5 resultados para Compositional Rule of Inference
em Duke University
Resumo:
The Laws is generally regarded as Plato’s attempt to engage with the practical realities of political life, as opposed to the more idealistic, or utopian, vision of the Republic. Yet modern scholars have often felt disquieted at the central role of religion in the Laws’ second-best city and regime. There are essentially the two dominant interpretations on offer today: either religion supports a repressive theocracy, which controls every aspect of the citizens’ lives to such an extent that even philosophy itself is discouraged, or religion is an example of the kind of noble lie, which the philosopher must deceive the citizens into believing—viz., that a god, not a man, is the author of the regime’s laws. I argue that neither of these interpretations do justice to the dialogue’s intricately dramatic structure, and therefore to Plato’s treatment of civil religion. What I propose is a third position in which Plato both takes seriously the social and political utility of religion, and views theology as a legitimate, and even necessary, subject of philosophical inquiry without going so far as to advocate theocracy as the second best form of regime.
I conclude that a proper focus on the dialogue form, combined with a careful historical analysis of Plato’s use of social and political institutions, reveals an innovative yet traditional form of civil religion, purified of the harmful influence of the poets, based on the authority of the oracle at Delphi, and grounded on a philosophical conception of god as the eternal source of order, wisdom, and all that is good. Through a union of traditional Delphic theology and Platonic natural theology, Plato gives the city of the Laws a common cult acceptable to philosopher and non-philosopher alike, and thus, not only bridges the gap between religion and philosophy, but also creates a sense of community, political identity, and social harmony—the prerequisites for political order and stability. The political theology of the Laws, therefore, provides a rational defense of the rule of law (νόμος) re-conceived as the application of divine Reason (νοῦς) to human affairs.
Resumo:
This dissertation seeks to advance our understanding of the roles that institutions play in economic development. How do institutions evolve? What mechanisms are responsible for their persistence? What effects do they have on economic development?
I address these questions using historical and contemporary data from Eastern Europe and Russia. This area is relatively understudied by development economists. It also has a very interesting history. For one thing, for several centuries it was divided between different empires. For another, it experienced wars and socialism in the 20th century. I use some of these exogenous shocks as quasi-natural social experiments to study the institutional transformations and its effects on economic development both in the short and long run.
This first chapter explores whether economic, social, and political institutions vary in their resistance to policies designed to remove them. The empirical context for the analysis is Romania from 1690 to the 2000s. Romania represents an excellent laboratory for studying the persistence of different types of historical institutional legacies. In the 18th and 19th centuries, Romania was split between the Habsburg and Ottoman Empires, where political and economic institutions differed. The Habsburgs imposed less extractive institutions relative to the Ottomans: stronger rule of law, a more stable and predictable state, a more developed civil society, and less corruption. In the 20th century, the Romanian Communist regime tried deliberately to homogenize the country along all relevant dimensions. It was only partially successful. Using a regression discontinuity design, I document the persistence of economic outcomes, social capital, and political attitudes. First, I document remarkable convergence in urbanization, education, unemployment, and income between the two former empires. Second, regarding social capital, no significant differences in organizational membership, trust in bureaucracy, and corruption persist today. Finally, even though the Communists tried to change all political attitudes, significant discontinuities exist in current voting behavior at the former Habsburg-Ottoman border. Using data from the parliamentary elections of 1996-2008, I find that former Habsburg rule decreases by around 6 percentage points the vote share of the major post-Communist left party and increases by around 2 and 5 percentage points the vote shares of the main anti-Communist and liberal parties, respectively.
The second chapter investigates the effects of Stalin’s mass deportations on distrust in central authority. Four deported ethnic groups were not rehabilitated after Stalin’s death; they remained in permanent exile until the disintegration of the Soviet Union. This allows one to distinguish between the effects of the groups that returned to their homelands and those of the groups that were not allowed to return. Using regional data from the 1991 referendum on the future of the Soviet Union, I find that deportations have a negative interim effect on trust in central authority in both the regions of destination and those of origin. The effect is stronger for ethnic groups that remained in permanent exile in the destination regions. Using data from the Life in Transition Survey, the chapter also documents a long-term effect of deportations in the destination regions.
The third chapter studies the short-term effect of Russian colonization of Central Asia on economic development. I use data on the regions of origin of Russian settlers and push factors to construct an instrument for Russian migration to Central Asia. This instrument allows me to interpret the outcomes causally. The main finding is that the massive influx of Russians into the region during the 1897-1926 period had a significant positive effect on indigenous literacy. The effect is stronger for men and in rural areas. Evidently, interactions between natives and Russians through the paid labor market was an important mechanism of human capital transmission in the context of colonization.
The findings of these chapters provide additional evidence that history and institutions do matter for economic development. Moreover, the dissertation also illuminates the relative persistence of institutions. In particular, political and social capital legacies of institutions might outlast economic legacies. I find that most economic differences between the former empires in Romania have disappeared. By the same token, there are significant discontinuities in political outcomes. People in former Habsburg Romania provide greater support for liberalization, privatization, and market economy, whereas voters in Ottoman Romania vote more for redistribution and government control over the economy.
In the former Soviet Union, Stalin’s deportations during World War II have a long-term negative effect on social capital. Today’s residents of the destination regions of deportations show significantly lower levels of trust in central authority. This is despite the fact that the Communist regime tried to eliminate any source of opposition and used propaganda to homogenize people’s political and social attitudes towards the authorities. In Central Asia, the influx of Russian settlers had a positive short-term effect on human capital of indigenous population by the 1920s, which also might have persisted over time.
From a development perspective, these findings stress the importance of institutions for future paths of development. Even if past institutional differences are not apparent for a certain period of time, as was the case with the former Communist countries, they can polarize society later on, hampering economic development in the long run. Different institutions in the past, which do not exist anymore, can thus contribute to current political instability and animosity.
Resumo:
My dissertation has three chapters which develop and apply microeconometric tech- niques to empirically relevant problems. All the chapters examines the robustness issues (e.g., measurement error and model misspecification) in the econometric anal- ysis. The first chapter studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treat- ment variable is mismeasured and endogenous. I characterize the sharp identified set for the local average treatment effect under the following two assumptions: (1) the exclusion restriction of an instrument and (2) deterministic monotonicity of the true treatment variable in the instrument. The identification strategy allows for general measurement error. Notably, (i) the measurement error is nonclassical, (ii) it can be endogenous, and (iii) no assumptions are imposed on the marginal distribution of the measurement error, so that I do not need to assume the accuracy of the measure- ment. Based on the partial identification result, I provide a consistent confidence interval for the local average treatment effect with uniformly valid size control. I also show that the identification strategy can incorporate repeated measurements to narrow the identified set, even if the repeated measurements themselves are endoge- nous. Using the the National Longitudinal Study of the High School Class of 1972, I demonstrate that my new methodology can produce nontrivial bounds for the return to college attendance when attendance is mismeasured and endogenous.
The second chapter, which is a part of a coauthored project with Federico Bugni, considers the problem of inference in dynamic discrete choice problems when the structural model is locally misspecified. We consider two popular classes of estimators for dynamic discrete choice models: K-step maximum likelihood estimators (K-ML) and K-step minimum distance estimators (K-MD), where K denotes the number of policy iterations employed in the estimation problem. These estimator classes include popular estimators such as Rust (1987)’s nested fixed point estimator, Hotz and Miller (1993)’s conditional choice probability estimator, Aguirregabiria and Mira (2002)’s nested algorithm estimator, and Pesendorfer and Schmidt-Dengler (2008)’s least squares estimator. We derive and compare the asymptotic distributions of K- ML and K-MD estimators when the model is arbitrarily locally misspecified and we obtain three main results. In the absence of misspecification, Aguirregabiria and Mira (2002) show that all K-ML estimators are asymptotically equivalent regardless of the choice of K. Our first result shows that this finding extends to a locally misspecified model, regardless of the degree of local misspecification. As a second result, we show that an analogous result holds for all K-MD estimators, i.e., all K- MD estimator are asymptotically equivalent regardless of the choice of K. Our third and final result is to compare K-MD and K-ML estimators in terms of asymptotic mean squared error. Under local misspecification, the optimally weighted K-MD estimator depends on the unknown asymptotic bias and is no longer feasible. In turn, feasible K-MD estimators could have an asymptotic mean squared error that is higher or lower than that of the K-ML estimators. To demonstrate the relevance of our asymptotic analysis, we illustrate our findings using in a simulation exercise based on a misspecified version of Rust (1987) bus engine problem.
The last chapter investigates the causal effect of the Omnibus Budget Reconcil- iation Act of 1993, which caused the biggest change to the EITC in its history, on unemployment and labor force participation among single mothers. Unemployment and labor force participation are difficult to define for a few reasons, for example, be- cause of marginally attached workers. Instead of searching for the unique definition for each of these two concepts, this chapter bounds unemployment and labor force participation by observable variables and, as a result, considers various competing definitions of these two concepts simultaneously. This bounding strategy leads to partial identification of the treatment effect. The inference results depend on the construction of the bounds, but they imply positive effect on labor force participa- tion and negligible effect on unemployment. The results imply that the difference- in-difference result based on the BLS definition of unemployment can be misleading
due to misclassification of unemployment.
Resumo:
Uncertainty quantification (UQ) is both an old and new concept. The current novelty lies in the interactions and synthesis of mathematical models, computer experiments, statistics, field/real experiments, and probability theory, with a particular emphasize on the large-scale simulations by computer models. The challenges not only come from the complication of scientific questions, but also from the size of the information. It is the focus in this thesis to provide statistical models that are scalable to massive data produced in computer experiments and real experiments, through fast and robust statistical inference.
Chapter 2 provides a practical approach for simultaneously emulating/approximating massive number of functions, with the application on hazard quantification of Soufri\`{e}re Hills volcano in Montserrate island. Chapter 3 discusses another problem with massive data, in which the number of observations of a function is large. An exact algorithm that is linear in time is developed for the problem of interpolation of Methylation levels. Chapter 4 and Chapter 5 are both about the robust inference of the models. Chapter 4 provides a new criteria robustness parameter estimation criteria and several ways of inference have been shown to satisfy such criteria. Chapter 5 develops a new prior that satisfies some more criteria and is thus proposed to use in practice.