We analyze a stochastic equilibrium contract-posting model. Firms post employment contracts, wages contingent on all payoff-relevant states. Aggregate productivity is subject to persistent shocks. Both employed and unemployed workers search randomly for these contracts, and are free to quit at any time. An equilibrium of this contract-posting game is Rank-Preserving [RP] if larger firms offer a larger value to their workers in all states of the world. We show that every equilibrium is RP, and equilibrium is unique, if firms differ either only in their initial size, or also in their fixed idiosyncratic productivity but more productive firms are initially larger, in which case turnover is always efficient, as workers always move from less to more productive firms. The RP equilibrium stochastic dynamics of firm size provide an explanation for the empirical finding that large employers are more cyclically sensitive (Moscarini and Postel-Vinay, 2009). RP equilibrium computation is tractable, and we simulate calibrated examples.
This paper produces a comprehensive theory of the value of Bayesian information and its static demand. Our key insight is to assume ‘natural units’ corresponding to the sample size of conditionally i.i.d. signals – focusing on the smooth nearby model of the precision of an observation of a Brownian motion with uncertain drift. In a two state world, this produces the heat equation from physics, and leads to a tractable theory. We derive explicit formulas that harmonize the known small and large sample properties of information, and reveal some fundamental properties of demand: (a) Value ‘non-concavity’: The marginal value of information is initially zero; (b) The marginal value is convex/rising, concave/peaking, then convex/falling; (c) ‘Lumpiness’: As prices rise, demand suddenly chokes off (drops to 0); (d) The minimum information costs on average exceed 2.5% of the payoff stakes; (e) Information demand is hill-shaped in beliefs, highest when most uncertain; (f) Information demand is initially elastic at interior beliefs; (g) Demand elasticity is globally falling in price, and approaches 0 as prices vanish; and (h) The marginal value vanishes exponentially fast in price, yielding log demand. Our results are exact for the Brownian case, and approximately true for weak discrete informative signals. We prove this with a new Bayesian approximation result.
We study a winner-take-all R&D race where firms are privately informed about the uncertain arrival rate of the invention. Due to the interdependent-value nature of the problem, the equilibrium displays a strong herding effect that distinguishes our framework from war-of-attrition models. Nonetheless, equilibrium expenditure in R&D is sub-optimal when the planner is sufficiently impatient. Pessimistic firms prematurely exit the race, so that the expected discounted amount of R&D activity is inefficiently low. This result stands in contrast to the overinvestment in research that is typical of winner-take-all R&D races without private information. We conclude that secrecy in R&D inefficiently slows down the pace of innovation.
We study a winner-take-all R&D race where firms are privately informed about the uncertain arrival rate of the invention. Due to the interdependent-value nature of the problem, the equilibrium displays a strong herding effect that distinguishes our framework from war-of-attrition models. Nonetheless, equilibrium expenditure in R&D is sub-optimal when the planner is sufficiently impatient. Pessimistic firms prematurely exit the race, so that the expected discounted amount of R&D activity is inefficiently low. This result stands in contrast to the overinvestment in research that is typical of winner-take-all R&D races without private information. We conclude that secrecy in R&D inefficiently slows down the pace of innovation.
We interpret workers’ confidence in their own skills as their morale, and investigate the implication of worker overconfidence on the firm’s optimal wage-setting policies. In our model, wage contracts both provide incentives and affect worker morale, by revealing private information of the firm about worker skills. We provide conditions for the non-differentiation wage policy to be profit-maximizing. In numerical examples, worker overconfidence is a necessary condition for the firm to prefer no wage differentiation, so as to preserve some workers’ morale; the non-differentiation wage policy itself breeds more worker overconfidence; finally, wage compression is more likely when aggregate productivity is low.
We investigate the outcomes of simultaneous price competition in the presence of private information on the demand side. Each of two sellers offers a different variety of a good to a buyer endowed with a private binary signal on their relative quality. We analyze how the unique equilibrium of the game changes as a function of the (common) prior belief on the relative quality of the goods and the precision of the private information of the buyer. Competition is fierce, and the buyer enjoys high rents, when the prior belief is biased in favor of one good and private signals are not very informative: the ex ante superior seller cannot resist the temptation to clear the market, and triggers an aggressive response by the competitor. When instead the distribution of ex post valuations is highly spread, due to a vague prior belief and strong signals, the sellers become local monopolists and extract high rents from the buyer. We provide a full characterization of the mixed-strategy equilibrium which arises when the two goods are mildly differentiated ex post. Overall, the market-clearing temptation effect destroys the monotonicity and convexity of the equilibrium profit of a seller in the prior belief. As a consequence, a competing seller does not necessarily benefit from revelation of public information, sometimes even if biased in its favor.
This paper analyzes the behavior of posterior distributions under the Jeffreys prior in a simultaneous equations model. The case under study is that of a general limited information setup with n + 1 endogenous variables. The Jeffreys prior is shown to give rise to a marginal posterior density which has Cauchy-like tails similar to that exhibited by the exact finite sample distribution of the corresponding LIML estimator. A stronger correspondence is established in the special case of a just-identified orthonormal canonical model, where the posterior density under the Jeffreys prior is shown to have the same functional form as the density of the finite sample distribution of the LIML estimator. The work here generalizes that of Chao and Phillips (1997), which gives analogous results for the special case of two endogenous variables.
We investigate the outcomes of simultaneous price competition in the presence of private information on the demand side. Each of two sellers offers a different variety of a good to a buyer endowed with a private binary signal on their relative quality. We analyze how the unique equilibrium of the game changes as a function of the (common) prior belief on the relative quality of the goods and the precision of the private information of the buyer. Competition is fierce, and the buyer enjoys high rents, when the prior belief is biased in favor of one good and private signals are not very informative: the ex ante superior seller cannot resist the temptation to clear the market, and triggers an aggressive response by the competitor. When instead the distribution of ex post valuations is highly spread, due to a vague prior belief and strong signals, the sellers become local monopolists and extract high rents from the buyer. We provide a full characterization of the mixed-strategy equilibrium which arises when the two goods are mildly differentiated ex post. Overall, the market-clearing temptation effect destroys the monotonicity and convexity of the equilibrium profit of a seller in the prior belief. As a consequence, a competing seller does not necessarily benefit from revelation of public information, sometimes even if biased in its favor.
This paper analyzes the behavior of posterior distributions under the Jeffreys prior in a simultaneous equations model. The case under study is that of a general limited information setup with n + 1 endogenous variables. The Jeffreys prior is shown to give rise to a marginal posterior density which has Cauchy-like tails similar to that exhibited by the exact finite sample distribution of the corresponding LIML estimator. A stronger correspondence is established in the special case of a just-identified orthonormal canonical model, where the posterior density under the Jeffreys prior is shown to have the same functional form as the density of the finite sample distribution of the LIML estimator. The work here generalizes that of Chao and Phillips (1997), which gives analogous results for the special case of two endogenous variables.
Keywords: Cauchy tails, exact finite sample distributions, Jeffreys prior, just identification, limited information, posterior density, simultaneous equations model
This paper revisits Wald’s (1947) sequential experimentation paradigm, now assuming that an impatient decision maker can run variable-size experiments each period at some increasing and strictly convex cost before finally choosing an irreversible action. We translate this natural discrete time experimentation story into a tractable control of variance for a continuous time diffusion. Here we robustly characterize the optimal experimentation level: It is rising in the confidence about the project outcome, and for not very convex cost functions, the random process of experimentation levels has a positive drift over time. We also explore several parametric shifts unique to our framework. Among them, we discover what is arguably an `anti-folk’ result: Where the experimentation level is positive, it is often higher for amore impatient decision maker.
This paper more generally suggests that a long-sought economic paradigm that delivers a sensible law of demand for information is our dynamic one — namely, allowing the decision maker an eternal repurchase (resample) option.
This paper revisits Wald’s (1947) sequential experimentation paradigm, now assuming that an impatient decision maker can run variable-size experiments each period at some increasing and strictly convex cost before finally choosing an irreversible action. We translate this natural discrete time experimentation story into a tractable control of variance for a continuous time diffusion. Here we robustly characterize the optimal experimentation level: It is rising in the confidence about the project outcome, and for not very convex cost functions, the random process of experimentation levels has a positive drift over time. We also explore several parametric shifts unique to our framework. Among them, we discover what is arguably an `anti-folk’ result: Where the experimentation level is positive, it is often higher for amore impatient decision maker.
This paper more generally suggests that a long-sought economic paradigm that delivers a sensible law of demand for information is our dynamic one — namely, allowing the decision maker an eternal repurchase (resample) option.