Predicting early data revisions to US GDP and the effects of releases on equity markets

The effects of data uncertainty on real-time decision-making can be reduced by predicting early revisions to US GDP growth. We show that survey forecasts efficiently anticipate the first-revised estimate of GDP, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the second-revised estimate. We consider the implications of these findings for analyses of the impact of surprises in GDP revision announcements on equity markets, and for analyses of the impact of anticipated future revisions on announcement-day returns.

International films and international markets: the globalisation of Hollywood entertainment, c.1921-1951

The international appeal of Hollywood films through the twentieth century has been a subject of interest to economic and film historians alike. This paper employs some of the methods of the economic historian to evaluate key arguments within the film history literature explaining the global success of American films. Through careful analysis of both existing and newly constructed data sets, the paper examines the extent to which Hollywood's foreign earnings were affected by: film production costs; the extent of global distribution networks; and also the international orientation of the films themselves. The paper finds that these factors influenced foreign earnings in quite distinct ways, and that their relative importance changed over time. The evidence presented here suggests a degree of interaction between the production and distribution arms of the major US film companies in their pursuit of foreign markets that would benefit from further archival-based investigation.

Bio-fabrication and physiological self-release of tissue equivalents using smart peptide amphiphile templates

In this study we applied a smart biomaterial formed from a self-assembling, multi-functional synthetic peptide amphiphile (PA) to coat substrates with various surface chemistries. The combination of PA coating and alignment-inducing functionalised substrates provided a template to instruct human corneal stromal fibroblasts to adhere, become aligned and then bio-fabricate a highlyordered, multi-layered, three-dimensional tissue by depositing an aligned, native-like extracellular matrix. The newly-formed corneal tissue equivalent was subsequently able to eliminate the adhesive properties of the template and govern its own complete release via the action of endogenous proteases. Tissues recovered through this method were structurally stable, easily handled, and carrier-free. Furthermore, topographical and mechanical analysis by atomic force microscopy showed that tissue equivalents formed on the alignment-inducing PA template had highly-ordered, compact collagen deposition, with a two-fold higher elastic modulus compared to the less compact tissues produced on the non-alignment template, the PA-coated glass. We suggest that this technology represents a new paradigm in tissue engineering and regenerative medicine, whereby all processes for the biofabrication and subsequent self-release of natural, bioprosthetic human tissues depend solely on simple templatetissue feedback interactions.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

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

Non-competitive markets

Among all the paradigms in economic theory, the theoretical predictions of oligopoly were the first to be examined in the laboratory. In this chapter, instead of surveying all the experiments with few sellers, we adopt a narrower definition of the term “oligopoly”, and focus on the experiments that were directly inspired by the basic oligopolistic models of Cournot, Bertrand, Hotelling, Stackelberg, and some extensions. Most of the experiments we consider in this chapter have been run in the last three decades. This literature can be considered as a new wave of experimental works aiming at representing basic oligopolistic markets and testing their properties. The chapter is divided into independent sections referring to different parts of the oligopolistic theory, including both monopoly as well as a number of extensions of the basic models, which have been chosen with the aim of providing a representative list of the relevant experimental findings.

Gender and the business cycle: an analysis of labour markets in the US and UK

Starting from an improved understanding of the relationship between gender labour market stocks and the business cycle, we analyse the contributing role of flows in the US and UK. Focusing on the post 2008 recession period, the subsequent greater rise in male unemployment can mostly be explained by a less cyclical response of flows between employment and unemployment for women, especially the entry into unemployment. Across gender and country, the inactivity rate is generally not sensitive to the state of the economy. However, a flows based analysis reveals a greater importance of the participation margin over the cycle. Changes in the rates of flow between unemployment and inactivity can each account for around 0.8-1.1 percentage points of the rise in US male and female unemployment rates during the latest downturn. For the UK, although the participation flow to unemployment similarly contributed to the increase of the female unemployment rate, this was not the case for men. The countercyclical flow rate from inactivity to employment was also more significant for women, especially in the US, where it accounted for approximately all of the fall in employment, compared with only 40% for men.

The Birmingham Urban Climate Laboratory: an open meteorological test bed and challenges of the smart city

Existing urban meteorological networks have an important role to play as test beds for inexpensive and more sustainable measurement techniques that are now becoming possible in our increasingly smart cities. The Birmingham Urban Climate Laboratory (BUCL) is a near-real-time, high-resolution urban meteorological network (UMN) of automatic weather stations and inexpensive, nonstandard air temperature sensors. The network has recently been implemented with an initial focus on monitoring urban heat, infrastructure, and health applications. A number of UMNs exist worldwide; however, BUCL is novel in its density, the low-cost nature of the sensors, and the use of proprietary Wi-Fi networks. This paper provides an overview of the logistical aspects of implementing a UMN test bed at such a density, including selecting appropriate urban sites; testing and calibrating low-cost, nonstandard equipment; implementing strict quality-assurance/quality-control mechanisms (including metadata); and utilizing preexisting Wi-Fi networks to transmit data. Also included are visualizations of data collected by the network, including data from the July 2013 U.K. heatwave as well as highlighting potential applications. The paper is an open invitation to use the facility as a test bed for evaluating models and/or other nonstandard observation techniques such as those generated via crowdsourcing techniques.