53,582 research outputs found

    Redemption from the Inside-Out: The Power of Faith-Based Programming

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    Prisons are tense, cheerless, and often degrading places in which all inmates struggle to maintain their equilibrium despite violence, exploitation, lack of privacy, stringent limitations on family and community contacts, and a paucity of opportunities for meaningful education, work, or other productive activities. As a general matter, prisoners come to see prison as their home and try to make the most of the limited resources available in prison; they establish daily routines that allow them to find meaning and purpose in their prison lives, lives that might otherwise seem empty and hopeless. The resilience shown by prisoners should not be construed as an argument for more or longer prison sentences or for more punitive regimes of confinement, but rather is a reminder that human beings can find meaning in adversity. Prisons are meant to be settings of adversity but should strive to accommodate the human needs of their inhabitants and to promote constructive changes in behavior. Here, there are programmatic offerings that may provide prisoners with the hope, skills, and empowerment necessary to overcome barriers to achievement and success as human beings in any social context. A current line of inquiry has focused on faith based prison programs and the potential benefits that a deepened spiritual life might have on coping with the doing time experience, changing old lifestyles, and reducing the likelihood of people returning to prison. These points will be explored throughout this chapter

    To Aggregate, Pool, or Neither: Testing the Rational Expectations Hypothesis Using Survey Data

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    It is well known that even if all forecasters are rational, estimated coefficients in unbiasedness regressions using consensus forecasts are inconsistent because forecasters have private information. However, if all forecasters face a common realization, pooled estimators are also inconsistent. In contrast, we show that when predictions and realizations are integrated and cointegrated, micro-homogeneity ensures that consensus and pooled estimators are consistent. Therefore, contrary to claims in the literature, in the absence of micro-homogeneity, pooling is not a solution to the aggregation problem. We reject micro-homogeneity for a number of forecasts from the Survey of Professional Forecasters. Therefore, for these variables unbiasedness can only be tested at the individual level.Rational Expectations, Micro-homogeneity, Heterogeneity Bias, Aggregation Bias, Survey Forecasts

    Testing the Rational Expectations Hypothesis using Survey Data

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    Because of the importance of inflation expectations, Lloyd B. Thomas Jr. (Fall 1999, p. 125-44) reexamines "the evidence on the nature and performance of various measures of expected inflation, with special attention given to the issue of rationality" (p. 126). Thomas tests the unbiasedness hypothesis using the Livingston and Michigan survey forecasts for the 1960 to 1997 time period and is unable to reject the null hypothesis of unbiasedness. Unfortunately, two types of problems due to aggregation plague such tests: private information bias and micro-heterogeneity bias. Therefore, for these survey forecasts, consensus regressions should generally not be used to test rationality; rationality can only be tested at the individual level.
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