This study provides a new theoretical result that a decline in the long‐term interest rate can trigger a stronger investment response by market leaders relative to market followers, thereby leading to more concentrated markets, higher profits, and lower aggregate productivity growth. This strategic effect of lower interest rates on market concentration implies that aggregate productivity growth declines as the interest rate approaches zero. The framework is relevant for antitrust policy in a low interest rate environment, and it provides a unified explanation for rising market concentration and falling productivity growth as interest rates in the economy have fallen to extremely low levels.

We argue that positive co-movements between land prices and business investment are a driving force behind the broad impact of land-price dynamics on the macroeconomy. We develop an economic mechanism that captures the co-movements by incorporating two key features into a DSGE model: We introduce land as a collateral asset in firms' credit constraints, and we identify a shock that drives most of the observed fluctuations in land prices. Our estimates imply that these two features combine to generate an empirically important mechanism that amplifies and propagates macroeconomic fluctuations through the joint dynamics of land prices and business investment.

of the postwar U. S. economy in the Tinbergen-Klein [32, 15, and 16] tradition,2 and to apply the model to an analysis of certain types of monetary and fiscal policy. The model is crude and exploratory,3 and the analysis is in aggregate terms. Needless to say, the U. S. economy cannot be adequately described by such a simple model, and the findings are necessarily highly tentative. The model and the simulations presented here are the initial result of a limited attempt to gain some knowledge about certain aspects of the economy in quantitative terms and to throw some light on the problems involved. The lag in effect in monetary and fiscal policy (Baumol [3], Culbertson [7 and 8], and Friedman [12]) is a case in point. Such a problem cannot be settled by theoretical analysis. An indication of the answer to the question can only be obtained through a quantitative study, however crude the approach and the indication may be. The model is constructed on fifty quarterly observations from the third quarter of 1947 to the fourth quarter of 1959. The structural equations are presented in Appendix A, with the variables and the sources of data listed in Appendix B. Sections 1-3 describe the model. The investment and consumption functions are presented in Section 1. A sub-model on inventory and price movements is formulated in Section 2. Functions for monetary and certain other variables are presented in Section 3. Extrapolations for the magnitudes of the major components of gnp are computed for 1960 and the first quarter of 1961 from the respective individual equations in Sections 1 1 The author wishes to express appreciation to the Ford Foundation whose faculty research fellowship made this research possible, to the Social Science Research Center of Cornell University for grants to support the initial computations, and to his colleagues at the Cornell Computing Center for their untiring cooperation. He is indebted to Marc Nerlove and A. S. Goldberger for discussion at various stages of the preparation

We consider a classical auction setting in which an asset/project is sold to buyers who privately receive signals about expected payoffs, and payoffs are more sensitive to a bidder's signal if he runs the project than if another bidder does. We show that a seller can increase revenues by sometimes allocating cash‐flow rights and control to different bidders, for example, with the highest bidder receiving cash flows and the second‐highest receiving control. Separation reduces a bidder's information rent, which depends on the importance of his private information for the value of his awarded cash flows. As project payoffs are most sensitive to a bidder's information if he controls the project, allocating cash flow to another bidder lowers bidders' informational advantage. As a result, when signals are close, the seller can increase revenues by splitting rights between the top two bidders.

We incorporate forward‐looking capital accumulation into a dynamic discrete choice model of migration. We characterize the steady‐state equilibrium; generalize existing dynamic exact‐hat algebra techniques to incorporate investment; and linearize the model to provide an analytical characterization of the economy's transition path using spectral analysis. We show that capital and labor dynamics interact to shape the economy's speed of adjustment toward steady state. We implement our quantitative analysis using data on capital stocks, populations, and bilateral trade and migration flows for U.S. states from 1965–2015. We show that this interaction between capital and labor dynamics plays a central role in explaining the observed decline in the rate of income convergence across U.S. states and the persistent and heterogeneous impact of local shocks.

We study the role of incomplete information and outside options in determining bargaining postures and surplus division in repeated bargaining between a long-run player and a sequence of short-run players. The outside option is not only a disagreement point but reveals information privately held by the long-run player. In equilibrium, the uninformed short-run players' offers do not always respond to changes in reputation and the informed long-run player's payoffs are discontinuous. The long-run player invokes inefficient random outside options repeatedly in order to build reputation to a level where the subsequent short-run players succumb to his extraction of a larger payoff, but he also runs the risk of losing reputation and relinquishing bargaining power. We investigate equilibrium properties when the discount factor goes to 1 and when the informativeness of outside option diffuses. In both cases, bargaining outcomes become more inefficient and the limit reputation building probabilities are interior.