Essays on Fiscal Institutions, Public Expenditures, and Debt

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

Role of delayed light polymerization of a dual-cured composite base on marginal adaptation of class II posterior composite open-sandwich restoration

Objective: To determine the effect of delayed light polymerization of a dual-cured composite base material on the marginal adaptation of class II composite restoration. Materials and Methods: 35 extracted human molar teeth were used to prepare class II mesio-occlusal or disto-occlusal slot preparations with gingival margins at the CEJ. The teeth were restored using an open-sandwich technique with a 2mm base increment of dual-cured composite, and divided into 5 groups based on the mode of the polymerization of the dual-cured composite base: Group A - self-cured after placement (5 mins), Group B - light-cured immediately after placement, Group C - light-cured 30 seconds after placement, Group D - light-cured 60 seconds after placement, Group E - light-cured 120 seconds after placement. Then a top layer of a light-cured composite resin is placed to complete the restoration. The teeth were thermocycled and immersed in 1% aqueous solution of methylene blue for 24 hours. Sectioning of the teeth and scoring under stereomicroscope was done. Data will be statistically evaluated using the kruskal wallis 1-way ANOVA. Results: Statistical analysis using kruskal wallis 1-way ANOVA showed that the dual-cured composite light polymerized 1 minute after placement exhibited the least microleakage. Conclusion: Delayed light polymerization of the dual-cured composite base reduced the microleakage in class II open-sandwich restorations

The effect of Remin Pro® on bleached enamel hardness: An in-vitro study

Introduction: Remineralization as a treatment procedure has received a lot of attention both from clinicians as well as researchers. The objective of this study was to assess the effect of Remin Pro® on enamel microhardness after bleaching the teeth with McInnes bleaching agent using Vickers microhardness tester. Materials and Methods: In this study, freshly extracted ten central incisors were taken which were subjected to baseline indentation by using Vickers microhardness indenter and then McInnes bleaching solution was applied for 5 min to demineralize these teeth. Remin Pro a newer remineralizing agent was applied for 7 days, which showed an increase in microhardness at the end of 7 days. Results: The values were subjected for statistical analysis using paired t-test. All the samples showed a decrease in the microhardness after bleaching with McInnes solution. The decrease in mean hardness from baseline to demineralization was found to be statistically significant (P < 0.001). However, remineralizing the same tooth with Remin Pro for 7 days, showed an increase in hardness, which was found to be statistically significant (P < 0.05). Conclusion: McInnes bleaching agent decreases the microhardness of enamel and Remin Pro® used in the study causes an increase in the microhardness of bleached enamel

Effective Automated Feature Construction and Selection for Classification of Biological Sequences

<div><p>Background</p><p>Many open problems in bioinformatics involve elucidating underlying functional signals in biological sequences. DNA sequences, in particular, are characterized by rich architectures in which functional signals are increasingly found to combine local and distal interactions at the nucleotide level. Problems of interest include detection of regulatory regions, splice sites, exons, hypersensitive sites, and more. These problems naturally lend themselves to formulation as classification problems in machine learning. When classification is based on features extracted from the sequences under investigation, success is critically dependent on the chosen set of features.</p><p>Methodology</p><p>We present an algorithmic framework (EFFECT) for automated detection of functional signals in biological sequences. We focus here on classification problems involving DNA sequences which state-of-the-art work in machine learning shows to be challenging and involve complex combinations of local and distal features. EFFECT uses a two-stage process to first construct a set of candidate sequence-based features and then select a most effective subset for the classification task at hand. Both stages make heavy use of evolutionary algorithms to efficiently guide the search towards informative features capable of discriminating between sequences that contain a particular functional signal and those that do not.</p><p>Results</p><p>To demonstrate its generality, EFFECT is applied to three separate problems of importance in DNA research: the recognition of hypersensitive sites, splice sites, and ALU sites. Comparisons with state-of-the-art algorithms show that the framework is both general and powerful. In addition, a detailed analysis of the constructed features shows that they contain valuable biological information about DNA architecture, allowing biologists and other researchers to directly inspect the features and potentially use the insights obtained to assist wet-laboratory studies on retainment or modification of a specific signal. Code, documentation, and all data for the applications presented here are provided for the community at <a href="http://www.cs.gmu.edu/~ashehu/?q=OurTools" target="_blank">http://www.cs.gmu.edu/~ashehu/?q=OurTools</a>.</p></div

Disjunction Features combining one positional and one negation of compositional feature.

<p>Disjunction Features combining one positional and one negation of compositional feature.</p