A dynamic stochastic general equilibrium model for Switzerland

This paper presents a DSGE (dynamic stochastic general equilibrium) model of the Swiss economy used since 2007 in the monetary policy decision process at the Swiss National Bank. In addition to forecasting the likely course of main macro variables under various scenarios for the Swiss economy, the model DSGE-CH serves as a laboratory for studying business cycles and examining the effects of actual and hypothetical monetary policies. The microfounded model DSGE-CH represents Switzerland as a small open economy with optimizing economic agents facing several real and nominal rigidities and exogenous foreign and domestic shocks. The comparison of the model's implications with the real world indicates that DSGE-CH performs well along standard dimensions. It captures the overall stochastic structure of the Swiss economy as represented by the moments of its key macroeconomic variables, furthermore, it has appropriate dynamic properties, as judged by its impulse response functions. Finally, it quite accurately replicates the historical path of major Swiss variables.DSGE, forecasting, small open economy, Switzerland

Seasonal climate forecasts for more effective raingrown grain-cotton production systems

Cropping is a risky business. Our highly variable climate makes it difficult to decide how best to manage crops and cropping systems. What works well one year might not work well the next. To develop better risk management practices, this project uses the APSIM cropping systems model to examine the profitability and sustainability of a range of alternative dryland cotton/grain cropping systems throughout the northern grain region of eastern Australia. It involves working closely with farmer collaborators in Central Queensland, the Darling Downs, the northwest slopes of NSW and the Liverpool Plains

The Madden Julian Oscillation and its relationship with rainfall in Queensland

The Madden Julian Oscillation is a large-scale atmospheric phenomenon that is generated above the tropical Indian Ocean. It is associated with large convective systems that propagate eastward across the Pacific Ocean. Since it is an atmospheric event limited to the equatorial domain, it was believed that it has little effect on non-tropical regions. However, recent research found correlations between the positioning of the active Madden Julian Oscillation phase along the Equator and rainfall events northeast Australia. The correlations were significant throughout Queensland. The phenomenon is subject to a study by climate scientists at four Australian institutions. It aims to develop a simple predictive tool of rainfall events that are linked with the active phase of the Madden Julian Oscillation and that is applicable throughout Queensland and possible beyond. The outcome of this research is to be linked with agricultural production systems model in order to help Queensland farmers to better time planting and harvesting, as well as scheduling of contractors whose operations might be delayed by rain

Spatially Varying Coefficient Regression with GAM Gaussian Process splines: GAM(e)-on

This paper describes initial work exploring GAM Gaussian Process (GP) splines parameterised by observation location, as a geographical varying coefficient model. Similar to GWR, this approach accommodates process spatial heterogeneity and generates spatially distributed, local coefficient estimates. These can be mapped to indicate the nature of the heterogeneity. The paper investigates the effect of the smoothing parameters used in the splines and how they alter the nature of the modelled heterogeneity. It optimises these in the GAM GP and the tuned model has subtle but important differences with the initial model. This has impacts on the nature of the process understanding (inference) that can be extracted from the model. This in turn suggest the need examine the underlying semantics of the resultant models in relation to the scale of process suggested by the smoothing parameters. A number of areas of further work are identified

Multiscale Spatially and Temporally Varying Coefficient Modelling Using a Geographic and Temporal Gaussian Process GAM (GTGP-GAM) (Short Paper)

The paper develops a novel approach to spatially and temporally varying coefficient (STVC) modelling, using Generalised Additive Models (GAMs) with Gaussian Process (GP) splines parameterised with location and time variables - a Geographic and Temporal Gaussian Process GAM (GTGP-GAM). This was applied to a Mongolian livestock case study and different forms of GTGP splines were evaluated in which space and time were combined or treated separately. A single 3-D spline with rescaled temporal and spatial attributes resulted in the best model under an assumption that for spatial and temporal processes interact a case studies with a sufficiently large spatial extent is needed. A fully tuned model was then created and the spline smoothing parameters were shown to indicate the degree of variation in covariate spatio-temporal interactions with the target variable

Management of a Patient with an Axillary Nerve Entrapment

HISTORY: A 27-year-old male reports to physical therapy evaluation with R shoulder pain following an injury during Jiu-jitsu 4 weeks prior. He experienced immediate onset of pain following a submission attempt where his arm was forcefully externally rotated. At time of evaluation, he experienced pain with pressing and pulling exercises in R shoulder that would sometimes radiate down to posteriolateral arm. PHYSICAL EXAMINATION: Initial examination of the R arm revealed hypomobility throughout thoracic and lower cervical spine, tight posterior shoulder capsule with anterior humeral head migration, and limited shoulder ROM secondary to pain. Neural testing resulted in + radial nerve tension, which was reduced with head-tilt, indicating proximal facilitation. His rotator cuff strength was strong and pain-free. He had extreme tenderness to palpation and reproduction of arm symptoms over axillary nerve in quadrangular space. DIFFERENTIAL DIAGNOSIS: Labral tear Rotator cuff tear/impingement Radiculopathy Neural tension Axillary nerve entrapment TESTS AND RESULTS: R shoulder AP and lateral radiographic views Bony structure and alignment intact FINAL WORKING DIAGNOSIS: R axillary nerve entrapment with C5-6 facilitation resulting in “double crush” TREATMENT AND OUTCOMES: Thoracic and cervical manipulation Posterior shoulder capsule mobilizations Cross-friction to teres minor and major Radial nerve sliders Progressive scapular strengthening Open-chain to closed-chain Mid-range to end-range Able to return to Jiu-jitsu and regular workout routine at 6 weeks. ROLE OF PRIMARY AUTHOR: Diagnosis and treatment of patient of interest