Improving the Aggregation and Evaluation of NBA Mock Drafts

Many enthusiasts and experts publish forecasts of the order players are drafted into professional sports leagues, known as mock drafts. Using a novel dataset of mock drafts for the National Basketball Association (NBA), we analyze authors' mock draft accuracy over time and ask how we can reasonably use information from multiple authors. To measure how accurate mock drafts are, we assume that both mock drafts and the actual draft are ranked lists, and we propose that rank-biased distance (RBD) of Webber et al. (2010) is the appropriate error metric for mock draft accuracy. This is because RBD allows mock drafts to have a different length than the actual draft, accounts for players not appearing in both lists, and weights errors early in the draft more than errors later on. We validate that mock drafts, as expected, improve in accuracy over the course of a season, and that accuracy of the mock drafts produced right before their drafts is fairly stable across seasons. To be able to combine information from multiple mock drafts into a single consensus mock draft, we also propose a ranked-list combination method based on the ideas of ranked-choice voting. We show that our method provides improved forecasts over the standard Borda count combination method used for most similar analyses in sports, and that either combination method provides a more accurate forecast over time than any single author.Comment: 16 pages, 3 figure

The Environmental Impacts of Trade Liberalization: A Quantitative Analysis for the United States Using TEAM

A highly disaggregated emissions factor model is presented. The model generates changes in emissions and resource use by state and 6-digit NAICS sector. Removal of all U.S. import restrictions is examined. Results for agriculture show that composition effects explain highly varied regional patterns of emission changes. Scale effects are also important for expanding sectors. Quantitative assessments such as this may prove useful in conducting full environmental reviews of U.S. trade agreements consistent with Executive Order 13141 and the Free Trade Act of 2002.trade, emissions, input-output, residuals, International Relations/Trade,

Mississippi Kids Count: Early Childhood Education

Early education is crucial to supporting healthy childhood development and to providing a strong foundation for future schooling and general success. Defined as education between birth and age eight, early childhood education is associated with a wide range of positive outcomes for both the child as well as the community as a whole. Scientific studies suggest that participation in high quality early education, which includes elements such as trained and skilled teachers, small class sizes, and frequent child interaction and participation, improves cognitive and social development among all, but especially among low-income children. Research shows that children develop ninety percent of their adult-size brains in the first five years of life and therefore the provision of abundant information, proper stimulation and sufficient encouragement are keys to future success

Mississippi Kids Count: High School Graduation Rates

Though national dropout rates have generally fallen over the past twenty years, almost 1.2 million students in the United States drop out of school each year, representing nearly one-third of high school students. At about 61%, Mississippi’s high school graduation rate falls slightly below the national figure, though school districts in the Mississippi Delta fare particularly poorly. Five of the ten districts with the highest four-year dropout rates in the state are located in Delta region counties: Leflore, Tallahatchie, Sunflower, Tunica, and Panola Counties

Balancing model structure and flexibility in forecasting financial time series

This dissertation advances statistical methodology en route to providing new solutions to major questions in empirical finance. The common theme is the balance between structure and flexibility in these models. I show that structure, while it is potentially statistical bias, improves model performance when wisely chosen. Specifically, I look at asset returns' behavior: their relationship with firm characteristics, how they change over time, and what elements may cause their behavior. First, I investigate the forecasting of multiple risk premia. Using the content of Fisher et al. (2019a), I introduce a simulation-free method to model and forecast multiple asset returns and employ it to investigate the optimal ensemble of features to include when jointly predicting monthly stock and bond excess returns. This approach builds on the Bayesian Dynamic Linear Models of West and Harrison (1997), and it can objectively determine, through a fully automated procedure, both the optimal set of regressors to include in the predictive system and the degree to which the model coefficients, volatilities, and covariances should vary over time. When applied to a portfolio of five stock and bond returns, I find that my method leads to large forecast gains, both in statistical and economic terms. In particular, I find that relative to a standard no-predictability benchmark, the optimal combination of predictors, stochastic volatility, and time-varying covariances increases the annualized certainty equivalent returns of a leverage-constrained power utility investor by more than 500 basis points. Here, linear structure is chosen, and then I analyze what parameters should be flexible over time. Second, I consider the problem of determining which characteristics of a firm impact its stock returns. Using the content of Fisher et al. (2019b), I first model a firm's expected return as a nonlinear, nonparametric function of its observable characteristics. I investigate whether theoretically-motivated monotonicity constraints on characteristics and nonstationarity of the conditional expectation function provide statistical and economic benefit. Then, using this model, I provide an approach for characteristic selection using utility functions to summarize the posterior distribution. Standard unexplained volume, short-term reversal, size, and variants of momentum are found to be significant characteristics, and there is evidence that this set changes in time. The data also provide strong support for monotonicity in some of the characteristics' relationships with returns. Hence, the flexibility of the nonlinear, nonparametric curves are regulated by monotonic constraints. Finally, I turn to causal inference to ask which of these characteristics have causal relationships with asset returns. Hahn et al. (2018b) allow for regularized estimation of heterogeneous effects, and I modify their work to allow for non-binary, continuous treatments. This method is highly flexible at fitting complicated response surfaces with discontinuities, interactions, and nonlinearities, and thus benefits from added structure in the form of regularization from shrinkage priors. I demonstrate the model's ability to show the effect of firm size on returns, while controlling for book-to-market.Information, Risk, and Operations Management (IROM

Invasion of the Botnet Snatchers: A Case Study in Applied Malware Cyberdeception

In this paper, we provide the initial steps towards a botnet deception mechanism, which we call 2face. 2face provides deception capabilities in both directions – upward, to the command and control (CnC) server, and downward, towards the botnet nodes – to provide administrators with the tools they need to discover and eradicate an infestation within their network without alerting the botnet owner that they have been discovered. The key to 2face is a set of mechanisms for rapidly reverse engineering the protocols used within a botnet. The resulting protocol descriptions can then be used with the 2face network deception tool to generate high-quality deceptive messaging, against the attacker. As context for our work, we show how 2face can be used to help reverse engineer and then generate deceptive traffic for the Mirai protocol. We also discuss how this work could be extended to address future threats

MPST Software: grl_pef_check

This innovation is a tool used to verify and validate spacecraft sequences at the predicted events file (PEF) level for the GRAIL (Gravity Recovery and Interior Laboratory, see http://www.nasa. gov/mission_pages/grail/main/index. html) mission as part of the Multi-Mission Planning and Sequencing Team (MPST) operations process to reduce the possibility for errors. This tool is used to catch any sequence related errors or issues immediately after the seqgen modeling to streamline downstream processes. This script verifies and validates the seqgen modeling for the GRAIL MPST process. A PEF is provided as input, and dozens of checks are performed on it to verify and validate the command products including command content, command ordering, flight-rule violations, modeling boundary consistency, resource limits, and ground commanding consistency. By performing as many checks as early in the process as possible, grl_pef_check streamlines the MPST task of generating GRAIL command and modeled products on an aggressive schedule. By enumerating each check being performed, and clearly stating the criteria and assumptions made at each step, grl_pef_check can be used as a manual checklist as well as an automated tool. This helper script was written with a focus on enabling the user with the information they need in order to evaluate a sequence quickly and efficiently, while still keeping them informed and active in the overall sequencing process. grl_pef_check verifies and validates the modeling and sequence content prior to investing any more effort into the build. There are dozens of various items in the modeling run that need to be checked, which is a time-consuming and errorprone task. Currently, no software exists that provides this functionality. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission

Inflammatory pathophysiology as a contributor to myeloproliferative neoplasms

Myeloid neoplasms, including acute myeloid leukemia (AML), myeloproliferative neoplasms (MPNs), and myelodysplastic syndromes (MDS), feature clonal dominance and remodeling of the bone marrow niche in a manner that promotes malignant over non-malignant hematopoiesis. This take-over of hematopoiesis by the malignant clone is hypothesized to include hyperactivation of inflammatory signaling and overproduction of inflammatory cytokines. In th

Reducing Poverty in California…Permanently

If California were to seriously commit to equalizing opportunity and reducing poverty, how might that commitment best be realized? This is of course a hypothetical question, as there is no evidence that California is poised to make such a serious commitment, nor have many other states gone much beyond the usual lip-service proclamations. There are many reasons for California’s complacency, but an important one is that most people think that poverty is intractable and that viable solutions to it simply don’t exist. When Californians know what needs to be done, they tend to go forward and get it done. When, for example, the state’s roads are in disrepair, there are rarely paralyzing debates about exactly how to go about fixing them; instead we proceed with the needed repairs as soon as the funds to do so are appropriated. The same type of sure and certain prescription might appear to be unavailable when it comes to reducing poverty. It is hard not to be overwhelmed by the cacophony of voices yielding a thick stream of narrow-gauge interventions, new evaluations, and piecemeal proposals.1 Although the research literature on poverty is indeed large and may seem confusing, recent advances have in fact been so fundamental that it is now possible to develop a science-based response to poverty. In the past, the causes of poverty were not well understood, and major interventions, such as the War on Poverty, had to be built more on hunch than science. It is an altogether different matter now. The causes of poverty are well established, and the effects of many possible policy responses to poverty are likewise well established. The simple purpose of this essay is to assemble these advances into a coherent plan that would, if implemented, reduce poverty in California substantially