This paper examines the impact of the borrower–lender relationship on the explicit loan interest rate and collateral, as well as the correlation between loan interest rates and collateral. Using a simultaneous equation approach, we find that collateral has a statistically significant positive impact of 200 to 400 basis points on loan interest rates. We find this positive association to be stronger for personal (or outside) collateral than collateral provided by the firm's assets (or inside collateral). Finally, we find the economic impact of the borrower–lender relationship to be 21 basis points for one standard deviation increase in relationship length.

Technology has dramatically reduced the cost of disclosing information to investors and created new conduits for securities' sales. The result is stock ownership, both direct and indirect, has never been more widely distributed. Equally important, changes have occurred in the institutional market for new offerings. Bought deals, Internet road shows, the preeminence of mutual funds and pension funds, and foreign investors and issuers have changed the market. In the wake of these changes, the SEC's disclosure policy has evolved. The evidence suggests we have moved from a world where information was released relatively infrequently and with significant lags to a world where information is released relatively rapidly on a continuous basis to as many investors as possible.

Geography, flat or not, creates special relationships between buyers and sellers who reside in the same neighborhoods, but Friedman turns this metaphor inside-out by using The World is Flat to warn us of the perils of a relationship-free world in which every economic transaction is contested globally. In his “flat” world, your wages are set in Shanghai. In fact, most of the footloose relationship-free jobs in apparel and footwear and consumer electronics departed the United States several decades ago, and few U.S. workers today feel the force of Chinese and Indian competition, notwithstanding the alarming anecdotes about the outsourcing of intellectual services. Of course, standardization, mechanization, and computerization all work to increase the number of footloose tasks, but innovation and education work in the opposite direction, creating relationship-based activities—like the writing of this review. It may only be personal conceit, but I imagine there is a reason why the Journal of Economic Literature asked me to do this review.

This paper considers the problem of selection of weights for averaging across leastsquares estimates obtained from a set of models. Existing model average methods are based on exponential AIC and BIC weights. In distinction, this paper proposes selecting the weights by minimizing a Mallows ’ criterion, the latter an estimate of the average squared error from the model average fit. We show that our new Mallows ’ Model Average (MMA) estimator is asymptotically optimal in the sense of achieving the lowest possible squared error in a class of discrete model average estimators. In a simulation experiment we show that the MMA estimator compares favorably with those based on AIC and BIC weights. The proof of the main result is an application of Li (1987). Research supported by the National Science Foundation. I gratefully thank the Co-Editor (Whitney Newey), three referees, and Benedickt Potscher for helpful comments.

This paper describes an analytically tractable model of balanced growth that is consistent with the observed size distribution of Þrms. Growth is the result of idiosyncratic Þrm productivity improvements, selection of successful Þrms, and imitation by entrants. Selection tends to improve aggregate productivity at a fast rate if entry and imitation are easy. The empirical phenomenon of Zipfs law can be interpreted to mean that entry costs are high or that imitation is difficult, or both. The small size of entrants indicates that imitation must be difficult. A calibration based on U.S. data suggests that about half of output growth can be attributed to selection. But the implied variance of the combined preference and technology shocks is puzzlingly high. ∗The views expressed herein are those of the author and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System. I thank Michele Boldrin, Jonathan Eaton, Xavier

ABSTRACT In this paper we examine whether and how accounting information about a firm manifests in its cost of capital, despite the forces of diversification. We build a model that is consistent with the Capital Asset Pricing Model and explicitly allows for multiple securities whose cash flows are correlated. We demonstrate that the quality of accounting information can influence the cost of capital, both directly and indirectly. The direct effect occurs because higher quality disclosures affect the firm's assessed covariances with other firms' cash flows, which is nondiversifiable. The indirect effect occurs because higher quality disclosures affect a firm's real decisions, which likely changes the firm's ratio of the expected future cash flows to the covariance of these cash flows with the sum of all the cash flows in the market. We show that this effect can go in either direction, but also derive conditions under which an increase in information quality leads to an unambiguous decline in the cost of capital.

We endogenize preferences using the “indirect evolutionary approach”. Individuals are randomly matched to play a two-person game. Individual (subjective) preferences determine their behaviour and may differ from the actual (objective) pay-offs that determine fitness. Matched individuals may observe the opponents' preferences perfectly, not at all, or with some in-between probability. When preferences are observable, a stable outcome must be efficient. When they are not observable, a stable outcome must be a Nash equilibrium and all strict equilibria are stable. We show that, for pure-strategy outcomes, these conclusions are robust to allowing almost perfect, and almost no, observability, with the notable exception that inefficient strict equilibria may fail to be stable with any arbitrarily small degree of observability (despite being stable with no observability).

Workers earn higher wages in cities vs. rural areas. This gap could arise because cities make workers more productive, or it could be the result of a non-random selection of workers into cities based on their ability and their endogenous history of career choices. To untangle these issues, this paper estimates a dynamic programming model, which embeds the choice of residing in a city or rural area within a model of career choices over time. After controlling for all the sources of selection and endogeneity, the estimates indicate that a given worker does earn more in the city for white-collar work, but not for blue-collar work. In addition, city work experience is found to be worth more than rural work experience in the rural area for white-collar work, but not for blue-collar work. These results support the interpretation that cities make white-collar workers more productive and suggest that workers may consider moving to the city not only in terms of locational choice, but also as a form of human capital investment. Copyright 2007, Wiley-Blackwell.