The Asymmetric Effects of Changes in Price and Income on Energy and Oil Demand

This paper estimates the effects on energy and oil demand of changes in income and oil prices, for 96 of the world's largest countries, in per-capita terms. We examine three important issues: the asymmetric effects on demand of increases and decreases in oil prices; the asymmetric effects on demand of increases and decreases in income; and the different speeds of demand adjustment to changes in price and in income. Its main conclusions are the following: (1) OECD demand responds much more to increases in oil prices than to decreases; ignoring this asymmetric price response will bias downward the estimated income elasticity; (2) demand's response to income decreases in many non-OECD countries is not necessarily symmetric to its response to income increases; ignoring this asymmetric income response will bias the estimated income elasticity; (3) the speed of demand adjustment is faster to changes in income than to changes in price; ignoring this difference will bias upward the estimated response to income changes. Using correctly specified equations for energy and oil demand, the long-run elasticity for increases in income is about 0.55 for OECD energy and oil, and 1.0 or higher for Non-OECD Oil Exporters, Income Growers and perhaps all Non-OECD countries. These income elasticity estimates are significantly higher than current estimates used by the US Department of Energy. Our estimates for the OECD countries are also higher than those estimated recently by Schmalensee-Stoker-Judson (1998) and Holtz-Eakin and Selden (1995), who ignore the asymmetric effects of prices on demand. Higher income elasticities, of course, will increase projections of energy and oil demand, and of carbon dioxide emissions.ENERGY DEMAND; OIL DEMAND; ASYMMETRY; IRREVERSIBILITY; INCOME ELASTICITY

Income's Effect On Car and Vehicle Ownership, Worldwide: 1960-2015

Ownership, growth projection, cars, vehicles, global economy, income levels

How Likely is the Consensus Projection of Oil Production Doubling in the Persian Gulf?

We examine a consensus in most recent long-term projections of the world oil market that OPEC oil capacity and production will increase rapidly over the next two decades to unprecedented levels, more than doubling in the Persian Gulf by 2020. Such projections are not based on behavioral analysis of Gulf countries' decisions; they are merely the calculated residual demand for OPEC oil, the difference between projected world oil demand and non-OPEC supply. We focus especially on the detailed projections of the International Energy Outlook 2001 (IEO-2001) by the Energy Information Administration within the U.S. Department of Energy (DOE). Their projections exhibit only minimal price-responsiveness, which leads to conclusion that the underlying model is internally inconsistent. If it accurately represents the price-responsiveness of world oil demand and non-OPEC supply, then both the Reference Case and the High Price Case project future oil prices that are far too low - because these cases rely on supply behavior by Gulf producers that is not in their own self-interest. The IEO-2001 projections of world oil prices could be reasonable, but only if world oil demand and/or non-OPEC supply are much more price-responsive than are represented in their numerical projections. Then, using an updated version of the model from Gately (1995), we demonstrate that the effect of greater priceresponsiveness for world oil demand and non-OPEC supply is to make faster output growth - not higher prices - the reliable path to higher OPEC revenue. We conclude with comments about the plausibility of consensus projections. Oil price in the range $20 to$25 (1999 $/barrel) is plausible, but it requires substantial growth in non-OPEC supply and much greater priceresponsiveness than is assumed in IEO-2001. Projections that Persian Gulf capacity and output will double by 2020, however, seem very implausible. It requires not only that Gulf producers experience high price-responsiveness to any slowdown in their output growth, but also that aggressive output growth must make them significantly better off than more modest expansion efforts. However, it was shown in Gately (1995) that discounted export revenue for the Gulf countries is relatively insensitive over a fairly wide range of output-growth strategies: modest output growth will do just about as well as aggressive growth.OPEC OIL OUTPUT; OPEC CAPACITY; OIL PRICE PROJECTIONS

Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships

Emissions of CO2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO2 emitted by US road transport at a resolution of 1 km annually for 1980-2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO2 emissions and population density at broad spatial/temporal scales, with total on-road CO2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. We make use of DARTE's bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national- or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Given cities' dual importance as sources of CO2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales.https://doi.org/10.1073/pnas.1421723112Published versio

The ‘oldest tricks in the book’ don’t work! Reports of burglary by DUMA detainees in Western Australia

Explores the methods and motivations of those actively involved in committing burglaries. Foreword Research investigating the methods and motivations of burglars has typically focused on incarcerated offenders. The Australian Institute of Criminology’s Drug Use Monitoring in Australia (DUMA) program provided an opportunity for the authors to explore the methods and motivations of those actively involved in committing burglaries, whether or not they had actually been caught or detained for that offence. The findings support Routine Activity Theory, indicating that offenders consider a number of factors in determining whether a property will be targeted for a break and enter offence. As might be expected, opportunistic burglars choose easy to access properties, stay a minimum length of time and take goods that can be disposed of easily. It was concluded that simple prevention strategies could minimise the risk of becoming a victim of opportunistic burglary, which also has implications for law enforcement, the security industry and insurance agencies

Building Intellectual Capital in Incubated Technology Firms

Purpose: The value of relational capital generated by entrepreneurs with their internal and external environment (Hormiga, Batista-Canino and Sanchez-Medina, 2011), provides considerable resources when properly leveraged. It is particularly important in environments such as the high tech sector of incomplete information and weak economic markets such as new products, markets or technologies (Davidsson, and Honig, 2003). The paper examines how incubated technology entrepreneurs build relational capital for a new venture formation in the social context of a Higher Education Institution. Design/methodology/approach: Our study took a qualitative approach based on content analysis of business plans and in-depth interviews with twenty-five technology entrepreneurs on an incubation programme – South East Enterprise Platform Programme - for technology graduates in the South East of Ireland. Findings: Our study found that technology entrepreneurs during new venture formation engaged in four types of relational capital activities, namely, development of networks and contacts, relationship building, accessing and leveraging knowledge experts and members of associations. Practical Implications: Incubator programmes need to actively support social building activities of technology entrepreneurs. HEI knowledge assets and networks are critical elements in supporting incubator technology entrepreneurs. Originality/Value: Our study identified four types of relational capital building. We also found using Evans Jones (1995) categorization of technology entrepreneurs that users, producers, opportunists and non–technical entrepreneurs engaged in client focused relational capital building, whereas researcher types networked with service providers and displayed arms length relational capital building styles

Are Intervention-Design Characteristics More Predictive than Baseline Participant Characteristics on Participant Attendance to a Paediatric, Community Weight Management Programme?

BACKGROUND: Approximately 50% of participants complete a paediatric weight management programme, yet the predictors of attendance and dropout are inconsistent. This study investigates subject and intervention-design characteristics associated with attendance at a group based, family weight management programme. SETTING AND SUBJECTS: Secondary data analysis of 2948 subjects (Age 10.4±2.8 years, BMI 26.0±5.7kg/m2, Standardised BMI (BMI SDS) 2.48±0.87, White 70.3%) from 244 MoreLife (UK) programmes. Subjects attend weekly for 10-12 weeks, sessions last 2-3 hours. Sessions include lifestyle guidance and physical activity. METHOD: Subject characteristics (demographics, psychological (body satisfaction & self-esteem) and sedentary behaviour) were gathered at first contact and BMI SDS was noted weekly. Intervention-design characteristics were recorded (year, length (weeks), group size, age segregation and day of session). Attendance was calculated as total number of sessions attended (%). Multivariate linear regression examined predictors of attendance and multiple imputation countered missing data. RESULTS: Average attendance was 59.4%±29.3%. Baseline subject characteristics were ‘poor’ predictors of attendance. Intervention year, group size and day of session significantly predicted attendance (Tables 1 & 2). Yet, the most predictive marker of attendance was a change in BMI SDS during the programme (B = -0.38, 95% CI = -0.43 - -0.33). CONCLUSION: A reduction in BMI was seen to predict greater attendance. However, baseline subject characteristics were weakly associated with attendance, refuting past findings. Dominant intervention characteristics (large groups, weekend sessions and recent delivery) predicted lower attendance. Future programmes may be better informed

Amphetamine users and crime in Western Australia, 1999–2009

This current study aims to examine the relationship between amphetamine use and crime among police detainees in Western Australia. Further, the study provides a brief profile of detainee amphetamine users and compares this with the profile of a non-user. Amphetamines have been increasingly available on Australian drug markets since the early 1990s (National Drug Research Institute 2007). Clandestine laboratory detections increased from 50 in 1996 to 250 in 2002 (Ministerial Council on Drugs Strategy 2004), although use decreased slightly in the general population between 2004 (3.2%) and 2007 (2.3%) (Australian Institute of Health and Welfare 2008). There has also been an increase in the amount of high-grade amphetamine detected by Customs and the Australian Federal Police (AFP). Amphetamine use has been associated with psychological, physical and social harm, criminal behaviour and violence (Dyer & Cruickshank 2005; Lynch, Kemp, Krenske, Conroy & Webster 2003; Wickes 1993). The Drug Use Monitoring in Australia (DUMA) project has collected data since 1999. This current study aims to examine the relationship between amphetamine use and crime among police detainees in Western Australia. Further, the study provides a brief profile of detainee amphetamine users and compares this with the profile of a non-user

Radar signal categorization using a neural network

Neural networks were used to analyze a complex simulated radar environment which contains noisy radar pulses generated by many different emitters. The neural network used is an energy minimizing network (the BSB model) which forms energy minima - attractors in the network dynamical system - based on learned input data. The system first determines how many emitters are present (the deinterleaving problem). Pulses from individual simulated emitters give rise to separate stable attractors in the network. Once individual emitters are characterized, it is possible to make tentative identifications of them based on their observed parameters. As a test of this idea, a neural network was used to form a small data base that potentially could make emitter identifications