100 research outputs found
Reforming Protestantism: resisting capitalism’s capture of desire through a teleological anthropology
Get PDFThesis (PhD)--Stellenbosch University, 2025.Keay, E. 2025. Reforming Protestantism: resisting capitalism’s capture of desire through a teleological anthropology. Unpublished doctoral dissertation. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/b622e274-a404-41f5-93e0-c7c6eaba195eA selection of Protestant anthropologies has been used to support capitalism’s capture of desire and reorientation of human ends, rather than to free desire and guide humanity towards its telos or final end in God. The common assumption that capitalism is a byproduct of Protestantism—a notion stemming from Max Weber’s The Protestant Ethic and the Spirit of Capitalism—has since been challenged by research showing that capitalism predated the Reformation, flourishing within late medieval Catholicism. However, Protestantism did contribute to the ascent and subsequent dominance of capitalism. This dissertation demonstrates that the connection between Protestantism and capitalism is an anthropological one, rooted in a problematic theological thread within premodern Western Christianity. The method employed is a systematic-theological genealogy of Protestant anthropologies of desire that begins in the present-day United States and then retraces its history back to the Reformation, followed by a discussion demonstrating the links between Luther and his late medieval predecessors, and then between Luther and Augustine himself. Once that inquiry is concluded, the conversation will return to the present to reintroduce a premodern teleological anthropology that resists capitalism’s capture of desire. Contrary to what has often been assumed, a capitalism-supporting theological anthropology predates Luther and is found in the works of medieval Franciscan theologians. Because Luther never entirely escaped their problematic theological ideas, he perpetuated them. Furthermore, as an Augustinian monk and theologian who heavily relied on Augustine’s anti-Pelagian works, a comparison of Luther’s anthropology with Augustine’s, as well as that of another Church Father, was crucial. For this purpose, the author has chosen Maximus the Confessor. Such a comparison reveals that while Augustine does make statements aligning with Luther’s anthropology, many of his teleological ideas firmly place him among other Early Church Fathers, resisting the capture of desire by capitalism. Thus, Luther’s focus on Augustine’s anti-Pelagian works, rather than Augustine’s teleological and Christian Platonist theology, shaped an anthropology that ultimately undergirded capitalism. If Protestantism is to guide humanity toward its proper telos in God, it must adopt liturgies, practices, and sacraments that free humans from capitalism’s capture of desire, enabling them to desire the Source and End of all desires.Doctora
Essays on average treatment effects
Get PDFThis dissertation consists of three essays on estimating average treatment effects (ATE) under counterfactual framework. In Chapter 1, I compare the performances of single-step and two-step estimators for estimating the ATE in a linear model when treatment assignment depends on unobservables. Recent advances in computing technology have enabled the extensive use of single-step estimators, such as Limited Information Maximum Likelihood (LIML), instead of 2SLS. In this study I make clear that there are two kinds of single-step estimators for estimating ATE. LIML-type estimator is the one which uses the control function method, on which the two-step method is also based, whereas FIML-type estimator directly uses the joint distribution of underlying errors or endogenous variables. I find that the relative asymptotic efficiency between two-step Heckit and single-step LIML cannot be determined in general. However, the relative efficiency of single-step LIML with respect to two-step Heckit is decreasing as the sample size increases, implying that if the asymptotic variances are same, then single-step LIML is less efficient in finite samples. On the other hand the FIML estimator tends to have very small finite sample variances, but it is less robust to misspecification. Newey-type series estimators are also considered for correcting the misspecification of error distributions, but it turned out that cost is greater than the benefit. Under weak many instrument cases, the advantage of LIML in terms of median bias was not as strong as in the linear models. Chapter 2 explores the ATE estimator proposed by Terza (2009)'s Nonlinear Full Endogenous Treatment (NFES) model, where count dependent and binary treatment variables are present. When the true conditional mean function takes the form of exponential function, the Heckit-type linear method, while it can be a good approximation, is inconsistent for the true ATE since it is derived under the assumption of linear conditional mean. The asymptotic distribution of nonlinear estimators have additional terms in asymptotic variance of which magnitudes depend on population coefficient. Due to their presence, the asymptotic variances of nonlinear estimators can be either larger or smaller than the linear counterparts depending on the values of coefficients. It turns out that they tend to have small variances when the variance of conditional ATE are small. And Monte Carlo experiments show that they are fairly robust to various distributional misspecifications. In summary, nonlinear ATE estimators are robust and consistent with small variance when the treatment effects are not substantially different across individuals. An application to Botswana fertility is given where the treatment is seven years of education with the dependent variable fertility.Chapter 3 presents a method for estimating ATE for the case that the dependent variable is count variable and the coefficients of covariates are random variables which are correlated with the binary treatment variable. The identifying assumptions are given and the estimating equation based on them is derived. Simulations show that, in large samples, it has usually smaller biases and larger variances than the linear methods have. An application on Botswana fertility is given with same variables as in Chapter 2.Thesis (Ph. D.)--Michigan State University, Department of Economics, 2012Includes bibliographical references (pages 170-175
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