Week 8: Privacy Policies, Incomplete Contracts, and Power

DSAN 5450: Data Ethics and Policy
Spring 2026, Georgetown University

Jeff Jacobs

jj1088@georgetown.edu

Wednesday, March 11, 2026

Privacy Regulations, Privacy Policies, and You

\[ \DeclareMathOperator*{\argmax}{argmax} \DeclareMathOperator*{\argmin}{argmin} \newcommand{\bigexp}[1]{\exp\mkern-4mu\left[ #1 \right]} \newcommand{\bigexpect}[1]{\mathbb{E}\mkern-4mu \left[ #1 \right]} \newcommand{\definedas}{\overset{\small\text{def}}{=}} \newcommand{\definedalign}{\overset{\phantom{\text{defn}}}{=}} \newcommand{\eqeventual}{\overset{\text{eventually}}{=}} \newcommand{\Err}{\text{Err}} \newcommand{\expect}[1]{\mathbb{E}[#1]} \newcommand{\expectsq}[1]{\mathbb{E}^2[#1]} \newcommand{\fw}[1]{\texttt{#1}} \newcommand{\given}{\mid} \newcommand{\green}[1]{\color{green}{#1}} \newcommand{\heads}{\outcome{heads}} \newcommand{\iid}{\overset{\text{\small{iid}}}{\sim}} \newcommand{\lik}{\mathcal{L}} \newcommand{\loglik}{\ell} \DeclareMathOperator*{\maximize}{maximize} \DeclareMathOperator*{\minimize}{minimize} \newcommand{\mle}{\textsf{ML}} \newcommand{\nimplies}{\;\not\!\!\!\!\implies} \newcommand{\orange}[1]{\color{orange}{#1}} \newcommand{\outcome}[1]{\textsf{#1}} \newcommand{\param}[1]{{\color{purple} #1}} \newcommand{\pgsamplespace}{\{\green{1},\green{2},\green{3},\purp{4},\purp{5},\purp{6}\}} \newcommand{\pedge}[2]{\require{enclose}\enclose{circle}{~{#1}~} \rightarrow \; \enclose{circle}{\kern.01em {#2}~\kern.01em}} \newcommand{\pnode}[1]{\require{enclose}\enclose{circle}{\kern.1em {#1} \kern.1em}} \newcommand{\ponode}[1]{\require{enclose}\enclose{box}[background=lightgray]{{#1}}} \newcommand{\pnodesp}[1]{\require{enclose}\enclose{circle}{~{#1}~}} \newcommand{\purp}[1]{\color{purple}{#1}} \newcommand{\sign}{\text{Sign}} \newcommand{\spacecap}{\; \cap \;} \newcommand{\spacewedge}{\; \wedge \;} \newcommand{\tails}{\outcome{tails}} \newcommand{\Var}[1]{\text{Var}[#1]} \newcommand{\bigVar}[1]{\text{Var}\mkern-4mu \left[ #1 \right]} \]

Image credit

Regulations: Comparative Perspective

• No single, “universal” data privacy law \(\implies\) compare and contrast various country/state/org attempts to tackle data policy issues
• Important to retain descriptive/normative distinction! They’ll become harder to distinguish as we discuss:
• What are the regulations currently in existence? (Descriptive)
  • Do we see a trend? (California Effect vs. Delaware Effect)
• What are their drawbacks? (Normative)
  • Fundamental problem of contracts
• Which drawbacks could be addressed “easily” via policy? (requires understanding processes of policy formation)
• Which ones could not? (Prisoner’s Dilemma!)

Present-Day Policy Framework: Notice and Consent

OECD 1980 \(\rightarrow\) EU 1995 \(\rightarrow\) GDPR 2018

OECD Guidelines, 1980

• “The basis for most modern privacy laws” (Sugimoto et al. 2016)
• Collection Limitation Principle: data may be collected “where appropriate, with the knowledge or consent of the data subject.” (OECD 1980, 14)
• Use Limitation Principle: “Personal data should not be disclosed, made available or otherwise used for purposes other than those specified [at time of collection] except with the consent of the data subject” (OECD 1980, 15)

EU Data Protection Directive, 1995

• Art. 7: Processing allowed when “the data subject has unambiguously given his [sic] consent.”
• Art. 8: Use of sensitive data is restricted, except where “the data subject has given his [sic] explicit consent to the processing of those data.”
• Art. 26: Prohibits export of personal data to non-Euro countries lacking “adequate data protection”, except when “the data subject has given his [sic] consent unambiguously to the proposed transfer” (Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the Protection of Individuals with Regard to the Processing of Personal Data and on the Free Movement of Such Data 1995)
• Superceded by GDPR in 2018

EU General Data Protection Regulation (GDPR), 2018

Effects of GDPR…

From Demirer et al. (2024)

• Need to be careful about interpretation!
• Could be due to less tracking, could also be due to monopolization

Effects of GDPR: Effect on Who?

Consumers: Reduced tracking

The GDPR lowered the average number of trackers by about four trackers per publisher

From Miller et al. (2025)

Firms: Harsher impact on small firms

Despite data minimization successes, GDPR had the unintended consequence of increasing relative concentration

From Frey and Presidente (2024)

Distributional Effects

From Demirer et al. (2024)

Going Beyond Just GDPR…

From Piwik.pro, “17 Privacy Laws Around the Globe”

Easy Mode: Policy Diffusion

From Romanosky et al. (2011)

(Policy Diffusion Curve!)

From Romanosky et al. (2011)

👀

Original (theoretical) “adoption curve”, from Rogers (2003)

Hard Mode: Impact of Policy Diffusion

Result (Note the explicitly-identified independent \(\rightarrow\) dependent vars!):

Table 5. Effect of law on identity theft

Dep Var: log(idtheft)	Basic	Basic + Controls
hasLaw	–0.050* (0.026)	–0.061*** (0.023)
Income per capita		0.000 (0.000)
Unemployment rate		0.003 (0.010)
Log(population)		–0.268 (0.343)
State and time fixed effects	Y	Y
Constant	6.852*** (0.014)	11.248** (5.317)
R-squared	0.848	0.850
***: \(p < 0.01\)	**: \(p < 0.05\)	*: \(p < 0.1\)

References

Demirer, Mert, Diego J. Jiménez Hernández, Dean Li, and Sida Peng. 2024. “Data, Privacy Laws and Firm Production: Evidence from the GDPR.” Working Paper No. 32146. Pre-published February. https://doi.org/10.3386/w32146.

Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the Protection of Individuals with Regard to the Processing of Personal Data and on the Free Movement of Such Data, OJ L (1995). http://data.europa.eu/eli/dir/1995/46/oj/eng.

Frey, Carl Benedikt, and Giorgio Presidente. 2024. “Privacy Regulation and Firm Performance: Estimating the GDPR Effect Globally.” Economic Inquiry 62 (3): 1074–89. https://doi.org/10.1111/ecin.13213.

Miller, Klaus M., Karlo Lukic, and Bernd Skiera. 2025. “The Impact of the General Data Protection Regulation (GDPR) on Online Tracking.” International Journal of Research in Marketing, ahead of print, March 11. https://doi.org/10.1016/j.ijresmar.2025.03.002.

OECD. 1980. OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data. Organisation for Economic Co-operation and Development. https://www.oecd-ilibrary.org/science-and-technology/oecd-guidelines-on-the-protection-of-privacy-and-transborder-flows-of-personal-data_9789264196391-en.

Rogers, Everett M. 2003. Diffusion of Innovations, 5th Edition. Simon and Schuster. https://books.google.com?id=9U1K5LjUOwEC.

Romanosky, Sasha, Rahul Telang, and Alessandro Acquisti. 2011. “Do Data Breach Disclosure Laws Reduce Identity Theft?” Journal of Policy Analysis and Management 30 (2): 256–86. https://doi.org/10.1002/pam.20567.

Sugimoto, Cassidy R., Hamid R. Ekbia, and Michael Mattioli. 2016. Big Data Is Not a Monolith. MIT Press. https://books.google.com?id=yp9SDQAAQBAJ.