Multilevel Governance and Accountability: Does Decentralization Promote Good Governance?

Today, the trend towards decentralization is far-reaching. Proponents of decentralization have argued that decentralization promotes responsive and accountable local government by shortening the distance between local representatives and their constituency. However, in this paper, I focus on the countervailing effect of decentralization on the accountability mechanism, arguing that decentralization, which increases the number of actors eligible for policy making and implementation in governance as a whole, may blur lines of responsibility, thus weakening citizens’ ability to sanction government in election. By using the ordinary least squares (OLS) interaction model based on historical panel data for 78 countries in the 2002 – 2010 period, I test the hypothesis that as the number of government tiers increases, there will be a negative interaction between the number of government tiers and decentralization policies. The regression results show empirical evidence that decentralization policies, having a positive impact on governance under a relatively simple form of multilevel governance, have no more statistically significant effects as the complexity of government structure exceeds a certain degree. In particular, this paper found that the presence of intergovernmental meeting with legally binding authority have a negative impact on governance when the complexity of government structure reaches to the highest level.

Combining Information from Multiple Sources in Bayesian Modeling

Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.

Poverty Dynamics: Empirical Evidence for Canada (Working Paper 29)

Poverty (low income) dynamics are explored using tax filer data covering the period 1992 to 1996. The distributions of short-and long-term episodes are identified, and reveal substantial differences by sex and family type. Entry and exit models explore the relationships between poverty transitions and sex, family status and other personal and situational attributes. Duration effects on exiting and re-entering poverty are found to be important, and models including past poverty experiences point to strong "occurrence dependence" for poverty entry and incidence. Fixed-effect panel data models confirm the above, and reveal asymmetries in the impacts of household transitions on poverty.

Crisis, educación y precariedad-afluencia. El rol de la educación en las condiciones de vida de la población española

El objeto de este artículo es estudiar la influencia del nivel educativo (capital cultural) en los procesos de precariedad-afluencia de la población española entre los años posteriores a la crisis de inicio de la década de 1990 y los años más duros de la crisis de 2007. A partir de los datos de las encuestas PHOGUE y ECV del Instituto Nacional de Estadística (INE) se han construido cuatro indicadores para medir la precariedad laboral, de ingresos, de salud y de vivienda y su distribución según distintas variables demográficas. Se pretende contrastar la hipótesis de que más educación significa más protección frente a la precariedad, estudiando diferentes condiciones de las condiciones de vida y existencia en momentos tanto de crecimiento como de crisis económica. Mediante un análisis multivariable se intenta determinar el nivel de impacto del capital cultural, alcance, evolución y, sobre todo, si sus efectos positivos o negativos están en proceso de expansión o desaceleración. El resultado tiene una doble aportación: de un lado, metodológica, consistente en la construcción de los indicadores; de otro lado, los resultados, con los que se puede reevaluar algunas generalizaciones sobre la pérdida de importancia del rol de la educación en las sociedades contemporáneas.

Impacts of FDI Renewable Energy Technology Spillover on China's Energy Industry Performance

Environmental friendly renewable energy plays an indispensable role in energy industry development. Foreign direct investment (FDI) in advanced renewable energy technology spillover is promising to improve technological capability and promote China’s energy industry performance growth. In this paper, the impacts of FDI renewable energy technology spillover on China’s energy industry performance are analyzed based on theoretical and empirical studies. Firstly, three hypotheses are proposed to illustrate the relationships between FDI renewable energy technology spillover and three energy industry performances including economic, environmental, and innovative performances. To verify the hypotheses, techniques including factor analysis and data envelopment analysis (DEA) are employed to quantify the FDI renewable energy technology spillover and the energy industry performance of China, respectively. Furthermore, a panel data regression model is proposed to measure the impacts of FDI renewable energy technology spillover on China’s energy industry performance. Finally, energy industries of 30 different provinces in China based on the yearbook data from 2005 to 2011 are comparatively analyzed for evaluating the impacts through the empirical research. The results demonstrate that FDI renewable energy technology spillover has positive impacts on China’s energy industry performance. It can also be found that the technology spillover effects are more obvious in economic and technological developed regions. Finally, four suggestions are provided to enhance energy industry performance and promote renewable energy technology spillover in China.

SURVEILLANCE OF, AND THE IMPACT OF COMMUNITY POLICING ON ARREST-RELATED DEATHS (ARDS): Exploring the surveillance of ARDs and the opportunities to prevent them in the United States

Thesis (Master's)--University of Washington, 2016-08

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

A Field Study of the Impact of a Performance-Based Incentive Plan

Much management accounting research focuses on design of incentive compensation contracts. A basic assumption in these contracts is that performance-based incentives improve employee performance. This paper reports on a field test of the multi-period incentive effects of a performance-based compensation plan on the sales of a retail establishment. Analysis of panel data for 15 retail outlets over 66 months indicates a sales increase when the plan is implemented, an effect that persists and increases over time. Sales gains are significantly lower in the peak selling season when more temporary workers are employed.

Obtención de un modelo estadístico para proporcionar QoS en enlaces inalámbricos ópticos submarinos

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Studio e validazione sperimentale di un nuovo sistema per ultrafiltrazione in emodialisi

La dialisi, le cui basi sono state fondate a metà ottocento dal chimico Thomas Graham, è la terapia, alternativa al trapianto, utilizzata su pazienti affetti da insufficienza renale. Ad oggi tale terapia ha un numero sempre maggiore di utilizzatori, più di 2,5 milioni di persone al mondo, ragione per cui ha un impatto sempre più grande sul sistema sanitario. La terapia, ha come scopo principale quello ripristinare gli equilibri idro-elettrolitico e acido-base del sangue del paziente utilizzando principi quali ultrafiltrazione, convezione e diffusione. Per raggiungere questo obiettivo, il sangue del paziente viene fatto scorrere controcorrente al liquido di dialisi, di composizione nota, ai capi di una membrana semipermeabile. Nel caso dell’emodialisi tutto il processo si svolge in circolazione extracorporea. La dialisi viene eseguita quando i reni del paziente non riescono più a espletare la loro funzione, con conseguente accumulo di tossine e di liquidi, che nel giro di pochi giorni porterebbe alla morte se non si interviene. Data la sua funzione, una parte importante della macchina che esegue l’emodialisi, è il sistema di controllo dell’ultrafiltrazione, che permette di rimuovere in maniera controllata i liquidi che il paziente non riesce a smaltire in maniera autonoma. La rimozione di liquidi avviene mediante la creazione di un gradiente pressorio tra il lato sangue e il lato dializzato, che causa il passaggio di liquidi da una parte all’altra della membrana semipermeabile. Esistono vari metodi che permettono di realizzare questo processo, che si differenziano per la strategia utilizzata per creare i gradienti pressori; ognuno dei quali permette di ottenere una determinata accuratezza. Scopo del mio lavoro di tesi è stato quello di studiare e validare un nuovo sistema di realizzazione e controllo dell’ultrafiltrazione.

Essays on Machine Learning and Hedonic Models

Thesis (Ph.D.)--University of Washington, 2016-08

Determinantes da liquidez das PME da indústria transformadora em Portugal

Este artigo visa identificar os determinantes da liquidez das pequenas e médias empresas (PME) portuguesas, assim como analisar até que ponto estes se alteram quando analisamos períodos de estabilidade ou de recessão financeira. Para tal, recorremos a uma amostra de dados em painel, considerando 4.355 PME, e analisando o período compreendido entre 2002 e 2011. De um modo geral, os resultados confirmam a existência de uma relação significativa entre algumas das variáveis independentes e a liquidez das empresas. Mais especificamente, os resultados evidenciam uma relação positiva entre a dimensão, a rendibilidade e a probabilidade de existência de problemas financeiros, e a liquidez das empresas, bem como uma relação negativa entre o grau de endividamento e a maturidade da dívida, e a liquidez das PME. Os resultados mostram ainda que a liquidez das empresas é afetada em períodos de crise financeira, verificando-se, nomeadamente, uma redução da dívida de curto prazo e um aumento da duração do ciclo de conversão de caixa.

Eleição nas escolas: uma análise do impacto do diretor eleito sobre o desempenho educacional no Estado da Bahia

In Brazil, the selection of school principals is set in a decentralized manner by each state and city, such that processes may vary with time for a specific locality. In the state of Bahia, school principals were appointed by a higher political hierarchy until 2008, when schools under state administration started selecting principals by elections. The main goal of this work is to evaluate whether changing this specific rule affected students proficiency levels. This is achieved by using a panel data and difference-in-differences approachs that compares state schools (treatment group) to city schools (control group) that did not face a selection rule change and thus kept having their principals politically appointed. The databases used are Prova Brasil 2007, 2009 and 2011, the first one prior and the other two former to the policy change. Our results suggest that students attending schools with principals that are selected and elected have slightly lower mean proficiency levels both in mathematics and in portuguese exams than those attending schools with appointed principals. This result, according to the literature, could be related to perverse effects of selecting school administrators by vote, such as corporatism, clientelism and politicization of the school environment

A Corrupção burocrática inibe o empreendedorismo? uma análise empírica dos estados brasileiros

This work aims to investigate the relationship between the entrepreneurship and the incidence of bureaucratic corruption in the states of Brazil and Federal District. The main hypothesis of this study is that the opening of a business in Brazilian states is negatively affected by the incidence of corruption. The theoretical reference is divided into Entrepreneurship and bureaucratic corruption, with an emphasis on materialistic perspective (objectivist) of entrepreneurship and the effects of bureaucratic corruption on entrepreneurial activity. By the regression method with panel data, we estimated the models with pooled data and fixed and random effects. To measure corruption, I used the General Index of Corruption for the Brazilian states (BOLL, 2010), and to represent entrepreneurship, firm entry per capita by state. Tests (Chow, Hausman and Breusch-Pagan) indicate that the random effects model is more appropriate, and the preliminary results indicate a positive impact of bureaucratic corruption on entrepreneurial activity, contradicting the hypothesis expected and found in previous articles to Brazil, and corroborating the proposition of Dreher and Gassebner (2011) that, in countries with high regulation, bureaucratic corruption can be grease in the wheels of entrepreneurship

Zero-rating in emerging mobile markets: Free Basics and Wikipedia Zero in Ghana

Despite widespread controversy surrounding zero-rating—that is, the practice of subsidizing mobile data—the field suffers from a lack of inquiry into user understanding of and experience with zero-rated services. This paper explores how Ghanaian mobile users interact with zero-rated mobile applications Free Basics and Wikipedia Zero. Based on semi-structured interviews with users and non-users of the applications, I discuss how mobile phone users perceive Free Basics and Wikipedia Zero, what motivates them to use or not use the applications, and how the availability of the applications influences their data-buying strategies. Findings suggest that respondents, including those who did not actively use the applications, understood and experienced Free Basics and Wikipedia Zero in ways divergent from the providers’ aim of expanding access to online content and services.