Team production in competitive labor markets with adverse selection

Capacity Constrained Firms in (Labor) Markets with Adverse Selection

We discuss a competitive (labor) market where firms face capacity constraints and individuals differ according to their productivity. Firms offer two-dimensional contracts like wage and task level. Then workers choose firms and contracts. Workers might be rationed if the number of applicants exceeds the capacity of the firm. We show that under reasonable assumptions on the distribution of capac...

Uninsurance and Adverse Selection in Health Insurance and Labor Markets

Competitive Insurance Markets and Adverse Selection in the Lab

We provide an experimental analysis of competitive insurance markets with adverse selection. Our parameterized version of the lemons’ model (Akerlof 1970) in the insurance context predicts total crowding out of low-risks when insurers offer a single full insurance contract. The therapy proposed by Rothschild and Stiglitz (1976) to solve this major inefficiency consists of adding a partial insur...

Ambiguity Aversion in Competitive Insurance Markets: Adverse and Advantageous Selection

We analyze an extension of the Rothschild-Stiglitz model with ambiguous loss probabilities and ambiguity-averse consumers to determine whether there are adverse or advantageous selection equilibria. We show that non-increasing absolute ambiguity aversion is sufficient for adverse selection. We show generally that actuarially fair pricing is also sufficient for adverse selection and that advanta...

Competitive Insurance Markets under Adverse Selection and Capacity Constraints

Ever since the seminal work by Rothschild and Stiglitz (1976) on competitive insurance markets under adverse selection the equilibrium-non-existence problem has been one of the major puzzles in insurance economics. We extend the original analysis by considering firms which face capacity constraints, which might be due to limited capital. We show that under mild assumptions a pure strategy equil...