`

10. `descriptive_stats _singlefam.qmd`

11. `detect_flood_variable _change_in_CCAO`

12. `Flood_Appeal_PINs.qmd - ARCHIVED`

13. `Flood_factor_pins.qmd - ARCHIVED`

14. `make_panel_data.qmd - ARCHIVED`

15. `mcmillen_salescomparison.qmd`

16. `pull_addresses_pins_wo_ffscores.R`

17. `pull_distinct_ resPINs.R`

18. `pull_floodfactor _pin_list.R`

19. `pull_individual_ assistance_applicants.R`

20. `pull_NFIP_ redactedclaims.R`

21. `pull_parcel_sfs.R`

22. `shapefile_sfha_changes.R`

23. `waterbasins_map.R`

24. `2_create_datasets.qmd`

25. `3_check_assumptions`

26. `Question1`

27. `Question2`

28. `Question3`

29. `data_prep_buildings.R`

30. `didFF_test.R`

31. `q1_assumption_tests.qmd`

32. `Question1_continued_staggered.qmd`

33. `comparison_2variables.R`

34. `comparison_3variables.R`