Essays on Law Enforcement Incentives

Law enforcement incentives have become a relevant discussion topic in recent years. Starting with sheriff offices, elections may introduce different incentives for sheriffs, impacting arrest rates and other behaviors around election periods. My first chapter examines the impact of both the primary and general elections on arrest rates in sheriff jurisdictions. Results show that offices led by a sheriff running for re-election see a decrease of 0:19 arrests per 1,000 capita following a loss in the primary. Offices with incumbents who win the primary but proceed to lose the general show 0:62 fewer arrests per 1,000 capita in the month following the general election. Further results indicate the decline following the loss in the general election stems mostly from drug arrests. These results suggest the electoral structure influences sheriff behavior, negatively impacting sheriff productivity, indicating substantial costs to elections, and possibly indicating different incentives across sheriffs during the election season. Revenue generated through the criminal justice system has also been shown to cause a change in the incentive structure of law enforcement agencies. I show evidence of this first in my second chapter through a second-stage estimation of the effect of civil asset forfeiture laws on estimated law enforcement technical efficiency scores. Agencies allowed to retain proceeds from asset seizure have an incentive to generate revenue. I estimate how counties utilize police personnel and expenditures to maximize crime deterrence and incident clearances. Technical efficiency estimates are computed at the county level from 2007 and 2012 data using the variable returns to scale data envelopment analysis estimator. To reduce estimation error and to allow for faster convergence, I use dimension reduction to estimate the Farrell output measure of police efficiency for county-level data. After testing for separability, results of a second-stage truncated regression show that the higher the allowed percentage of retained assets for a county, the more inefficient the county is at making arrests and deterring crime. I conclude in my third chapter by discussing the growing law enforcement revenue generation incentive and how law enforcement revenues have become a key component of local government budgets across the United States. While numerous restrictions exist to constrain traditional sources of revenue, only recently have legislators introduced checks on the fiscal profitability of fines, fees, forfeitures, and asset seizures. Left unrestricted, fiscal incentives have demonstrably manifested in the enforcement patterns and discretionary decisions of police. The transformation of officers into agents of revenue creation leads to increased targeting of minority populations and out-of-towners, with emphasis on arrests that yield potential property seizure, with negative consequences for both community trust and the provision of public safety. Those burdened with legal financial obligations are disproportionately poor, positioning the criminal justice system as a pointedly regressive form of taxation. We discuss the mechanisms behind criminal justice revenue generation, the consequences to law enforcement outcomes, and policies designed to reform and mitigate revenue-driven law enforcement

In search of owners : lessons of experience with privatization and corporate governance in transition economies

The author reviews the goals of privatization and evaluates various methods used to achieve them in different transition settings. The task is not only to change ownership but to create corporate governance and to further the development of legal norms and supporting institutions needed in full-fledged market economies. Initial results of privatization programs are only part of the picture. How they foster further evolution of ownership is equally important. Experiments in privatization abound, from extensive efforts at sales to strategic owners (as in Estonia and Hungary), to programs based primarily on insider buyouts (as in Russia and Slovenia), to innovative mass privatization programs involving the creation of large and powerful new financial intermediaries (as in the Czech and Slovak Republics and Poland). Each approach has inherent strengths and risks. But if the objectives are to severe the links between the state and the enterprise, to school the population in market basics, and to foster further ownership change, the initial weight of evidence seems to favor significant reliance on voucher privatization, especially given the difficulty most countries have finding willing cash investors. Formal programs of enterprise privatization are often only a small part of the picture, although they get the most attention. Even where formal privatization has been slow (as in Bulgaria and the Ukraine), a process of asset"recombination"is occurring, often behind the scenes - whether a recombination from state to private firms or from some private firms to others. In the Czech Republic, for example, the ownership of enterprise shares by funds or fund shares by individuals will change through formal and informal trading, but the ownership of enterprise assets may also shift to some extent as owners or managers sell or spin-off assets into new companies. In Russia, this shifting of assets to new, more closely held firms may be quite widespread, as managers with small minority ownership stakes in newly privatized firms try to gain greater control over assets. As one Hungarian observer noted, this is the period of"primitive capital accumulation"in the post-socialist world. Formal programs may lay important ground rules but uncertainties of every type overwhelm most formal efforts at privatization. The final outcome is far from predictable.Banks&Banking Reform,Financial Crisis Management&Restructuring,International Terrorism&Counterterrorism,Economic Theory&Research,Municipal Financial Management,Economic Systems,Economic Theory&Research,Banks&Banking Reform,Municipal Financial Management,Financial Crisis Management&Restructuring

TOWARDS A HOLISTIC RISK MODEL FOR SAFEGUARDING THE PHARMACEUTICAL SUPPLY CHAIN: CAPTURING THE HUMAN-INDUCED RISK TO DRUG QUALITY

Counterfeit, adulterated, and misbranded medicines in the pharmaceutical supply chain (PSC) are a critical problem. Regulators charged with safeguarding the supply chain are facing shrinking resources for inspections while concurrently facing increasing demands posed by new drug products being manufactured at more sites in the US and abroad. To mitigate risk, the University of Kentucky (UK) Central Pharmacy Drug Quality Study (DQS) tests injectable drugs dispensed within the UK hospital. Using FT-NIR spectrometry coupled with machine learning techniques the team identifies and flags potentially contaminated drugs for further testing and possible removal from the pharmacy. Teams like the DQS are always working with limited equipment, time, and staffing resources. Scanning every vial immediately before use is infeasible and drugs must be prioritized for analysis. A risk scoring system coupled with batch sampling techniques is currently used in the DQS. However, a risk scoring system only allows the team to know about the risks to the PSC today. It doesn’t let us predict what the risks will be in the future. To begin bridging this gap in predictive modeling capabilities the authors assert that models must incorporate the human element. A sister project to the DQS, the Drug Quality Game (DGC), enables humans and all of their unpredictability to be inserted into a virtual PSC. The DQG approach was adopted as a means of capturing human creativity, imagination, and problem-solving skills. Current methods of prioritizing drug scans rely heavily on drug cost, sole-source status, warning letters, equipment and material specifications. However, humans, not machines, commit fraud. Given that even one defective drug product could have catastrophic consequences this project will improve risk-based modeling by equipping future models to identify and incorporate human-induced risks, expanding the overall landscape of risk-based modeling. This exploratory study tested the following hypotheses (1) a useful game system able to simulate real-life humans and their actions in a pharmaceutical manufacturing process can be designed and deployed, (2) there are variables in the game that are predictive of human-induced risks to the PSC, and (3) the game can identify ways in which bad actors can “game the system” (GTS) to produce counterfeit, adulterated, and misbranded drugs. A commercial-off-the-shelf (COTS) game, BigPharma, was used as the basis of a game system able to simulate the human subjects and their actions in a pharmaceutical manufacturing process. BigPharma was selected as it provides a low-cost, time-efficient virtual environment that captures the major elements of a pharmaceutical business- research, marketing, and manufacturing/processing. Running Big Pharma with a Python shell enables researchers to implement specific GxP-related tasks (Good x Practice, where x=Manufacturing, Clinical, Research, etc.) not provided in the COTS BigPharma game. Results from players\u27 interaction with the Python shell/Big Pharma environment suggest that the game can identify both variables predictive of human-induced risks to the PSC and ways in which bad actors may GTS. For example, company profitability emerged as one variable predictive of successful GTS. Player\u27s unethical in-game techniques matched well with observations seen within the DQS

The analysis and use of motor vehicle telemetry data

In order to operate a vehicle, information about the vehicle must be communicated to the operator, as it is difficult or impossible to determine otherwise. Information such as vehicle speed, remaining fuel or whether seatbelts are on can be measured and transmitted electrically. Some measurements can be specific to a vehicle type or require processing with other metrics to provide value. The measurements can be displayed immediately or stored for a longer period of time before they are sent for a longer time period analysis. Besides the immediate need to access vital operating metrics, there are also other uses for gathered data. Analyzing measurements from a longer period of time can show trends in time. Combining various metrics can also provide a tangible metric for more abstract concepts, such as vehicle efficiency, convenience or safety. Data is also more valuable if gathered from a larger number of similar vehicles. A larger business can use a larger dataset to obtain good comparison points and a robust average for future estimates. The value derived from vehicle telemetry in businesses appears in different forms. Most notably, business analytics can be applied to reduce vehicle downtime and predict future profits and costs. The performance of hired drivers can also be compared to each other to improve performance by rewarding good driving practices. Measurements a vehicle makes can also be used to discover indicators for parts wear and predict future failures. Vehicle telemetry is not only limited to private use, as services such as vehicle live location are brought to consumers as well through different applications. In the future, more data is required for more complicated applications. For autonomous vehicles, the vehicle will require measurements an operator would normally make themselves, such as a visual of other vehicles. Besides the operating capacity, the ability to detect wear and smaller malfunctions within the vehicle itself is imperative, as there might be no person to notice and report them. A concrete stepping stone for this is the ability to track passengers within the vehicle. For public transportation, the vehicle must know when passengers are done entering and leaving. If the amount of people is measured, it is also possible to deduce the number of people inside the vehicle at a given point in time. This information can be used by a business to measure the number of passenger miles a vehicle provides, or by consumers in order to avoid crowded transportation vehicles

Perspectives on sabbaticals and job satisfaction in nonprofit organizations

For mission-driven organizations with limited resources to invest in employee salary and development, retaining top talent is a critical challenge. The monetary toll of turnover is particularly harmful to small organizations, which make up 66.3 percent of the nonprofit sector. To keep staff satisfied and incentivized to stay, nonprofits need to innovate creative new strategies to retain employees. The nonprofit sabbatical, a period of rest and renewal given to reward years of service, is one possible solution to reduce burnout and reward longevity. This exploratory study investigated the benefits and challenges of nonprofit sabbaticals in relation to theories of job satisfaction. To gather perspectives on the sabbatical experience, the researcher conducted cross-industry interviews with prior sabbatical recipients, nonprofit human resource practitioners, and direct service nonprofit staff. The research goal was to deepen general understanding of the sabbatical experience, including conditions for and barriers to success. This study reports the findings, compiles recommendations for the best ways to implement sabbaticals in nonprofit organizations, and examines the implications of sabbatical for various stakeholders. It is the hope of the researcher that this study will help nonprofits to consider how the sabbatical reward might motivate overall job satisfaction for employees in mission-driven roles

Entrepreneurial Operations Management

In the presence of tight capital, time and talent constraints, many traditional operational challenges are reinforced (and sometimes redefined) in the entrepreneurial setting. This dissertation addresses some of these challenges by examining theoretically and experimentally several problems in entrepreneurship and innovation for which the existing literature offers little guidance. The dissertation is organized into three chapters. When tight time-to-market constraints are binding an important question in product development is how much time a development team should spend on generating new ideas and designs vs executing the idea, and who should make that decision. In the first chapter of this dissertation I develop an experimental approach to examining this question. Entrepreneurial ventures can have limited (often zero) cash inflow and limited access to capital, and so use equity ownership to compensate founders and early employees. In the second chapter I focus on the challenges of equity-based incentive design, examining the effects of contract form (equal vs non-equal equity splits) and time (upfront vs. delayed contracting) on effort and value generation in startups. In "technology-push" (relative to "demand-pull") innovation, technology teams often develop a new capability that may find voice in a wide range of industrial settings. However, the team may lack the appropriate marketing budget to explore each in great depth, or even all of them at any depth. In the third chapter I study entrepreneurial market identification, developing and testing search strategies for choosing a market for a new technology when the number of potential markets is large but the search budget is small.PHDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145946/1/ekagan_1.pd