Aggregate stock prices, relative to virtually any indicator of fundamental value, soared to unprecedented levels in the 1990s. Even today, after the market declines since 2000, they remain well above historical norms. Why? We consider one particular explanation: a fall in macroeconomicrisk, or the volatility of the aggregate economy. Empirically, we find a strong correlation between low-frequency movements in macroeconomic volatility and low-frequency movements in the stock market. To model this phenomenon, we estimate a two-state regime switching model for the volatility and mean of consumption growth, and find evidence of a shift to substantially lower consumption volatility at the beginning of the 1990s. We then use these estimates from postwar data to calibrate a rational asset pricing model with regime switches in both the mean and standard deviation of consumption growth. Plausible parameterizations of the model are found to account for a significant portion of the run-up in asset valuation ratios observed in the late 1990s.

This paper develops a nonparametric theory of preferences over one's own and others' monetary payoffs. We introduce ?more altruistic than? (MAT), a partial ordering over such preferences, and interpret it with known parametric models. We also introduce and illustrate ?more generous than? (MGT), a partial ordering over opportunity sets. Several recent studies focus on two-player extensive form games of complete information in which the first mover (FM) chooses a more or less generous opportunity set for the second mover (SM). Here reciprocity can be formalized as the assertion that an MGT choice by the FM will elicit MAT preferences in the SM. A further assertion is that the effect on preferences is stronger for acts of commission by FM than for acts of omission. We state and prove propositions on the observable consequences of these assertions. Finally, empirical support for the propositions is found in existing data from investment and dictator games, the carrot and stick game, and the Stackelberg duopoly game and in new data from Stackelberg mini-games.

Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. The signals are independent and identically distributed across time but not necessarily across agents. We show that when each agent's signal space is finite, the agents will commonly learn the value of the parameter, that is, that the true value of the parameter will become approximate common knowledge. The essential step in this argument is to express the expectation of one agent's signals, conditional on those of the other agent, in terms of a Markov chain. This allows us to invoke a contraction mapping principle ensuring that if one agent's signals are close to those expected under a particular value of the parameter, then that agent expects the other agent's signals to be even closer to those expected under the parameter value. In contrast, if the agents' observations come from a countably infinite signal space, then this contraction mapping property fails. We show by example that common learning can fail in this case.

We study information transmission via polling. A policymaker polls constituents, who differ in their information and ideology, to determine policy. Full revelation is an equilibrium in a poll with a small sample, but not with a large one. In large polls, full information aggregation can arise in an equilibrium where constituents endogenously sort themselves into centrists, who respond truthfully, and extremists, who do not. We find polling statistics that ignore strategic behavior yield biased estimators and mischaracterize the poll's margin of error. We construct estimators that account for strategic behavior. Finally, we compare polls and elections.

In time series regressions with nonparametrically autocorrelated errors, it is now standard empirical practice to use kernel-based robust standard errors that involve some smoothing function over the sample autocorrelations. The underlying smoothing parameter b, which can be defined as the ratio of the bandwidth (or truncation lag) to the sample size, is a tuning parameter that plays a key role in determining the asymptotic properties of the standard errors and associated semiparametric tests. Small-b asymptotics involve standard limit theory such as standard normal or chi-squared limits, whereas fixed-b asymptotics typically lead to nonstandard limit distributions involving Brownian bridge functionals. The present paper shows that the nonstandard fixed-b limit distributions of such nonparametrically studentized tests provide more accurate approximations to the finite sample distributions than the standard small-b limit distribution. In particular, using asymptotic expansions of both the finite sample distribution and the nonstandard limit distribution, we confirm that the second-order corrected critical value based on the expansion of the nonstandard limiting distribution is also second-order correct under the standard small-b asymptotics. We further show that, for typical economic time series, the optimal bandwidth that minimizes a weighted average of type I and type II errors is larger by an order of magnitude than the bandwidth that minimizes the asymptotic mean squared error of the corresponding long-run variance estimator. A plug-in procedure for implementing this optimal bandwidth is suggested and simulations confirm that the new plug-in procedure works well in finite samples.

ABSTRACT This paper models transaction costs as the rents that a monopolistic market maker extracts from impatient investors who trade via limit orders. We show that limit orders are American options. The limit prices inducing immediate execution of the order are functionally equivalent to bid and ask prices and can be solved for various transaction sizes to characterize the market maker's entire supply curve. We find considerable empirical support for the model's predictions in the cross‐section of NYSE firms. The model produces unbiased, out‐of‐sample forecasts of abnormal returns for firms added to the S&P 500 index.

Why didn’t the Japanese miracle take place before World War II? The culprit we identify is a barrier that kept prewar agricultural employment constant. Using a standard neoclassical two‐sector growth model, we show that the barrier‐induced sectoral distortion and an ensuring lack of capital accumulation account well for the depressed output level. Without the barrier, Japan’s prewar GNP per worker would have been at least about a half of that of the United States, not about a third as in the data. The labor barrier existed because, we argue, the prewar patriarchy forced the son designated as heir to stay in agriculture.

ABSTRACT We develop a model in which a firm can devote effort either to increasing sales growth, or to improving per‐unit profit margins. If the firm's manager cares about the current stock price, she will favor the growth strategy when the market pays more attention to growth numbers. Conversely, it can be rational for the market to weight growth measures more heavily when it is known that the firm is following a growth strategy. This two‐way feedback between firms' strategies and the market's pricing rule can lead to excess volatility in real variables, even absent any external shocks.

ABSTRACT Reversal is the current stylized fact of weekly returns. However, we find that an opposing and long‐lasting continuation in returns follows the well‐documented brief reversal. These subsequent momentum profits are strong enough to offset the initial reversal and to produce a significant momentum effect over the full year following portfolio formation. Thus, ex post, extreme weekly returns are not too extreme. Our findings extend to weekly price movements with and without public news. In addition, there is no relation between news uncertainty and the momentum in 1‐week returns.

A long-standing assumption among economists is that nursing home quality is common across Medicaid and private-pay patients within a shared facility. However, there has been only limited empirical work addressing this issue. Using a unique individual level panel of residents of nursing homes from seven states, we exploit both within-facility and within-person variation in payer source and quality to examine this issue. We also test the robustness of these results across states with different Medicaid and private-pay rate differentials. Across various identification strategies, our results are consistent with the assumption of common quality across Medicaid and private-paying patients within facilities.