Endogenous Group Formation

While the rules governing the formation of groups engaging in collective action may have significant impact on group size and behavior of members, most experiments on public goods have been conducted with the subjects in exogenously fixed groups or of fixed sizes. We study endogenous formation of groups in a public‐goods provision game by allowing subjects to change groups under three sets of rules: free entry/exit, restricted entry with free exit, and free entry with restricted exit. We find that the rules governing entry and exit do have a significant impact on individual behavior and group‐level outcomes.     

TRADE OPENNESS: AN AUSTRALIAN PERSPECTIVE

Australia's external trade is relatively low compared with the size of its economy. Indeed, Australia's openness ratio (exports plus imports as a proportion of GDP) in 2002 was the third-lowest among the 30 OECD countries. This paper seeks to understand Australia's low openness by analysing the empirical determinants of aggregate country trade. We present an equation for country openness which explains a substantial amount of the cross-country variation. The most important explanators of openness are population and a measure of distance to potential trade partners. Countries with larger populations trade less, as do countries that are relatively more remote. Furthermore, after controlling for trade policy there is little evidence of a positive correlation between openness and economic development. The openness equation suggests that Australia's level of trade is relatively close to what would be expected. The most important factors in explaining Australia's low openness ratio are its large geographic size and distance to the rest of the world.     

Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

Do Household Wealth Shocks Affect Productivity? Evidence from Innovative Workers During the Great Recession

We investigate how the deterioration of household balance sheets affects worker productivity, and in turn economic downturns. Specifically, we compare the output of innovative workers who experienced differential declines in housing wealth during the financial crisis but were employed at the same firm and lived in the same metropolitan area. We find that, following a negative wealth shock, innovative workers become less productive and generate lower economic value for their firms. The reduction in innovative output is not driven by workers switching to less innovative firms or positions. These effects are more pronounced among workers at greater risk of financial distress.     

Investigation of the Effects of Disclosure Statements in Rental Car Advertisements

State attorneys general recently proposed mandatory disclosures for rental car advertising. This study investigates the effects of alternate disclosure statements on consumers' beliefs. The results suggest that a shorter disclosure statement may be as effective as the one proposed.     

Benefits from U.S. Monetary Policy Experimentation in the Days of Samuelson and Solow and Lucas

A policy maker knows two models. One implies an exploitable inflation-unemployment trade-off, the other does not. The policy maker's prior probability over the two models is part of his state vector. Bayes' law converts the prior probability into a posterior probability and gives the policy maker an incentive to experiment. For models calibrated to U.S. data through the early 1960s, we compare the outcomes from two Bellman equations. The first tells the policy maker to "experiment and learn." The second tells him to "learn but don't experiment." In this way, we isolate a component of government policy that is due to experimentation and estimate the benefits from intentional experimentation. We interpret the Bellman equation that learns but does not intentionally experiment as an "anticipated utility" model and study how well its outcomes approximate those from the "experiment and learn" Bellman equation. The approximation is good. For our calibrations, the benefits from purposeful experimentation are small because random shocks are big enough to provide ample unintentional experimentation.