nonlinear pricing to produce information we investigate the firm s dynamic nonlinear pricing problem when facing consumers whose tastes vary according to a scalar index we relax the standard assumption that the firm knows the distribution of this index in general the firm should determine its marginal price schedule as if it were myopic and produce information by lowering the price schedule bunching consumers at positive purchase levels should be avoided as a special case we also consider a market characterized by homogeneous consumers with a static but unknown demand curve we show that when there are repeat purchases the forward looking firm should tend towards penetration pricing otherwise its strategy should tend towards skimming we extend our insights to more general settings and discuss implications for pricing product lines

learning from others outcomes i develop a simple model of social learning in which players observe others outcomes but not their actions a continuum of players arrives continuously over time and each player chooses once and for all between a safe action which succeeds with known probability and a risky action which succeeds with fixed but unknown probability depending on the state of the world the actions also differ in their costs before choosing a player observes the outcomes of k earlier players there is always an equilibrium in which success is more likely in the good state and this alignment property holds whenever the initial generation of players is not well informed about the state in the case of an outcome improving innovation where the risky action may yield a higher probability of success players take the correct action as k in the case of a cost saving innovation where the risky action involves saving a cost but accepting a lower probability of success inefficiency persists as k in any aligned equilibrium whether inefficiency takes the form of under adoption or over adoption also depends on the nature of the innovation convergence of the population to equilibrium may be non monotone

regulatory fog the role of information in regulatory persistence abstract regulation is very persistent even when inefficient we propose an explanation for regulatory persistence based on regulatory fog the phenomenon by which regulation obscures information regarding the value of counterfactual policies we construct a dynamic model of regulation in which the underlying need for regulation varies stochastically and regulation undermines the social planner s ability to observe the state of the world compared to a full information benchmark regulation is highly persistent often lasting indefinitely regulatory fog is robust to a broad range of partially informative policies and can be quite detrimental to social welfare regulatory experiments modeled as costly and imperfect signals of the underlying state do not eliminate the effects of regulatory fog we characterize their effects and provide a framework for choosing amongst a set of potential regulatory experiments

dynamic agency with feedback a principal has a stochastically evolving target that he wishes an agent to repeatedly hit with his effort the agent does not obtain utility from hitting the target and therefore attempts to shirk the agent s utility is determined by a second process that symmetrically is of no use to the principal the principal cannot control effort or payoffs but can transmit signals to the agent who is relatively uninformed the principal s optimal signal may cause the agent s labor to be highly serially correlated this serial correlation has empirical relevance for the theory of managerial incentives and for the theory of business cycle fluctuations

simultaneously learning and optimizing using controlled variance pricing price experimentation is an important tool for firms to find the optimal selling price of their products it should be conducted properly since experimenting with selling prices can be costly a firm therefore needs to find a pricing policy that optimally balances between learning the optimal price and gaining revenue in this paper we propose such a pricing policy called controlled variance pricing cvp the key idea of the policy is to enhance the certainty equivalent pricing policy with a taboo interval around the average of previously chosen prices the width of the taboo interval shrinks at an appropriate rate as the amount of data gathered gets large this guarantees sufficient price dispersion for a large class of demand models we show that this procedure is strongly consistent which means that eventually the value of the optimal price will be learned and derive upper bounds on the regret which is the expected amount of money lost due to not using the optimal price numerical tests indicate that cvp performs well on different demand models and time scales this paper was accepted by assaf zeevi stochastic models and simulation

price dispersion and incomplete learning in the long run abstract in each period a seller chooses a price and the customer for that period buys either one unit or nothing the relationship between price and purchase probability is one of two linear functions it is shown that the seller behaving optimally does not necessarily learn which function is the actual relationship since there can be a positive probability of sequences of prices converging to the price at which the two functions give the same purchase probability

learning in mis specified models and the possibility of cycles abstract i study the problem of a monopolist maximizing a sum of discounted profits facing a linear demand curve whose slope and intercept are unknown i show that if the monopolist has a mis specified model i e if the true slope and intercept lie outside of the support of the monopolist s prior beliefs then actions and beliefs may cycle on every sample path this behavior is shown to be robust to perturbations in the prior true parameter and actions such behavior is not possible if the agent s model is correctly specified instead actions and beliefs necessarily converge

experimentation and learning with networks effects abstract this paper considers learning in an competitive setting by allowing an opponent a head start unsuccessful unilateral experimentation may jeopardize future sales and profits we show that even in the absence of spillover and signalling effects competition can inhibit the scope of learning relative to a monopoly

learning public good provision and the information trap abstract we consider an economy with uncertainty about the true production function for a public good by using bayes rule the economy can learn from experience we show that it may learn the truth but that it may also converge to an inefficient policy where no further inference is possible so that the economy is stuck in an information trap we also show that our results are robust with respect to small experimentation

learning about variable demand in the long run this paper studies the problem of a monopoly who is uncertain about the demand it faces and learns about it over time through its pricing experience the demand curve facing the monopoly is not constant it changes over time in a markovian fashion we characterize the monopoly s optimal policy and inquire how it differs from an informed monopoly s policy it turns out that even when the rate at which the demand varies is negligible the stationary probability with which the monopoly s policy deviates from its informed counterpart is nonnegligible as long as the discount factor is below 1

on the surprising sufficiency of linear models for dynamic pricing with demand learning we consider a multiperiod single product pricing problem with an unknown demand curve the seller s objective is to adjust prices in each period so as to maximize cumulative expected revenues over a given finite time horizon in doing so the seller needs to resolve the tension between learning the unknown demand curve and maximizing earned revenues the main question that we investigate is the following how large of a revenue loss is incurred if the seller uses a simple parametric model that differs significantly i e is misspecified relative to the underlying demand curve we measure performance by analyzing the price trajectory induced by this misspecified model and quantifying the magnitude of revenue losses as a function of the time horizon relative to an oracle that knows the true underlying demand curve the price of misspecification is expected to be significant if the parametric model is overly restrictive somewhat surprisingly we show under reasonably general conditions that this need not be the case this paper was accepted by gerard cachon stochastic models and simulation

a dynamic oligopoly structural model for the prescription drug market after patent expiration this article incorporates consumer learning and heterogeneity into a dynamic oligopoly model for the prescription drug market in the model both firms and patients need to learn the generic qualities via patients experiences generic firms entry decisions are endogenous but their entry timings depend on a random approval process i apply the model to examine the impact of shortening the expected generic approval time although this policy experiment brings generics to the market sooner it increases a potential entrant s likelihood of entering a crowded market and hence could reduce the total number of generic entrants and consumer welfare

another look at the radner stiglitz nonconcavity in the value of information abstract this paper revisits the well known result of r radner and j stiglitz 1984 in bayesian models of economic theory elsevier amsterdam which shows that under certain conditions the value of information exhibits increasing marginal returns over some range their result assumes that both the number of states and the number of signal realizations are finite assumptions which preclude most analyses of optimal information acquisition we provide sufficient conditions that yield this nonconcavity in the value of information in a general framework the role that these conditions play is clarified and illustrated with several examples we also discuss the robustness of the nonconcavity result and the difficulties involved in getting the value of information to be globally concave journal of economic literature classification number d83

redesigning cooperative boundaries the emergence of new models in a mid 1990s aaea invited paper session the presenters and discussants posited challenges and opportunities for agricultural cooperation fulton hypothesized that forces external to the cooperative especially technology and member individualism would increasingly emerge as obstacles to success in north american agricultural cooperatives cook hypothesized forces internal to the cooperative especially potential negative consequences of vaguely defined property rights would challenge cooperative organizational growth in subsequent years three strategic choices were identified as potentially efficient that is the option to exit either the sector or the organizational form to continue strategically and structurally with moderate changes to organization form or to shift to a more radical form of organizational structure this article and session attempt to describe and analyze organizational design initiatives adopted since the mid 1990s this article complements and expands a typology of discrete institutional arrangements i e cooperative models based upon a broad definition of ownership rights comprising residual claim and control rights chaddad and cook we argue that cooperative models may be distinguished by how ownership rights are defined and assigned to economic agents tied contractually to the firm members patrons and investors in addition we develop a set of observations that suggest a research agenda based on a new institutional approach

why are capitalists the bosses this paper addresses the question why does capital typically hire labor rather than the other way around it models a situation in which a capitalist owner of money capital can choose between lending out his capital for production and using it to set up production under his own supervision it is demonstrated that the moral hazard of potential borrowers on account of limited liability provides the capitalist with the incentive to become a firm owner supervising hired labor the capitalist s choice is endogenized in terms of his opportunity cost of time it is argued that moral hazard with respect to the use of borrowed capital is an important determinant of the social hierarchy in the workplace copyright 1989 by royal economic society

learning from others a welfare analysis abstract this paper considers a smooth and noisy version of the statistical prediction model studied in the herding informational cascades literature and compares market and optimal learning the latter is characterized by defining a decentralized welfare benchmark as the solution to an infinite horizon team problem market behavior involves herding in the sense that agents put too little weight on their private information for any given precision of public information and yields underinvestment in the production of public information however both market and optimal learning involve slow learning examples of the model include learning by doing reaching consensus and consumer learning about quality journal of economic literature classification numbers d82 d83

experimentation and competition abstract this paper examines the effect of competition on firms efforts to experiment and learn about market demand consumers are assumed to know prices only at sellers they have actually visited but must bear search costs to find the prices of other sellers under these conditions we show that firms incentives to experiment are diluted by comparison with the monopoly case and that this effect is stronger the smaller the search cost the learning environment we portray gives rise to several time paths which have been empirically documented including penetration pricing cream skimming and cyclical pricing journal of economic literature classification numbers c73 d43 d83

price dispersion and learning in a dynamic differentiated goods duopoly we study the evolution of prices set by duopolists who are uncertain about the perceived degree of product differentiation customers sometimes view the products as close substitutes sometimes as highly differentiated as the informativeness of the quantities sold increases with the price differential there is scope for active learning by firms when information has low value to the firms they charge the same price as would be set by myopic players and there is no price dispersion when firms value information more highly on the other hand they actively learn by creating price dispersion such price dispersion arises in a cyclical fashion and is most likely to be observed when the firms environment changes sufficiently often but not too frequently firms payoffs are higher when they use correlated pricing strategies contrary to what one might expect such coordination need not hurt consumers provided they are sufficiently impatient

bayesian economist bayesian agents i an alternative approach to optimal learning we generalize the results on bayesian learning based on the martingale convergence theorem to the sequential framework we show that the variability in the sequential framework is sufficient under mild conditions to circumvent the incomplete learning results that characterize the optimal learning literature we then give an alternative approach whereby the economist is bayesian with a prior on the space of agent priors we illustrate the usefulness of our approach by applying it to two popular economic examples a monopolist who does not know the demand curve he faces and the stochastic single sector growth model with an unknown production function

a theory of public debt management with unobservable demand the literature on debt management has devoted little attention to the practice of floating debt using subscription issues i e at a fixed price and quantity even if this practice is rather common in many countries as an alternative to placement techniques that involve competitive bidding the focus of this paper is on this marketing strategy for a public debt manager facing uncertain market conditions in particular we consider a framework where government bonds are the only investment opportunity the debt manager therefore holds monopoly power over the market for financial assets and solves his profitmaximisation problem by setting the price of the bonds in the face of an unobservable demand function intertemporal economic decisions under uncertainty can be modelled as multiperiod control problems when the parameters of the true model are unknown as in our case a tradeoff typically arises between current profits and the value of information which can be extracted through price experimentation in an active learning framework in particular agents are assumed to use such information in order to update their stock of knowledge according to bayes rule 2 several applications of the modelling strategy discussed above have been explored for example an active learning setting can fit the description of the problem of a consumer facing the decision to buy a good with uncertain quality alternatively the same setting can be employed in order to investigate the behaviour of a monopolistic firm facing an unknown demand for its product in this paper we model the macroeconomic policy oriented issue previously illustrated as a stochastic multiperiod control problem with learning we therefore assume that debt policy and in particular the debt manager s pricing strategy is the result of the intertemporal maximisation of the government s objective function subject to a budget constraint in a context where information is optimally employed in the decision process in addition the

the elasticity of labor supply at the establishment level monopsonistic wage setting power requires that the supply of labor directed toward individual establishments is upward sloping this study utilizes institutional features to identify the supply curve the elasticity of labor supply is estimated using data for the norwegian teacher labor market in a period where the only variation in the wage level was determined centrally and with information on whether there is excess demand or not at the school level in fixed effects models the supply elasticity faced by individual schools is estimated to about 1 4 and is in the range 1 0 1 9 in different model specification

cooperatives and contracting in agriculture the case of west liberty foods the west liberty foods turkey cooperative was formed in 1996 to purchase the assets and assume operations of louis rich foods an investor owned processing firm which at the time announced the imminent shutdown of its west liberty iowa processing facility we study the creation and performance of this new generation cooperative using field interviews with grower members and company management we describe changes before and after the buyout in the contractual apparatus used for procuring live turkeys and in the communication requirements work expectations and financial positions of growers during the private ownership period most of the inputs except labor and facilities were provided by the firm there was substantial supervision of the growers actions growers faced little price and production risk and growers equity was due largely to ownership of land and other farm assets our interviews reveal that after cooperative formation growers were exposed to considerable additional risk monitoring of growers by the firm was less intensive grower time and effort commitments to turkey production increased substantially and a significant fraction of firm cooperative equity came from growers willingness to leverage their farm and personal assets and hence indirectly their existing relationships with local lenders we argue that some of these changes are consistent with a financial contract where asset pledging and its corollary risk generate higher work effort by growers and a reduction in agency rents these economies likely compensate for an organizational deadweight loss traditionally associated with cooperative governance

learning about the arrival of sales abstract we analyse optimal stopping when the economic environment changes because of learning a primary application is optimal selling of an asset when demand is uncertain the seller learns about the arrival rate of buyers as time passes without a sale the seller becomes more pessimistic about the arrival rate when the arrival of buyers is not observed the rate at which the seller revises her beliefs is affected by the price she sets learning leads to a higher posted price by the seller when the seller does observe the arrival of buyers she sets an even higher price

private monitoring in auctions abstract we study infinitely repeated first price auctions in which a bidder only learns whether or not he won the object while repetition of the stage game equilibrium is the unique nash equilibrium in public strategies with patient bidders there are simple nash equilibria in private strategies that improve on bid rotation sequential rationality is appropriately captured by essentially perfect bayesian equilibrium epbe which ignores behavior after irrelevant histories our main result is the construction of epbea that improve upon bid rotation assuming symmetry the exclusionary schemes of skrzypacz and hopenhayn tacit collusion in repeated auctions j econ theory 114 2004 153 169 including asymptotically efficient ones are supported as epbea

learning and strategic pricing we consider the situation where a single consumer buys a stream of goods from different sellers over time the true value of each seller s product to the buyer is initially unknown additional information can be gained only by experimentation for exogeneously given prices the buyer s problem is a multi armed bandit problem the innovation in this paper is to endogenize the cost of experimentation to the consumer by allowing for price competition between the sellers the role of prices is then to allocate intertemporally the costs and benefits of learning between buyers and sellers we examine how strategic aspects of the oligopoly model interact with the learning process all markov perfect equilibria mpe are efficient we identify an equilibrium which besides its unique robustness properties has a strikingly simple seemingly myopic pricing rule prices below marginal cost emerge naturally to sustain experimentation intertemporal exchange of the gains of learning is necessary to support efficient experimentation we analyze the asymptotic behavior of the equilibria

an empirical model of optimal dynamic product launch and exit under demand uncertainty this paper considers the decision problem of a firm that is uncertain about the demand and hence profitability of a new product we develop a model of a decision maker who sequentially learns about the true product profitability from observed product sales based on the current information the decision maker decides whether to scrap the product central to this decision problem are sequential information gathering and the option value of scrapping the product at any point in time the model predicts the optimal demand for information e g in the form of test marketing and it predicts how the launch or exit policy depends on the firm s demand uncertainty furthermore it predicts what fraction of newly developed products should be launched on average and what fraction of these products will fail i e exit the model is solved using numerical dynamic programming techniques we present an application of the model to the case of the u s ready to eat breakfast cereal industry simulations show that the value of reducing uncertainty can be large and that under higher uncertainty firms should strongly increase the fraction of all new product opportunities launched even if their point estimate of profits is negative alternative simpler decision rules are shown to lead to large profit losses compared to our method finally we find that the high observed exit rate in the u s ready to eat cereal industry is optimal and to be expected based on our model

bayesian dynamic pricing policies learning and earning under a binary prior distribution motivated by applications in financial services we consider a seller who offers prices sequentially to a stream of potential customers observing either success or failure in each sales attempt the parameters of the underlying demand model are initially unknown so each price decision involves a trade off between learning and earning attention is restricted to the simplest kind of model uncertainty where one of two demand models is known to apply and we focus initially on performance of the myopic bayesian policy mbp variants of which are commonly used in practice because learning is passive under the mbp that is learning only takes place as a by product of actions that have a different purpose it can lead to incomplete learning and poor profit performance however under one additional assumption a constrained variant of the myopic policy is shown to have the following strong theoretical virtue the expected performance gap relative to a clairvoyant who knows the underlying demand model is bounded by a constant as the number of sales attempts becomes large this paper was accepted by gerard p cachon stochastic models and simulation

a value function arising in the economics of information abstract the value function for a problem in the economics of the optimal accumulation of information is calculated as a fixed point of a contraction mapping by direct numerical iteration the optimal policy function is obtained as is the function defined as the sum of current expected reward and the discounted expected value of following the optimal policy in the future the optimal policy function is shown to be sensitive to the discount factor indeed for large values of the discount factor weighting the future heavily the policy function has a break and the value function is apparently not differentiable

leaving some stones unturned a reassessment of iterative planning theory abstract drawbacks of standard iterative planning algorithms include i planner actions are just on paper calculations without direct economic consequences and may converge very slowly ii planners cannot act systematically on hunches and intuitions and iii planners can observe unrealistically detailed information these problems are addressed through a bayesian learning model it is shown in sharp contrast to the standard literature that planners will not necessarily settle in the long run on even approximately optimal prices in an example the planner can end up setting prices in every period that guarantee chronic shortage this is an outcome of a fully optimizing model

a theory of learning with heterogeneous agents the authors study learning in organizations comprised of short lived agents with heterogeneous beliefs it is shown that the sequence of actions converges in probability to the set of ex post optimal actions under some identifiability conditions beliefs also converge in probability to point mass on the truth moreover while actions and posterior beliefs converge in probability they can simultaneously almost surely fail to converge the authors simulations of n kiefer s 1989 monopoly learning model suggest that if the firm is operated by a sequence of short lived managers with heterogeneous beliefs then complete learning of the demand curve obtains copyright 1995 by economics department of the university of pennsylvania and the osaka university institute of social and economic research association

searching for good policies policymaking is hard policymakers typically have imperfect information about which policies produce which outcomes and they are left with little choice but to fumble their way through the policy space via a trial and error process this raises a question at the heart of democracy do democratic systems identify good policies to answer this question i introduce a novel model of policymaking in complex environments i show that good policies are often but not always found and i identify the possibility of policymaking getting stuck at outcomes that are arbitrarily bad notably policy stickiness occurs in the model even in the absence of institutional constraints this raises the question of how institutions and the political environment impact experimentation and learning i show how a simple political friction uncertainty over voter preferences interacts with political competition and policy uncertainty in a subtle way that surprisingly improves the quality of policymaking over time

combined pricing and inventory control under uncertainty this paper addresses the simultaneous determination of pricing and inventory replenishment strategies in the face of demand uncertainty more specifically we analyze the following single item periodic review model demands in consecutive periods are independent but their distributions depend on the item s price in accordance with general stochastic demand functions the price charged in any given period can be specified dynamically as a function of the state of the system a replenishment order may be placed at the beginning of some or all of the periods stockouts are fully backlogged we address both finite and infinite horizon models with the objective of maximizing total expected discounted profit or its time average value assuming that prices can either be adjusted arbitrarily upward or downward or that they can only be decreased we characterize the structure of an optimal combined pricing and inventory strategy for all of the above types of models we also develop an efficient value iteration method to compute these optimal strategies finally we report on an extensive numerical study that characterizes various qualitative properties of the optimal strategies and corresponding optimal profit values

financial markets and the political structure of the enterprise abstract this paper argues that competitive financial markets disfavor democratic enterprises even assuming such enterprises suffer no allocational deficiencies this conclusion follows from five assertions a the democratic enterprise requires access to credit markets b access to credit presupposes access to equity markets c the democratic firm s optimal risk level is lower than that desired by stockholders d the risk level assumed by the firm is costly to observe subject to inaccurate measurement and contractually unenforceable and e the incentives required to induce stockholder favorable risk behavior are more costly for democratic firms than for firms with stockholder accountable management

searching and learning by trial and error i study a dynamic model of trial and error search in which agents do not have complete knowledge of how choices are mapped into outcomes agents learn about the mapping by observing the choices of earlier agents and the outcomes that are realized the key novelty is that the mapping is represented as the realized path of a brownian motion i characterize for this environment the optimal behavior each period as well as the trajectory of experimentation and learning through time applied to new product development the model shares features of the data with the well known product life cycle jel d81 d83 d92 l26

optimal growth with unobservable resources and learning abstract this paper examines the problem of choosing optimal resource consumption from an imperfectly observable aggregate capital wealth or resource stock which the decision maker learns about over time learning is complicated by the fact that the planner receives information about an object the true resource stock which is a moving target under the assumption that the utility of zero consumption is we show that the optimal policy follows a completely deterministic cautious or minmax policy that assumes the worst in each period and optimizes against that when this model is compared to a model with completely observable wealth levels the following insights are obtained 1 there is over saving 2 investment and output processes are more volatile than consumption and 3 regressions underestimate the risk aversion of agents information about the wealth or stock level is only valuable if it alters the support of the agent s beliefs thus information may be statistically informative yet economically valueless if information changes the support of the agent s beliefs then the optimal solution features an endogenous resource discovery process

entry and vertical differentiation this paper analyzes the entry of new products into vertically differentiated markets where an entrant and an incumbent compete in quantities the value of the new product is initially uncertain and new information is generated through purchases in the market we derive the unique markov perfect equilibrium of the infinite horizon game under the strong long run average payoff criterion the qualitative features of the optimal entry strategy are shown to depend exclusively on the relative ranking of established and new products based on current beliefs superior products are launched relatively slowly and at high initial prices whereas substitutes for existing products are launched aggressively at low initial prices the robustness of these results with respect to different model specifications is discussed

strategic ignorance as a self disciplining device we analyse the decision of an agent with time inconsistent preferences to consume a good that exerts an externality on future welfare the extent of the externality is initially unknown but may be learned via a costless sampling procedure we show that when the agent cannot commit to future consumption and learning decisions incomplete learning may occur on a markov perfect equilibrium path of the resulting intra personal game in such a case each agent s incarnation stops learning for some values of the posterior distribution of beliefs and acts under self restricted information this conduct is interpreted as strategic ignorance all equilibria featuring this property strictly pareto dominate the complete learning equilibrium for any posterior distribution of beliefs

learning by doing and the value of optimal experimentation abstract recent research on learning by doing has provided the limit properties of beliefs and actions for a class of learning problems in which experimentation is an important aspect of optimal decision making however under these conditions the optimal policy cannot be derived analytically because bayesian learning about unknown parameters introduces a nonlinearity in the dynamic optimization problem this paper utilizes numerical methods to characterize the optimal policy function for a learning by doing problem that is general enough for practical economic applications the optimal policy is found to incorporate a substantial degree of experimentation under a wide range of initial beliefs about the unknown parameters dynamic simulations indicate that optimal experimentation dramatically improves the speed of learning and the stream of future payoffs furthermore these simulations reveal that a policy which separates control and estimation and does not incorporate experimentation frequently induces a long lasting bias in the control and target variables while these sequences tend to converge steadily under the optimal policy they frequently exhibit non stationary behavior when estimation and control are treated separately

industrial targeting experimentation and long run specialization abstract this paper emphasizes the experimental nature of industrial targeting policies under uncertainty in a small open economy a government promotes entry of new firms in selected industries and updates its beliefs about the country s comparative advantage in a bayesian way this selective targeting policy is analyzed in the framework of a special type of statistical decision problem known as the multi armed bandit the paper analyzes how the costs and benefits of learning about a country s comparative advantage depend on the characteristics of the targeted industries the framework suggests that even an optimally designed industrial targeting policy may eventually steer the country away from specializing according to its true comparative advantage

is there monopsonistic discrimination against immigrants the authors investigate immigrants and natives labor supply to the firm within an estimation approach based on a dynamic monopsony framework applying duration models that account for unobserved worker heterogeneity to a large administrative employer employee data set for germany they find that immigrants supply labor less elastically to firms than do natives under monopsonistic wage setting the estimated elasticity differential predicts a 7 7 log points wage penalty for immigrants thereby accounting for the entire unexplained native immigrant wage differential of 5 8 to 8 2 log points when further distinguishing immigrant groups differing in their time spent in the german labor market their immigration cohort and their age at entry the authors find that the observed unexplained wage differential is larger for those groups that show a larger elasticity differential relative to natives these findings not only suggest that search frictions are a likely cause of employers more pronounced monopsony