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This study investigates how the structural mix of USA regional economies affects their volatility of economic growth. Four exogenous sectors are chosen for this investigation: Federal Government, construction, manufacturing, and tourism. Perhaps unsurprisingly, evidence suggests that a larger share of Federal Government employment in an economy reduces the variability of overall employment growth, while a larger share of construction activity elevates it. More telling is a finding that, recently, manufacturing has not contributed as much to such variability, and that a larger tourism presence increases it. The increasing integration of technology in tourism offers significant opportunities for a network approach and innovation in regional development.

The Characterization of the Weatherization Assistance Program (WAP) Network was designed to describe the national network of State and local agencies that provide WAP services to qualifying low-income households. The objective of this study was to profile the current WAP network. To achieve the objective, two national surveys were conducted: one survey collected data from 49 State WAP agencies (including the coterminous 48 States and the District of Columbia), and the second survey collected data from 920 (or 81 percent) of the local WAP agencies.

The Energy Policy Socioeconomic Impact Model (EPSIM) is an econometric simulation model that runs on IBM-compatible personal computers. It can be used to assess the economic impact of energy policies and programs, such as utility rate designs and demand-side management programs, on various population groups, such as minority and low-income households. The econometric submodels that constitute the internal structure of EPSIM are described in detail.

Electricity demand has consistently exceeded available supply in India. While the electricity deficit varies across states, nationally it was estimated to be of the order of 12percent on peak and 11percent for electricity during 2008-09. This paper explores a demand-side focused potential for energy efficiency improvement to eliminate the electricity deficit compared to a business as usual (BAU) supply-side focused scenario. The limited availability of finance and other legal and administrative barriers have constrained the construction of new power plant capacity in India. As a result, under the BAU scenario, India continues to face an electricity deficit beyond the end of the Twelfth Five Year Plan. The demand-side cost-effective potential achieved through replacement of new electricity-using products, however, is large enough to eliminate the deficit as early as 2013 and subsequently reduce the future construction of power plants and thus reduce air pollutant emissions. Moreover, energy efficiency improvements cost a fraction of the cost for new supply and can lead to a substantial increase in India's economic output or gross domestic product (GDP). Eliminating the deficit permits businesses that have experienced electricity cutbacks to restore production. We estimate the size of the cumulative production increase in terms of the contribution to GDP at a $505 billion between 2009 and 2017, the end of India's Twelfth Five Year Plan, which may be compared with India's 2007-08 GDP of $911 billion. The economic output is influenced by the size of the electricity savings and rate of penetration of energy efficient technologies, and that of self-generation equipment and inverters used by businesses faced with electricity cuts. Generation and inverters are estimated to service 23percent of these customers in 2009, which increase to 48percent by 2020. The reduction in the construction and operation of new power plants reduces the cumulative CO2 emissions by 65 Mt, and those of sulfur dioxide and nitrogen oxides by 0.4 Mt each, while also reducing India's imports of coal and natural gas. By 2020, the cumulative GDP benefit increases to $608 billion, the CO2 savings expand to 333 Mt and SO2 and NOx to 2.1 Mt.

This paper presents a methodology for modeling residential appliance uptake as a function of root macroeconomic drivers. The analysis concentrates on four major energy end uses in the residential sector: refrigerators, washing machines, televisions and air conditioners. The model employs linear regression analysis to parameterize appliance ownership in terms of household income, urbanization and electrification rates according to a standard binary choice (logistic) function. The underlying household appliance ownership data are gathered from a variety of sources including energy consumption and more general standard of living surveys. These data span a wide range of countries, including many developing countries for which appliance ownership is currently low, but likely to grow significantly over the next decades as a result of economic development. The result is a 'global' parameterization of appliance ownership rates as a function of widely available macroeconomic variables for the four appliances studied, which provides a reliable basis for interpolation where data are not available, and forecasting of ownership rates on a global scale. The main value of this method is to form the foundation of bottom-up energy demand forecasts, project energy-related greenhouse gas emissions, and allow for the construction of detailed emissions mitigation scenarios.

In July 1986, the US Department of Energy (DOE) awarded competitive grants to five states to conduct pilot projects to establish partnerships and use resource leveraging to stimulate support for low-income residential energy retrofits. The projects were conducted under DOE's Partnerships in Low-Income Residential Retrofit (PILIRR) Program. These projects have been monitored and analyzed through a concurrent process evaluation conducted by the Pacific Northwest Laboratory (PNL). This study reports the findings of that evaluation. The overriding goal of the PILIRR Program was to determine whether the states could stimulate support for low-income residential energy improvements from non-federal sources. The goal for the process evaluation was to conduct an assessment of the processes used by the states and the extent to which they successfully established partnerships and leveraged resources. Five states were selected to participate in the program: Florida, Iowa, Kentucky, Oklahoma and Washington. Each state proposed a different approach to promote non-federal support for low-income residential weatherization. Three of the five states--Florida, Iowa, and Washington--established partnerships that led to retrofits during the monitoring period (October 1986--October 1988). Kentucky established its partnership during the monitoring period, but did not accomplish its retrofits until after monitoring was complete. Oklahoma completed development ofmore » its marketing program and had begun marketing efforts by the end of the monitoring period. 16 refs., 7 figs., 1 tab.« less

Historical estimates of productivity growth in India's aluminum sector vary from indicating an improvement to a decline in the sector's productivity. The variance may be traced to the time period of study, source of data for analysis, and type of indices and econometric specifications used for reporting productivity growth. An analysis shows that in the twenty year period, 1973 to 1993, productivity in the aluminum sector declined slightly by 0.2%. An econometric analysis reveals that technical progress in India's aluminum sector has been biased towards the use of energy, while it has been labor saving. The decline in productivity was mainly driven by a decline in the 1970s when capacity utilization was low and the energy crisis hit India and the world. From the early 1980s on productivity recuperated. The authors examine the current changes in structure and energy efficiency in the sector. Their analysis shows that the Indian aluminum sector has high potential to move towards world-best technology, which will result in fewer carbon emissions and more efficient energy use. Substantial energy savings and carbon reduction options exist.

In the last decade, many malaria-endemic countries, like Zambia, have achieved significant reductions in malaria incidence among children <5 years old but face ongoing challenges in achieving similar progress against malaria in older age groups. In parts of Zambia, changing climatic and environmental factors are among those suspectedly behind high malaria incidence. Changes and variations in these factors potentially interfere with intervention program effectiveness and alter the distribution and incidence patterns of malaria differentially between young children and the rest of the population. We used parametric and non-parametric statistics to model the effects of climatic and socio-demographic variables on age-specific malaria incidence vis-à-vis control interventions. Linear regressions, mixed models, and Mann-Kendall tests were implemented to explore trends, changes in trends, and regress malaria incidence against environmental and intervention variables. Our study shows that while climate parameters affect the whole population, their impacts are felt most by people aged ≥5 years. Climate variables influenced malaria substantially more than mosquito nets and indoor residual spraying interventions. We establish that climate parameters negatively impact malaria control efforts by exacerbating the transmission conditions via more conducive temperature and rainfall environments, which are augmented by cultural and socioeconomic exposure mechanisms. We argue that an intensified communications and education intervention strategy for behavioural change specifically targeted at ≥5 aged population where incidence rates are increasing, is urgently required and call for further malaria stratification among the ≥5 age groups in the routine collection, analysis and reporting of malaria mortality and incidence data.