Bank of Minneapolis and University of Minnesota. We thank the NSF for financial support. The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System. The Great Depression is not yet well understood. Economists have offered many theories for both the massive decline and the slow recovery of output during 1929—39, but no consensus has formed on the main forces behind this major economic event. Here we describe and demonstrate a simple methodology for determining which types of theories are the most promising. Several prominent theories blame the Great Depression on frictions in labor and capital markets. The sticky wage theory is that wage stickiness together with a monetary contraction produces a downturn in output. (See Michael Bordo, Christopher Erceg, and Charles Evans 2001.) The cartelization theory is that an increase in cartelization and unionization leads to a slow recovery. (See Harold Cole and Lee Ohanian 2001.) The investment friction theory is that monetary contractions increase frictions in capital markets that produce investment-driven downturns in output.

Productivity Differences across Employers: The Roles of Employer Size, Age, and Human Capital by John C. Haltiwanger, Julia I. Lane and James Spletzer. Published in volume 89, issue 2, pages 94-98 of American Economic Review, May 1999

That fluctuations in primary commodity export markets have significant impacts on the economies of the producing countries is intuitively clear and widely accepted. But there is little consensus on the direction and significance of these impacts on economic development. Fluctuations in the value of primary commodity production and exports have the potential for affecting the growth path through a number of channels. This paper is concerned with delineating these channels of influence and with establishing quantitative dimensions for their effects. As an illustration we focus on coffee in relation to the economy of Brazil. The relationships between the coffee producing sector and the national economy are established econometrically and integrated into a macro model of the Brazilian economy. Alternative scenarios for coffee production and exports illustrate the nature of the impacts throughout the economy and the potential effects on Brazilian growth.

Since my recent article, which cast considerable doubt on the statistical estimation approach to the derivation of cost functions, I have been expecting a comment from proponents of that approach. Instead, I am pleasantly surprised to be replying to disciples of the process analysis approach. J. R. Marsden, D. E. Pingry, and A. Whinston (MPW) feel that a linear programming application of process analysis to petroleum refining has basically the same disadvantages as the statistical cost function technique, but that these could be overcome with the adoption of their particular approach. They propose a more general formulation utilizing non-linear programming techniques and allowing for nonconvex production technologies. Let us begin by considering their four objections to my application of process analysis to petroleunm refining. First, MPW assert that the test of the classical cost function assumptions (i.e., marginal costs slope upward and average costs are U-shaped) was not really a test at all but proceeded directly from the convexity assumptions of the linear programming model of the refinery. Certainly, the fixed capital process constraints imply a finite output and a rising marginal cost curve, but the relevant question is over what output range do marginal costs rise. MPW apparently feel that because of the convexity assumption marginal costs must necessarily rise over a broad output range. To demonstrate the error in their assertion, one need only examine some output range from b74) to b(n+l) over which the basis x* does not change. Since the basis is unchanged, the dual solution vector y* will similarly not change, thereby proving that short-run marginal costs (given by the jth element of y*) are constant over the given output range. As an example, Figure 1 of my paper illustrates a case where a basis change did not occur over the output range 8.4 to 8.9 MMB/D and marginal costs are constant. Furthermore, the dots in Figure 1, indicating basis changes, suggest that even after basis changes, marginal costs need not necessarily increase as the basis changes. Therefore, under this standard linear programming problem where the production processes are convex, short-run marginal costs can either rise in a step-wise manner or remain horizontal over the output range up to the full utilization of the capital stock at which point marginal costs become vertical. Either rising short-run marginal costs or an inverted L-shaped short-run marginal cost can be obtained assuming a standard convex production technology. Since the same result may be found in statistical cost studies (i.e., constant short-run marginal costs over the observed output range), the results in both Figures 1 and 2 indicating a rising marginal cost function over a broad output range certainly do not follow from the convexitv assumptions as MPW assert. Secondly, MPW are apparently disturbed because the short-run marginal cost function as drawn in Figure 1 does not change in a step function manner. They argue that the use of parametric programming would have revealed these steps and other useful information regarding capacity limitations. Contrary to MPW's assertion, parametric programming with UNIVAC's Omega package was utilized which reports the activities entering and exiting the basis at each basis change. As indicated in footnote 10, page 49, the particular parametrics option chosen does not report the complete solution vector at each basis change within the 6 increment to the output constraint bj, but rather reports the solution values for the first basis change * Department of economics, University of Pennsylvania and the University of Houston.

It has been argued by William Baumol and Richard Quandt (1964) and Day (1967) that rules of thumb can be efficient economic strategies when decision making is costly and when decision makers have imperfect information. The present paper augments this literature and analyzes an industrial growth model in which firms determine production and investment levels by solving a single period optimizing problem. The solution is carried out period after period rather than by making a complete lifetime plan involving forecasts of the future. We portray the firm as myopically groping toward an unknown equilibrium through successive one-period movements made by a simple linear programming allocation of the firm's cash budget.' Cash availability is the channel through which market feedback, operating through the demand function, modifies behavior. Our model can be thought of as a dynamic, rule of thumb, approximation to an intertemporally optimal investment and production path for the firm and industry. It is shown that, under certain conditions of demand and cost, an industry whose firms use our myopic investment rules will converge asymptotically to a perpetually maintainable capital stock. This solution is the long-run equilibrium of the perfectly competitive industry in which price just covers total costs of the marginal firm. In other words, a shortsighted optimization based on complete ignorance of demand can lead to equilibrium in the sense of theories based on perfect knowledge and polyperiodic time horizons. This is only one of several possible outcomes, however, for under somewhat different market conditions fluctuations in investment and production levels will eventually occur, perhaps after a protracted period of growth. The model can also generate S-shaped industry growth paths, simultaneous saving and investment, and investment at less than the maximum possible rate (excess borrowing capacity). All of these are commonly observed patterns of industry behavior. The possibility of industrial instability suggests the need for a risk-avoiding rule at the firm level. The rule introduced is the safety-first principle (see Andrew Roy, Day, Dennis Aigner and Smith), a device that is easily seen to reduce the likelihood of unstable oscillations about industrial equilibrium.

Investor protection is associated with greater investment sensitivity to q and lower investment sensitivity to cash flow. Finance plays a role in causing these effects; in countries with strong investor protection, external finance increases more strongly with q , and declines more strongly with cash flow. We further find that q and cash flow sensitivities are associated with ex post investment efficiency; investment predicts growth and profits more strongly in countries with greater q sensitivities and lower cash flow sensitivities. The paper's findings are broadly consistent with investor protection promoting accurate share prices, reducing financial constraints, and encouraging efficient investment.

We analyze institutional allocation in initial public offerings (IPOs) using a new data set of U.S. offerings between 1997 and 1998. We document a positive relationship between institutional allocation and day one IPO returns. This is partly explained by the practice of giving institutions more shares in IPOs with strong premarket demand, consistent with book‐building theories. However, institutional allocation also contains private information about first‐day IPO returns not reflected in premarket demand and other public information. Our evidence supports book‐building theories of IPO underpricing, but suggests that institutional allocation in underpriced issues is in excess of that explained by book‐building alone.

The behavior of time-weighted bid–ask spreads over the trading day are examined. The plot of minute-by-minute spreads versus time of day has a crude reverse J-shaped pattern. Schwartz identifies four determinants of spreads: activity, risk, information, and competition. Using a linear regression model, a significant relationship between these same factors and intraday spreads is demonstrated, but dummy variables for time of day have a reverse J-shape. For given values of the activity, risk, information and competition measures, spreads are higher at the beginning and end of the day relative to the interior period.

This paper tests the effectiveness of techniques proposed by: Scholes-Williams; Dimson; Fowler, Rorke, and Jog; and Cohen, Hawawini, Maier, Schwartz, and Whitcomb to control for bias in beta estimates from thin trading and price adjustment delays. Each technique produces beta estimates that reduce the amount of this bias, but the amount of reduction in the best case is only 29%.