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,

Model simplification and optimization of a passive wind turbine generator

In this paper, the design of a "low cost full passive structure" of wind turbine system without active electronic part (power and control) is investigated. The efficiency of such device can be obtained only if the design parameters are mutually adapted through an optimization design approach. For this purpose, sizing and simulating models are developed to characterize the behavior and the efficiency of the wind turbine system. A model simplification approach is presented, allowing the reduction of computational times and the investigation of multiple Pareto-optimal solutions with a multiobjective genetic algorithm. Results show that the optimized wind turbine configurations are capable of matching very closely the behavior of active wind turbine systems which operate at optimal wind powers by using a MPPT control device

Integrated Optimal Design of a Passive Wind Turbine System: An Experimental Validation

This work presents design and experimentation of a full passive wind turbine system without active electronic part(power and control). The efficiency of such device can be obtained only if the system design parameters are mutually adapted through an Integrated Optimal Design (IOD) method. This approach based on multiobjective optimization, aims at concurrently optimizing the wind power extraction and the global system losses for a given wind speed profile while reducing the weight of the wind turbine generator. It allows us to obtain the main characteristics (geometric and energetic features) of the optimal Permanent Magnet Synchronous Generator (PMSG) for the passive wind turbine. Finally, experiments on the PMSG prototype built from this work show a good agreement with theoretical predictions. This validates the design approach and confirms the effectiveness of such passive device

Case studies of thermally driven heat pump assisted drying

In general, most heat losses in industrial dryers arise due to the discharge of humid air. By using heat pump drying (HPD) systems, heat from the exhaust humid air can be recovered, thus improving the energy efficiency substantially. In this study, the performance of thermally driven HP integration in an animal food and a blood dryer were examined. Computer simulation models of the original high temperature dryers and the proposed system with HP integration and auxiliary heating were developed. It is found that, when using a gas engine, the maximum energy cost saving is limited by the temperature of the coolant fluid. The maximum energy cost saving when using a gas turbine is a bit higher, however at a much higher operating temperature

A distributed auction-based algorithm to allocate bandwidth over paths

Session 01 : Scheduling and bandwidth allocationInternational audienceIn the literature, Vickrey-Clark-Groves (VCG) double-sided auctions have been applied to inter-domain traffic exchange because they provide incentives to be truthful and lead to an efficient use of the network, among relevant properties of mechanism design. Unfortunately, the resulting resource allocation scheme is neither budget-balanced nor solvable in a decentralized way, two important properties. We present a different but more realistic auction-based algorithm for allocating bandwidth over paths to end users or ISPs, leading to a new budget-balanced pricing scheme for which allocations and charges can be computed in a decentralized way

Robust design of a passive wind turbine system

The effectiveness of full passive Wind Turbine (WT) systems has been recently demonstrated. Such low cost and reliable structures without active control and with a minimum number of sensors can be efficient only if the system design parameters are mutually adapted through an integrated optimal design approach. Even if there is a good agreement between theoretical design models and an experimental prototype, it is relevant to evaluate the WT efficiency with respect to design variable variations. Thus, this work is devoted more specifically to the sensitivity analysis of a passive WT system according to electrical variable variations of the Permanent Magnet Synchronous Generator (PMSG). It also investigates the interest of a robust design approach for reducing the sensitivity of the WT efficiency to specific variable variations

Post harvest needs assessment in the Teso and Lango farming systems of Uganda: Marketing systems analysis and farmers' perspectives

In November 1999, a Post Harvest Needs Assessment was conducted in the Teso and Lango fanning systems of Uganda. The needs assessment consisted of a farmer questionnaire and a rapid market assessment exercise. This report documents the findings from both activities: Part A identifies proposals for future activities; Part B concerns the marketing assessment; and Part C the farmer interviews

Improvements in the storage and marketing quality of grain legumes: Final technical report

The objective of this three-year project based in northern Ghana was to identify qualitative and quantitative losses in the storage of grain legumes by small-scale farmers and develop means of reducing the losses. The project used participatory surveys to monitor the loss in value during storage, both on-farm and in the markets. These surveys showed that heavy losses occurred during storage in markets

Ex2Vec: Characterizing Users and Items from the Mere Exposure Effect

The traditional recommendation framework seeks to connect user and content, by finding the best match possible based on users past interaction. However, a good content recommendation is not necessarily similar to what the user has chosen in the past. As humans, users naturally evolve, learn, forget, get bored, they change their perspective of the world and in consequence, of the recommendable content. One well known mechanism that affects user interest is the Mere Exposure Effect: when repeatedly exposed to stimuli, users' interest tends to rise with the initial exposures, reaching a peak, and gradually decreasing thereafter, resulting in an inverted-U shape. Since previous research has shown that the magnitude of the effect depends on a number of interesting factors such as stimulus complexity and familiarity, leveraging this effect is a way to not only improve repeated recommendation but to gain a more in-depth understanding of both users and stimuli. In this work we present (Mere) Exposure2Vec (Ex2Vec) our model that leverages the Mere Exposure Effect in repeat consumption to derive user and item characterization and track user interest evolution. We validate our model through predicting future music consumption based on repetition and discuss its implications for recommendation scenarios where repetition is common