We consider demand function competition with a finite number of agents and private information. We show that any degree of market power can arise in the unique equilibrium under an information structure that is arbitrarily close to complete information. In particular, regardless of the number of agents and the correlation of payoff shocks, market power may be arbitrarily close to zero (so we obtain the competitive outcome) or arbitrarily large (so there is no trade in equilibrium). By contrast, price volatility is always less than the variance of the aggregate shock across all information structures.
We develop the first structural model of a multitasking salesforce to address questions of job design and incentive compensation design. The model incorporates three novel features: (i) multitasking effort choice given a multidimensional incentive plan; (ii) salesperson’s private information about customers and (iii) dynamic intertemporal tradeoffs in effort choice across the tasks. The empirical application uses data from a micro nance bank where loan officers are jointly responsible and incentivized for both loan acquisition repayment but has broad relevance for salesforce management in CRM settings involving customer acquisition and retention. We extend two-step estimation methods used for unidimensional compensation plans for the multitasking model with private information and intertemporal incentives by combining flexible machine learning (random forest) for the inference of private information and the first-stage multitasking policy function estimation. Estimates reveal two latent segments of salespeople-a “hunter” segment that is more efficient in loan acquisition and a “farmer” segment that is more efficient in loan collection. We use counterfactuals to assess how (1) multi-tasking versus specialization in job design; (ii) performance combination across tasks (multiplicative versus additive); and (iii) job transfers that impact private information impact firm profits and specific segment behaviors.
Jacob Marschak shaped the emergence of monetary theory and portfolio choice at the Cowles Commission (which he directed from 1943 to 1948, but with which he was involved already from 1937) at the University of Chicago, where he was the doctoral teacher of Leonid Hurwicz, Harry Markowitz and Don Patinkin, and then from 1955 at the Cowles Foundation at Yale University, where he was a senior colleague of James Tobin until moving to UCLA in 1960. Marschak’s later attempts to clarify the concept of liquidity and to emphasize the role of new information for economic behavior date back as far as to his early experiences with hyperinflationary processes in the Northern Caucasus during the Russian Revolution. Marschak came to monetary theory with his 1922 Heidelberg doctoral dissertation on the quantity theory equation of exchange (published in 1924 as “Die Verkehrsgleichung”), and embedded monetary theory in a wider theory of asset market equilibrium in studies of “Money and the Theory of Assets” (1938), “Assets, Prices, and Monetary Theory” (with Helen Makower, 1938), “Role of Liquidity under Complete and Incomplete Information” (1949), “The Rationale of the Demand for Money and of ‘Money Illusion’” (1950), and “Monnaie et liquidité dans les modèles macroéconomiques et microéconomiques” (1955), as well as in Income, Employment and the Price Level (lectures Marschak gave at Chicago, edited by Fand and Markowitz, 1951). We examine Marschak’s analysis of money within a broader theory of asset market equilibrium and explore the relation of his work to the monetary and portfolio theories of his doctoral students Markowitz and Patinkin and his colleague Tobin and to the revival of the quantity theory of money by Milton Friedman, a University of Chicago colleague unsympathetic to the methodology of the Cowles Commission.
Abstract
This paper explores the development of dynamic modelling of macroeconomic fluctuations at the Cowles Commission from Roos, Dynamic Economics (Cowles Monograph No. 1, 1934) and Davis, Analysis of Economic Time Series (Cowles Monograph No. 6, 1941) to Koopmans, ed., Statistical Inference in Dynamic Economic Models (Cowles Monograph No. 10, 1950) and Klein’s Economic Fluctuations in the United States, 1921-1941 (Cowles Monograph No. 11, 1950), emphasizing the emergence of a distinctive Cowles Commission approach to structural modelling of macroeconomic fluctuations influenced by Cowles Commission work on structural estimation of simulation equations models, as advanced by Haavelmo (“A Probability Approach to Econometrics,” Cowles Commission Paper No. 4, 1944) and in Cowles Monographs Nos. 10 and 14.
This paper is part of a larger project, a history of the Cowles Commission and Foundation commissioned by the Cowles Foundation for Research in Economics at Yale University.
Presented at the Association Charles Gide workshop “Macroeconomics: Dynamic Histories. When Statics is no longer Enough,” Colmar, May 16-19, 2019.
In a world in which internet troll farms attempt to influence foreign elections, can we afford to ignore the power of viral stories to affect economies? In this groundbreaking book, Nobel Prize winning economist and New York Times bestselling author Robert Shiller offers a new way to think about the economy and economic change.
Using a rich array of historical examples and data, Shiller argues that studying popular stories that affect individual and collective economic behavior, what he calls “narrative economics” has the potential to vastly improve our ability to predict, prepare for, and lessen the damage of financial crises, recessions, depressions, and other major economic events.
Spread through the public in the form of popular stories, ideas can go viral and move markets, whether it’s the belief that tech stocks can only go up, that housing prices never fall, or that some firms are too big to fail. Whether true or false, stories like these, transmitted by word of mouth, by the news media, and increasingly by social media, drive the economy by driving our decisions about how and where to invest, how much to spend and save, and more. But despite the obvious importance of such stories, most economists have paid little attention to them. Narrative Economics sets out to change that by laying the foundation for a way of understanding how stories help propel economic events that have had led to war, mass unemployment, and increased inequality. The stories people tell, about economic confidence or panic, housing booms, the American dream, or Bitcoin, affect economic outcomes. Narrative Economics explains how we can begin to take these stories seriously.
A single seller faces a sequence of buyers with unit demand. The buyers are forward-looking and long-lived. The arrival time and the valuation is private information of each buyer. Any incentive compatible mechanism has to induce truth-telling about the arrival time and the evolution of the valuation.
We derive the optimal stationary mechanism in closed form and characterize its qualitative structure. As the arrival time is private information, the buyer can choose the time at which he reports his arrival. The truth-telling constraint regarding the arrival time can be represented as an optimal stopping problem. The stopping time determines the time at which the buyer decides to participate in the mechanism. The resulting value function of each buyer cannot be too convex and must be continuously differentiable everywhere, reflecting the option value of delaying participation. The optimal mechanism thus induces progressive participation by each buyer: he participates either immediately or at a future random time.
A single seller faces a sequence of buyers with unit demand. The buyers are forwardlooking and long-lived but vanish (and are replaced) at a constant rate. The arrival time and the valuation is private information of each buyer and unobservable to the seller. Any incentive compatible mechanism has to induce truth-telling about the arrival time and the evolution of the valuation.
We derive the optimal stationary mechanism in closed form and characterize its qualitative structure. As the arrival time is private information, the buyer can choose the time at which he reports his arrival. The truth-telling constraint regarding the arrival time can be represented as an optimal stopping problem. The stopping time determines the time at which the buyer decides to participate in the mechanism. The resulting value function of each buyer cannot be too convex and must be continuously differentiable everywhere, reflecting the option value of delaying participation. The optimal mechanism thus induces progressive participation by each buyer: he participates either immediately or at a future random time.
A single seller faces a sequence of buyers with unit demand. The buyers are forward-looking and long-lived but vanish (and are replaced) at a constant rate. The arrival time and the valuation is private information of each buyer and unobservable to the seller. Any incentive compatible mechanism has to induce truth-telling about the arrival time and the evolution of the valuation.
We derive the optimal stationary mechanism, characterize its qualitative structure, and derive a closed-form solution. As the arrival time is private information, the buyer can choose the time at which he reports his arrival. The truth-telling constraint regarding the arrival time can be represented as an optimal stopping problem. The stopping time determines the time at which the buyer decides to participate in the mechanism. The resulting value function of each buyer cannot be too convex and must be continuously differentiable everywhere, reflecting the option value of delaying participation. The optimal mechanism thus induces progressive participation by each buyer: he participates either immediately or at a future random time.
This paper presents new results on the existence of pure-strategy Bayesian equilibria in specified functional forms. These results broaden the scope of methods developed by Reny (2011) well beyond monotone pure strategies. Applications include natural models of first-price and all-pay auctions not covered by previous existence results. To illustrate the scope of our results, we provide an analysis of three auctions: (i) a first-price auction of objects that are heterogeneous and imperfect substitutes; (ii) a first-price auction in which bidders’ payoffs have a very general interdependence structure; and (iii) an all-pay auction with non-monotone equilibrium.
We document that the nature of business cycles evolves over the process of development and structural change. In countries with large declining agricultural sectors, aggregate employment is uncorrelated with GDP.
During booms, employment in agriculture declines while labor productivity increases in agriculture more than in other sectors. We construct a unified theory of business cycles and structural change consistent with the stylized facts. The focal point of the theory is the simultaneous decline and modernization of agriculture. As capital accumulates, agriculture becomes increasingly capital intensive as modern agriculture crowds out traditional agriculture. Structural change accelerates in booms and slows down in recessions. We estimate the model and show that it accounts well for both the structural transformation and the business cycle fluctuations of China.