Tests of Hypotheses Arising In the Correlated Random Coefficient Model

This paper examines the correlated random coecient model. It extends the analysis of Swamy (1971, 1974), who pioneered the uncorrelated random coecient model in economics. We develop the properties of the correlated random coecient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coecient model against the null hypothesis of the uncorrelated random coecient model.Random coecient models, correlated random coecient models, instrumental variables

Testing the correlated random coefficient model

The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coefficient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coefficient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and find evidence of sorting into schooling based on unobserved components of gains.

Graston Soft Tissue Mobilization And Dynamic Balance Training Effects On Pain And Dynamic Postural Control Of Young Athletes With Chronic Ankle Instability

A review of a randomized single-blind controlled trial by Schaefer and Sandrey was done to determine the effects of Graston soft tissue mobilization (GISTM) and dynamic balance training (DBT) on dynamic postural control of young athletes with chronic ankle instability (CAI). Three intervention groups were utilized in this study. The first group interventions consisted of dynamic balance training and Graston instrument-assisted soft-tissue mobilization (DBT/GISTM). The second group interventions consisted of dynamic balance training and Graston instrument-assisted soft-tissue mobilization sham (DBT/GISTM-S). The third group intervention was dynamic balance training as a control group (DBT/C). Based on the following outcome measures: Foot and Ankle Ability Measure (FAAM), activities of daily living (ADL), FAAM Sport, visual analog scale (VAS), and Star Excursion Balance Test (SEBT); all three intervention groups had statistically significant improvements from pre to post-assessments. All intervention groups exceeded the minimal detectable change/minimally clinical important difference for all outcome measures with the exception of the VAS. This article supports the use of GISTM and DBT when treating high school and collegiate athletes with CAI. This study does not provide clinicians with knowledge of the effects of GISTM alone on CAI. Limitations of the study include convenient sampling, single blind controlled trial, and short treatment duration (4 weeks) with no long term follow-up

Photosynthesis, quantum requirements, and energy demand for crop production in controlled environments

In this work, energy costs for LED (light emitting diodes) lighting of a virtual plant stand exhibiting C3photosynthesis have been calculated via a model considering the quantum demand to build-up dry matter and energy efficiency of state-of-the art LEDs. Optimistic and pessimistic scenarios have been calculated by taking into account uncertainties regarding the H+/ATP stoichiometry of photosynthesis and different management strategies for indoor plant production. Energy costs were between 265 and 606 kWh for a production cycle ranging over 100 days and resulting in 2500 g dry matter per square meter for the optimistic and the pessimistic scenario respectively. The conversion efficiencies from electrical energy to energy bound in phytomass at the end of the production cycle were 2.07 % and 4.72 % (pessimistic and optimistic scenario, respectively). This was lower than the theoretical maximum values calculated for C3 plants that are given as 9.5 % in the literature. However, when the losses that occur during the conversion from electrical energy to light energy were excluded and only the efficiency of the conversion from incident light energy to phyto-energy was calculated, values increased to 4.0 and 9.1 %. The differences between the optimistic and the pessimistic scenario was caused by decreased photorespiration via carbon dioxide fertilization, which increased the conversion efficiencies by 38 %, followed by different assumptions about the H+ requirement for ATP production (34 %) and an increased rate of active absorption of light energy (24 %). Considering cumulative as well as feedback effects of all of the mentioned parameters, the conversion efficiency in the optimistic scenario was 2.3 times higher than in the pessimistic scenario. A system for measuring gas-exchange of whole plants or plant stands was developed in order to be able to investigate and improve the above mentioned management strategies in the future. CO2 sensors and temperature and humidity sensors were used to detect water loss and CO2. Readily available off-the-shelf electronic and mechanical materials were used in order to build a low-cost system that can be used in high throughput experiments. The results indicate that around 90 % of the transpirational water was detected by the system. We conclude that parts of the transpirational water condensed on the surfaces thus not leaving the chamber. When checking the accuracy of the H2O and CO2 sensors using an industry quality infrared gas analyser (IRGA), we found significant deviations from the values given by the IRGA and used this data for calibration of the CO2 sensors. The responses of the CO2-sensors were also linearly coupled to the H2O concentrations (about -0.1 % ppm CO2 / ppm H2O). A regression analysis was performed and the coefficients were used to correct the sensor readings. Since LEDs exhibit a higher energy-to-light ratio when operated at lower light levels, we tested a very small growing gibberellin (GA) deficient super dwarf rice genotype in a climate chamber experiment under different illumination levels and different levels of nitrogen supply to assess its suitability for crop production in artificial environments. A 25 % reduction in illumination lead to a 75 % reduction in yield, mainly due to a 60 % reduction in formed tillers and 20 % reduction in kernel weight, and an 80 % reduction in illumination caused total yield loss. Whereas leaf area under reduced illumination was significantly lower, only marginal changes in the dimensions of single leaves were observed. Photosynthesis at growing light conditions was not different between control plants and plants under 75 % illumination. This was explained by a higher photochemical efficiency under lower light conditions and a reduced mesophyll resistance. Therefore, we conclude that this genotype is an interesting candidate for crop production in vertical plant production systems, especially because of its short stature and the absence of shade avoidance mechanisms, such as leaf elongation, that would complicate production in small-height growing racks under low-light conditions. Nitrogen concentrations of 2.8 and 1.4 mmol L-1 in the nutrient solution lead to no differences in plant growth. We conclude that a nitrogen concentration of 1.4 mmol L-1 is sufficient for this genotype under the light intensities that were applied here. A software tool for simulations of photosynthesis in the python programming language was developed. The software implements a classical Farquhar-von CaemmererBerry (FvCB) model of leaf photosynthesis coupled with a model for the estimation of stomatal behaviour dependent on environmental conditions. We want to emphasize that the use of such models is essential to understand the complex interactions between plant growth, leaf photosynthesis and the environment. Knowledge on those relationships is the key to improve the efficiency of plant production in controlled environments.In dieser Arbeit wurden die Energiekosten für LED-Beleuchtung (Licht emittierende Dioden) eines virtuellen C3 Pflanzenstandes mit Hilfe eines Modells berechnet, das einerseits den Quantenbedarf für den Aufbau von pflanzlicher Trockenmasse und andererseits die Energieeffizienz von modernen LEDs berücksichtigt. Optimistische und pessimistische Szenarien wurden unter Berücksichtigung von Unsicherheiten bezüglich der H+/ATP-Stöchiometrie der Photosynthese und verschiedener Managementstrategien für die Pflanzenproduktion in kontrollierten Umwelten berechnet. Die Energiekosten lagen zwischen 265 und 606 kWh für einen Produktionszyklus von 100 Tagen Länge und einem finalen Ertrag von 2500 g Trockenmasse pro Quadratmeter für das optimistische bzw. pessimistische Szenario. Die Umwandlungswirkungsgrade von elektrischer Energie in in Phytomasse gebundene Energie am Ende des Produktionszyklus betrugen 2,07 % und 4,72 % (pessimistisches und optimistisches Szenario). Dies war niedriger als die theoretischen Höchstwerte, die für C3-Pflanzen berechnet und in der Literatur mit 9,5 % angegeben werden. Wenn man jedoch die Verluste, die bei der Umwandlung von elektrischer Energie in Lichtenergie auftreten, ausschließt und nur die Effizienz der Umwandlung von einfallender Lichtenergie in Phytoenergie berechnet, stiegen die Werte auf 4,0 und 9,1 %. Die Unterschiede zwischen dem optimistischen und dem pessimistischen Szenario wurden durch eine verminderte Photorespiration durch Kohlendioxiddüngung verursacht, die die Umwandlungseffizienz um 38 % erhöhte, gefolgt von unterschiedlichen Annahmen über den H+-Bedarf für die ATP-Produktion (34 %) und einer erhöhten Rate der aktiven Absorption von Lichtenergie (24 %). Berücksichtigt man sowohl kumulative als auch Rückkopplungseffekte aller genannten Parameter, war der Umwandlungswirkungsgrad im positiven Szenario 2,3 Mal höher als im pessimistischen Szenario. Ein System zur Messung des Gasaustausches von Pflanzen oder Pflanzenbeständen wurde entwickelt, um die oben genannten Managementstrategien in Zukunft zu untersuchen und zu verbessern. Es wurden handelsübliche elektronische und mechanische Materialien verwendet, um ein kostengünstiges System zu entwerfen, das in Hochdurchsatzexperimenten eingesetzt werden kann. Die Ergebnisse zeigen, dass etwa 90 % des Transpirationswassers durch das System erfasst wurden. Wir schließen daraus, dass Teile des Transpirationswassers auf den Oberflächen kondensierten und somit das System nicht verließen. Die Reaktionen der CO2Sensoren waren ebenfalls linear an die H2O-Konzentrationen gekoppelt (ca. -0,1 % ppm CO2 / ppm H2O). Da LEDs ein höheres Energie zu Licht-Verhältnis aufweisen, wenn sie bei niedrigeren Lichtstärken betrieben werden, testeten wir einen sehr kleinen wachsenden Gibberellin (GA) defizienten Super-Zwergreis-Genotyp in einem Klimakammerexperiment unter verschiedenen Beleuchtungsstärken und unterschiedlicher Stickstoffzufuhr, um seine Eignung für den Pflanzenbau in künstlichen Umgebungen zu beurteilen. Eine 25 %ige Verringerung der Beleuchtung führte zu einer Ertragsreduzierung von 75 %, hauptsächlich aufgrund einer 60 %igen Verringerung Anzahl an geformten Bestockungstrieben und einer 20 %igen Verringerung des Korngewichts. Eine 80 %ige Verringerung der Beleuchtung verursachte einen Gesamtverlust bezüglich Kornertrag. Während die Blattfläche unter reduzierter Beleuchtung deutlich geringer war, wurden nur marginale Veränderungen in der Morphologie der Blätter beobachtet. Die Photosyntheseleistung in den jeweiligen Wachstumsbeleuchtungsstärken unterschied sich nicht zwischen Kontrollpflanzen und Pflanzen unter 75 % Beleuchtung. Dies wurde durch eine höhere photochemische Effizienz unter geringeren Lichtbedingungen und eine reduzierte Mesophyllresistenz erklärt. Daher kamen wir zu dem Schluss, dass dieser Genotyp ein interessanter Kandidat für die Pflanzenproduktion in Vertikalen Pflanzenproduktionssystemen ist, insbesondere wegen seiner kleinen Statur und dem Fehlen von Mechanismen zur Schattenvermeidung, die die Produktion in niedrigen Produktionssystemen unter Schwachlichtbedingungen erschweren würden. Es wurde ein SoftwareTool zur Simulation der Photosynthese in der Programmiersprache Python entwickelt. Die Software implementiert ein klassisches Farquhar-von-Caemmerer-Berry (FvCB)-Modell der Blattfotosynthese, gekoppelt mit einem Modell zur Abschätzung der stomatären Leitfähigkeit in Abhängigkeit von den Umweltbedingungen. Wir möchten betonen, dass die Verwendung solcher Modelle wesentlich ist, um die komplexen Wechselwirkungen zwischen Pflanzenwachstum, Blattfotosynthese und Umwelt zu verstehen. Kenntnisse über diese Beziehungen ist essentiell bezüglich der Erhöhung der Effizienz von Pflanzenproduktion in künstlichen Umwelten

Better Late than Never: How the Online Advertising Industry’s Response to Proposed Privacy Legislation Eliminates the Need for Regulation

Although Julie Matlin liked the shoes she saw on Zappos.com, she ultimately left the site without purchasing them. However, it was not the last time she would see that pair of shoes. For the next several days, the shoes followed Ms. Matlin to numerous other websites. “It was as if Zappos had unleashed a persistent salesmen who wouldn’t take no for an answer.” Understandably, Ms. Matlin found this “online stalking” disturbing, but she was more troubled when ads for her online dieting service started following her as well. She stated, “They are still following me around, and it makes me feel fat.

Testing the Correlated Random Coefficient Model

The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coefficient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coefficient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and find evidence of sorting into schooling based on unobserved components of gains.instrumental variables, testing, correlated random coefficient, power of tests based on IV