Summary
Focusing on verifiability, PRIVDIMA studies the regulation of data privacy to protect consumers from excessive price discrimination in digital markets.
PRIVDIMA breaks with previous literature by acknowledging that data has a verifiability effect. It proposes a study of data privacy regulation by explicitly modelling this verifiability effect. Its motivation is as follows: 1) data collection in digital markets renders private information verifiable; 2) due to unravelling, this verifiability effect of data impacts regulation at a fundamental level; 3) extant work on privacy regulation abstracts from the effect; 4) data privacy rules that ignore verifiability effects lead to misguided regulation. PRIVDIMA is to rectify this.
PRIVDIMA has 3 objectives. Objective 1 is to incorporate verifiability in the state-of-the-art theories of mechanism and information design, readying them for the analysis of a new range of problems where verifiability matters. Objective 2 is to derive concrete policy implications for data privacy based on regulating the use of data to limit price discrimination. It yields new insights on regulating both long and short run contracts in models of behaviour-based price discrimination. Objective 3 is to derive concrete policy implications for data privacy based on regulating the collection of data. It yields insights on how to prevent an unravelling of private information by which the verifiability effect of data hurts consumers.
Objective 1 implies a major advancement for the field of economic theory. Objectives 2 and 3 ensure that consumers obtain a fair share of the benefits from digitalization, promoting not only equity and fairness, but also public support for future digitalization, allowing societies to reap its benefits while avoiding social conflict.
As PRIVDIMA’s PI, I have a proven track record in developing and applying the required methods, and expertise in working with both verifiable and non-verifiable information.
PRIVDIMA breaks with previous literature by acknowledging that data has a verifiability effect. It proposes a study of data privacy regulation by explicitly modelling this verifiability effect. Its motivation is as follows: 1) data collection in digital markets renders private information verifiable; 2) due to unravelling, this verifiability effect of data impacts regulation at a fundamental level; 3) extant work on privacy regulation abstracts from the effect; 4) data privacy rules that ignore verifiability effects lead to misguided regulation. PRIVDIMA is to rectify this.
PRIVDIMA has 3 objectives. Objective 1 is to incorporate verifiability in the state-of-the-art theories of mechanism and information design, readying them for the analysis of a new range of problems where verifiability matters. Objective 2 is to derive concrete policy implications for data privacy based on regulating the use of data to limit price discrimination. It yields new insights on regulating both long and short run contracts in models of behaviour-based price discrimination. Objective 3 is to derive concrete policy implications for data privacy based on regulating the collection of data. It yields insights on how to prevent an unravelling of private information by which the verifiability effect of data hurts consumers.
Objective 1 implies a major advancement for the field of economic theory. Objectives 2 and 3 ensure that consumers obtain a fair share of the benefits from digitalization, promoting not only equity and fairness, but also public support for future digitalization, allowing societies to reap its benefits while avoiding social conflict.
As PRIVDIMA’s PI, I have a proven track record in developing and applying the required methods, and expertise in working with both verifiable and non-verifiable information.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101096682 |
| Start date: | 01-10-2023 |
| End date: | 30-09-2028 |
| Total budget - Public funding: | 1 860 125,00 Euro - 1 860 125,00 Euro |
Cordis data
Original description
Focusing on verifiability, PRIVDIMA studies the regulation of data privacy to protect consumers from excessive price discrimination in digital markets.PRIVDIMA breaks with previous literature by acknowledging that data has a verifiability effect. It proposes a study of data privacy regulation by explicitly modelling this verifiability effect. Its motivation is as follows: 1) data collection in digital markets renders private information verifiable; 2) due to unravelling, this verifiability effect of data impacts regulation at a fundamental level; 3) extant work on privacy regulation abstracts from the effect; 4) data privacy rules that ignore verifiability effects lead to misguided regulation. PRIVDIMA is to rectify this.
PRIVDIMA has 3 objectives. Objective 1 is to incorporate verifiability in the state-of-the-art theories of mechanism and information design, readying them for the analysis of a new range of problems where verifiability matters. Objective 2 is to derive concrete policy implications for data privacy based on regulating the use of data to limit price discrimination. It yields new insights on regulating both long and short run contracts in models of behaviour-based price discrimination. Objective 3 is to derive concrete policy implications for data privacy based on regulating the collection of data. It yields insights on how to prevent an unravelling of private information by which the verifiability effect of data hurts consumers.
Objective 1 implies a major advancement for the field of economic theory. Objectives 2 and 3 ensure that consumers obtain a fair share of the benefits from digitalization, promoting not only equity and fairness, but also public support for future digitalization, allowing societies to reap its benefits while avoiding social conflict.
As PRIVDIMA’s PI, I have a proven track record in developing and applying the required methods, and expertise in working with both verifiable and non-verifiable information.
Status
SIGNEDCall topic
ERC-2022-ADGUpdate Date
31-07-2023
Images
No images available.
Geographical location(s)
Structured mapping
