First-order asymptotic theory for parametric misspecification tests of Garch models

publication-status: Publishedtypes: ArticleFinal version of the article as published in Econometric Theory, vol. 35, issue 2, pp. 364-410. Copyright © Cambridge University Press 2009. Available online at http://journals.cambridge.org/This paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and No. (1993, Journal of Finance 48. 1749-1777) and the nonlinearity test of Lundbergh and Terasvirta (2002, Journal of Econometrics 110, 417-435), are asymptotically invalid. A second contribution is the proposed use of alternative tests for asymmetry and/or nonlinearity that, it is conjectured, should enjoy improved power properties. A Monte Carlo study supports the principal theoretical findings and also suggests that the new tests have fairly good size and very good power properties when compared with the Engle and Ng (1993) and Lundbergh and Terasvirta (2002) procedures

Robust Ecosystem Demography (RED version 1.0): a parsimonious approach to modelling vegetation dynamics in Earth system models

A significant proportion of the uncertainty in climate projections arises from uncertainty in the representation of land carbon uptake. Dynamic global vegetation models (DGVMs) vary in their representations of regrowth and competition for resources, which results in differing responses to changes in atmospheric CO2 and climate. More advanced cohort-based patch models are now becoming established in the latest DGVMs. These models typically attempt to simulate the size distribution of trees as a function of both tree size (mass or trunk diameter) and age (time since disturbance). This approach can capture the overall impact of stochastic disturbance events on the forest structure and biomass – but at the cost of increasing the number of parameters and ambiguity when updating the probability density function (pdf) in two dimensions. Here we present the Robust Ecosystem Demography (RED), in which the pdf is collapsed onto the single dimension of tree mass. RED is designed to retain the ability of more complex cohort DGVMs to represent forest demography, while also being parameter sparse and analytically solvable for the steady state. The population of each plant functional type (PFT) is partitioned into mass classes with a fixed baseline mortality along with an assumed power-law scaling of growth rate with mass. The analytical equilibrium solutions of RED allow the model to be calibrated against observed forest cover using a single parameter – the ratio of mortality to growth for a tree of a reference mass (μ0). We show that RED can thus be calibrated to the ESA LC_CCI (European Space Agency Land Cover Climate Change Initiative) coverage dataset for nine PFTs. Using net primary productivity and litter outputs from the UK Earth System Model (UKESM), we are able to diagnose the spatially varying disturbance rates consistent with this observed vegetation map. The analytical form for RED circumnavigates the need to spin up the numerical model, making it attractive for application in Earth system models (ESMs). This is especially so given that the model is also highly parameter sparse

Emergent constraints for the climate system as effective parameters of bulk differential equations

Planning for the impacts of climate change requires accurate projections by Earth system models (ESMs). ESMs, as developed by many research centres, estimate changes to weather and climate as atmospheric greenhouse gases (GHGs) rise, and they inform the influential Intergovernmental Panel on Climate Change (IPCC) reports. ESMs are advancing the understanding of key climate system attributes. However, there remain substantial inter-ESM differences in their estimates of future meteorological change, even for a common GHG trajectory, and such differences make adaptation planning difficult. Until recently, the primary approach to reducing projection uncertainty has been to place an emphasis on simulations that best describe the contemporary climate. Yet a model that performs well for present-day atmospheric GHG levels may not necessarily be accurate for higher GHG levels and vice versa. A relatively new approach of emergent constraints (ECs) is gaining much attention as a technique to remove uncertainty between climate models. This method involves searching for an inter-ESM link between a quantity that we can also measure now and a second quantity of major importance for describing future climate. Combining the contemporary measurement with this relationship refines the future projection. Identified ECs exist for thermal, hydrological and geochemical cycles of the climate system. As ECs grow in influence on climate policy, the method is under intense scrutiny, creating a requirement to understand them better. We hypothesise that as many Earth system components vary in both space and time, their behaviours often satisfy large-scale differential equations (DEs). Such DEs are valid at coarser scales than the equations coded in ESMs which capture finer high-resolution grid-box-scale effects. We suggest that many ECs link to such effective hidden DEs implicit in ESMs and that aggregate small-scale features. An EC may exist because its two quantities depend similarly on an ESM-specific internal bulk parameter in such a DE, with measurements constraining and revealing its (implicit) value. Alternatively, well-established process understanding coded at the ESM grid box scale, when aggregated, may generate a bulk parameter with a common “emergent” value across all ESMs. This single emerging parameter may link uncertainties in a contemporary climate driver to those of a climate-related property of interest. In these circumstances, the EC combined with a measurement of the driver that is uncertain constrains the estimate of the climate-related quantity. We offer simple illustrative examples of these concepts with generic DEs but with their solutions placed in a conceptual EC framework.</p

Trapping and Wiggling: Elastohydrodynamics of Driven Microfilaments

We present a general theoretical analysis of semiflexible filaments subject to viscous drag or point forcing. These are the relevant forces in dynamic experiments designed to measure biopolymer bending moduli. By analogy with the ``Stokes problems" in hydrodynamics (fluid motion induced by that of a wall bounding a viscous fluid), we consider the motion of a polymer one end of which is moved in an impulsive or oscillatory way. Analytical solutions for the time-dependent shapes of such moving polymers are obtained within an analysis applicable to small-amplitude deformations. In the case of oscillatory driving, particular attention is paid to a characteristic length determined by the frequency of oscillation, the polymer persistence length, and the viscous drag coefficient. Experiments on actin filaments manipulated with optical traps confirm the scaling law predicted by the analysis and provide a new technique for measuring the elastic bending modulus. A re-analysis of several published experiments on microtubules is also presented.Comment: RevTex, 24 pages, 15 eps figs, uses cite.sty, Biophysical

High sensitivity of future global warming to land carbon cycle processes

Unknowns in future global warming are usually assumed to arise from uncertainties either in the amount of anthropogenic greenhouse gas emissions or in the sensitivity of the climate to changes in greenhouse gas concentrations. Characterizing the additional uncertainty in relating CO2 emissions to atmospheric concentrations has relied on either a small number of complex models with diversity in process representations, or simple models. To date, these models indicate that the relevant carbon cycle uncertainties are smaller than the uncertainties in physical climate feedbacks and emissions. Here, for a single emissions scenario, we use a full coupled climate–carbon cycle model and a systematic method to explore uncertainties in the land carbon cycle feedback. We find a plausible range of climate–carbon cycle feedbacks significantly larger than previously estimated. Indeed the range of CO2 concentrations arising from our single emissions scenario is greater than that previously estimated across the full range of IPCC SRES emissions scenarios with carbon cycle uncertainties ignored. The sensitivity of photosynthetic metabolism to temperature emerges as the most important uncertainty. This highlights an aspect of current land carbon modelling where there are open questions about the potential role of plant acclimation to increasing temperatures. There is an urgent need for better understanding of plant photosynthetic responses to high temperature, as these responses are shown here to be key contributors to the magnitude of future change

Temperature-Dependence of Air-Broadened Line Widths and Shifts in the nu3 Band of Ozone

The 9.6-micron bands of O3 are used by many remote-sensing experiments for retrievals of terrestrial atmospheric ozone concentration profiles. Line parameter errors can contribute significantly to the total errors in these retrievals, particularly for nadir-viewing. The McMath-Pierce Fourier transform spectrometer at the National Solar Observatory on Kitt Peak was used to record numerous high-resolution infrared absorption spectra of O3 broadened by various gases at temperatures between 160 and 300 K. Over 30 spectra were analyzed simultaneously using a multispectrum nonlinear least squares fitting technique to determine Lorentz air-broadening and pressure-induced shift coefficients along with their temperature dependences for selected transitions in the 3 fundamental band of (16)O3. We compare the present results with other measurements reported in the literature and with the ozone parameters on the 2000 and 2004 editions of the HITRAN database

Evaluation of a workplace suicide prevention program in the Australian manufacturing industry : protocol for a cluster-randomised trial of MATES in manufacturing

Males are at higher risk of death by suicide than females in Australia, and among men, blue-collar males are at higher risk compared to other working males. In response, MATES in Construction developed a workplace suicide prevention program for the construction sector in 2007 that has been widely implemented in Australia. In the current project, this program is being adapted and trialled in the manufacturing sector. The common aims of MATES programs are to improve suicide prevention literacy, help-seeking intentions, and helping behaviours. The program will be evaluated using a cluster randomised-controlled trial design with waitlist controls across up to 12 manufacturing worksites in Australia. We hypothesise that after 8 months of the MATES in Manufacturing program, there will be significantly greater improvements in help-seeking intentions (primary outcome) compared to waitlist controls. The project is led by Deakin University in collaboration with the University of Melbourne, and in partnership with MATES in Construction and a joint labour-management Steering Group. Trial registration: The trial was registered retrospectively with the Australian New Zealand Clinical Trials Registry on 25 January 2022 (ACTRN12622000122752)

Exploring Entrepreneurial Skills and Competencies in Farm Tourism

Diversification to farm tourism is increasingly seen as a viable development strategy to promote a more diverse and sustainable rural economy and to counter declining farm incomes. However, our understanding of the dynamics of the modern farm tourism business and the entrepreneurial and competitive skills farmers require in making the transition from agriculture to a diversified - and service based - enterprise remains limited. Hence, the aim of this paper is to explore the range of skills and competencies that farmers in the North West of England identify as important when adopting a diversification strategy to farm tourism. With the findings indicating that that whilst a range of managerial skills are valued by farmers, they lack many of the additional business and entrepreneurial competencies required for success. Moreover, this paper acknowledges the need to generate consensus on the requisite skill-set that farm tourism operators require, along with a need for a currently fragmented rural tourism literature to acknowledge the significance of rural entrepreneurship and the characteristics of successful farmers and farm tourism ventures