Sales tax enforcement: An empirical analysis of compliance enforcement methodologies and pathologies

Most research on tax evasion has focused on the income tax. Sales tax evasion has been largely ignored and dismissed as immaterial. This paper explored the differences between income tax and sales tax evasion and demonstrated that sales tax enforcement is deserving of and requires the use of different tools to achieve compliance. Specifically, the major enforcement problem with sales tax is not evasion: it is theft perpetrated by companies that act as collection agents for the state. Companies engage in a principal-agent relationship with the state and many retain funds collected as an agent of the state for private use. As such, the act of sales tax theft bears more resemblance to embezzlement than to income tax evasion. It has long been assumed that the sales tax is nearly evasion free, and state revenue departments report voluntary compliance in a manner that perpetuates this myth. Current sales tax compliance enforcement methodologies are similar in form to income tax compliance enforcement methodologies and are based largely on trust. The primary focus is on delinquent filers with a very small percentage of businesses subject to audit. As a result, there is a very large group of noncompliant businesses who file on time and fly below the radar while stealing millions of taxpayer dollars. ^ The author utilized a variety of statistical methods with actual field data derived from operations of the Southern Region Criminal Investigations Unit of the Florida Department of Revenue to evaluate current and proposed sales tax compliance enforcement methodologies in a quasi-experimental, time series research design and to set forth a typology of sales tax evaders. This study showed that current estimates of voluntary compliance in sales tax systems are seriously and significantly overstated and that current enforcement methodologies are inadequate to identify the majority of violators and enforce compliance. Sales tax evasion is modeled using the theory of planned behavior and Cressey’s fraud triangle and it is demonstrated that proactive enforcement activities, characterized by substantial contact with non-delinquent taxpayers, results in superior ability to identify noncompliance and provides a structure through which noncompliant businesses can be rehabilitated.^

Does management capacity increase organizational performance? An empirical analysis of public housing agencies

Since the 1990s, scholars have paid special attention to public management’s role in theory and research under the assumption that effective management is one of the primary means for achieving superior performance. To some extent, this was influenced by popular business writings of the 1980s as well as the reinventing literature of the 1990s. A number of case studies but limited quantitative research papers have been published showing that management matters in the performance of public organizations. ^ My study examined whether or not management capacity increased organizational performance using quantitative techniques. The specific research problem analyzed was whether significant differences existed between high and average performing public housing agencies on select criteria identified in the Government Performance Project (GPP) management capacity model, and whether this model could predict outcome performance measures in a statistically significant manner, while controlling for exogenous influences. My model included two of four GPP management subsystems (human resources and information technology), integration and alignment of subsystems, and an overall managing for results framework. It also included environmental and client control variables that were hypothesized to affect performance independent of management action. ^ Descriptive results of survey responses showed high performing agencies with better scores on most high performance dimensions of individual criteria, suggesting support for the model; however, quantitative analysis found limited statistically significant differences between high and average performers and limited predictive power of the model. My analysis led to the following major conclusions: past performance was the strongest predictor of present performance; high unionization hurt performance; and budget related criterion mattered more for high performance than other model factors. As to the specific research question, management capacity may be necessary but it is not sufficient to increase performance. ^ The research suggested managers may benefit by implementing best practices identified through the GPP model. The usefulness of the model could be improved by adding direct service delivery to the model, which may also improve its predictive power. Finally, there are abundant tested concepts and tools designed to improve system performance that are available for practitioners designed to improve management subsystem support of direct service delivery.^

An empirical analysis of the global audit market: International Financial Reporting Standards-related changes and differences within the Big 4 global networks

Ongoing debates within the professional and academic communities have raised a number of questions specific to the international audit market. This dissertation consists of three related essays that address such issues. First, I examine whether the propensity to switch between auditors of different sizes (i.e., Big 4 versus non-Big 4) changes as adoption of International Financial Reporting Standards (IFRS) becomes a more common phenomenon, arguing that smaller auditors have an opportunity to invest in necessary skills and training needed to enter this market. Findings suggest that clients are relatively less (more) likely to switch to (away from) a Big 4 auditor if the client's adoption of IFRS occurs in more recent years. ^ In the second essay, I draw on these inferences and test whether the change in audit fees in the year of IFRS adoption changes over time. As the market becomes less concentrated, larger auditors becomes less able to demand a premium for their services. Consistent with my arguments, results suggest that the change in audit service fees declines over time, although this effect seems concentrated among the Big 4. I also find that this effect is partially attributable to a differential effect of the auditors' experience in pricing audit services related to IFRS based on the period in which adoption occurs. The results of these two essays offer important implications to policy debates on the costs and benefits of IFRS adoption. ^ In the third essay, I differentiate Big 4 auditors into three classifications—Parent firms, Brand Name affiliates, and Local affiliates—and test for differences in audit fee premiums (relative to non-Big 4 auditors) and audit quality. Results suggest that there is significant heterogeneity between the three classifications based on both of these characteristics, which is an important consideration for future research. Overall, this dissertation provides additional insights into a variety of aspects of the global audit market.^

Household Preferences for Financing Hurricane Risk Mitigation: A Survey Based Empirical Analysis

After a series of major storms over the last 20 years, the state of financing for U.S. natural disaster insurance has undergone substantial disruptions causing many federal and state backed programs against residential property damage to become severally underfunded. In order to regain actuarial soundness, policy makers have proposed a shift to a system that reflects risk-based pricing for property insurance. We examine survey responses from 1394 single-family homeowners in the state of Florida for support of several natural disaster mitigation policy reforms. Utilizing a partial proportional odds model we test for effects of location, risk perception, socio-economic and housing characteristics on support for policy reforms. Our findings suggest residents across the state, not just risk-prone homeowners, support the current subsidized model. We also examine several other policy questions from the survey to verify our initial results. Finally, the implications of our findings are discussed to provide inputs to policymakers.

Financial constraints on research and development

This dissertation examines whether-there exists financial constraints and, if so, their implications for investment in research and development expenditures. It develops a theoretical model of credit rationing and research and development in which both are determined simultaneously and endogenously. The model provides a useful tool to examine different policies that may help alleviate the negative the effect of financial constraints faced by firms.^ The empirical evidence presented deals with two different cases, namely, the motor vehicle industry in Germany (1970-1990) and the electrical machinery industry In Spain (1975-1990).^ The innovation in the empirical analysis is that it follows a novel approach to identify events that allow us to isolate the effect of financial constraints in the determination of research and development.^ Further, empirical evidence is presented to show that in the above two cases financial constraints affect investment in physical capital as well.^ The empirical evidence presented supports the results of the theoretical model developed in this dissertation, showing that financial constraints negatively affect the rate of growth of innovation by reducing the intensity of research and development activity. ^

Essays in environmental economic valuation and decision making in the presence of an environmental disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

Three essays on the interrelationships among financial restatements, corporate governance, market microstructure and the firm's rate of return

The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature did not differentiate between single and multiple restatements announcements. This research investigated the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm’s rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examined the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigated how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results supported the non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examined the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examined the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supported the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examined the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis showed that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

Four essays of environmental risk-mitigation

Expected damages of environmental risks depend both on their intensities and probabilities. There is very little control over probabilities of climate related disasters such as hurricanes. Therefore, researchers of social science are interested identifying preparation and mitigation measures that build human resilience to disasters and avoid serious loss. Conversely, environmental degradation, which is a process through which the natural environment is compromised in some way, has been accelerated by human activities. As scientists are finding effective ways on how to prevent and reduce pollution, the society often fails to adopt these effective preventive methods. Researchers of psychological and contextual characterization offer specific lessons for policy interventions that encourage human efforts to reduce pollution. This dissertation addresses four discussions of effective policy regimes encouraging pro-environmental preference in consumption and production, and promoting risk mitigation behavior in the face of natural hazards. The first essay describes how the speed of adoption of environment friendly technologies is driven largely by consumers' preferences and their learning dynamics rather than producers' choice. The second essay is an empirical analysis of a choice experiment to understand preferences for energy efficient investments. The empirical analysis suggests that subjects tend to increase energy efficient investment when they pay a pollution tax proportional to the total expenditure on energy consumption. However, investments in energy efficiency seem to be crowded out when subjects have the option to buy health insurance to cover pollution related health risks. In context of hurricane risk mitigation and in evidence of recently adopted My Safe Florida Home (MSFH) program by the State of Florida, the third essay shows that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow home inspection to seek mitigation information. The fourth essay evaluates the impact of utility disruption on household well being based on the responses of a household-level phone survey in the wake of hurricane Wilma. Findings highlight the need for significant investment to enhance the capacity of rapid utility restoration after a hurricane event in the context of South Florida.

Four Essays of Environmental Risk-Mitigation

Expected damages of environmental risks depend both on their intensities and probabilities. There is very little control over probabilities of climate related disasters such as hurricanes. Therefore, researchers of social science are interested identifying preparation and mitigation measures that build human resilience to disasters and avoid serious loss. Conversely, environmental degradation, which is a process through which the natural environment is compromised in some way, has been accelerated by human activities. As scientists are finding effective ways on how to prevent and reduce pollution, the society often fails to adopt these effective preventive methods. Researchers of psychological and contextual characterization offer specific lessons for policy interventions that encourage human efforts to reduce pollution. This dissertation addresses four discussions of effective policy regimes encouraging pro-environmental preference in consumption and production, and promoting risk mitigation behavior in the face of natural hazards. The first essay describes how the speed of adoption of environment friendly technologies is driven largely by consumers’ preferences and their learning dynamics rather than producers’ choice. The second essay is an empirical analysis of a choice experiment to understand preferences for energy efficient investments. The empirical analysis suggests that subjects tend to increase energy efficient investment when they pay a pollution tax proportional to the total expenditure on energy consumption. However, investments in energy efficiency seem to be crowded out when subjects have the option to buy health insurance to cover pollution related health risks. In context of hurricane risk mitigation and in evidence of recently adopted My Safe Florida Home (MSFH) program by the State of Florida, the third essay shows that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow home inspection to seek mitigation information. The fourth essay evaluates the impact of utility disruption on household well being based on the responses of a household-level phone survey in the wake of hurricane Wilma. Findings highlight the need for significant investment to enhance the capacity of rapid utility restoration after a hurricane event in the context of South Florida.

Metahistoria nacional y metaficcion biografica en "Historia de Mayta", de Mario Vargas Llosa

The thesis explores Mario Vargas Llosa's Historia de Mayta in light of recent studies of Latin America's new historical novel (Menton, Juan-Navarro) and in connection with contemporary literary theory (Waugh, Stonehill) and new trends in the philosophy of history (White, Foucault). In my study, I focus on three major levels of analysis: (1) significant events in Peruvian history to which the novel alludes; (2) biographical elements that strongly evoke the lives of Ernesto "Che" Guevara, Jacinto Renteria, and Vargas Llosa himself; and (3) the self-referential devices that aim at questioning the validity of empirical analysis in both fiction and history. The allegorical dimension of the novel's view of modern Peruvian politics, its biographical component, and the self-consciousness of its historiographic approach make of Historia de Mayta both a metahistory of Peru and a biographical metafiction. The thesis ultimately reveals the problematic borderline between fiction and reality, the novel and history.

A multi-method approach for the assessment of composite indices and rankings

There is growing popularity in the use of composite indices and rankings for cross-organizational benchmarking. However, little attention has been paid to alternative methods and procedures for the computation of these indices and how the use of such methods may impact the resulting indices and rankings. This dissertation developed an approach for assessing composite indices and rankings based on the integration of a number of methods for aggregation, data transformation and attribute weighting involved in their computation. The integrated model developed is based on the simulation of composite indices using methods and procedures proposed in the area of multi-criteria decision making (MCDM) and knowledge discovery in databases (KDD). The approach developed in this dissertation was automated through an IT artifact that was designed, developed and evaluated based on the framework and guidelines of the design science paradigm of information systems research. This artifact dynamically generates multiple versions of indices and rankings by considering different methodological scenarios according to user specified parameters. The computerized implementation was done in Visual Basic for Excel 2007. Using different performance measures, the artifact produces a number of excel outputs for the comparison and assessment of the indices and rankings. In order to evaluate the efficacy of the artifact and its underlying approach, a full empirical analysis was conducted using the World Bank's Doing Business database for the year 2010, which includes ten sub-indices (each corresponding to different areas of the business environment and regulation) for 183 countries. The output results, which were obtained using 115 methodological scenarios for the assessment of this index and its ten sub-indices, indicated that the variability of the component indicators considered in each case influenced the sensitivity of the rankings to the methodological choices. Overall, the results of our multi-method assessment were consistent with the World Bank rankings except in cases where the indices involved cost indicators measured in per capita income which yielded more sensitive results. Low income level countries exhibited more sensitivity in their rankings and less agreement between the benchmark rankings and our multi-method based rankings than higher income country groups.

Essays in book -tax income differences and analyst forecasts /recommendations

Prior research suggests that book-tax income differences (BTD) relate to both firms' earnings quality and operating performance. In this dissertation, I explore whether and how financial analysts signal the implications of BTD efficiently. This dissertation is comprised of three essays on BTD. The three essays seek to develop a better understanding of how financial analysts utilize information reflected in BTD (derived from the ratio of taxable income to book income). The first essay is a review and discussion of prior research regarding BTD. The second essay of this dissertation investigates the role of BTD in indicating the consensus and dispersion of analyst recommendations. I find that sell recommendations are positively related to BTD. I also document that analyst coverage has a positive effect on the standard deviation of consensus recommendations with respect to BTD. The third essay is an empirical analysis of analysts' forecast optimism, analyst coverage, and BTD. I find a negative association between forecast optimism and BTD. My results are consistent with a larger BTD being associated with less forecast bias. Overall, I interpret the sum of the evidence as being consistent with BTD reflecting information about earnings quality, and consistent with analysts examining and using this information in making decisions regarding both forecasts and recommendations.

Essays in Environmental Economic Valuation and Decision Making in the Presence of an Environmental Disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.