A comparison of tests of non-linear cointegration with an application to the predictability of US interest rates using the term structure

We test whether there are nonlinearities in the response of short- and long-term interest rates to the spread in interest rates, and assess the out-of-sample predictability of interest rates using linear and nonlinear models. We find strong evidence of nonlinearities in the response of interest rates to the spread. Nonlinearities are shown to result in more accurate short-horizon forecasts, especially of the spread.

Forecasting real estate returns using financial spreads

This paper examines the predictability of real estate asset returns using a number of time series techniques. A vector autoregressive model, which incorporates financial spreads, is able to improve upon the out of sample forecasting performance of univariate time series models at a short forecasting horizon. However, as the forecasting horizon increases, the explanatory power of such models is reduced, so that returns on real estate assets are best forecast using the long term mean of the series. In the case of indirect property returns, such short-term forecasts can be turned into a trading rule that can generate excess returns over a buy-and-hold strategy gross of transactions costs, although none of the trading rules developed could cover the associated transactions costs. It is therefore concluded that such forecastability is entirely consistent with stock market efficiency.

Forecasting models of retail rents

The authors model retail rents in the United Kingdom with use of vector-autoregressive and time-series models. Two retail rent series are used, compiled by LaSalle Investment Management and CB Hillier Parker, and the emphasis is on forecasting. The results suggest that the use of the vector-autoregression and time-series models in this paper can pick up important features of the data that are useful for forecasting purposes. The relative forecasting performance of the models appears to be subject to the length of the forecast time-horizon. The results also show that the variables which were appropriate for inclusion in the vector-autoregression systems differ between the two rent series, suggesting that the structure of optimal models for predicting retail rents could be specific to the rent index used. Ex ante forecasts from our time-series suggest that both LaSalle Investment Management and CB Hillier Parker real retail rents will exhibit an annual growth rate above their long-term mean.

Efficient interactive budget planning and adjusting under financial stress

One of the most challenging tasks in financial management for large governmental and industrial organizations is Planning and Budgeting (P&B). The processes involved with P&B are cost and time intensive, especially when dealing with uncertainties and budget adjustments during the planning horizon. This work builds on our previous research in which we proposed and evaluated a fuzzy approach that allows optimizing the budget interactively beyond the initial planning stage. In this research we propose an extension that handles financial stress (i.e. drastic budget cuts) occurred during the budget period. This is done by introducing fuzzy stress parameters which are used to re-distribute the budget in order to minimize the negative impact of the financial stress. The benefits and possible issues of this approach are analyzed critically using a real world case study from the Nuremberg Institute of Technology (NIT). Additionally, ongoing and future research directions are presented.

The real-time optimisation of DNO owned storage devices on the LV network for peak reduction

Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

A simple framework for assessing the trade-off between the climate impact of aviation carbon dioxide emissions and contrails for a single flight

Persistent contrails are an important climate impact of aviation which could potentially be reduced by re-routing aircraft to avoid contrailing; however this generally increases both the flight length and its corresponding CO emissions. Here, we provide a simple framework to assess the trade-off between the climate impact of CO emissions and contrails for a single flight, in terms of the absolute global warming potential and absolute global temperature potential metrics for time horizons of 20, 50 and 100 years. We use the framework to illustrate the maximum extra distance (with no altitude changes) that can be added to a flight and still reduce its overall climate impact. Small aircraft can fly up to four times further to avoid contrailing than large aircraft. The results have a strong dependence on the applied metric and time horizon. Applying a conservative estimate of the uncertainty in the contrail radiative forcing and climate efficacy leads to a factor of 20 difference in the maximum extra distance that could be flown to avoid a contrail. The impact of re-routing on other climatically-important aviation emissions could also be considered in this framework.

Infrared absorption spectra, radiative efficiencies, and global warming potentials of newly-detected halogenated compounds: CFC-113a, CFC-112 and HCFC-133a

CFC-113a (CF3CCl3), CFC-112 (CFCl2CFCl2) and HCFC-133a (CF3CH2Cl) are three newly detected molecules in the atmosphere that are almost certainly emitted as a result of human activity. It is important to characterise the possible contribution of these gases to radiative forcing of climate change and also to provide information on the CO2-equivalence of their emissions. We report new laboratory measurements of absorption cross-sections of these three compounds at a resolution of 0.01 cm−1 for two temperatures 250 K and 295 K in the spectral range of 600–1730 cm−1. These spectra are then used to calculate the radiative efficiencies and global warming potentials (GWP). The radiative efficiencies are found to be between 0.15 and 0.3 W∙m−2∙ppbv−1. The GWP for a 100 year time horizon, relative to carbon dioxide, ranges from 340 for the relatively short-lived HCFC-133a to 3840 for the longer-lived CFC-112. At current (2012) concentrations, these gases make a trivial contribution to total radiative forcing; however, the concentrations of CFC-113a and HCFC-133a are continuing to increase. The 2012 CO2-equivalent emissions, using the GWP (100), are estimated to be about 4% of the current global CO2-equivalent emissions of HFC-134a

Forecast uncertainty—ex Ante and ex Post: U.S. inflation and output growth

Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to the ex post measure as the forecast horizon shortens. There is little evidence of a link between individuals’ ex post forecast accuracy and their ex ante subjective assessments.

Effects of land management on different forms of soil carbon in olive groves in Mediterranean areas

This study analyses soil organic carbon (SOC) and hot-water extractable carbon (HWC), both measures of soil quality, under different land management: (1) conventional tillage (CT); (2) CT plus the addition of oil mill waste alperujo (A); (3) CT plus the addition of oil mill waste olive leaves (L); (4) no tillage with chipped pruned branches (NT1); and (5) no tillage with chipped pruned branches and weeds (NT2); in a typical Mediterranean agricultural area; the olive groves of Andalucía, southern Spain. SOC values in CT, A, NT1 and NT2 decreased with depth, but in NT2 the surface horizon (0-5 cm) had higher values than the other treatments, 47% more than the average values in the other three soils. In L, SOC also decreased with depth, although there was an increase of 88.5% from the first (0-10 cm) to the second horizon (10-16 cm). Total SOC stock values were very similar under A (101.9 Mg ha−1), CT (101.7 Mg ha−1), NT1 (105.8 Mg ha−1) and NT2 (111.3 Mg ha−1, if we consider the same depth of the others). However, SOC under L was significantly higher (p < 0.05) at 250.2 Mg ha−1. HWC decreased with depth in A, CT and NT1. NT2 and L followed the same pattern as the other management types but with a higher value in the surface horizon (2.3 and 4.9 mg g−1 respectively). Overall, our results indicate that application of oil mill waste olive leaves under CT (L) is a good management practice to improve SOC and reduce waste.

Predicting solar disturbance effects on navigation systems

A variety of operational systems are vulnerable to disruption by solar disturbances brought to the Earth by the solar wind. Of particular importance to navigation systems are energetic charged particles which can generate temporary malfunctions and permanent damage in satellites. Modern spacecraft technology may prove to be particularly at risk during the next maximum of the solar cycle. In addition, the associated ionospheric disturbances cause phase shifts of transionospheric and ionosphere-reflected signals, giving positioning errors and loss of signal for GPS and Loran-C positioning systems and for over-the-horizon radars. We now have sufficient understanding of the solar wind, and how it interacts with the Earth's magnetic field, to predict statistically the likely effects on operational systems over the next solar cycle. We also have a number of advanced ways of detecting and tracking these disturbances through space but we cannot, as yet, provide accurate forecasts of individual disturbances that could be used to protect satellites and to correct errors. In addition, we have recently discovered long-term changes in the Sun, which mean that the number and severity of the disturbances to operational systems are increasing.

Cluster's last stand?

On 4 June last year the first attempt to make three-dimensional measurements in space was lost when the Ariane 5 rocket veered off course and self-destructed, 39 s into its maiden flight. On board were four identical spacecraft which made up Cluster,a mission that the European Space Agency called a “cornerstone” of its Horizon 2000 scientific programme. A full description of the Cluster satellites is given in a special issue of Space Science Reviews (Escoubet et al. 1997). Their loss dealt a devastating blow to the Cluster scientists and to those working on other missions and projects planned to interact with Cluster. Many discoveries have been made during the 15 years in which Cluster progressed from an idea to the state-of-the-art satellites that were on top of Ariane 501 on 4 June. However, these discoveries invariably underline rather than undermine the importance of Cluster. Now plans to recover the unique and exciting research that was to be done using Cluster are well advanced.

Real-time factor model forecasting and the effects of instability

Factor forecasting models are shown to deliver real-time gains over autoregressive models for US real activity variables during the recent period, but are less successful for nominal variables. The gains are largely due to the Financial Crisis period, and are primarily at the shortest (one quarter ahead) horizon. Excluding the pre-Great Moderation years from the factor forecasting model estimation period (but not from the data used to extract factors) results in a marked fillip in factor model forecast accuracy, but does the same for the AR model forecasts. The relative performance of the factor models compared to the AR models is largely unaffected by whether the exercise is in real time or is pseudo out-of-sample.

Do US macroeconomic forecasters exaggerate their differences?

Application of the Bernhardt et al. (Journal of Financial Economics 2006; 80(3): 657–675) test of herding to the calendar-year annual output growth and inflation forecasts suggests forecasters tend to exaggerate their differences, except at the shortest horizon, when they tend to herd. We consider whether these types of behaviour can help to explain the puzzle that professional forecasters sometimes make point predictions and histogram forecasts which are mutually inconsistent.

Metrics for linking emissions of gases and aerosols to global precipitation changes

Recent advances in understanding have made it possible to relate global precipitation changes directly to emissions of particular gases and aerosols that influence climate. Using these advances, new indices are developed here called the Global Precipitation-change Potential for pulse (GPP_P) and sustained (GPP_S) emissions, which measure the precipitation change per unit mass of emissions. The GPP can be used as a metric to compare the effects of different emissions. This is akin to the global warming potential (GWP) and the global temperature-change potential (GTP) which are used to place emissions on a common scale. Hence the GPP provides an additional perspective of the relative or absolute effects of emissions. It is however recognised that precipitation changes are predicted to be highly variable in size and sign between different regions and this limits the usefulness of a purely global metric. The GPP_P and GPP_S formulation consists of two terms, one dependent on the surface temperature change and the other dependent on the atmospheric component of the radiative forcing. For some forcing agents, and notably for CO2, these two terms oppose each other – as the forcing and temperature perturbations have different timescales, even the sign of the absolute GPP_P and GPP_S varies with time, and the opposing terms can make values sensitive to uncertainties in input parameters. This makes the choice of CO2 as a reference gas problematic, especially for the GPP_S at time horizons less than about 60 years. In addition, few studies have presented results for the surface/atmosphere partitioning of different forcings, leading to more uncertainty in quantifying the GPP than the GWP or GTP. Values of the GPP_P and GPP_S for five long- and short-lived forcing agents (CO2, CH4, N2O, sulphate and black carbon – BC) are presented, using illustrative values of required parameters. The resulting precipitation changes are given as the change at a specific time horizon (and hence they are end-point metrics) but it is noted that the GPPS can also be interpreted as the time-integrated effect of a pulse emission. Using CO2 as a references gas, the GPP_P and GPP_S for the non-CO2 species are larger than the corresponding GTP values. For BC emissions, the atmospheric forcing is sufficiently strong that the GPP_S is opposite in sign to the GTP_S. The sensitivity of these values to a number of input parameters is explored. The GPP can also be used to evaluate the contribution of different emissions to precipitation change during or after a period of emissions. As an illustration, the precipitation changes resulting from emissions in 2008 (using the GPP_P) and emissions sustained at 2008 levels (using the GPP_S) are presented. These indicate that for periods of 20 years (after the 2008 emissions) and 50 years (for sustained emissions at 2008 levels) methane is the dominant driver of positive precipitation changes due to those emissions. For sustained emissions, the sum of the effect of the five species included here does not become positive until after 50 years, by which time the global surface temperature increase exceeds 1 K.