119 research outputs found

    An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schools

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    Several previous studies have relied on religious affiliation and the proximity to Catholic schools as exogenous sources of variation for identifying the effect of Catholic schooling on a wide variety of outcomes. Using three separate approaches, we examine the validity of these instrumental variables. We find that none of the candidate instruments is a useful source of identification of the Catholic school effect, at least in currently available data sets

    Direct Estimation of Policy Impacts

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    This paper specifies a general set of conditions under which the impacts of a policy can be identified using data generated under a different policy regime. We show that some of the policy impacts can be identified under relatively weak conditions on the data and structure of a model. Based on the identification results we develop estimators of policy impacts. We discuss a nonparametric method to implement the estimation but also discuss semiparametric methods in order to reduce the conditioning dimension. We then provide an empirical example of the impact of tuition subsidies using the ideas. While the framework used in this paper is fairly narrow, we believe this approach can be applied to a broad set of problems.

    Estimating the Effect of Student Aid on College Enrollment: Evidence from a Government Grant Policy Reform

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    In this paper, we investigate the responsiveness of the demand for college to changes in student aid arising from a Danish reform. We separately identify the effect of aid from that of other observed and unobserved variables such as parental income. We exploit the combination of a kinked aid scheme and a reform of the student aid scheme to identify the effect of direct costs on college enrollment. To allow for heterogeneous responses due to borrowing constraints, we use detailed information on parents' assets. We find that enrollment is less responsive than found in other studies and that the presence of borrowing constraints only deters college enrollment to a minor extent.

    Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools

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    We develop estimation methods that use the amount of selection on the observables in a model as a guide to the amount of selection on the unobservables. We show that if the observed variables are a random subset of a large number of factors that influence the endogenous variable and the outcome of interest, then the relationship between the index of observables that determines the endogenous variable and the index that determines the outcome will be the same as the relationship between the indices of unobservables that determine the two variables. In some circumstances this fact may be used to identify the effect of the endogenous variable. We also propose an informal way to assess selectivity bias based on measuring the ratio of selection on unobservables to selection on observables that would be required if one is to attribute the entire effect of the endogenous variable to selection bias. We use our methods to estimate the effect of attending a Catholic high school on a variety of outcomes. Our main conclusion is that Catholic high schools substantially increase the probability of graduating from high school and, more tentatively, college attendance. We do not find much evidence for an effect on test scores.

    Effects of the French Contrast Method on Maximum Strength and Vertical Jumping Performance

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    Introduction: French Contrast Method (FCM) was first created by French track and field coach Gilles Cometti. Anecdotally, FCM is widely utilized by strength and conditioning coaches in their programming for athletes. However, research on the effectiveness of this method is limited. Methods: A pre-post design was used to examine the effects of FCM on maximum strength and vertical jumping performance. A total of 10 weight-trained males volunteered to participate in this study (Age: 21.84Ā±2.38, Height: 175.37Ā±4.94, Body Mass: 80.6Ā±11.11 Training Age: 4.7Ā±2.3, one repetition maximum (1RM) Back Squat: 136.9Ā±37.14, 1RM Trap Bar Deadlift: 189Ā±42.85)

    Econometric Mixture Models and More General Models for Unobservables in Duration Analysis

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    This paper considers models for unobservables in duration models. It demonstrates how cross-section and time-series variation in regressors facilitates identification of single-spell, competing risks and multiple spell duration models. We also demonstrate the limited value of traditional identification studies by considering a case in which a model is identified in the conventional sense but cannot be consistently estimated.

    Skeletal Muscle Fiber Adaptations Following Resistance Training Using Repetition Maximums or Relative Intensity

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    The purpose of the study was to compare the physiological responses of skeletal muscle to a resistance training (RT) program using repetition maximum (RM) or relative intensity (RISR). Fifteen well-trained males underwent RT 3 dĀ·wkāˆ’1 for 10 weeks in either an RM group (n = 8) or RISR group (n = 7). The RM group achieved a relative maximum each day, while the RISR group trained based on percentages. The RM group exercised until muscular failure on each exercise, while the RISR group did not reach muscular failure throughout the intervention. Percutaneous needle biopsies of the vastus lateralis were obtained pre-post the training intervention, along with ultrasonography measures. Dependent variables were: Fiber type-specific cross-sectional area (CSA); anatomical CSA (ACSA); muscle thickness (MT); mammalian target of rapamycin (mTOR); adenosine monophosphate protein kinase (AMPK); and myosin heavy chains (MHC) specific for type I (MHC1), type IIA (MHC2A), and type IIX (MHC2X). Mixed-design analysis of variance and effect size using Hedgeā€™s g were used to assess within- and between-group alterations. RISR statistically increased type I CSA (p = 0.018, g = 0.56), type II CSA (p = 0.012, g = 0.81), ACSA (p = 0.002, g = 0.53), and MT (p \u3c 0.001, g = 1.47). RISR also yielded a significant mTOR reduction (p = 0.031, g = āˆ’1.40). Conversely, RM statistically increased only MT (p = 0.003, g = 0.80). Between-group effect sizes supported RISR for type I CSA (g = 0.48), type II CSA (g = 0.50), ACSA (g = 1.03), MT (g = 0.72), MHC2X (g = 0.31), MHC2A (g = 0.87), and MHC1 (g = 0.59); with all other effects being of trivial magnitude (g \u3c 0.20). Our results demonstrated greater adaptations in fiber size, whole-muscle size, and several key contractile proteins when using RISR compared to RM loading paradigm

    Skeletal Muscle Fiber Adaptations Following Resistance Training Using Repetition Maximums or Relative Intensity

    Get PDF
    The purpose of the study was to compare the physiological responses of skeletal muscle to a resistance training (RT) program using repetition maximum (RM) or relative intensity (RISR). Fifteen well-trained males underwent RT 3 dĀ·wkāˆ’1 for 10 weeks in either an RM group (n = 8) or RISR group (n = 7). The RM group achieved a relative maximum each day, while the RISR group trained based on percentages. The RM group exercised until muscular failure on each exercise, while the RISR group did not reach muscular failure throughout the intervention. Percutaneous needle biopsies of the vastus lateralis were obtained pre-post the training intervention, along with ultrasonography measures. Dependent variables were: Fiber type-specific cross-sectional area (CSA); anatomical CSA (ACSA); muscle thickness (MT); mammalian target of rapamycin (mTOR); adenosine monophosphate protein kinase (AMPK); and myosin heavy chains (MHC) specific for type I (MHC1), type IIA (MHC2A), and type IIX (MHC2X). Mixed-design analysis of variance and effect size using Hedgeā€™s g were used to assess within- and between-group alterations. RISR statistically increased type I CSA (p = 0.018, g = 0.56), type II CSA (p = 0.012, g = 0.81), ACSA (p = 0.002, g = 0.53), and MT (p \u3c 0.001, g = 1.47). RISR also yielded a significant mTOR reduction (p = 0.031, g = āˆ’1.40). Conversely, RM statistically increased only MT (p = 0.003, g = 0.80). Between-group effect sizes supported RISR for type I CSA (g = 0.48), type II CSA (g = 0.50), ACSA (g = 1.03), MT (g = 0.72), MHC2X (g = 0.31), MHC2A (g = 0.87), and MHC1 (g = 0.59); with all other effects being of trivial magnitude (g \u3c 0.20). Our results demonstrated greater adaptations in fiber size, whole-muscle size, and several key contractile proteins when using RISR compared to RM loading paradigms
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