This three-essay dissertation focuses on the political economy of fiscal rules in a comparative context and highlights their unintended consequences – an issue that has received relatively little attention in public financial management literature. The first essay examines whether numerical limits on deficits, or balanced budget rules, influence the composition of public spending, particularly in the social sector. Using a combination of fixed effects and GMM regressions on a large panel of developed and developing economies, this essay finds that while deficit targets are effective in improving fiscal balances, they also tend to reduce social spending on health and social protection. This effect is particularly prominent in democratic countries, which often witness overspending problems. Countries that are considering adoption of such rules should carefully examine the effects of these requirements on expenditures that may have long-term positive externalities. Policymakers should explore mechanisms to minimize the distortionary effects of fiscal limits on spending composition. The second essay focusses on whether the adoption of deficit targets by subnational governments in India influenced the composition of public spending. Using a combination of fixed effects and GMM regressions, this essay finds that the adoption of Fiscal Responsibility and Budget Management (FRBM) legislation by Indian states improved their budget balances significantly. However, the post-FRBM period also witnessed significant cuts in development spending. Furthermore, states have reduced their capital outlay and social spending after the adoption of fiscal responsibility laws. Reduced expenditure on development, and capital projects may affect long-term economic growth, therefore future amendments to the FRBM law should explore mechanisms to minimize the distortionary impacts of fiscal targets on the composition of subnational spending. The third essay shifts attention to the effect of supermajority voting requirements on credit ratings and borrowing costs in the subnational debt market in the United States. Using a combination of generalized ordered logit and linear regression analyses on a sample of general obligation bonds issued by American state governments between 2001 and 2014, this essay finds that states with supermajority voting requirements for tax increases are more likely to receive a lower credit rating on their bonds. Furthermore, on average, the states with a supermajority voting requirement pay a premium of 18 to 21 basis points in true interest cost for their bonds. States that are considering adopting supermajority requirements should consider the unintended effects in terms of lower credit ratings and higher borrowing costs while adopting or designing such fiscal rules. The findings of this dissertation inform the policy debate on the subject and improve our understanding of the impact of fiscal institutions that are being increasingly adopted to regulate the behavior of governments across the world.

Obezita představuje ve vyspělých zemích závažný zdravotní problém a hlavní rizikový faktor rozvoje kardiovaskulárních onemocnění, cukrovky 2. typu, nemocí pohybového aparátu a některých nádorových onemocnění. Je také provázena řadou komplikací a výrazně zhoršuje kvalitu života. 27 pacientů, kteří byli hospitalizováni za účelem redukce hmotnosti na oddělení D3 III. interní kliniky Všeobecné fakultní nemocnice v Praze v období ledna až počátku dubna roku 2017 byli sledováni z hlediska výskytu komorbidit a příjmu a výdeje energie za použití aplikace kaloricketabulky.cz, portálu casprozdravi.cz a krokoměrů Garmin Vivofit. Byla hodnocena vhodnost bioimpedanční metody pro sledování změn složení těla pacientů během redukčních pobytů za použití přístroje InBody S10. V souladu s teorií se ve sledované skupině pacientů vyskytovala v důsledku extrémní obezity celá řada komplikací. Diagnostická kritéria pro metabolický syndrom splňovalo 23 (85%) pacientů. Rozdílné hodnoty obsahu energie a jednotlivých živin v aplikacích kaloricketabulky.cz a Nutriservis jsou příčinou průměrného denního rozdílu 717 kJ mezi záznamy pacientů a nemocničním rozpisem. Průměrně pacienti ušli denně 4713 kroků. Pacienti průměrně zredukovali hmotnost o 7,6 kg (SD ±3,54). Bioimpedanční metoda vykazuje příliš vysokou variabilitu a není...

Introduction: Weight loss programs are based on inducing a negative energy balance by decreasing energy intake while increasing energy expenditure. Energy needs of obese patients are difficult to determine. The value of resting energy expenditure, as the largest component of the energy needs, is usually calculated to asses an adequate energy intake for obese patient. In clinical practice, predictive equations are most commonly used for this purpose, because of their simplicity, although many clinical studies have shown that in obese individuals they may generate errors large enough to impact the outcome of treatment. It leads to the prescription of an inadequate diet that does not meet the criterion of long-term sustainability. Objective: The aim of the thesis is to compare the values of resting energy expenditure (REE) measured by indirect calorimetry with values calculated with Harris-Benedict predictive equation in a selected group of obese individuals. Methods: The sample includes 38 subjects, 28 women and 10 men, patients of the General University Hospital in Prague. The average age is 48 ± 11,71 years, the mean BMI is 42,88 ± 9,09 kg/m2 . For each subject, resting energy expenditure was measured by indirect calorimetry and calculated by the Harris-Benedict predictive equation. Indirect...

Being able to effectively match energy intake to energy expenditure (EE) is an important aspect in preventing weight re-gain in the post-obese. Although it is generally agreed upon that resting EE decreases concomitantly with weight loss, there is no set standard comparing the deviations with differing weight loss protocols and additionally, controversy remains as to whether this decrease is greater than can predicted. In order to address these issues 2977 subjects were analyzed using a systematic review and the differences of both the protocol and length of various interventions in addition to sex were compared. Next, data was selected from this systematic review and 815 subjects were analyzed for weight loss-induced changes in resting EE, FM and FFM. Another subgroup of studies (n = 1450) was analyzed and compared against the Harris-Benedict prediction equation to determine whether the changes in resting EE were greater than what was expected. Finally, in order to determine which factors may be involved in regulating changes in resting EE during weight loss, a secondary analysis was performed on 28 post-menopausal women (age= 50.4 ± 2.0 yrs; BMI= 32.4 ± 5.2 kg/m²) who were submitted to a 6-month caloric restriction. Body composition (DXA), resting EE (indirect calorimetry), physical activity EE (PAEE) and total EE (TEE) (doubly-labelled water) were measured before and after the 6 month weight loss. Blood samples were collected before and after to measure leptin and peptide YY. The results indicate that there was indeed a depression in resting EE during weight loss regardless of the type of intervention utilized. Furthermore, these findings suggest that the changes could not fully be explained by changes of FM and FFM alone and that leptin may be an important contributor to the changes of resting EE during weight loss.

This study explores healthcare coverage disparity using a quantitative analysis on a large dataset from the United States. One of the objectives is to build supervised models including decision tree and neural network to study the efficient factors in healthcare coverage. We also discover groups of people with health coverage problems and inconsistencies by employing unsupervised modeling including K-Means clustering algorithm. Our modeling is based on the dataset retrieved from Medical Expenditure Panel Survey with 98,175 records in the original dataset. After pre-processing the data, including binning, cleaning, dealing with missing values, and balancing, it contains 26,932 records and 23 variables. We build 50 classification models in IBM SPSS Modeler employing decision tree and neural networks. The accuracy of the models varies between 76% and 81%. The models can predict the healthcare coverage for a new sample based on its significant attributes. We demonstrate that the decision tree models provide higher accuracy that the models based on neural networks. Also, having extensively analyzed the results, we discover the most efficient factors in healthcare coverage to be: access to care, age, poverty level of family, and race/ethnicity.

In this research, we apply data mining techniques to a nationally-representative expenditure data from the US to predict very high-cost patients in the top 5 cost percentiles, among the general population. Samples are derived from the Medical Expenditure Panel Survey’s Household Component data for 2006-2008 including 98,175 records. After pre-processing, partitioning and balancing the data, the final MEPS dataset with 31,704 records is modeled by Decision Trees (including C5.0 and CHAID), Neural Networks. Multiple predictive models are built and their performances are analyzed using various measures including correctness accuracy, G-mean, and Area under ROC Curve. We conclude that the CHAID tree returns the best G-mean and AUC measures for top performing predictive models ranging from 76% to 85%, and 0.812 to 0.942 units, respectively. Among a primary set of 66 attributes, the best predictors to estimate the top 5% high-cost population include individual’s overall health perception, history of blood cholesterol check, history of physical/sensory/mental limitations, age, and history of colonic prevention measures. It is worthy to note that we do not consider number of visits to care providers as a predictor since it has a high correlation with the expenditure, and does not offer a new insight to the data (i.e. it is a trivial predictor). We predict high-cost patients without knowing how many times the patient was visited by doctors or hospitalized. Consequently, the results from this study can be used by policy makers, health planners, and insurers to plan and improve delivery of health services.

The main objective of this thesis was to examine the independent effects of sleep duration and timing on appetite, food reward and energy balance. Study 1 investigated the associations between satiety quotient (SQ) with habitual, self-reported sleep duration, quality and timing. No significant associations were noted between SQ and sleep parameters. Short-duration sleepers had a lower mean SQ vs. those with ≥7h sleep/night (P=0.04). Study 2 evaluated associations between changes in sleep duration, efficiency and timing with changes in next day food reward. Greater sleep duration and earlier wake-times were associated with greater food reward (P=0.001). However, these associations were no longer significant after controlling for elapsed time between awakening and completion of the food reward task. Study 3 examined the effects of 50% sleep restriction (SR) anchored during the first (delayed bedtime) or second (advanced wake-time) half of the night on appetite, SQ, food reward, energy intake (EI) and energy expenditure (EE). Greater appetite ratings and explicit high-fat food reward were noted following SR with an advanced wake-time vs. control and SR with a delayed bedtime (P=0.03-0.01). No difference in SQ was noted between sessions. Energy and carbohydrate intakes were greater on day 2 and over 36h in the delayed bedtime vs. control session (P=0.03). Activity EE and moderate-intensity physical activity (PA) time were greater following delayed bedtime vs. control and advanced wake-time on day 1, whereas vigorous-intensity PA time was greater following advanced wake-time vs. delayed bedtime on day 1 (P=0.01-0.04). Greater sleep quality and slow-wave sleep duration between SR sessions were associated with lower EI and increased vigorous-intensity PA time, respectively (P=0.01-0.04). Collectively, these findings suggest that appetite, SQ and food reward are influenced by sleep parameters, but these changes may not alter EI. These findings also suggest that individuals with greater sleep quality in response to SR had greater vigorous-intensity activity time and lower EI.

Thesis is concerned with transferred competency of municipalities and its financing. There has come through a reform of public administration in the Czech Republic not long ago, which transferred a part of execution of state administration to municipalities. Thesis summarizes legal basis on which this process is realized. It also describes typology of municipalities and the extent of its transferred competence. Main part of this thesis is focused on analysis of transferred competency financing. Object of the thesis is to prove or to disprove an idea that the municipalities have to use their own funds to finance the execution of the state administration.

The diploma thesis deals with the crisis of the welfare state, which is causing problems in the public finance and deteriorating economic situation in many countries. Compares two groups of similar economic level OECD countries which spend the highest and the lowest social expenditure in percentage of GDP. Observes differences in their economic and demographic situation. The thesis also deals with the causes of the crisis and provides an example of successful economic reform, which significantly reduced growth of the welfare state and started a very successful economic period. The results of the analysis and the example of the reform provide some proposals for the welfare state cisis solution throught liberal way.

One of the key tasks ahead for EU countries is assessment and fight against poverty and social exclusion. Each member of european community has to concern with poverty measurement and prediction of households, which are by poverty endangered. Related to household income decrease under certain level (poverty line) is change of consumer behaviour, which can lead to increase of material inanition. This diploma work is therefore focused on determination of indicators, which either increase the risk of czech household decreasing below poverty line or monitor differences in customer behaviour of relatively "poor" and "rich" households.