Abstract:Relationships between a number of measures of household energy use behavior are estimated using a unique dataset of approximately 5,000 households in ten EU countries and Norway. Knowledge of energy consumption and energy-efficient technology options is found to be associated with household use of energy conservation practices, but not with adoption of energy-efficient technologies. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy savings for environmental reasons, while households with a high share of elderly members place more importance on financial savings. Education also influences attitudes towards energy conservation. Low education households indicate they primarily save electricity for financial reasons, while high education households indicated they are motivated by environmental concerns. Significant country differences also exist. Households in transitioning Eastern European countries generally have lower levels of energy-efficient technology adoption, but strong propensities to employ energyconservation practices, and place less importance on saving electricity for environmental reasons compared to households in Western European countries. EU policies to promote residential adoption of energy-efficient technologies and energy conservation practices must be sensitive to both cross-country and intra-county variations in household energy use behavior.

As residential Internet access in the United States shifts toward high-speed connections, a gap has emerged in rural high-speed access relative to urban high-speed access. Potential causes of this high-speed ``digital divide'' include rural—urban differences in people, place, and infrastructure. In this article, Current Population Survey data from 2000, 2001, and 2003 are combined with novel infrastructure data to determine the relative roles of these factors in the rural—urban divide. Bootstrapped decompositions of logit model results demonstrate that rural—urban differences in income and in network externalities, but not in infrastructure, are the dominant causes of the high-speed gap.

This study examines the impact that participation in the Food Stamp Program has on household food insecurity using data from the Panel Survey of Income Dynamics. Two strategies are used to identify the causal effect of the program. First, endogenous treatment effect models are estimated using state‐level errors in payments of benefits as instruments. Additionally the impact of losing benefits due to a government decision on the food insecurity of program participants is examined. The paper finds that program participation lowers food insecurity by at least 18%.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractThe EU appliance energy consumption labeling scheme is a key component of efforts to increase the diffusion of energy-efficient household appliances. In this paper, the determinants of consumer knowledge of the energy label for household appliances and the choice of class-A energy-efficient appliances are jointly estimated using data from a large survey of more than 20,000 German households. The results for five major appliances suggest that lack of knowledge of the energy label can generate considerable bias in both estimates of rates of uptake of class-A appliances and in estimates of the underlying determinants of choice of class-A appliance. Simulations of the choice to purchase a class-A appliance, given knowledge of the labeling framework, reveal that residence characteristics and, in several cases, regional electricity prices strongly increase the propensity to purchase a class-A appliance, but socio-economic characteristics have surprisingly little impact on appliance energy-class choice.

A consistent gap exists between home Internet use in metropolitan areas and in non-metropolitan areas in the U.S. This digital divide may stem from technology differences in home Internet connectivity. Alternatively, differences in education, income, and other household attributes may explain differences in metropolitan and non-metropolitan area home Internet access. Effective programs to reduce the metropolitan-non-metropolitan digital divide must be based on an understanding of the relative roles that technology and household characteristics play in determining differential Internet usage. The household Internet adoption decision is modeled using a logit estimation approach with data from the 2001 U.S. Current Population Survey Internet and Computer Use Supplement. A decomposition of separate metropolitan and non-metropolitan area estimates shows that differences in household attributes, particularly education and income, account for 63 percent of the current metropolitan-non-metropolitan digital divide. The result raises significant doubts that policies which focus solely on infrastructure and technology access will mitigate the current metropolitan-non-metropolitan digital divide. Copyright 2003 Gatton College of Business and Economics, University of Kentucky..