12,949 research outputs found

    On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?

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    Includes: On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?:COMMENT, by Thomas A. Hirschl; On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?: REPLY, by Monica Fisher. Research shows people are more likely to be poor in rural versus urban America. Does this phenomenon partly reflect that people who choose rural residence have unmeasured attributes related to human impoverishment? To address this question, two models are estimated using Panel Study of Income Dynamics data. A single equation Probit model of individual poverty replicates the well-documented finding of higher poverty risk in rural places. However, an instrumental variables approach, accounting for correlation between rural residence and the poverty equation error term, finds no measured effect of rural location on poverty. Results suggest failure to correct for endogeneity or omitted variable bias may overestimate the "rural effect."endogeneity, instrumental variables, omitted variable bias, poverty, rural, Food Security and Poverty,

    The determination of velocity fluctuations in shear flows by means of PTV

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    The present study considers the effects of some parameters in image acquisition and analysis procedures in connection with the use of the Particle Tracking Velocimetry (PTV) technique. The interest is focused towards flow fields with large velocity gradients as shear flows; in the paper, velocity measurements by PTV are performed in a turbulent channel flow upstream and downstream of a backward facing step at low Reynolds numbers. This is a flow field largely investigated in the past with available numerical and experimental to make comparison with. Among the possible parameters to be chosen in particle image acquisition and analysis, the following are considered - the concentration of seeding particles in the imaged region; - the spatial resolution of the image acquisition system; - the parameters used in the image analysis algorithm

    Job Developer Types, Placement Practices and Outcomes Technical Report

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    Despite numerous employment initiatives, people with disabilities are significantly more likely to experience unemployment and consequently, reduced economic and social well-being and a dminished quality of life than their non disabled peers. In a recent national survey of employers, less than 14% of companies indicated that they actively recruit jobseekers with disabilities. Thus, the role of the job development professional is pivotal to helping job seekers with disabilities to find, secure and maintain employment. This research report examined the attitudes and beliefs of job development processionals articulated in a previous technical report by TransCen, Inc. and looked to further explore the relationship between the types, other personal characteristics and placement outcomes of the various job developer types

    Traces and Extensions of Bounded Divergence-Measure Fields on Rough Open Sets

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    We prove that an open set ΩRn\Omega \subset \mathbb{R}^n can be approximated by smooth sets of uniformly bounded perimeter from the interior if and only if the open set Ω\Omega satisfies \begin{align*} &\qquad \qquad\qquad\qquad\qquad\qquad\qquad \mathscr{H}^{n-1}(\partial \Omega \setminus \Omega^0)<\infty, \qquad &&\quad\qquad\qquad \qquad\qquad (*) \end{align*} where Ω0\Omega^0 is the measure-theoretic exterior of Ω\Omega. Furthermore, we show that condition (*) implies that the open set Ω\Omega is an extension domain for bounded divergence-measure fields, which improves the previous results that require a strong condition that Hn1(Ω)<\mathscr{H}^{n-1}(\partial \Omega)<\infty. As an application, we establish a Gauss-Green formula up to the boundary on any open set Ω\Omega satisfying condition (*) for bounded divergence-measure fields, for which the corresponding normal trace is shown to be a bounded function concentrated on ΩΩ0\partial \Omega \setminus \Omega^0. This new formula does not require the set of integration to be compactly contained in the domain where the vector field is defined. In addition, we also analyze the solvability of the divergence equation on a rough domain with prescribed trace on the boundary, as well as the extension domains for bounded BVBV functions.Comment: 29 page

    DO TROPICAL FORESTS PROVIDE A SAFETY NET? INCOME SHOCKS AND FOREST EXTRACTION IN MALAWI

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    We use seasonal household data on income shocks and forest extraction to study how households in Malawi use forests to cope with income shortfalls. In particular, we study household response to receipt of a positive income shock delivered in the form of a technology assistance package. We estimate a random-effects model of forest extraction to examine whether household forest use is responsive to income shocks received in a prior period. We also measure the extent to which households subsequently save out of transitory income. Findings indicate that forest extraction by asset-poor households was more responsive to income shocks than forest extraction by better-off households. Findings also suggest households save out of transitory income, and in the process accumulate physical assets that may reduce their dependence on forests for weathering subsequent income shocks. Results show how policies aimed at poverty alleviation among those living adjacent to tropical forests can also alleviate forest pressure.Resource /Energy Economics and Policy,

    DOES ECONOMIC VULNERABILITY DEPEND ON PLACE OF RESIDENCE? ASSET POVERTY ACROSS THE RURAL-URBAN CONTINUUM

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    This paper uses Panel Study of Income Dynamics data for 1989, 1994, and 1999 to examine why some U.S. households are asset poor; that is, why households have insufficient resources to invest in their future or to sustain household members at a basic level during times of economic disruption. The study contributes to an improved understanding of asset poverty's correlates by examining the influence of place of residence; the extant literature has focused on individual-level explanations. We estimate a random-effects logistic model of the probability that an individual is asset poor at a given point in time as a function of household-level (e.g. age, gender, race of the household head and family structure) and place-level (regional and rural-urban continuum) variables. The central finding of the paper is that place of residence is an important determinant of asset poverty, above and beyond the influence of household characteristics. We find that living in a central metropolitan county and in a nonmetropolitan area is associated with a higher risk of being asset poor, all else being equal. Implications for future research are discussed.Food Security and Poverty,
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