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.

The objective of this thesis is to investigate if human capital has a significant impact on economic growth. This is tested with a panel data regression model where data is taken annually from the Sub-Saharan Africa region between the years 1988-2011. The final regression model displayed education as a positive factor for GDP per capita growth, but not at a significant level. This result resembles many previous studies, and leads to the conclusion that we do not have a significant relationship between education enrolment and economic growth. The result raises the question if enrolment rates in school are a valid variable to capture human capital with, and calls for more investigations on the quality aspect of education.

This thesis examines both the long run and the short run impact of Exchange Rate Volatility on Foreign Direct Investment using an unbalanced panel data from three Sub-Saharan African countries of Kenya, Uganda and Tanzania. This is accomplished by generating Exchange Rate Volatility figures by the GARCH(1,1) methodology. The control variables included in this study include GDP, GDP growth, Economic Openness and Exchange rate. In order to capture the impact of economic openness on exchange rate volatility and thus foreign direct investment, different econometric specifications are adopted. The unbalanced panel data used in the analysis ranges for different time period for the specific countries considered in the panel.

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This thesis contributes to the under-researched field of political selection, namely one’s re-selection onto the party list after one has been elected in the previous term. The theoretical rationale is to introduce a broader concept of political selection to a field mostly focused on political recruitment, one’s first point of entry into Politics. We show that the framework developed to study political recruitment can be adapted to study any kind of political selection that involves a broad pool of aspirants from which successful candidates must be selected. To this end, we utilise a panel dataset containing data on 387 Czech legislators covering the period between 1996 and 2013. Using fixed- and random-effects panel models, we show that voting along the party line and preferential vote share at time t are strong predictors of getting a better party-list rank at t+1. Legislative experience, however, is negatively associated with how well one fares at the re-selection process. We also provide evidence that it is left-wing parties rather than their right-wing counterparts that discriminate against women at the re-selection stage. The study thus contributes, directly or otherwise, to debates on women’s representation, political careers and re-election.

The participation of irrigation districts (IDs) in surface water transfers from agriculture-to-municipal uses is studied by examining IDs’ economic and political behavior, comparing their performance with non-districts (non-IDs), and analyzing the role of economic and demographic heterogeneities in water transfers. Economic modeling, econometric, and analytical techniques are used to investigate these issues. An economic model is developed to investigate how the collective-type institutional structure of IDs in the presence of local interdependencies (between internal water delivery and external water transfers) and increasing returns to scale in the internal water delivery causes reduction in marginal benefit of water transfers and the optimal transfers. The model is also used to investigate how the involvement of the U.S. Bureau of Reclamation in IDs causes more water uses in agriculture availing less for external transfers. The conjunction of multiple uses and exclusion rights without ownership rights in IDs’ water and vote-maximizing political structure of IDs are found to create disincentive for water conservation and transfers. Water transfer responses of IDs and non-IDs are empirically investigated by using a Quasi Maximum Likelihood Estimation (QMLE) technique. Based on the analysis of 38 years of time series water transfer data, IDs are found to be less responsive in water transfers relative to non-IDs in terms of water right-weighted transfers. It is found that water scarcity, private housing permits, and nonfarm establishments are positively associated with water transfers. The marginal effect of water scarcity on water transfer is stronger for non-IDs than for IDs. Impacts of economic and demographic heterogeneities on water transfer behavior of IDs are investigated using unbalanced panel data econometric techniques. Water right holdings and population in nearby cities of IDs are found to be significantly correlated with water transfer behaviors of IDs. Larger IDs with higher water right holdings and higher population centers in nearby cities are found to be more responsive to water transfers. The findings complement previous studies that commend public attention for policy redesign including institutional changes to motivate IDs to increase their water transfer activity.

In longitudinal studies of chronic diseases, the disease states of individuals are often collected at several pre-scheduled clinical visits, but the exact states and the times of transitioning from one state to another between observations are not observed. This is commonly referred to as "panel data". Statistical challenges arise in panel data in regard to identifying predictors governing the transitions between different disease states with only the partially observed disease history. Continuous-time Markov models (CTMMs) are commonly used to analyze panel data, and allow maximum likelihood estimations without making any assumptions about the unobserved states and transition times. By assuming that the underlying disease process is Markovian, CTMMs yield tractable likelihood. However, CTMMs generally allow covariate effect to differ for different transitions, resulting in a much higher number of coefficients to be estimated than the number of covariates, and model overfitting can easily happen in practice. In three papers, I develop a regularized CTMM using the elastic net penalty for panel data, and implement it in an R package. The proposed method is capable of simultaneous variable selection and estimation even when the dimension of the covariates is high. In the first paper (Section 2), I use elastic net penalty to regularize the CTMM, and derive an efficient coordinate descent algorithm to solve the corresponding optimization problem. The algorithm takes advantage of the multinomial state distribution under the non-informative observation scheme assumption to simplify computation of key quantities. Simulation study shows that this method can effectively select true non-zero predictors while reducing model size. In the second paper (Section 3), I extend the regularized CTMM developed in the previous paper to accommodate exact death times and censored states. Death is commonly included as an endpoint in longitudinal studies, and exact time of death can be easily obtained but the state path leading to death is usually unknown. I show that exact death times result in a very different form of likelihood, and the dependency of death time on the model requires significantly different numerical methods for computing the derivatives of the log likelihood, a key quantity for the coordinate descent algorithm. I propose to use numerical differentiation to compute the derivatives of the log likelihood. Computation of the derivatives of the log likelihood from a transition involving a censored state is also discussed. I carry out a simulation study to evaluate the performance of this extension, which shows consistently good variable selection properties and comparable prediction accuracy compared to the oracle models where only true non-zero coefficient are fitted. I then apply the regularized CTMM to the airflow limitation data to the TESAOD (The Tucson Epidemiological Study of Airway Obstructive Disease) study with exact death times and censored states, and obtain a prediction model with great size reduction from a total of 220 potential parameters. Methods developed in the first two papers are implemented in an R package markovnet, and a detailed introduction to the key functionalities of the package is demonstrated with a simulated data set in the third paper (Section 4). Finally, some conclusion remarks are given and directions to future work are discussed (Section 5). The outline for this dissertation is as follows. Section 1 presents an in-depth background regarding panel data, CTMMs, and penalized regression methods, as well as an brief description of the TESAOD study design. Section 2 describes the first paper entitled "Regularized continuous-time Markov model via elastic net'". Section 3 describes the second paper entitled "Regularized continuous-time Markov model with exact death times and censored states"'. Section 4 describes the third paper "Regularized continuous-time Markov model for panel data: the markovnet package for R"'. Section 5 gives an overall summary and a discussion of future work.

The impact of fuel price changes can be seen in practically all sectors of the United States economy. Fuel prices directly and indirectly influence the daily life of most Americans. The national economy as well as the high standard of living we have come to enjoy in the United States is run on gasoline. Since the late 1990's the days of cheap oil and $1.00 gallons of gas are clearly over, understanding the influences of fuel price is more important now than ever. Since 1998 regular gasoline prices have increased $0.22 per gallon per year on average through the present with little evidence suggesting this trend will slow down or reverse substantially. The drastic and permanent change to the status quo of fuel prices has potentially rendered traditional knowledge of fuel price elasticities inapplicable to current analysis. Obtaining accurate measures of fuel price elasticities is important as it is used as a measure of personal mobility and can be related to the quality of life the public is experiencing. Price elasticities are also used in determining the future revenue available for surface transportation projects. Traditionally, short-run fuel price elasticities are thought to be inelastic allowing transportation agencies to ignore short-run fuel price changes to some degree when creating future projects and evaluating its economic feasibility. By using driving data collected from The National Evaluation of a Mileage-based Road User Study the fuel price elasticity of vehicle-miles traveled (VMT), as well as the sensitivity of gas prices relative to a historical high price, were estimated for the first year study participants using a panel data set approach with linear regression. The short-run fuel price elasticity of VMT was determined to be -1.71 with a range of -1.93 and -1.48. The elasticities found were significantly higher than the average short-run fuel price elasticity of -0.45 but can be rationalized by the impact poor economic conditions as well as the historically high fuel prices experienced prior to the researches time table had on the individuals driving behavior. The results suggest current short-run elasticities are not inelastic, if this trend continues transportation agencies must re-evaluate how they predict the future funding available for surface transportation projects.

The dissertation seeks to meld the two dominant competing theories of party identifi?cation in the US context: the expressive view, where Party ID is seen as a long standing psychological attachment to a political party; and the instrumental view, where Party ID is subject to reevaluation. Using ANES panel data, the paper examines both expressive and instrumental elements of partisanship. In keeping with past research, it finds strong evidence for the expressive understanding of Party ID; partisan groupings tend to be highly stable. However, the strength of identifications varies considerably over time, with perceptions of candidates, presidential approval, policy preferences, and ideological orientations driving these changes. These results are in keeping with an instrumental conceptualization of partisan identities.

The objective of this thesis is to investigate if the share of women in the municipality board affects the municipalities spending patterns. The study is based on the assumption that women as a group have particular needs, interest and concerns, and when represented, the political decision making will be affected. I used panel data over all 290 municipalities in Sweden over the years 2011, 2015 and 2019, to study the following public spending areas; reception of refugees, elderly care, education and childcare. I conducted a panel regression model with entity and time fixed effects and also added several control variables. The result suggests that there is a significant effect of female representation on spending related to the reception of refugees, but the effect of the other spending areas examined; childcare, education and care of elderly is negative but not significant.