- Stochastic Demand Theory of Gene Regulation
- Exploratory Analysis of Price Changes in Business-to-Business Sales
Dr. Karaesmen Aydin
- Donor Disasters or Disaster Donors: Analysis of Data from the American Red Cross
Dr. Karaesmen Aydin
- Improving Measurements of Neighborhood Attributes at Multiple Spatial Scales Using the Geostatistical Method of Kriging
Dr. Michael Bader
- Affine Models of the Term Structure
- Special Education Technologies
Dr. Sarah Irvine Belson
- A Scientific Computing Toolkit for the Volunteer Grid
Dr. Michael Black
- Geospatial Determinants of Voting Behavior
- "Preliminary" Global Liquidity and Corporate Risk-Taking
Dr. Valentina Bruno
- Development of a Local Spatial Indicator of Association Based on Modified Moran's I
- Accelerating Social Science Analysis for a New Age (ASSANA): Moving from Traditional Methods for Analyzing Large Scale Text-Based Data to Socially Intelligent High-Performance Computational Methods
Dr. Derrick Cogburn
- Credit Ratings and the Cost of Municipal Financing
Kim Cornaggia, Jess Cornaggia, and Ryan Israelsen
- Home Bias in Credit Ratings: Evidence from Municipal Bonds
Kim Cornaggia, Jess Cornaggia, and Ryan Israelsen
- Revolving Doors on Wall Street
Kim Cornaggia, Jess Cornaggia, and Han Xia
- Terrorist Attacks during Ramadan
- Disasters, Federal Disaster Relief Policy, and Bankruptcy Filings
- Solving Twisty Puzzles
Dr. Donna Dietz
- Analysis of Periodic Point Processes
- Banks, Market Organization, and Macroeconomic Performance: An Agent-Based Computational Analysis
- Information Theoretic Modeling
Amos Golan, Skipper Seabold and Dr. Heath Henderson
- Ground Delay Programs
- Listening to Noise
- The Effect of Federal Subsidies on the Outcomes of Children in Foster Care
Drs. Mary Eschelbach Hansen and Kara Reynolds
- Standards of Proof in Child Welfare
Dr. Mary Eschelbach Hansen, Nick Kahn, and Josh Gupta-Kagan
- Ideological or Strategic? Using Electoral Loss to Understand Contribution Motivations
- Exploiting Entanglement for Simulation of Few Body Systems
Dr. Nathan Harshman
- Three Essays on the Interaction of Fiscal Shocks and Budgetary Constraints on the Public Education Sector
- Designing Novel Many-Body Quantum States of Ultracold Atoms Using Dynamically Transforming Optical Lattices
Dr. Philip R. Johnson
- Land Titling and Investment in Sub Saharan Africa
- Measuring Economic Uncertainty in the United States
- Revolutionary Pathways: The Effects of Domestic Revolutions
- Robust Long-Term Streamflow Forecasting
Dr. Inga Maslova
- Genetic Algorithms for Experimental Design
- Exchanging Fire: Trade, Conflict, and the Strategic Incentives of Indirect Economic Interdependence
- Forecasting Financial Data with Agent Based Models
- Examining Differential International Responses to HIV/AIDS
Dr. Nathan Paxton
- Color Vision and Hyperspectral Images
Dr. Arthur Shapiro
- An Adaptive Truncated Product Method
Dr. Xuguang Sheng
- Comorbidity of ASD and ADHD in the Brain
- Migration, Population imbalance and Decentralization in Indonesia
- Fundamentals, Derivatives Market Information and Oil Price Volatility
Jonathan Wallen and Michael Robe
- Characterization of Felid SINEs
- On the roots of truncated hypergeometric series over prime fields
Dr. Kenneth Ward
- Gender Impact of Malawi Input Subsidy
- Cost-Effectiveness of a Lifeline Telephone Crisis Center for Reducing Emergency Department Visits and Preventing Suicide, 2009-2014
Completed research projects supported by the Zorro HPC System are listed below, organized in reverse chronological order by start date:
Stochastic Demand Theory of Gene Regulation
Corinne Abolafia (MA Candidate, Mathematics)
Dr. Tuncay Alparslan (CAS/Mathematics and Statistics)
We develop a stochastic model based on continuous-time Markov chains for selection between different modes of gene regulation.
Thesis or Dissertation
MA Thesis, Mathematics, Stochastic Demand Theory of Gene Regulation, completed 2014.
Exploratory Analysis of Price Changes in
Dr. Karaesmen Aydin (Kogod/ITEC)
We investigate how salespeople use the information provided to them to set the prices in business-to-business transactions. Of particular interest to us is how salespeople use price recommendations coming from a decision support tool. We do this by building reduced-form models and testing those on a data set obtained by a grocery products distributor.
Donor Disasters or Disaster Donors:
Analysis of Data from the American Red Cross
Dr. Karaesmen Aydin (Kogod/ITEC)
There is a close relationship between donor behavior and marketing communications for every non-profit organization that relies on gifts from its donors to fund its services: Marketing communications and interactions may influence individual donor behavior and vice versa. Yet, in the end, what matters is not an individual donor and his gift but the total amount that has been collected. We participated in a research proposal competition and won an award, in the form of a data set, from the American Red Cross. In this project, we will build "explanatory" and "predictive" models to study donor behavior. Specifically, we will investigate what factors influence repeat donations, and how marketing communications influence the frequency and magnitude of giving.
Improving Measurements of Neighborhood Attributes at Multiple Spatial Scales Using the Geostatistical Method of Kriging
Dr. Michael Bader (CAS/Sociology)
With the growth of interest in accurately measuring neighborhood environments to study the influence of neighborhoods on individual-level outcomes, investigators have focused on improving two aspects of measurement: developing methods to create theoretically relevant measures and defining neighborhoods with relevant boundaries at appropriate spatial scales. Unfortunately, advancements made to improve the theoretical relevance of measures have been largely incompatible with defining appropriate neighborhood boundaries and vice-versa. In this paper, we argue that many neighborhood characteristics that social scientists are interested in studying should be conceptualized as changing from block-to-block rather than changing according to a patchwork of predefined discrete ecological units. We describe how a geostatistical method known as kriging can be combined with the existing econometric frameworkâ€"an innovative method for measuring theoretically relevant attributes of discrete, ecological unitsâ€"at small scales to develop city-block level estimates of theoretically nuanced measures that can then be flexibly reconfigured to multiple definitions of neighborhood boundaries. Using a cross-validation study with data from a 2002 systematic social observation of physical disorder on 1,663 city-blocks in Chicago, we show that this method creates valid results under assumptions of normality. We then demonstrate, using neighborhood measures aggregated to three different spatial scales, that the relationship between residents' perceptions of fear and neighborhood characteristics varies substantially across different spatial scales.
Bader, Michael DM, and Jennifer A. Ailshire. 2014. "Creating Measures of Theoretically Relevant Neighborhood Attributes at Multiple Spatial Scales," Sociological Methodology. Available: http://smx.sagepub.com/content/early/2014/02/07/0081175013516749.full
Affine Models of the Term Structure
Barton Baker, PhD candidate (CAS/Economics)
My dissertation topic is fitting and solution methods of affine models of the term structure. The first two chapters will focus on extending the applicability of informing macroeconomic variables to the pricing kernel of the time series of yields on government bonds of various maturities, focusing specifically on aggregate uncertainty (Chapter 1), and real time data (Chapter 2). This added information will be used to tested with out-of-sample tests in the U.S and possibly Europe. Chapter 3 will present a solution class written in Python and C that I wrote from scratch for affine models of the term structure and possibility present a broad theoretical approach to solving affine models of the term structure, with and without unobserved factors. Many of these calculations involve complex operations and many iterations, so the resources provided by the HPC will benefit me immensely.
Thesis or Dissertation
A computational approach to affine models of the term structure, completed 2014.
Special Education Technologies
Dr. Sarah Irvine Belson (CAS/SETH)
The objective of Dr. Irvine Belson's project is to design applications that allow teachers and students with behavioral disorders to collect behavioral data using handheld devices and then to manipulate the data in a virtual, 3D environment. While self-monitoring and self-graphing have been proven to support students' acquisition of socially appropriate and academically useful behaviors (Cartledge et al., 2008, Maag 1999), there has been little development of tools that allow teachers and students to study behaviors over time and across multiple settings. The study of behaviors across settings is critical because students who fail to meet teacher expectations of social behavior are at an increased risk for unfavorable school outcomes. For example, these students have poor interactions with teachers and peers, poor academic performance, and high rates of disciplinary problems (Nowicki, 2003). Dr. Irvine Belson has experience directing school-based research projects examining implementation of high-end technology and telecommuni-cations in the classroom. She has trained pre-service and in-service teachers in electronic communication and technology integration, and she serves as a consultant to schools and businesses on design, implementation, and analysis of technology-based applications for instruction.
The intellectual merit of this project lies in its pedagogical innovation. The use of handheld devices to generate data on behaviors that can be quickly and cheaply visualized has the potential to transform instruction in special education. The broader impact of this program lies in the contributions to the research based on technology in education and to broader society in the effect of these tools to support long-term student achievement.
The intellectual merit of Lawrence's project lies in its potential to untangle epistemological questions stemming from the differences between the spatial orientation of Native scholars and the temporal-historical orientations of non-Native scholars (Deloria, 1992; Meyer, 2008). The reconfiguration of the history of federal Indian policy through simultaneous sedimentary (corresponding to temporal-historical) and spatial analyses has the potential to reshape the study of education history by facilitating the incorporation of rich qualitative data. The broader impact of this research will be felt in the field of educational policy studies because sedimentary analysis could, for example, help make successful school programs more easily replicable.
A Scientific Computing Toolkit for the Volunteer Grid
Dr. Michael Black (CAS/Computer Science)
Dr. Black will implement a mathematics and scientific computing toolkit that uses volunteer grid computing resources. The toolkit will equip the proposed HPC server with software to solve common mathematics problems using large-scale volunteer parallel resources and an interface allowing researchers to submit problems to the server. The server will divide the problems into sub-problems and dispatch the sub-problems to volunteers' computers to solve while they would otherwise sit idle. The toolkit will utilize the volunteer grid using the Berkeley Open Infrastructure for Network Computing (BOINC) framework (Anderson, 2004). Existing parallel solutions to these applications generally require researchers to dedicate their own resources to the problem and to have experience with software development (Ghuloum, 2007). On the other hand, most existing BOINC projects are specialized. Software in the proposed toolkit will be designed to solve satisfiability equations, calculate gradient descent, and compute graph coloringâ€"very common problems. Dr. Black is prepared to complete this toolkit. He has published on porting the BOINC framework to new platforms (Black and Edgar, 2009) and has recently completed "proof-of-concept" satisfiability and gradient-descent solvers that use the BOINC framework.
The intellectual merit of this research lies in its innovative code to port the sub-problems through BOINC. The broader impact of this research lies in the potential of the toolkit to harness unused computing resources to help the worldwide community of researchers quickly solve important scientific problems.
Dr. Black's long-term research goal is to create a "meta BOINC project," not tied to any application, allowing less computer-savvy researchers to use the volunteer grid in their research and giving volunteers a single place they can go to contribute to many different research projects. The proposed toolkit is the first step in this meta-project.
Geospatial Determinants of Voting Behavior
Andrew Breza (SPA/Public Policy)
Faculty Sponsor: Alan Ford (CAS/GIS/Computer Science)
Does the distance that an individual lives from a polling place affect his or her likelihood of voting? Scholars and practitioners have written thousands of articles and books on why some people choose to vote while others do not, but many of them ignore local geography or focus on individual cities. This study seeks to calculate the decision to vote based on the distance that an individual lives from a polling place. Instead of focusing on a single city, as past researchers have done, this study uses the voter registration data and 2008 and 2012 voter histories from six states in order to generalize results. Because of the diversity of the sample, distance is regressed with several other independent variables, including access to and use of public transportation, income, unemployment, dominant local industries, and several other factors. Regressions will include a logistic regression with "Voted in person" as its dependent variable, and a multinomial logit regression with three dependent variables: voted in person, voted absentee, and did not vote. This study represents a unique contribution to voting choice literature due to the size and diversity of its sample, block-level demographic data, and use of a Geographic Information System (GIS).
"Preliminary" Global Liquidity and Corporate Risk-Taking
Dr. Valentina Bruno (Kogod/Finance)
I plan to investigate whether global liquidity provided by the intermediary sector through cross-border capital flows has increased the corporate risk-taking by firms before the financial crisis.
Bruno, Valentina, and Hyun Song Shin. 2014. "Globalization of corporate risk taking." Journal of International Business Studies. Available: http://www.palgrave-journals.com/doifinder/10.1057/jibs.2014.12
Development of a Local Spatial Indicator of Association Based on Modified Moran's I
Jess Chen (CAS/Economics)
Local indicators of spatial association (LISAs) are used to detect clusters in spatial data. I derive and implement a LISA based on Jackson et al.'s Modified Moran's I (2010). I also conduct a simulation study to compare the power of this test against that of existing LISAs under various scenarios of underlying populations, spatial weight matrices, local and global clusters, and various degrees of data sparseness. This is one part of my dissertation, which will be on methods and applications in spatial statistics.
"A New Local Indicator of Spatial Association," Robyn Rafferty Mathias Student Research Conference, March 2014 and Women in Stats Conference, May 2014
Thesis or Dissertation
"Local Spillovers in Bankruptcy: Analysis Using Local Modified Moran's I and Other Methods" (completed Oct 2016)
Accelerating Social Science Analysis for a New Age (ASSANA): Moving from Traditional Methods for Analyzing Large Scale Text-Based Data to Socially Intelligent High-Performance Computational Methods
Dr. Derrick Cogburn (SIS/International Communication)
The purpose of this project is to develop, test, refine and disseminate a repeatable interdisciplinary methodology and a related software tool for the computer-assisted analysis of large-scale text-based social science data. In keeping with the recent MOSAIC report , our overarching goal is to stimulate the next generation of social science research by providing analytical resources and interdisciplinary training to conduct textual analysis in PC and HPC environments. Key deliverables will be: 1) procedures for the ASSANA methodology; 2) an open-source HPC software tool; and 3) capacity building on ASSANA through workshops, seminars, and publications.
Credit Ratings and the Cost of Municipal Financing
Kim Cornaggia (KSB/Finance and Real Estate), Jess Cornaggia, and Ryan Israelsen
Moody's recalibrated its municipal bond rating scale in 2010, resulting in upgrades of zero to four notches on $2.2 trillion of bonds. We find the upgraded bonds earn abnormal returns, increasing in upgrade magnitude. Upgraded municipalities subsequently issue more bonds, relative to non-upgraded municipalities, and the new issues have lower relative offer yields. Additional tests indicate that ratings affect bond prices and debt capacity both because ratings provide information and because higher ratings reduce regulatory compliance costs. Overall, this recalibration event sheds light on the information environment in the municipal bond market and on the real effects of ratings.
Home Bias in Credit Ratings: Evidence from Municipal Bonds
Kim Cornaggia (KSB/Finance and Real Estate), Jess Cornaggia, and Ryan Israelsen
We identify detailed characteristics of lead credit analysts on municipal bond rating reports generated by Moody's and Standard & Poor's (S&P). We employ the lead analysts' state of origin, and separately state of education, to test for home bias in ratings. Controlling for analyst education, age, gender, and tenure, along with bond-month fixed effects, we find that home analysts award significantly higher ratings (more favorable to the issuer) compared to ratings from outside analysts. The effect is increasing in credit risk and expands affected municipalities' debt capacity. The effect on offer yields varies by rater. Because the effect is driven by analysts' states of origin, but not by where analysts reside at the time they produce ratings, we conclude that our results reflect favoritism by home analysts rather than superior information.
Revolving Doors on Wall Street
Kim Cornaggia (KSB/Finance and Real Estate), Jess Cornaggia, and Han Xia
Credit analysts often leave rating agencies to work at firms they rate. These analyst transfers provide a unique laboratory for studying revolving door effects. Benchmark rating agencies provide counterfactuals which allow us to measure rating inflation in a difference-in-differences framework. We find that analysts transitioning to managerial positions and to top banks become more favorable to their future employers prior to their transitions. Further, these conflicted ratings become less responsive to changes in market-based measures of hiring firms' credit quality. Our results reveal the presence of previously untested forces that affect information production by credit analysts.
Terrorist Attacks During Ramadan
Suat Cubukcu, Instructor, SPA/JLC
In this project, I would like to analyse the distribution of terrorist attacks during holy month Ramadan and other times.
Disasters, Federal Disaster Relief Policy,
and Bankruptcy Filings
Matthew Davis (CAS/Econ)
Bankruptcy is an important social program that annually results in the transfer of $42 billion from creditors to debtors, and its use has been increasing. According to the adverse events hypothesis, bankruptcy filings are triggered by a shock that pushes individuals "over the edge." Natural disasters are an important example of such a shock that affects many Americans. It has been noted that the bankruptcy rate increases in the period following hurricanes (Lawless, 2005). It is currently unknown how large this effect is, whether it pertains to other disaster types, or whether public funds expended to aid recovery following large disasters have an appreciable mitigating effect on such increases. This research project uses a new data set combining information on disasters, disaster declarations, and bankruptcy filings to determine the extent to which natural disasters increase bankruptcy rates and the extent to which different types of government aid mitigate increases.
Thesis or Dissertation
The Political Economy of National Disasters, Bankruptcy and Federal Disaster Aid, completed 2016.
Solving Twisty Puzzles
Donna Dietz (CAS/Mathematics)
Many solutions abound for the well-known Rubik's Cube puzzle. Similarly, any "twisty puzzle" made up of regular corner/edge/center pieces can be solved using basic tools of abstract algebra. However, if a sufficient number of pieces are fused together, a "bandaged puzzle" emerges, and the mathematics behind this is very complicated. In fact, it is known to be at least NP-hard, as a class of puzzles. All bandaging patterns for the standard Rubik's Cube have been solved, but beyond this, there is still much which is unknown about this class of puzzles. For a further explanation of the ideas in this paragraph, please see Jaap Scherphuis' explanation at: http://www.jaapsch.net/puzzles/pspace.htm
The project we are currently working on is to count (or estimate) the color-free configurations of a particular bandaging pattern for the Megaminx. The Megaminx is a dodecahedral puzzle with each face having a center, 5 edges, and 5 corners. The bandaging pattern we are investigating is one we found a pattern for on an internet chat board for twisty puzzles. (The thread is presently at: http://www.twistypuzzles.com/forum/viewtopic.php?f=9&t=18677)
Analysis of Periodic Point Processes
Kevin Duke (CAS/Mathematics)
Our work focuses on extracting information from periodic point processes. These problems arise in numerous situations, from radar pulse repetition interval analysis to bit synchronization in communication systems. We divide our analysis into two cases: periodic processes created by a single source, and those processes created by several sources. We wish to extract the fundamental period of the generators, and, in the second case, to deinterleave the processes. We are developing efficient algorithms for extracting the fundamental period from a set of sparse and noisy observations of single and multiple source periodic processes. The algorithms are computationally straightforward, stable with respect to noise, and converges quickly.
Banks, Market Organization, and Macroeconomic Performance: An Agent-Based Computational Analysis
Dr. Boris Gershman (CAS/Economics)
This project is an exploratory analysis of the role that banks play in supporting the mechanism of exchange. It considers a model economy in which exchange activities are facilitated and coordinated by a self-organizing network of entrepreneurial trading firms. Collectively, these firms play the part of the Walrasian auctioneer, matching buyers with sellers and helping the economy to approximate equilibrium prices that no individual is able to calculate. Banks affect macroeconomic performance in this economy because their lending activities facilitate entry of trading firms and also influence their exit decisions. Both entry and exit have conflicting effects on performance, and we resort to computational analysis to understand how they are resolved. Our analysis sheds new light on the conflict between micro-prudential bank regulation and macroeconomic stability. Specifically, it draws an important distinction between "normal" performance of the economy and "worst-case" scenarios, and shows that micro prudence conflicts with macro stability only in bad times. The analysis also shows that banks provide a "financial stabilizer" that in some respects can more than counteract the more familiar financial accelerator.
Information Theoretic Modeling
Dr. Amos Golan (CAS/Economics/Info-Metrics Institute)
Dr. Heath Henderson (Research Associate, Info-Metrics Institute)
Skipper Seabold (PhD Candidate, Economics)
This project, joint with Heath Henderson and Skipper Seabold, develops an improved information-theoretic estimator. It is a computational semi-intensive method that has proved to dominate other traditional methods for all finite and complex data.
Ground Delay Programs
Justin Grana (CAS/Economics)
We examine the potential for a simple auction to allocate arrival slots during Ground Delay Programs (GDPs) more efficiently than the currently used system. The analysis of these auctions uses Predictive Game Theory (PGT) , a new approach that produces a probability distribution over strategies instead of an equilibrium set. Furthermore, the game we consider is one of imperfect information and we show how averaging over priors still generates quantities of interest from the PGT distribution. We find that the second-price slot auction has the potential to lower social costs but further analysis is needed to determine which pre-GDP schedules are best suited for an auction.
"Decision-Theoretic Prediction and Policy Design of GDP Slot Auctions," American Institute of Aeronautics and Astronautics 2014-2163, J. Bono, D. Wolpert, D. Xie, and J. Grana, June 2014."
Listening to Noise
Justin Grana (CAS/Economics)
Faculty Sponsor: Alan Isaac (CAS/Econ)
Attempting to see if noise in trader activity influences the behavior of institutional traders.
The Effect of Federal Subsidies on the Outcomes of Children in Foster Care
Drs. Hansen and Reynolds will simulate the effect of extending federal subsidies to all children in foster care on the health outcomes of child victims of abuse and neglect. Currently, state child welfare systems cannot claim the same federal support for all of the children in foster care. States therefore have an incentive to provide more services to children who are eligible for federal support. This project will be the first to measure the extent to which eligibility for federal support influences services provided and health outcomes, and it will be the first to simulate the effect of broadening federal support to all children in foster care. It is critically important to understand how the structure of federal incentives affects outcomes because over $25 billion in child welfare services are provided annually to nearly a million children (DeVooght, Allen, and Geen, 2008). Dr. Hansen's expertise is in the economics of foster care policy. Hansen and Hansen (2006) and Hansen (2007, 2008) have shown that children who are eligible for federal subsidies for adoption after foster care get higher levels of support. The proposed project extends the work to consider health outcomes and services provided while children are still in foster care. Dr. Reynolds brings to the project her expertise in structural modeling (Feinberg and Reynolds, 2010; Reynolds (nee Olson, 2004), which is the preferred, but computationally-intensive, method for estimation of underlying policy invariant parameters in the policy simulation (Heckman, 2000).
Standards of Proof in Child Welfare
Mary Eschelbach Hansen (CAS/Econ), Nick Kahn (SPA/DPAP), and Josh Gupta-Kagan (Univ. of South Carolina School of Law)
We study the extent to which differences between states in the standards of proof required at the various stages of a case of child abuse or neglect influence the outcomes of the case.We use administrative data on all reports of child abuse and neglect as captured in the National Child Abuse and Neglect Data System, and we study the substantiation decision, the filing of a juvenile petition, and the decision to place children into foster care.
"The Standard of Proof in the Substantiation of Child Abuse and Neglect," George Mason University Public Choice Seminar, March 4, 2015.
Nicholas E. Kahn, Mary Eschelbach Hansen, and Josh Gupta-Kagan, "The Standard of Proof in the Substantiation of Child Abuse and Neglect", forthcoming in Journal of Empirical Legal Studies.
Ideological or Strategic? Using Electoral Loss to Understand Contribution Motivations
Political scientists have long noted the ideological nature of individual campaign contributors. Relative to PAC contributors, individuals are motivated by policy goals and seek to support candidates closest to their ideological ideal point. Yet, a similar line of research also argues that individual contributors tend to disperse their money across the country to ideological/partisan friends running in competitive elections. This project seeks to disentangle these two related, yet often times distinct motivations for individual campaign contributions: ideology and strategy. I argue that one can better understand the motivations of contributors by examining how contributors respond (in subsequent cycles) to losing elections. If contributors continue to contribute in the aftermath of loss (particularly persistent loss over time), then we can take this as an indicator of ideological motivations. By answering the open empirical question about how contributors respond to electoral loss, we can better understand campaign contributors. With an innovative empirical approach and an exhaustive behavioral measure of motivations, this research project is uniquely positioned to answer this question.
Exploiting Entanglement for Simulation of Few Body Systems
Dr. Nathan Harshman (CAS/Physics)
Team Members: Noel Klingler, Ryan Tillis
The goal of this project is to characterize entanglement in few body systems, and then to use this knowledge to optimize calculation and computation of few body dynamics. Few body systems are important at many physical scales, but this project will focus on atomic systems because implementations of quantum information processing devices, like ultracold atoms in optical lattices, require a precise understanding of few body dynamics. For example, few body effects are limiting sources of decoherence and loss in atomic interferometer experiments. The key to this method is that it finds a natural basis for efficient computation by choosing observables to describe the system such that energy eigenstates have minimal entanglement. For each additional particle in a simulation, complexity grows rapidly, and increases in efficiency become critical. More generally, studying entanglement is a theoretical probe that exposes kinematic and dynamical symmetries in both bound state and scattering problems. In this light, characterizing entanglement in few body systems shows how preferred physical observables are selected by the interactions even in complicated multiparticle systems. The outcomes of this project will include specific computational applications to cold atom systems and general results about entanglement in few body systems.
J. Revels, N.L. Harshman, Poster: "Optimized basis transformations for the symmetrization of a few ultra-cold atoms in a harmonic trap," APS March Meeting, Denver, March 2014.
Three Essays on the Interaction of Fiscal Shocks and Budgetary Constraints on the Public Education Sector
Michael Hayes (SPA)
My dissertation examines how budgetary constraints on school districts create a host of challenges for public managers, including higher levels of teacher turnover, as well as an unequal distribution of state funding across school districts. I plan to use the HPC to run bootstrapped quantile regressions.
Thesis or Dissertation
Three Essays on the Interaction of Fiscal Shocks and Budgetary Constraints on the Public Education Sector, completed 2014.
Modern Value Chains and the Organization of Agrarian Production
Empirical studies of agrarian production in developing countries often find that smallholders possess a productivity advantage over large farms. Eswaran and Kotwal famously derive this inverse farm-size/productivity relationship from the structure of agrarian production. Their model predicts that in otherwise equivalent economies a more egalitarian land distribution raises output and producer welfare. However, developing countries have experienced the rapid emergence of modern value chains. Recent research provides evidence that this transformation alters the welfare possibilities of agrarian economies. We therefore extend the Eswaran-Kotwal model by incorporating a modern value chain. In our model, the inverse farm-size/productivity relationship persists, but we contradict previous sanguine conclusions about egalitarian redistributions of the means of production. We find a potential equity/efficiency tradeoff in the distribution of land.
Thesis or Dissertation
"Nicaragua, the food crisis, and the future of smallholder agriculture."
Heath Henderson, Alan G. Isaac; Modern Value Chains and the Organization of Agrarian Production. American Journal of Agricultural Econonomics, 2017 aaw092. doi: 10.1093/ajae/aaw092
Designing Novel Many-Body Quantum States of Ultracold Atoms using Dynamically Transforming Optical Lattices
Dr. Philip R. Johnson (CAS/Physics)
The objective of Dr. Johnson's research is to develop and simulate a new method for creating and probing quantum states of ultracold matter not ordinarily existing in nature. He will use dynamical transformation of optical lattice potentials. Optical lattices are, essentially, crystals of light that can hold and control atoms suspended at the potential minima in a vacuum. The shapes of optical lattices can be dynamically transformed by manipulation of laser beams. Dr. Johnson will simulate the creation of quantum states by a sequence of single-well splitting and double-well merging operations on arbitrary pairings of adjacent lattice sites. Experimental tests of the simulations are within reach of leading experimental groups, including Dr. Johnson's collaborators at the Joint Quantum Institute of NIST and the University of Maryland, but experiments have not been performed because of the complexity of the modeling required to understand the physics. Dr. Johnson's previous work using numerical simulations of the macroscopic quantum mechanics of superconducting qubits uses similar methods (Johnson, 2003; Berkley 2003) and he has the requisite knowledge of optical lattices to carry out this work (Spielman, 2007; Johnson, 2009).
This research has intellectual merit because it designs a fundamentally new method for studying many-body states with optical lattices and because it is likely to yield explicit predictions that can be tested in the lab. Optical lattices have great promise as analogs for studying quantum phase transitions; therefore, the broader impact of the work is that it will contribute to the important goal of designing revolutionary materials such as high-temperature superconductors.
S. Paul, P.R. Johnson, E. Tiesinga, "Hubbard model for ultracold bosonic atoms interacting via zero-point-energy-induced three-body interactions", Physical Review A 93, 043616 (2016).
K.W. Mahmud, E. Tiesinga, P.R. Johnson, "Dynamically decoupled three-body interactions with applications to interaction-based quantum metrology", Physical Review A 90, 041602 Rapid Communications (2014). Selected as "Editors Suggestion".
X.Y. Yin, D. Blume, P.R. Johnson, E. Tiesinga, "Universal and nonuniversal effective N-body interactions for ultracold harmonically trapped few-atom systems", Physical Review A 90, 043631 (2014). Selected as "Editors Suggestion".
K.W. Mahmud, L. Jiang, P.R. Johnson, E. Tiesinga, "Collapse and revivals for systems of short-range phase coherence", New Journal of Physics 16, 103009 (2014).
K.W. Mahmud, L. Jiang, E. Tiesinga, P.R. Johnson, "Bloch oscillations and quench dynamics of interaction bosons in an optical lattice", Physical Review A 89, 023606 (2014).
E. Tiesinga, P.R. Johnson, "Quadrature interferometry for nonequilibrium ultracold atoms in optical lattices", Physical Review A 87, 013423 (2013).
P.R. Johnson, D. Blume, X.Y. Yin, W. Flynn, E. Tiesinga, "Effective renormalized multi-body interactions of harmonically confined ultracold neutral bosons", New Journal of Physics 14, 053037 (2012).
"Collapse-and-revival and effective interactions in optical lattices", Washington State University, Department Colloquium, Pullman, WA (March, 2015)
"Influence of trap anisotropy and dimensionality on perturbative effective 2- and 3- body interactions", Institute of Nuclear Theory, Program on Universality in Few Body Physics, University of Washington, Seattle, WA (April, 2014).
"Effective multibody interactions of confined ultracold bosons", 2013 Annual Meeting of the Division of Atomic, Molecular, and Optical Physics (DAMOP) of the American Physical Society (APS), Quebec, Canada (June 2013).
Land Titling and Investment in Sub Saharan Africa
Woubet Kassa Independent research student (CAS/Economy)
The role of property rights in resource allocation has been one of the central themes in development economics. There has existed extensive theoretical arguments that property rights in land are closely associated with the allocative efficiency of agricultural resources as well as investment decisions. However, empirical findings have not been conclusive. This has been complicated due to possible endogeneity of titles, unobserved hetrogeneities and the non-experimental nature of the data. This study employs various econometric tools to address these challenges using the Living Standards Measurement Study surveys of six Sub-Sahran African countries.
Measuring Economic Uncertainty in US States
This paper uses a database of primarily small, local news sources to assemble US state-level economic uncertainty measures. We report the quantity of news related to both uncertainty and a collection of economic terms as a share of the total news volume in the given time and place. The economic terms reflect local concerns focusing mainly on regionally-important industries, jobs and budgeting. This improves upon existing economic uncertainty measures in several ways. Existing measures are generally presented at the national level, which has the advantage of accommodating the use of common macroeconomic indicators, such as stock market volatility or GDP and inflation forecasts. The disadvantage is the loss of information inherent in such aggregation, particularly in a country as large and diverse as the United States where conditions in one state may vary widely from conditions in another. While news based indices do not necessarily suffer from this data constraint, in practice all existing measures we are aware of are national in scale, and maintain a focus on policy and finance that we show misses important signals of economic uncertainty. The data covers all 50 states from 1995 to 2015, and the results track well with both reasonable expectations and, in the case of non-war and non-terrorism related economic uncertainty, act as a leading indicator of state unemployment rates. When the process is re-run with more traditional policy and finance search terms, neither is true.
Revolutionary Pathways: The Effects of Domestic Revolutions
Edward Lucas (SIS)
How much and in what ways do individual leaders matter for international politics? This paper sheds new light on these questions by considering the consequences of domestic revolutions in international relations. We argue that revolutions have international effects due to two separate pathways, one associated with the event and one associated with the new leader's administration. In the first pathway, a revolutionary event disrupts established relationships and perceptions, both within the state and abroad. In the second pathway, revolutions put individuals into office who are more willing to challenge the status quo, and who have publicly committed to a sustained shift in policies during their administration. These two distinct pathways suggest that the important question about revolutions is not whether leaders or events matter most, but rather the conditions under which they matter. Consequently, we studied these pathways on three phenomena: international economic sanctions, domestic economic growth, and interstate alliances. We find that revolutionary events have a short-term negative effect on domestic economic growth, while revolutionary leaders have a long-term effect on the probability that a revolutionary state is targeted for sanctions. Both the revolutionary leader and its immediate events alter the state's international alliances. Our findings suggest that no single level of analysis completely dominates, and the answer depends on the outcome of interest.
Edward Lucas, "Revolutionary Pathways: Leaders and the International Impacts of Domestic Revolutions" American Political Science Association Annual Meeting, 2015
Colgan, Jeff, and Edward Lucas, "Revolutionary Pathways: Leaders and the International Impacts of Domestic Revolutions" International Interactions [forthcoming].
Colgan, Jeff, and Edward Lucas, "Revolutionary Pathways: Leaders and the International Impacts of Domestic Revolutions" International Interactions [forthcoming].
Robust Long-Term Streamflow Forecasting
Dr. Inga Maslova (CAS/Mathematics & Statistics)
The objective of this research project is to develop and demonstrate a new data-driven modeling approach to provide long-term forecasts of streamflow. The modeling approach will incorporate wavelet-based analysis techniques used in statistical signal processing and a multivariate relevance vector machine (MVRVM) that uses a Bayesian regression method. We will develop a methodology that detects patterns in changes in Pacific sea surface temperature (SST), snowpack and streamflow using wavelet decomposition. This information will then be used to improve the forecasting potential of the MVRVM.
I. Maslova,, A. M. Ticlavilca, and M. McKee, Adjusting wavelet-based multiresolution analysis boundary conditions for long-term streamflow forecasting. Hydrol. Process.,30: 5774. doi: 10.1002/hyp.10564, 2016.
Genetic Algorithms for Experimental Design
Ryan Moore (SPA/Government)
Blocking before treatments are assigned can improve the precision of causal estimates, make experimental estimates more robust to unlucky randomizations or inadequate parametric adjustment, and preserve power, even in relatively small group-randomized trials. But how should experimentalists best incorporate valuable covariate information into blocked designs? We focus on the critical question of setting the covariate weights that define the extent to which experimental units are similar or different. Using simulated and applied data, we assess the relative performance of covariate weights derived from two sources: first, from genetic matching algorithms which explicitly seek to optimize balance; second, from Mahalanobis distances without explicit balance-seeking. We show that balance in randomized experiments that use genetic covariate reweighting is superior to that obtained by random allocation, but also by Mahalanobis-metric blocking alone, even when done optimally. Further, we show that a genetic algorithm can directly improve the robustness of a design to unobserved confounding when tuned to do so. Our results provide guidance for experimentalists and offer new insights about how to improve practice in experimental design.
Exchanging Fire: Trade, Conflict, and the Strategic Incentives of Indirect Economic Interdependence
David Ohls (SIS)
How do indirect economic participation in common global networks of production and trade dampen conflict incentives between antagonistic pairs of states? Using a formal model of resource allocation in the context of dyadic conflict, I show that latent economic interdependence reduces fighting incentives. I then test this empirically using dyad-year panel data from 1948 to 2000. I find evidence consistent with the hypothesis that mutual reliance on the same outside trading partner and densely-linked trade networks strongly decreases the likelihood of interstate disputes and increases scores on conflict-cooperation scales. This effect is particularly strong in rivalrous dyads, which frequently come into conflict; although such pairs of states tend to have have limited direct economic engagement, they often share great underlying structural potential for cooperation. These results have important implications for theoretical research on the links between economics and security, dyadic rivalries, and the role of third parties in international disputes.
Forecasting Financial Data with Agent Based Models
PhD Candidate Georgi Panterov (CAS/Economics)
The purpose of this research is to build a rich, multi-agent artificial stock market where agents have endogenous expectations. Agents are able to act as sophisticated econometricians employing modern methods like Artificial Neural Networks and Genetic Algorithms. Unlike in standard financial models, agents are able to learn and update expectations using various Bayesian and non-Bayesian rules. This project will build a model that replicates some of the standard characteristics of financial markets such as volatility clustering and fat tail return distributions. At the end, there will be an attempt to calibrate the model using some real world price/orders data.
Examining Differential International Responses to HIV/AIDS
Dr. Nathan Paxton (SIS)
This project explores the role that organizational learning processes play in state HIV/AIDS policy development. The puzzle addressed is the large degree of variation in policy output across states that are similar in terms of political or economic character. Although one can tell individual stories about each country, the overall variation defies the cross-applicability of many typical explanations. Where states better draw lessons from experience we should expect two results. First, structural characteristics of the state or of the set of HIV policy responders affects the character and degree of learning: the configuration of decision-making authority and information analytics interacts with the learning process, affecting the lessons drawn and policies pursued. Second, over time we observe some degree of policy convergence among states due to comparison and adaptation from others. The dissertation employs a mixed-methods approach. As a plausibility probe, econometric analysis tests for such patterns. The research employs an original dataset of 72 countries over 6 years and approximately 25 variables. To address data missingness, multiple imputation techniques were used. There were statistically and substantively significant relationships and patterns, indicating further exploration of the underlying processes.
Color vision and hyperspectral images
Dr. Arthur Shapiro (CAS/Psychology)
The laboratory is investigating various aspects of color vision. In particular, we are analyzing hyperspectral images in order to develop algorithms to defeat camouflage of human-made objects.
An Adaptive Truncated Product Method
Dr. Xuguang Sheng (CAS/Economics)
In the multiple testing literature, Zaykin et al. (2002) developed a truncated product method that combines only those p-values less than some pre-specified threshold, but the lack of a clear choice of truncation point becomes a major obstacle to its more widespread use. We solve this problem by proposing an adaptive truncated product method that optimizes the selection of the truncation point among a set of candidate cut-off values. We then develop a bootstrap re-sampling procedure to efficiently estimate the distribution of the adaptive method. We illustrate the performance of the proposed method through Monte Carlo simulation and an empirical example in the context of panel cointegration tests.
Sheng, X. and L. Cheng, Combinations of "Combinations of P-values," forthcoming in Empirical Economics
Sheng, X. and J Yang, Truncated Product Methods for Panel Unit Root Tests (2013), Oxford Bulletin of Economics and Statistics, vol. 75, pp. 624-636.
Sheng, X. and J Yang, An Adaptive Truncated Product Method for Combining Dependent P-values (2013), Economics Letters, vol. 119, pp. 180-182.
2nd Annual Conference of the International Association for Applied Econometrics (IAAE), Thessaloniki, Greece, 2015
22nd Symposium of the Society for Nonlinear Dynamics and Econometrics (SNDE), New York, NY, 2014
American Economic Association (AEA) Annual Meeting, Chicago, IL, 2012
North American Summer Meeting of the Econometric Society, St. Louis, MO, 2011
Comorbidity of ASD and ADHD in the Brain
Devon Shook, Independent Research Student (BCAN/CAS)
Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder are two of the most commonly diagnosed developmental disorders and often co-occur in the same child. Neuroimaging research on both disorders has consistently found the cerebellum to be a site of structural and functional abnormality. However, until the DSM-5 allowed for a comorbid diagnosis, study of their shared etiology has been a challenge. In the present study, we investigate the structural and functional abnormalities of comorbid ASD and ADHD with a particular focus on the cerebellum.
Migration, Population Imbalance and Decentralization in Indonesia
Smriti Tiwari Independent research student (CAS/Economics)
Most studies on migration focus on the impact of migration and/or remittances on the economic development of the migrant sending countries. But would better opportunities at home generated through economic development deter migrants? By using the unique features of decentralization in Indonesia, this paper aims to get at the role of local development on migration behaviors. In the case of Indonesia, it will also shed light on its implications, if any, on the differences in population pressures.
Thesis or Dissertation
Development and migration interactions using natural experiments, completed 2015
Smriti Tiwari. Does Local Development Influence Outmigration Decisions? Evidence from Indonesia. Forthcoming in World Development http://dx.doi.org/10.1016/j.worlddev.2016.12.028
Fundamentals, Derivatives Market Information,
and Oil Price Volatility
Jonathan Wallen and Michael Robe (KSB/Finance and Real Estate)
We investigate price volatility in the West Texas Intermediate (WTI) and Brent crude oil markets between 2000 and 2014. We provide empirical evidence of a relationship between the term structure of option-implied volatilities and global macroeconomic conditions, physical market fundamentals (OPEC surplus output capacity, oil storage) and economy-wide financial uncertainty (captured by the equity VIX). Based on public data regarding trader positions in U.S. futures markets, the intensity of oil speculation is statistically insignificant. Unexpected disruptions in the crude oil space are associated with large regression residuals. Our findings suggest that derivatives ("paper") markets contain information on the magnitude and duration of major oil market disruptions.
Robe, Michel A., and Jonathan Wallen. "Fundamentals, Derivatives Market Information and Oil Price Volatility." Journal of Futures Markets 36, no. 4 (2016): 317-344. http://onlinelibrary.wiley.com/doi/10.1002/fut.21732/full
Characterization of Felid SINEs
Kathryn Walters-Conte (CAS/Biology)
Short-interspersed nuclear elements (SINEs) comprise a class of nuclear DNA that can define evolutionary history. Abundant in mammalian genomes, these transposable elements can characterize lineages. A SINE family'CanSINE' has been described in the order Carnivora. We are pursing examination of these motifs in the Feliformia suborder (cat-like animals) and Felidae family (cats) with respect to the distribution of conserved and non-conserved insertion sites, the utility of these sequences as markers for hybridized cats and the implementation of SINEs as tools in undergraduate education.
Internal Grant Proposal
"Transposable Elements as Markers of Hybrid Felines and Beacons of Cellular Diversity," 2014.
On the roots of truncated hypergeometric series
over prime fields
We consider natural truncations of the hypergeometric functions 2F1, 3F2, and the Kummer hypergeometric functions 1F1 over the finite field Fp, for primes p. For the associated polynomials Q (of degree proportional to p), we obtain bounds for the number of roots of various congruences Q modulo p, which correspond to rational point counts where methods from algebraic geometry fail. Via a correspondence to families of elliptic curves, we obtain sharp bounds in some cases. We also show that the functions 2F1 and 3F2 are associated with K3 surfaces, including some previously studied for their modularity. For the Kummer hypergeometrics, we obtain a power saving for a large class of the parameter values within an algebraic closure of Fp by modification of methods from transcendence theory.
"Cyclotomy in finite field arithmetic," Keynote speech, Algebra seminar, University of Pennsylvania, 2016.
"Factoring curves over finite fields," Talk, Number Theory Seminar, Dartmouth College, 2016.
"A few open problems in lifting," Paper presentation, Mathematics Seminar, University of Athens, Greece, 2016.
Gender Impact of Malawi Input Subsidy
Paul Winters (CAS/Economics) and Wendy Karamba (CAS/Economics)
Alleviating gender differences in agricultural productivity is not only a matter of equity but it is vital for poverty reduction. While a number of studies suggest that gender differences in agricultural productivity are a result of female farmers having limited access to resources, few studies investigate the role of agricultural interventions in alleviating the constraints to input use and subsequently the gender gap in productivity. For the first time, this study investigates whether there are gendered gains in agricultural productivity from participating in an input subsidy program. Using nationally-representative data that is disaggregated at the plot level, this study analyzes the large-scale voucher-based Farm Input Subsidy Program in Malawi. Focusing on the total value of output per hectare, the relationships are evaluated using weighted estimators where the weights are constructed from propensity scores since beneficiaries are not randomly selected. Spatial fixed effects are employed to deal with the unobservables that may confound the relationship between program participation and productivity.
Karamba, R. Wendy, and Paul C. Winters. "Gender and agricultural productivity: implications of the Farm Input Subsidy Program in Malawi." Agricultural Economics 46, no. 3 (2015): 357-374.
Cost-Effectiveness of a Lifeline Telephone Crisis Center for Reducing Emergency Department Visits and Preventing Suicide, 2009-2014
Brian Yates (CAS/Psychology) and Katheryn Ryan (PhD candidate)
Suicide is a serious public health problem with considerable societal costs. However, few previous studies have compared the costs of suicide prevention programs to positive outcomes for society as well as the individual. Suicide prevention hotlines are widespread and provide suicide prevention for callers in crisis. However, the cost-effectiveness of such hotlines is unknown. This study will obtain data from a large Lifeline call center serving a tri-state area in the United States for the period January 1, 2009 to January 1, 2014. We will test whether the empirically-based Lethality Assessment conducted by Lifeline workers leads high-risk callers to seek emergency department (ED) services. As EDs can be over-utilized by suicidal persons, we hypothesize that Lifeline can triage only those callers who need immediate medical care. Lifeline is a low-cost option to ED care for low-risk callers. This research includes the immediate and direct costs of preventable ED visits related to suicide. Additionally, we hypothesize that Lifeline is a cost-effective suicide prevention program in that it increases Quality Adjusted Life Years (QALYs) for high-risk callers who receive ED care. The cost-utility analysis of QALYs will examine, whether the cost of operating Lifeline yields an economic benefit a low incremental cost ratio for service operations compared to QALYs gained.
Thesis or Dissertation
Katheryn Ryan, Costs, benefits, and quality-adjusted life years of a lifeline crisis center, 2009 through 2013," completed 2015.
Katheryn Ryan and Brian Yates, Costs, Benefits, and Quality Adjusted Life Years of a Lifeline Crisis Center, 2009 through 2013