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Working Paper
A Model of Charles Ponzi
We develop a model of Ponzi schemes with asymmetric information to study Ponzi frauds. A long-lived agent offers to save on behalf of short-lived agents at a higher rate than they can earn themselves. The long-lived agent may genuinely have a superior savings technology, but may be an imposter trying to steal from short-lived agents. The model identifies when a Ponzi fraud can occur and what interventions can prevent it. A key feature of Ponzi frauds is that the long-lived agent builds trust over time and improves their reputation by keeping the scheme going.
Working Paper
A Model of Charles Ponzi
We develop a model of Ponzi schemes with asymmetric information to study Ponzi frauds. A long-lived agent offers to save on behalf of short-lived agents at a higher rate than they can earn themselves. The long-lived agent may genuinely have a superior savings technology, but may be an imposter trying to steal from short-lived agents. The model identifies when a Ponzi fraud can occur and what interventions can prevent it. A key feature of Ponzi frauds is that the long-lived agent builds trust over time and improves their reputation by keeping the scheme going.
Working Paper
Very Simple Markov-Perfect Industry Dynamics
This paper develops an econometric model of industry dynamics for concentrated markets that can be estimated very quickly from market-level panel data on the number of producers and consumers using a nested fixed-point algorithm. We show that the model has an essentially unique symmetric Markov-perfect equilibrium that can be calculated from the fixed points of a finite sequence of low-dimensional contraction mappings. Our nested fixed point procedure extends Rust's (1987) to account for the observable implications of mixed strategies on survival. We illustrate the model's empirical ...
Working Paper
Insurance and Inequality with Persistent Private Information
We study optimal insurance contracts for an agent with Markovian private information. Our main results characterize the implications of constrained efficiency for long-run welfare and inequality. Under minimal technical conditions, there is Absolute Immiseration: in the long run, the agent?s consumption and utility converge to their lower bounds. When types are persistent and utility is unbounded below, there is Relative Immiseration: low-type agents are immiserated at a faster rate than high-type agents, and ?pathwise welfare inequality? grows without bound. These results extend and ...
Working Paper
Insurance and Inequality with Persistent Private Information
This paper studies the optimal tradeoff between insurance and inequality in economies with persistent private information.We consider a principal-agent model in which the principal insures the agent against privately-observed shocks to his endowment, which follows an ergodic finite-state Markov chain that may exhibit arbitrary serial correlation. The optimal contract always induces immiseration: the agent’s consumption and utility become arbitrarily negative in the long run. When the endowment is positively serially correlated, the optimal contract provides increasingly high-powered ...
Working Paper
Insurance and Inequality with Persistent Private Information
This paper studies the implications of optimal insurance provision for long-run welfare and inequality in economies with persistent private information. We consider a model in which a principal insures an agent whose privately observed endowment follows an ergodic, finite Markov chain. The optimal contract always induces immiseration: the agent’s consumption and utility decrease without bound. Under positive serial correlation, the optimal contract also features backloaded high-powered incentives: the sensitivity of the agent’s utility with respect to his report increases without bound. ...
Working Paper
Insurance and Inequality with Persistent Private Information
This paper studies the implications of optimal insurance provision for long-run welfare and inequality in economies with persistent private information. We consider a model in which a principal insures an agent whose privately observed endowment follows an ergodic, finite Markov chain. The optimal contract always induces immiseration: the agent’s consumption and utility decrease without bound. Under positive serial correlation, the optimal contract also features backloaded high-powered incentives: the sensitivity of the agent’s utility with respect to his report increases without bound. ...
Working Paper
Insurance and Inequality with Persistent Private Information
We study the implications of optimal insurance provision for long-run welfare and inequality in economies with persistent private information. A principal insures an agent whose private type follows an ergodic, finite-state Markov chain. The optimal contract always induces immiseration: the agent’s consumption and utility decrease without bound. Under positive serial correlation, it also backloads high-powered incentives: the sensitivity of the agent’s utility with respect to his reports increases without bound. These results extend—and help elucidate the limits of—the hallmark ...
Working Paper
Insurance and Inequality with Persistent Private Information
We study the implications of optimal insurance provision for long-run welfare and inequality in economies with persistent private information. A principal insures an agent whose private type follows an ergodic, finite-state Markov chain. The optimal contract always induces immiseration: the agent’s consumption and utility decrease without bound. Under positive serial correlation, it also backloads high-powered incentives: the sensitivity of the agent’s utility with respect to his reports increases without bound. These results extend—and help elucidate the limits of—the hallmark ...
Working Paper
Extended Supplement to “Insurance and Inequality with Persistent Private Information”
This supplement contains auxiliary technical results and proofs omitted from Bloedel, Krishna, and Leukhina (2025) (henceforth BKL) and its Supplemental Appendix (henceforth SA). First, Section I proves parts (a)–(c) and (e)–(f) of Theorem 3 from Appendix B.1 of BKL. (Part (d) of Theorem 3 is proved in SA-E.1 of BKL.) Second, Section J proves Proposition 3.2 from Section 3.3 of BKL and Lemma B.2 from Appendix B.2 of BKL. Finally, Section K proves supporting facts for Properties (a)–(e) from Section 5.2 of BKL. Throughout, we follow the numbering and labeling conventions from BKL and its ...