Low-Risk Anomalies?

This paper shows that low-risk anomalies in the capital asset pricing model and in traditional factor models arise when investors require compensation for coskewness risk. Empirically, we find that option-implied ex ante skewness is strongly related to ex post residual coskewness, which allows us to construct coskewness factor-mimicking portfolios. Controlling for skewness renders the alphas of betting-against-beta and betting-against-volatility insignificant. We also show that the returns of beta- and volatility-sorted portfolios are driven largely by a single principal component, which in turn is explained largely by skewness.     

The Effect of Regulatory Harmonization on Cross‐Border Labor Migration: Evidence from the Accounting Profession

The paper examines whether international regulatory harmonization increases cross‐border labor migration. To study this question, we analyze European Union initiatives that harmonized accounting and auditing standards. Regulatory harmonization should reduce economic mobility barriers, essentially making it easier for accounting professionals to move across countries. Our research design compares the cross‐border migration of accounting professionals relative to tightly matched other professionals before and after regulatory harmonization. We find that international labor migration in the accounting profession increases significantly relative to other professions. We provide evidence that this effect is due to harmonization, rather than increases in the demand for accounting services during the implementation of the rule changes. The findings illustrate that diversity in rules constitutes an economic barrier to cross‐border labor mobility and, more specifically, that accounting harmonization can have a meaningful effect on cross‐border migration.     

THE VALUE OF IN‐STREAM WATER TEMPERATURE FORECASTS FOR FISHERIES MANAGEMENT

Water temperature is an important factor affecting aquatic life within the stream environment. Cold water species, such as salmonids, are particularly susceptible to elevated water temperatures. This paper examines the economic value of short‐term water temperature forecasts for salmonid management. Forecasts may have economic value if they allow the water resource manager to make better water allocation decisions. This study considers two applications: water releases for management of Chinook salmon in the Klamath River and leasing water from agriculture for management of steelhead trout in the John Day River. We incorporate biophysical models and water temperature distribution data into a Bayesian framework to simulate changes in fish populations and the corresponding benefit from recreational fishing and opportunity cost of water under different temperature forecast accuracies. Simulation results indicate that use of the forecasts results in increased fish production and that marginal costs decline and net benefits increase as forecast accuracy increases, suggesting that provision and use of such stream temperature forecasts would have value to society. (JEL Q22, Q25, Q28, Q50)     

Performance Measurement under Asymmetric Information and Investment Constraints

The fact that investment policies are often restricted appears to have been neglected in the performance measurement literature. This paper, using a standard information model, shows how the introduction of constraints on the proportion of assets to be invested in the market affects the expected portfolio returns and the value of a portfolio manager's performance. The results are related to the classical Treynor and Mazuy (1966) conjectures about characteristic lines.     

Robustness and U.S. Monetary Policy Experimentation

We study how a concern for robustness modifies a policymaker's incentive to experiment. A policymaker has a prior over two submodels of inflation‐unemployment dynamics. One submodel implies an exploitable trade‐off, the other does not. Bayes' law gives the policymaker an incentive to experiment. The policymaker fears that both submodels and his prior probability distribution over them are misspecified. We compute decision rules that are robust to misspecifications of each submodel and of the prior distribution over submodels. We compare robust rules to ones that Cogley, Colacito, and Sargent (2007) computed assuming that the models and the prior distribution are correctly specified. We explain how the policymaker's desires to protect against misspecifications of the submodels, on the one hand, and misspecifications of the prior over them, on the other, have different effects on the decision rule.     

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.     

Forward Foreign Exchange Rates,Expected Spot Rates,and Premia: A Signal-Extraction Approach

In this paper, we implement a methodology to identify and measure premia in the pricing of forward foreign exchange that involves application of signal-extraction techniques from the engineering literature. Diagnostic tests indicate that these methods are quite successful in capturing the essence of the time-series properties of premium terms. The estimated premium models indicate that premia show a certain degree of persistance over time and that more than half the variance in the forecast error that results from the use of current forward rates as predictors of future spot rates is accounted for by variation in premium terms. The methodology can be applied straightforwardly to the measurement of unobservables in other financial markets.