Estimating economic relationships subject to firm- and time-varying equality and inequality constraints

Applied econometricians often fail to impose economic regularity constraints in the exact form economic theory prescribes. We show how the Singular Value Decomposition (SVD) Theorem and Markov Chain Monte Carlo (MCMC) methods can be used to rigorously impose time- and firm-varying equality and inequality constraints. To illustrate the technique we estimate a system of translog input demand functions subject to all the constraints implied by economic theory, including observation-varying symmetry and concavity constraints. Results are presented in the form of characteristics of the estimated posterior distributions of functions of the parameters. Copyright (C) 2001 John Wiley Sons, Ltd.

Energy cost of physical activity in cystic fibrosis

Objective: The purpose of this study was to compare the energy cost of standardized physical activity (ECA) between patients with cystic fibrosis (CF) and healthy control subjects. Design: Cross-sectional study using patients with CF and volunteers from the community. Setting: University laboratory. Subjects: Fifteen patients (age 24.6 +/- 4.6 y) recruited with consent from their treating physician and 16 healthy control subjects (age 25.3 +/- 3.2) recruited via local advertisement. Interventions. Patients and controls walked on a computerised treadmill at 1.5 km/h for 60 min followed by a 60 min recovery period and, on a second occasion, cycled at 0.5 kp (kilopond), 30 rpm followed by a 60 min recovery. The ECA was measured via indirect calorimetry. Resting energy expenditure (REE), nutritional status, pulmonary function and genotype were determined. Results: The REE in patients was significantly greater than the REE measured in controls (P = 0.03) and was not related to the severity of lung disease or genotype. There was a significant difference between groups when comparing the ECA for walking kg root FFM (P = 0.001) and cycling kg root FFM (P = 0.04). The ECA for each activity was adjusted (ECA(adj)) for the contribution of REE (ECA kJ kg root FFM 120 min(-1) - REE kJ kg root FFM 120 min(-1)). ECA(adj) revealed a significant difference between groups for the walking protocol (P = 0.001) but no difference for the cycling protocol (P = 0.45). This finding may be related to the fact that the work rate during walking was more highly regulated than during cycling. Conclusions ECA in CF is increased and is likely to be explained by an additional energy-requiring component related to the exercise itself and not an increased REE. Sponsorship. The Prince Charles Hospital Foundation; MLR was in receipt of a QUTPRA Scholarship.

Energy cost of activity assessed by indirect calorimetry and a (CO2)-C-13 breath test

Purpose: The aim of this study was to assess the accuracy of a (CO2)-C-13 breath test for the prediction of short-duration energy expenditure. Methods: Eight healthy volunteers walked at 1.5 km.h(-1) for 60 min followed by 60-min recovery. During this time, the energy cost of physical activity was measured via respiratory calorimetry and a C-13 bicarbonate breath test. A further eight subjects were tested using the same two methods during a 60-min cycle at 0.5 kp. 30 ipm followed by a 60-min recovery. The rate of appearance of (CO2)-C-13, (RaCO2) was measured and the mean ratio, (V) over dot CO2/RaCO2 was used to calculate energy expenditure using the isotopic approach. Results: As would be expected, there was a significant difference in the energy cost of walking and cycling using both methods (P < 0.05). However. no significant differences were observed between respiratory calorimetry and the isotope method for measurement of energy expenditure while walking or cycling. Conclusions: These data suggest that the C-13 breath test is a valid method that can be used to measure the energy cost of short duration physical activity in a field setting.

Cost of malaria control in China: Henan's consolidation programme from community and government perspectives

Objective To assist with strategic planning for the eradication,of malaria in Henan Province, China, which reached the consolidation phase of malaria control in 1992, when only 318 malaria cases were reported, Methods We conducted a prospective two-year study of the costs for Henan's malaria control programme. We used a cost model that could also be applied to other malaria programmes in-mainland China, and analysed the cost of the three components of Henan's malaria programme. suspected malaria case management,, vector surveillance,,and population blood surveys. Primary cost data were collected from the government, and data on suspected malaria patient's were collected in two malaria counties (population 2 093 100). We enlisted the help of 260 village doctors. in six-townships or former communities (population 247 762), and studied all 12 315 reported cases of suspected malaria in catchment areas in 1994 and 1995. Findings The average-annual government investment in malaria control was estimated to be US$ 111 516 (case-management 59%; active blood surveys 25%;vector surveillance 12%; and contingencies and special projects 4%). The average cost (direct and indirect) for-patients seeking-treatment for suspected malaria was US$ 3.48, equivalent,to 10 days' income for rural residents. Each suspected malaria case cost the government an, average of US$ 0.78. Conclusion Further cuts in government funding will increase future costs, when epidemic malaria returns; investment in malaria control should therefore continue at least at current levels,of US$ 0.03 per person a risk.

Estimating Two-Stage Models for Genetic Influences on Alcohol, Tobacco or Drug Use Initiation and Dependence Vulnerability in Twin and Family Data

Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

Technical, allocative, cost and scale efficiencies in Bangladesh rice cultivation: A non-parametric approach

Applying programming techniques to detailed data for 406 rice farms in 21 villages, for 1997, produces inefficiency measures, which differ substantially from the results of simple yield and unit cost measures. For the Boro (dry) season, mean technical efficiency was efficiency was 56.2 per cent and 69.4 per cent, allocative efficiency was 81.3 per cent, cost efficiency was 56.2 per cent and scale efficiency 94.9 per cent. The Aman (wet) season results are similar, but a few points lower. Allocative inefficiency is due to overuse of labour, suggesting population pressure, and of fertiliser, where recommended rates may warrant revision. Second-stage regressions show that large families are more inefficient, whereas farmers with better access to input markets, and those who do less off-farm work, tend to be more efficient. The information on the sources of inter-farm performance differentials could be used by the extension agents to help inefficient farmers. There is little excuse for such sub-optimal use of survey data, which are often collected at substantial costs.

Functional assessment tools for paediatric clients with Juvenile Chronic Arthritis: An update and review for occupational therapists

Juvenile chronic arthritis (JCA) is one cause of chronic illness and disability in childhood. Traditional clinical assessment of clients with JCA include objective measures of joint deformity, joint swelling, range of motion, duration of morning stiffness, pain, walking speed, running speed and muscle strength. In many instances, these traditional measures have little or no significance or relevance to paediatric clients and their parents whereas functional skills used in everyday living are more likely to be meaningful. Measures of physical, social, and psychological functioning ensure a comprehensive health assessment. Responsible occupational therapy assessment and management of paediatric clients diagnosed with JCA requires the use of reliable, valid and sensitive measures of function. Several instruments are now available which measure a child's or adolescent's functional abilities. In this paper, JCA and the impact of JCA on functional development are reviewed. As well, seven functional assessment tools designed for use with paediatric clients with JCA which occupational therapists can use in their clinical practice will be appraised. The various characteristics of these tools are discussed in order to assist practitioners and researchers in selecting the functional instrument which best meets their needs.

High-performance L-band series and parallel switches using low-cost p-i-n diodes

Low-cost UHF-band p-i-n diodes are used to develop high-performance L-band series and parallel switches. To stop the rectification of large RF, signals, the diodes are biased at a large reverse-bias voltage. Parasitic elements of the diodes are tuned out using LC circuits in biasing circuits without increasing the size of the switches. (C) 2002 John Wiley Sons, Inc.

Microstrip circular phased array design and development using microwave antenna CAD tools

The complex design and development of a planar multilayer phased array antenna in microstrip technology can be simplified using two commercially available design tools 1) Ansoft Ensemble and 2) HP-EEsof Touchstone. In the approach presented here, Touchstone is used to design RF switches and phase shifters whose scattering parameters are incorporated in Ensemble simulations using its black box tool. Using this approach, Ensemble is able to fully analyze the performance of radiating and beamforming layers of a phased array prior to its manufacturing. This strategy is demonstrated in a design example of a 12-element linearly-polarized circular phased array operating at L band. A comparison between theoretical and experimental results of the array is demonstrated.

Estimating and evaluating the statistics of gapped local-alignment scores

We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate than existing regression-based and lookup table methods. We explore a more sophisticated way of modeling and estimating the score distributions (using a two-component mixture model and expectation maximization), but conclude that this does not improve significantly over simply ignoring scores with small E-values during estimation. Finally, we measure the classification accuracy of p-values estimated in different ways and observe that inaccurate p-values can, somewhat paradoxically, lead to higher classification accuracy. We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length.