Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States

Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.

Exchange rate pass-through to prices in macrodata: a comparative sensitivity analysis

This paper compares exchange rate pass-through to aggregate prices in the US, Germany and Japan across a number of dimensions. Building on the empirical approaches in the recent literature, our contribution is to perform a thorough sensitivity analysis of pass-through estimates. We find that the econometric method, data frequency and variable proxy employed matter for the precision of details, yet they often agree on some general trends. Thus, pass-through to import prices has declined in the 1990s relative to the 1980s, pass-through to export prices remains country-specific and pass-through to consumer prices is nowadays negligible in all three economies we considered.

Evaluating interval forecasts of high-frequency financial data

A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen (1998), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression-based test, and a modified version of Christoffersen's Markov chain test for independence, and analyse their properties when the financial time series exhibit periodic volatility. These approaches lead to different conclusions when interval forecasts of FTSE100 index futures returns generated by various GARCH(1,1) and periodic GARCH(1,1) models are evaluated.

Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive

The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

Simulation of the diurnal cycle in a climate model and its evaluation using data from Meteosat 7

The representation of the diurnal cycle in the Hadley Centre climate model is evaluated using simulations of the infrared radiances observed by Meteosat 7. In both the window and water vapour channels, the standard version of the model with 19 levels produces a good simulation of the geographical distributions of the mean radiances and of the amplitude of the diurnal cycle. Increasing the vertical resolution to 30 levels leads to further improvements in the mean fields. The timing of the maximum and minimum radiances reveals significant model errors, however, which are sensitive to the frequency with which the radiation scheme is called. In most regions, these errors are consistent with well documented errors in the timing of convective precipitation, which peaks before noon in the model, in contrast to the observed peak in the late afternoon or evening. When the radiation scheme is called every model time step (half an hour), as opposed to every three hours in the standard version, the timing of the minimum radiance is improved for convective regions over central Africa, due to the creation of upper-level layer-cloud by detrainment from the convection scheme, which persists well after the convection itself has dissipated. However, this produces a decoupling between the timing of the diurnal cycles of precipitation and window channel radiance. The possibility is raised that a similar decoupling may occur in reality and the implications of this for the retrieval of the diurnal cycle of precipitation from infrared radiances are discussed.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

Monitoring changes in precipitation and radiative energy using satellite data and climate models

Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

The significance of volcanic eruption strength and frequency for climate

A simple physical model of the atmospheric effects of large explosive volcanic eruptions is developed. Using only one input parameter - the initial amount of sulphur dioxide injected into the stratosphere - the global-average stratospheric optical-depth perturbation and surface temperature response are modelled. The simplicity of this model avoids issues of incomplete data (applicable to more comprehensive models), making it a powerful and useful tool for atmospheric diagnostics of this climate forcing mechanism. It may also provide a computationally inexpensive and accurate way of introducing volcanic activity into larger climate models. The modelled surface temperature response for an initial sulphur-dioxide injection, coupled with emission-history statistics, is used to demonstrate that the most climatically significant volcanic eruptions are those of sufficient explosivity to just reach into the stratosphere (and achieve longevity). This study also highlights the fact that this measure of significance is highly sensitive to the representation of the climatic response and the frequency data used, and that we are far from producing a definitive history of explosive volcanism for at least the past 1000 years. Given this high degree of uncertainty, these results suggest that eruptions that release around and above 0.1 Mt SO2 into the stratosphere have the maximum climatic impact.

A link between low-frequency mesoscale eddy variability around Madagascar and the large-scale Indian Ocean variability

A connection is shown to exist between the mesoscale eddy activity around Madagascar and the large-scale interannual variability in the Indian Ocean. We use the combined TOPEX/Poseidon-ERS sea surface height (SSH) data for the period 1993–2003. The SSH-fields in the Mozambique Channel and east of Madagascar exhibit a significant interannual oscillation. This is related to the arrival of large-scale anomalies that propagate westward along 10°–15°S in response to the Indian Ocean dipole (IOD) events. Positive (negative) SSH anomalies associated to a positive (negative) IOD phase induce a shift in the intensity and position of the tropical and subtropical gyres. A weakening (strengthening) results in the intensity of the South Equatorial Current and its branches along east Madagascar. In addition, the flow through the narrows of the Mozambique Channel around 17°S increases (decreases) during periods of a stronger and northward (southward) extension of the subtropical (tropical) gyre. Interaction between the currents in the narrows and southward propagating eddies from the northern Channel leads to interannual variability in the eddy kinetic energy of the central Channel in phase with the one in the SSH-field.

Nitrous acid: vibrational frequency shifts due to 15N substitution, and the harmonic force field

Vibration rotation spectra of HO15 NO and DO15 NO have been measured at a resolution of 0•04 cm-1 to determine the isotopic shifts in the vibrational band origins. These have been used together with recently determined data on the vibrational band origins, Coriolis constants, and centrifugal distorition constants, to determine the harmonic force field of both cis and trans nitrous acid in least squares refinement calculations. The results are discussed in relation to recent ab initio calculations, the inertia defects, and the torsional potential function.

A double data rate (DDR) architecture for OFDM based wireless consumer devices

The creation of OFDM based Wireless Personal Area Networks (WPANs) has allowed the development of high bit-rate wireless communication devices suitable for streaming High Definition video between consumer products, as demonstrated in Wireless-USB and Wireless-HDMI. However, these devices need high frequency clock rates, particularly for the OFDM, FFT and symbol processing sections resulting in high silicon cost and high electrical power. The high clock rates make hardware prototyping difficult and verification is therefore very important but costly. Acknowledging that electrical power in wireless consumer devices is more critical than the number of implemented logic gates, this paper presents a Double Data Rate (DDR) architecture for implementation inside a OFDM baseband codec in order to reduce the high frequency clock rates by a complete factor of 2. The presented architecture has been implemented and tested for ECMA-368 (Wireless- USB context) resulting in a maximum clock rate of 264MHz instead of the expected 528MHz clock rate existing anywhere on the baseband codec die.

A benchmark method for global optimization problems in structure determination from powder diffraction data

Quasi-Newton-Raphson minimization and conjugate gradient minimization have been used to solve the crystal structures of famotidine form B and capsaicin from X-ray powder diffraction data and characterize the chi(2) agreement surfaces. One million quasi-Newton-Raphson minimizations found the famotidine global minimum with a frequency of ca 1 in 5000 and the capsaicin global minimum with a frequency of ca 1 in 10 000. These results, which are corroborated by conjugate gradient minimization, demonstrate the existence of numerous pathways from some of the highest points on these chi(2) agreement surfaces to the respective global minima, which are passable using only downhill moves. This important observation has significant ramifications for the development of improved structure determination algorithms.

Mixture models for capture-recapture count data

The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.