Yusufcan Masatlioglu
Biographic Data
| ID | 8920528 |
|---|---|
| NAME | Yusufcan Masatlioglu |
| GIVEN NAMES | Yusufcan |
| FAMILY NAME | Masatlioglu |
| SIGNATURE | MASATLIOGLU Y |
| AFFILIATIONS | Department of Economics, University of Maryland, College Park, MD |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Context-Dependent Heterogeneous Preferences: A Comment on Barseghyan and Molinari (2023)
Barseghyan and Molinari give sufficient conditions for semi-nonparametric point identification of parameters of interest in a mixture model of decision-making under risk, allowing for unobserved heterogeneity in utility functions and limited consideration. A key assumption in the model is that the heterogeneity of risk preferences is unobservable but context-independent. In this comment, we build on their insights and present identification resul…
Progressive Random Choice
We introduce a flexible framework to study probabilistic choice that accommodates heterogeneous types and bounded rationality. We provide a novel progressive structure for the heterogeneous types to capture heterogeneity due to varying levels of a behavioral trait. Given an order of alternatives, our progressive structure sorts the types by the extent to which they align with this order. Unlike the random-utility model, our model uniquely identif…
A Random Attention Model
This paper illustrates how one can deduce preference from observed choices when attention is not only limited but also random. In contrast to earlier approaches, we introduce a Random Attention Model (RAM) where we abstain from any particular attention formation, and instead consider a large class of nonparametric random attention rules. Our model imposes one intuitive condition, termed Monotonic Attention, which captures the idea that each consi…
A Random Attention Model
This paper illustrates how one can deduce preference from observed choices when attention is not only limited but also random. In contrast to earlier approaches, we introduce a Random Attention Model (RAM) where we abstain from any particular attention formation, and instead consider a large class of nonparametric random attention rules. Our model imposes one intuitive condition, termed Monotonic Attention, which captures the idea that each consi…
A Random Attention Model
This paper illustrates how one can deduce preference from observed choices when attention is not only limited but also random. In contrast to earlier approaches, we introduce a Random Attention Model (RAM) where we abstain from any particular attention formation, and instead consider a large class of nonparametric random attention rules. Our model imposes one intuitive condition, termed Monotonic Attention, which captures the idea that each consi…
Progressive Random Choice
We introduce a flexible framework to study probabilistic choice that accommodates heterogeneous types and bounded rationality. We provide a novel progressive structure for the heterogeneous types to capture heterogeneity due to varying levels of a behavioral trait. Given an order of alternatives, our progressive structure sorts the types by the extent to which they align with this order. Unlike the random-utility model, our model uniquely identif…
Context-Dependent Heterogeneous Preferences: A Comment on Barseghyan and Molinari (2023)
Barseghyan and Molinari give sufficient conditions for semi-nonparametric point identification of parameters of interest in a mixture model of decision-making under risk, allowing for unobserved heterogeneity in utility functions and limited consideration. A key assumption in the model is that the heterogeneity of risk preferences is unobservable but context-independent. In this comment, we build on their insights and present identification resul…
Decision-Making and Behavioral Economics (3 works) · Econometrics (3 works) · Economic and Environmental Valuation (3 works) · Artificial Intelligence (2 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Economics (2 works) · Mathematics (2 works) · Microeconomics (2 works) · Nonparametric statistics (2 works)