Hello everyone,


I am doing research about racial discrimination in mortgage interest.

Many researchers use the OLS model to investigate whether minorities pay a higher interest rate than comparable white borrowers, controlling for borrower demographic characteristics, creditworthiness, and loan features. In addition, researchers will apply the ''year fixed effect'' and ''county/MSA effect'' to control the unobserved housing market situation at the year of loan origination and the unobserved effect due to the different geographic locations of the property. As an example, please see table 4 on page 45 in paper https://faculty.haas.berkeley.edu/mo...rs/discrim.pdf

However, the data being used in these papers are in fact cross-sectional data instead of panel data. For example, one uses 20000 obs of loan data at the individual level, which were generated between 2009 - 2019. Each obs is a loan being originated by a unique borrower.

As an example of the data:

Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input int(as_of_year county_code) long msamd byte(applicant_race_1 applicant_ethnicity) str10 respondent_id byte(loan_type loan_purpose) long loan_amount_000s
2017   7     . 6 3 "0000068601" 1 1  175
2017   5 38540 5 2 "0000063194" 2 1  196
2017   1 36084 6 3 "0000451965" 1 1 1079
2017  53 33460 6 1 "41-1842999" 1 3  199
2017  47 35614 6 3 "0000613307" 1 3  800
2017 141 21340 5 1 "0000451965" 1 3  170
2017 209 28140 6 2 "0000016450" 2 1  157
2017  39 26420 6 3 "73-1577221" 1 3  183
2017  31 27260 5 2 "0000068490" 1 3   62
2017  91 33874 5 2 "0000451965" 2 1  196
end

In cross-sectional data, data are not observed at T time periods, as a result, the unobserved variables cannot be eliminated by demeaning the variables using the within transformation. Also, the explanatory variable of interest, "race of borrower", is a time-constant variable. It will be swept away by using the within transformation.

Hence, my question is, are the "year fixed effect" and "county/MSA fixed effect" in these papers actually just two sets of dummies?

To be more specific, a set of dummies for the year of loan origination between 2009 - 2019, e.g. if a loan was originated in 2009, then the dummy for 2009 is 1.

And a set of dummies for all counties/MSA, e.g. if a loan was originated at county 86, then the dummy of county 86 is 1.


Thank you!
Lei