The individual essay is a 500 (minimum) – 700 (maximum) words paper that you will write (open book exam and unlimited time) on a chosen or given topic among the ones discussed in the lectures. It will test the capacity of your own in depth study and in depth understanding of concepts and research outputs (especially the methodologies, the results and their real-word implications) visible in the way how you will describe the state-of-the-art. It will also test your critical-creative analysis and evaluation of the academic articles (from indexed journals only, between 5 and 15, within which and at least 5 from the last 10 years) to be comparatively discussed.
sources:
Group A: The “Human Bias” Problem (Why we need machines)
These papers establish the baseline problem: human appraisers are biased.
- Freddie Mac (2021). “Racial and Ethnic Valuation Gaps in Home Purchase Appraisals.”
- Link:
- Note: This is the primary industry study you should cite first.
- Korver-Glenn, E. (2018). “Compounding Inequalities: How Racial Stereotypes and Discrimination Accumulate across the Housing Market.” (American Sociological Review).
- Link: or
- Howell, J., & Korver-Glenn, E. (2021). “Neighborhoods, Race, and the Twenty-first-century Housing Appraisal Industry.” (Sociology of Race and Ethnicity).
- Link:
Group B: The “Machine Solution” (The Industry Defense)
These sources argue that AVMs are the solution because they are “blind” to race.
- HouseCanary (2021). “Reducing Racial Bias in Home Appraisals Using Automated Valuation Technology.”
- Link:
- Lai, T., & Van Order, R. (2020). “Assessing the Accuracy of Automated Valuation Models.”
- Link: or
Group C: The “Machine Reality” (The Critical Rebuttal)
These papers prove that AVMs just replicate the old bias because they use old data.
- Neal, M., et al. (2020). “How Automated Valuation Models Can Disproportionately Affect Majority-Black Neighborhoods.” (Urban Institute).
- Link:
- Note: This is your most critical source for the “counter-argument.”
- Yadav, N. (2022). “Automated Valuation Models and the Valuation Gap.”
- Link: (You may need to search the title on Google Scholar if the direct SSRN link requires a login).
Bartlett, R., et al. (2022). “Consumer-Lending Discrimination in the FinTech Era.” (Journal of Financial Economics).
template:
Real Estate Evaluation 2025-26 – Luca S. DAcci Individual Assignment
A Comparative Analysis of Racial Bias
in Human and Automated Real Estate Valuations
Student:
Matricola:
Abstract: ~100words
Introduction: ~150 words
Body 1:~150words(traditional method)
body 2:~150 words(modern method)
Critical Synthesis:~100words
conclusion:~60-80 words
references: PLEASE INCLUDE ALL REFERENCES AND ENSURE THEY ARE ALL COHERENTLY WRITTEN BECAUSE THE PROFESSOR FOCUSES ON THIS THE MOST
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