Information content and forecasting ability of sentiment indicators: case of real estate market

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data over 1988-2010, we test the efficacy of several sentiment measures by comparing them with other coincident economic indicators. Overall, our analysis suggests that the sentiment in real estate convey valuable information that can help predict changes in real estate returns. These findings have important implications for investment decisions, from consumers' as well as institutional investors' perspectives.

Satellite-supported flood forecasting in river networks: a real case study

Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting.

Reducing noise associated with the Monte Carlo Independent Column Approximation for weather forecasting models

The Monte Carlo Independent Column Approximation (McICA) is a flexible method for representing subgrid-scale cloud inhomogeneity in radiative transfer schemes. It does, however, introduce conditional random errors but these have been shown to have little effect on climate simulations, where spatial and temporal scales of interest are large enough for effects of noise to be averaged out. This article considers the effect of McICA noise on a numerical weather prediction (NWP) model, where the time and spatial scales of interest are much closer to those at which the errors manifest themselves; this, as we show, means that noise is more significant. We suggest methods for efficiently reducing the magnitude of McICA noise and test these methods in a global NWP version of the UK Met Office Unified Model (MetUM). The resultant errors are put into context by comparison with errors due to the widely used assumption of maximum-random-overlap of plane-parallel homogeneous cloud. For a simple implementation of the McICA scheme, forecasts of near-surface temperature are found to be worse than those obtained using the plane-parallel, maximum-random-overlap representation of clouds. However, by applying the methods suggested in this article, we can reduce noise enough to give forecasts of near-surface temperature that are an improvement on the plane-parallel maximum-random-overlap forecasts. We conclude that the McICA scheme can be used to improve the representation of clouds in NWP models, with the provision that the associated noise is sufficiently small.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

Nontraditional employment: the careers of temporary workers

This chapter focuses upon the careers of temporary workers. Temporary employment for many workers presents a route to permanent employment. Other workers, however, get trapped into temporary employment or cycle between unstable jobs and spells of unemployment. Predictors of such transitions are multiple. We selected two broad categories, namely perceived employability from the area of career research and health and well-being from the area of occupational health and well-being research. The overall conclusion is that the association between temporary employment and both perceived employability and health and well-being is inconclusive. This suggests that there are boundary conditions that may make some temporary workers successful and others not. Risk factors include dynamics related to the dual labor market, including lower job quality, lower investments on the part of employers, and negative stereotyping of temporary workers as second-class citizens. On the positive side, many temporary workers have learned to manage their careers in the sense that they invest in training and in continuous job search.

Contingencies of contingent employment: psychological contract, job insecurity and employability of contracted workers

Drawing on psychological contract literature, the present study examines the emerging contingent employment relationships, which involve the contracted workers, the employment agency and the client organization on whose premises these employees work. This sample includes eighty-eight white-collar employees working for four Portuguese agencies. The results suggest that the perceived fulfilment of client?s obligations relates positively to the perceived fulfilment of agency?s obligations and that these constructs are independent of one another. Furthermore, as expected, we have found that the perception of job insecurity relates negatively to the fulfilment of agency?s obligations. No relationship was found between employability and the perceived fulfilment of client?s obligations. The results have implications for practitioners and future research.

The impact of outward investments on parent company's employment and skill composition

This paper investigates the impact of outward foreign direct investment (FDI) by Italian multinationals on their total employment and skill composition. Specifically, by comparing data on 108 Italian manufacturing firms that became multinational (for the first time) in the period 1998–2004 with a counterfactual group of 2500 national firms that remained national in the same period, we provide descriptive and econometric evidence that the internationalisation of production activities did not reduce domestic employment in the parent companies neither for investments in developed or developing countries. As far as the skill composition is concerned, results reveal that only firms investing in Central and Eastern European countries experience some skill upgrading relative to firms that remained national.

Improving the health forecasting alert system for cold weather and heat-waves in England: a proof-of-concept using temperature-mortality relationships

Objectives In this study a prototype of a new health forecasting alert system is developed, which is aligned to the approach used in the Met Office’s (MO) National Severe Weather Warning Service (NSWWS). This is in order to improve information available to responders in the health and social care system by linking temperatures more directly to risks of mortality, and developing a system more coherent with other weather alerts. The prototype is compared to the current system in the Cold Weather and Heatwave plans via a case-study approach to verify its potential advantages and shortcomings. Method The prototype health forecasting alert system introduces an “impact vs likelihood matrix” for the health impacts of hot and cold temperatures which is similar to those used operationally for other weather hazards as part of the NSWWS. The impact axis of this matrix is based on existing epidemiological evidence, which shows an increasing relative risk of death at extremes of outdoor temperature beyond a threshold which can be identified epidemiologically. The likelihood axis is based on a probability measure associated with the temperature forecast. The new method is tested for two case studies (one during summer 2013, one during winter 2013), and compared to the performance of the current alert system. Conclusions The prototype shows some clear improvements over the current alert system. It allows for a much greater degree of flexibility, provides more detailed regional information about the health risks associated with periods of extreme temperatures, and is more coherent with other weather alerts which may make it easier for front line responders to use. It will require validation and engagement with stakeholders before it can be considered for use.

Testosterone is associated with self-employment among Australian men

Testosterone has pronounced effects on men’s physiological development and smaller, more nuanced, impacts on their economic behavior. In this study of 1199 Australian adult males, we investigate the relationship between the self-employed and their serum testosterone levels. Because prior studies have identified that testosterone is a hormone that is responsive to external factors (e.g. competition, risk-taking), we explicitly control for omitted variable bias and reverse causality by using an instrumental variable approach. We use insulin as our primary instrument to account for endogeneity between testosterone and self-employment. This is because prior research has identified a relationship between insulin and testosterone but not between insulin and self-employment. Our results show that there is a positive association between total testosterone and self-employment. Robustness checks using bioavailable testosterone and another similar instrument (daily alcohol consumption) confirm this positive finding.

Knowledge and perception of Ghanaian cocoa farmers on mirid control and their willingness to use forecasting systems

Annual losses of cocoa in Ghana to mirids are significant. Therefore, accurate timing of insecticide application is critical to enhance yields. However, cocoa farmers often lack information on the expected mirid population for each season to enable them to optimise pesticide use. This study assessed farmers’ knowledge and perceptions of mirid control and their willingness to use forecasting systems informing them of expected mirid peaks and time of application of pesticides. A total of 280 farmers were interviewed in the Eastern and Ashanti regions of Ghana with a structured open and closed ended questionnaire. Most farmers (87%) considered mirids as the most important insect pest on cocoa with 47% of them attributing 30-40% annual crop loss to mirid damage. There was wide variation in the timing of insecticide application as a result of farmers using different sources of information to guide the start of application. The majority of farmers (56%) do not have access to information on the type, frequency and timing of insecticides to use. However, respondents who are members of farmer groups had better access to such information. Extension officers were the preferred channel for information transfer to farmers with 72% of farmers preferring them to other available methods of communication. Almost all the respondents (99%) saw the need for a comprehensive forecasting system to help farmers manage cocoa mirids. The importance of accurate timing for mirid control based on forecasted information to farmer groups and extension officers was discussed.

Forecasting elections

In this paper we assess opinion polls, prediction markets, expert opinion and statistical modelling over a large number of US elections in order to determine which perform better in terms of forecasting outcomes. In line with existing literature, we bias-correct opinion polls. We consider accuracy, bias and precision over different time horizons before an election, and we conclude that prediction markets appear to provide the most precise forecasts and are similar in terms of bias to opinion polls. We find that our statistical model struggles to provide competitive forecasts, while expert opinion appears to be of value. Finally we note that the forecast horizon matters; whereas prediction market forecasts tend to improve the nearer an election is, opinion polls appear to perform worse, while expert opinion performs consistently throughout. We thus contribute to the growing literature comparing election forecasts of polls and prediction markets.

The pitfalls of ecological forecasting

Ecological forecasting is difficult but essential, because reactive management results in corrective actions that are often too late to avert significant environmental damage. Here, we appraise different forecasting methods with a particular focus on the modelling of species populations. We show how simple extrapolation of current trends in state is often inadequate because environmental drivers change in intensity over time and new drivers emerge. However, statistical models, incorporating relationships with drivers, simply offset the prediction problem, requiring us to forecast how the drivers will themselves change over time. Some authors approach this problem by focusing in detail on a single driver, whilst others use ‘storyline’ scenarios, which consider projected changes in a wide range of different drivers. We explain why both approaches are problematic and identify a compromise to model key drivers and interactions along with possible response options to help inform environmental management. We also highlight the crucial role of validation of forecasts using independent data. Although these issues are relevant for all types of ecological forecasting, we provide examples based on forecasts for populations of UK butterflies. We show how a high goodness-of-fit for models used to calibrate data is not sufficient for good forecasting. Long-term biological recording schemes rather than experiments will often provide data for ecological forecasting and validation because these schemes allow capture of landscape-scale land-use effects and their interactions with other drivers.

Do jumps matter for volatility forecasting? Evidence from energy markets

This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high-frequency data on four prominent energy markets, we perform a model-free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in-sample and out-of-sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions

Self-concept clarity and compulsive Internet use: the role of preference for virtual interactions and employment status in British and North-American samples

Background and Aims Compulsive Internet Use (CIU) describes a maladaptive relationship with the Internet characterised by loss of control and conflict. Although also affecting adults, most studies use teenage samples, and theoretical development on risk factors is scarce. According to Davis (2001), the social connectivity function of the Internet is key in identifying traits associated with CIU. Since Self-Concept Clarity (SCC) is strongly related to social anxiety, and virtual interactions allow “self-edition”, we hypothesized that individuals low in SCC could choose virtual interactions as safer alternative to satisfy their social needs. This could in turn increase the risk of CIU. Building on a previous study, we also expected CIU to be more harmful in the unemployed. Methods We collected samples from the UK (N = 532) and US (N = 502) with equal distribution of employed and unemployed individuals. We ran Measurement Invariance tests to confirm that the constructs were equivalent across countries. Subsequently, we conducted mediation and moderation analysis to test our hypothesis with Multigroup Confirmatory Factor Analysis. Results Measurement Invariance was confirmed. The relationship between SCC and CIU was partially mediated by preference of virtual interactions in both countries. This preference was significantly related to lower social support. Short term unemployment seemed to accentuate the negative impact of CIU on life satisfaction in both countries, although only marginally significantly in the US. The unemployed reported significantly lower levels of life satisfaction. Conclusion We demonstrated that SCC is a key vulnerability factor to CIU in adults, and confirmed the additional risks for the unemployed.