Estimation and Inference for Threshold Effects in Panel Data Stochastic Frontier Models

One of the most enduring problems in cross-section or panel data models is heterogeneity among individual observations. Different approaches have been proposed to deal with this issue, but threshold regression models offer intuitively appealing econometric methods to account for heterogeneity. We propose three different estimators that can accommodate multiple thresholds. The first two, allowing respectively for fixed and random effects, assume that the firms specific inefficiency scores are time-invariant while the third one allows for time-varying inefficiency scores. We rely on a likelihood ratio test with m − 1 regimes under the null against m regimes. Testing for threshold effects is problematic because of the presence of a nuisance parameter which is not identified under the null hypothesis. This is known as Davies problem. We apply procedures pioneered by Hansen (1999) to test for the presence of threshold effects and to obtain a confidence set for the threshold parameter. These procedures specifically account for Davies problem and are based on non-standard asymptotic theory. Finally, we perform an empirical application of the fixed effects model on a panel of Quebec dairy farms. The specifications involving a trend and the Cobb- Douglas and Translog functional forms support three thresholds or four regimes based on farm size. The efficiency scores vary between 0.95 and 1 in models with and without thresholds. Therefore, productivity differences across farm sizes are most likely due to technological heterogeneity.Stochastic frontier models, threshold regression, technical efficiency, bootstrap, dairy production, C12, C13, C23, C52, Research Methods/ Statistical Methods,

BOOTSTRAPPING YOUR FISH OR FISHING FOR BOOTSTRAPS?: PRECISION OF WELFARE LOSS ESTIMATES FROM A GLOBALLY CONCAVE INVERSE DEMAND MODEL OF COMMERCIAL FISH LANDINGS IN THE U.S. GREAT LAKES

Replaced with revised version of paper 06/30/04.Demand and Price Analysis, Resource /Energy Economics and Policy,

Energy Substitutability in Canadian Manufacturing: Econometric Estimation with Bootstrap Confidence Intervals

This study provides estimates of the price and Morishima substitution elasticities between energy and non-energy inputs in two Canadian energy-intensive manufacturing industries: Primary Metal and Cement. The elasticities are estimated using annual industry-level KLEM data (1961- 2003) and relying on two flexible functional forms: the Translog and the Symmetric Generalized McFadden (SGM) cost functions. In addition to the point estimates, the confidence intervals of the elasticities are computed using single- and double-bootstrap resampling techniques. For both industries, the estimation results suggest that capital, labour, material and energy are pairwise substitutes and that energy is the most substitutable input. However, the low magnitudes of the estimated elasticities do not seem to offer great flexibility to these industries to adapt to high increases in energy prices.Energy; Elasticity of substitution; Translog cost function; Symmetric Generalized McFadden (SGM) Cost Function; Single Bootstrap; Double Bootstrap.

Testing for Common Values in Canadian Treasury Bill Auctions

We develop a test for common values in auctions in which some bidders possess information about rivals’ bids. This information causes a bidder to bid differently when she has a private value than when her value depends on rivals’ information. In a divisible good setting, such as treasury bill auctions, bidders with private values who obtain information about rivals’ bids use this information only to update their prior about the distribution of residual supply. In the model with a common value component, they also update their prior about the value of the good being auctioned.We apply the data from the Canadian treasury bill market, where some bidders have to route their bids through dealers who also submit bids on their own. Furthermore, we use the structural model to estimate the value of customer order flow to a dealer. We find that the extra information contained in customers’ bids leads on average to an increase in payoff equal to about 0.5 of a basis point, or 32% of the expected surplus of dealers from participating in these auctions.multiunit auctions, treasury auctions, structural estimation, nonparametric identification and estimation, test for common value

On the estimation of the influence curve

We prove the asymptotic validity of bootstrap confidence bands for the influence curve from its usual estimator (the sensitive curve). The proof is based on the use of Gill's (1989) generalized delta method for Hadamard differentiable operators. The scope and applicability of this result are also discussed