Uncertainty and liquidity in corporate bond market

We examine the uncertainty–liquidity connection in the corporate bond market. Using monthly corporate bond data from 2005 to 2010, we construct proxies for parameter uncertainty by using firm-level parameters generated from a structural model of corporate debt. We find that uncertainty about firm parameters decreases trading volume but increases bid-ask spreads and price bouncing in the cross-section and across time. In addition, the panel VAR results show that parameter uncertainty has negative forecasting power for future bond liquidity, with greater uncertainty in the current month leading to lower trading volume, higher bid-ask spreads and higher price fluctuations on subsequent months. We conclude that parameter uncertainty is one of the underlying factors giving rise to the high level of illiquidity in the corporate bond market.     

A New Method for Estimating Market Power with an Application to Norwegian Sawmilling

In this paper we apply an innovative econometric tool to estimate mark-ups in an output market. The contribution of the paper is in the novel use of the stochastic frontier approach that is widely used to estimate efficiency. We show that this method, which we call the stochastic frontier estimator of market power, can be used both in the dual cost function framework and in the primal framework, and that mark-ups can be estimated with or without constant returns to scale. We apply this method to the Norwegian sawmilling industry, 1974–91.     

Production risk in multi-output industries: estimates from Norwegian dairy farms

Farmers who produce multiple outputs are portfolio managers in the sense that they use inputs to balance expected economic return and variance of return. This article estimates the structure of the stochastic multioutput production technology in Norwegian dairy farming, allowing for a more flexible specification of the technology than previous studies. We find that an increase in input levels leads primarily to higher output variability, and that inputs also influence the covariance of shocks between outputs. Risk reducing effects of inputs on outputs are primarily present in the covariance functions. Technical change leads to shifts in the profit distribution over the data period, but no welfare improvement for risk averse farmers.     

Forecasting with preliminary data: a comparison of two methods

This study examines two alternate methods, a vector autoregression error correction model and a state space model, to forecast revised United States trade balance figures. Both these methods incorporate preliminary and revised trade data. The results obtained from these methods were compared to the benchmark forecasts generated by revised-data-only models. This Study finds that the state space model performs worse than the benchmark. The vector autoregression model performs better than the benchmark only in the one-step forecast. These results indicate that incorporating preliminary data may not be useful in forecasting the revised data.     

An empirical analysis of the relationship between hedge ratio and hedging horizon using wavelet analysis

In this article, optimal hedge ratios are estimated for different hedging horizons for 23 different futures contracts using wavelet analysis. The wavelet analysis is chosen to avoid the sample reduction problem faced by the conventional methods when applied to non‐overlapping return series. Hedging performance comparisons between the wavelet hedge ratio and error‐correction (EC) hedge ratio indicate that the latter performs better for more contracts for shorter hedging horizons. However, the performance of the wavelet hedge ratio improves with the increase in the length of the hedging horizon. This is true for both within‐sample and out‐of‐sample cases. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:127–150, 2007     

Risk aversion,disappointment aversion,and futures hedging

This article examines the effect of disappointment aversion on futures hedging. We incorporated a constant‐absolute‐risk‐aversion (CARA) utility function into the disappointment‐aversion framework of Gul (1991). It is shown that a more disappointment‐averse hedger will choose an optimal futures position closer to the minimum‐variance hedge than will a less‐disappointment‐averse hedger. The effect of disappointment aversion is stronger when the hedger is less risk averse. A small disappointment aversion will cause a near‐risk neutral hedger to take a drastically different position. In addition, a more‐risk‐averse or disappointment‐averse hedger will have a lower reference point. Numerical results indicate that the reference point of a disappointment‐averse hedger tends to be lower than that of a conventional loss‐averse hedger. Consequently, the disappointment‐averse hedger will act more conservatively, not exploiting profitable opportunities as much as the conventional loss averse hedger will. © 2002 John Wiley & Sons, Inc. Jrl Fut Mark 22:123–141, 2002     

Turnover in U.S. Agricultural Labor Markets

Agricultural workers move in and out of agriculture frequently. Migration between types of jobs takes relatively little time. Legal female workers tend to stay out of the U.S. labor market longer once they stop being employed and their access to jobs outside of agriculture is more limited than that of their male counterparts. Predictions made when the 1986 Immigration Reform and Control Act was passed that granting people amnesty would induce most of them to leave agriculture were incorrect.