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The desire is infinite, but the resources are limited. The relationship between fiscal decentralization and long-run economic growth is ambiguous. Several economists have made the case for fiscal decentralization as a means of promoting long-run economic growth based on the view that it leads to better resource allocation and a more productive, and possibly smaller, public sector. Countries have pursued decentralization policies both for political and developmental reasons. Fiscal decentralization, the allocation of tax and spending powers to lower levels of government, currently in vogue is based on notions of economic efficiency criteria. Although it is theoretically expected that decentralization leads to efficient provision of local public services and stimulates economic development, the theoretical underpinnings for this relationship remain largely undeveloped. The absence of an adequate theoretical framework has undermined the validity of the empirical work on this subject. Advocates of fiscal decentralization argue that among other benefits, it can increase the efficiency of delivery of government services. We use data from 23 counties (cities) of the Taiwan province. The empirical findings can be stated as follows. The primary finding is that the estimated coefficient on fiscal decentralization variable is positive and statistically significant . This finding provides evidence that fiscal decentralization contributes to economic growth. This paper is also one of the first to evaluate this claim empirically by looking at the association between expenditure decentralization and the efficiency of local government .We also provide evidence that expenditure (revenue) decentralization is a negative (positive) relation with the efficiency of local government. Further Tobit panel regression of 23 counties (cities) provide robust evidence that more decentralization is not associated with higher efficiency of local governments. Therefore that fiscal decentralization contributes to the efficiency of local governments is ambiguous in the previous period.

Linear mixed models and generalized linear mixed models are random-effects models widely applied to analyze clustered or hierarchical data. Generally, random effects are often assumed to be normally distributed in the context of mixed models. However, in the mixed-effects logistic model, the violation of the assumption of normally distributed random effects may result in inconsistency for estimates of some fixed effects and the variance component of random effects when the variance of the random-effects distribution is large. On the other hand, summary statistics used for assessing goodness of fit in the ordinary logistic regression models may not be directly applicable to the mixed-effects logistic models. In this dissertation, we present our investigations of two independent studies related to goodness-of-fit tests in generalized linear mixed models. First, we consider a semi-nonparametric density representation for the random effects distribution and provide a formal statistical test for testing normality of the random-effects distribution in the mixed-effects logistic models. We obtain estimates of parameters by using a non-likelihood-based estimation procedure. Additionally, we not only evaluate the type I error rate of the proposed test statistic through asymptotic results, but also carry out a bootstrap hypothesis testing procedure to control the inflation of the type I error rate and to study the power performance of the proposed test statistic. Further, the methodology is illustrated by revisiting a case study in mental health. Second, to improve assessment of the model fit in the mixed-effects logistic models, we apply the nonparametric local polynomial smoothed residuals over within-cluster continuous covariates to the unweighted sum of squares statistic for assessing the goodness-of-fit of the logistic multilevel models. We perform a simulation study to evaluate the type I error rate and the power performance for detecting a missing quadratic or interaction term of fixed effects using the kernel smoothed unweighted sum of squares statistic based on the local polynomial smoothed residuals over x-space. We also use a real data set in clinical trials to illustrate this application.

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Product reliability is an important characteristic for all manufacturers, engineers and consumers. Industrial statisticians have been planning experiments for years to improve product quality and reliability. However, rarely do experts in the field of reliability have expertise in design of experiments (DOE) and the implications that experimental protocol have on data analysis. Additionally, statisticians who focus on DOE rarely work with reliability data. As a result, analysis methods for lifetime data for experimental designs that are more complex than a completely randomized design are extremely limited. This dissertation provides two new analysis methods for reliability data from life tests. We focus on data from a sub-sampling experimental design. The new analysis methods are illustrated on a popular reliability data set, which contains sub-sampling. Monte Carlo simulation studies evaluate the capabilities of the new modeling methods. Additionally, Monte Carlo simulation studies highlight the principles of experimental design in a reliability context. The dissertation provides multiple methods for statistical inference for the new analysis methods. Finally, implications for the reliability field are discussed, especially in future applications of the new analysis methods. / Ph. D.

內生經濟成長認為政府支出結構與收入結構均會影響恆定狀態成長率之觀點和事實是否一致呢？許多先前相關之研究需被修正，因為這些研究在政府預算限制式的設定並不完全，導致實證之結果產生偏誤。本文除了將討論忽略這些偏誤所會導致之影響外，進一步將以One-Way與TwO-Way的固定效果與隨機效果模型來進行估計，並修正先前研究所發生之問題，然後找出強力的證據來支持Barro模型（1990）所做的預測。本文的樣本資料取自東亞經濟前瞻與亞洲開發銀行，以亞洲新、舊四小龍，加上申國，共九個國家的17年時間序列資料所形成的揉合資料（pooling data）為實證對象。分析結果發現在考慮異質性與同期相關性下，若採用似無相關迴歸技巧來對One-Way固定效果模型進行估計，則：（1）不論政府是以租稅收入或是非租稅收入作為融通財源，資本性支出的增加均會提高經濟成長率，經常性支出的增加則均會對經濟成長率造成負面影響；（2）在政府以租稅收入為融通來源下，非租稅收入增加將會降低經濟成長率；若政府以非租稅收入作為融通之財源，則此時租稅收入之增加將會降低經濟成長。 〔關鍵字〕資本支出、經常支出、同期相關性（Contemporaneous correlation）、異質性（HetereSkedaStiCity）、One-Way fixed（random）effect model、Two-way fixed（random）effect model、似無相關迴歸（Seemingly unrelated regression）