information technology services
Summary of Research Projects
We ask each research group to submit a short abstract describing their work using the Linux Cluster. The current projects using the cluster, arranged alphabetically by research group, are:
James Anderson (Economics)
The project is going to econometrically estimate implicit trade costs for some 450 commodities for over 100 countries using bilateral trade flow data (around 10,000 observations). Stage 1 is this estimation. Stage 2 is the use of these trade costs to calculate their incidence on the seller and buyer sides of the market. For each commodity, the incidence calculation requires the solution of some 100 nonlinear equations in as many unknowns. In order to create confidence intervals for the incidence calculations, the nonlinear system must be solved many times.
S. Anukriti (Economics)
My research focuses on topics in development economics, demography, and the economics of gender. In ongoing work, I use data from large-scale household surveys to examine (a) whether financial incentives can simultaneously decrease fertility and the sex ratio at birth in societies with a strong preference for sons and (b) the effects of trade liberalizationon fertility and child survival in India.
Pierluigi Balduzzi (Finance)
The project examines whether and how time-variation in the daily return co-movements between developed markets and emerging markets as a whole can be linked to measures of developed stock markets uncertainty. Preliminary findings suggest that developed markets uncertainty has important cross-market pricing influences. The project will examine the dynamics of correlations cross equity markets using DCC-GARCH models and Regime-Shifting models with time varying Markov transition probabilities. The project will also investigate unconditional portfolio performance of policies that take into account time-varying correlations.
Stephanie Berzin (Social Work)
The Graduate School of Social Work team will use the Cluster for various examinations of adolescent health using the National Longitudinal Study of Adolescent Health (Add Health). Access to a nationally representative, longitudinal data set will allow for faculty and students to investigate a variety of health topics related to youth, such as racial and social disparities in sexually transmitted infections, and stress-related mental health disparities among sexual minorities.
Christopher Baum (Economics)
This project evaluates various behavioral risk factors in a public health context, including the effect of tobacco taxes and smoke-free legislation on mothers' smoking and babies' birthweight; the relation between smoke-free legislation and the incidence of childhood asthma; and the use of tobacco products by adolescents.
Kevin Bedell (Physics)
Our project is focused on the study of exotic collective modes in the magnetically ordered systems based on the Landau Fermi liquid theory. We use the Landau kinetic equation in the spin channel, to study the dynamics of the fluctuation to the ground state we start with. By solving the kinetic equation in the hydrodynamic region, we can determine the dispersion of the collective modes. We also calculate the spin response function of the system to further study the dispersion and the effect of the collective modes to the ground state.
Alexander Bleier (Marketing)
In the current reseach project we investigate the effectiveness of retargeting, an increasingly employed method of personalized online advertising. In retargeting, firms track consumers’ individual shopping behaviors in their online stores to provide them with individualized banner ads as they continue browsing the Internet. Using field experiments as well as observational data, we analyze click-stream data at the individual consumer level to infer behavioral changes induced by the exposition to differentially personalized ads.
Henry Braun (LSOE)
This project uses a conditional growth chart method to track student academic growth. This method is based on a regression model called quantile regression. The specific part that requires intensive computing is a simulation extrapolation (SIMEX) method that we apply to quantile regression to correct for measurement error-induced bias, since student academic achievements are measured by test scores which contain considerable amount of measurement error. The basic idea of the SIMEX method is to add simulated additional measurement error with increasing variance to the original data in a resampling-like stage, identify a trend of measurement error-induced bias versus the variance of the added measurement error, and extrapolate the trend back to the pointwith no measurement error.
David Broido (Physics)
Our research group focusses on the study of heat transport in bulk and nanostructured semiconductor materials. Our goal is to develop an accurate theoretical approach that will allow us to provide guidance to experimental groups who perform measurements of these materials, as well as contributing to the development of new nanomaterials engineered for specific applications. We are employing state-of-the-art computational methods (for example, ab initio and adiabatic bond charge calculations of phonon dispersions, iterative solution of phonon Boltzmann equation) in this effort that require multiple fast cpu's and substantial memory.
K.S. Burch (Physics)
We look at the lattice vibrations in various materials, with a goal of understanding their role in material properties. Our interest is in comparing theoretical predictions with experimental measurements made with Infrared and Raman spectroscopy to gain insight into the origins of anomalous phonon response. The also enables us to guide future design of materials with optimized properties.
Jeffrey A. Byers (Chemistry)
The Byers group will use the Cluster for the molecular modeling of transition metal complexes. These complexes will be used as catalysts for important chemical transformations in organic chemistry, inorganic chemistry, and materials science. Theoretical investigations carried out with Gaussian and/or Jaguar will be invaluable to the catalyst development process
Rocio Calvo (Social Work)
Few studies have focused on the social determinants of health disparities among second-generation immigrants. This project explores individual-level determinants of health disparities such as race, income, social and human capital on health disparities among a
representative sample of post-1965 immigrants in the United States. We seek to answer the following questions: (1) how self-reported depression, obesity, well-being, etc. vary across ethnic/racial groups and over time as respondents enter young adulthood; (2) what individual and contextual factors determine depression, obesity, well-being, etc.; (3) what social mechanisms underlie the relationship between individual and contextual-level characteristics and the social determinants of health among the second-generation in the US.
David A. Chapman (Finance)
I examine households' optimal consumption/saving and portfolio allocation policies under alternative Social Security policy changes designed to address the long-term solvency of the Social Security system. Households have generalized disappointment aversion utility, and they receive exogenous labor income and Social Security tax and annuity formulas that follow the actual policies. Financial markets consist of a risk-free asset and a single risky asset with constant expected returns and a lognormal distribution. I compute the optimal policies of different households across the labor income distribution where income is calibrated to match the heterogeneity found in the prior literature.
Ryan Chahrour (Economics)
Economists have traditionally viewed prices as extremely efficient mechanisms for transmitting individuals' private information to others. My research seeks to understand when this view is justified and when and how prices may fail to fully transmit relevant information. Solving dynamic models where prices transmit information is computationally challenging and requires both new algorithms and substantial computational resources. I will use the cluster to advance my research and solve more complex versions of the model described in www.chahrour.net/Intersectoral_Linkages_Information.pdf
Thomas J. Chemmanur (Finance)
We study that social network has first-order effect on the portfolio holdings and trades for mutual fund managers. We examine whether there is valuable information transmitted through the network or the effect is due to the herding behavior of professional money managers.
Peter Clote (Biology)
Our work involves developing new algorithms concerning RNA structure prediction (protein as well). Our algorithms run in times of O(n4) and O(n5) with space an order of magnitude less.
Timothy Connolly (Biology)
The primary objective of the project is to introduce students to some basic concepts of bioinformatics and re-enforce concepts in genetics and genomics in order to improve their understanding of the biological predispositions to disease, disease processes and potential avenues to treat disease. The field of genomics and bioinformatics is having a significant impact in the field of Biology and Medicine.
Using a web user interface, and a series of real public genomic datasets, undergraduate students can bioinformatics methods used to analyze genome-scale data in regard to real world, unmet scientific challenges where genomic technologies are having an impact. A series of presentations, manuals and guide workflows will help student ability to acquire large genomic datasets and use different computational methods used to analyze these datasets. Using a guided series of small objective exercises to introduce individual approaches, students can gain hands-on experience with various approaches to genomic analyses. In doing so, students can gauge their interest in the field of bioinformatics and computational biology.
Thomas Crea (Social Work)
This project seeks to answer a number of research questions using the National Longitudinal Study of Adolescent Health (Add Health), including the following: an examination of how neighborhood context contributes to the racial and social disparities in sexually transmitted infections among young adults in the United States; an exploration into the relationship between childhood maltreatment and risk taking behavior over time; an examination of how peer networks, social capital, and adolescent friendships serve as protective factors against long-term risk and promote long-term wellbeing, using social network analyses of friendships nested within contextual/neighborhood data; and an exploration the influence of natural mentor relationships on emotional well-being among sexual minority youth in comparison to non-sexual minority youth. Our research will also examine topics including youth with disabilities, sexual minority youth, health outcomes for immigrant youth, transitional living and aging out of foster care, siblings as a protective factor for child maltreatment, and developmental trajectories for youth who have experienced trauma.
Patricia Doherty (Institute for Scientific Research)
Our research efforts have included the study of ionospheric data from probes measuring electron and ion densities, auroral electron precipitation and atmospheric infrared visible and ultraviolet emissions. We develop, validate and update various models that propagate electromagnetic waves under quiescent and disturbed conditions. These models facilitate data comparisons and theoretical calculations requiring a background atmosphere, as well as providing convenient engineering solutions.
Marek Domin (Mass Spectometry)
The Linux computational cluster is used for processing large batches of data, for both targeted and non-targeted metabolomics analysis. Typical MS data processing workflow comprises, raw data file import, filtering/smoothing, peak picking, peak list deisotoping, alignment, gap filling and normalization. We use MZmine 2, an open source software toolbox for LC-MS data processing. The MZmine 2 modules cover all these workflow stages and also include additional functionality for the visualization and interpretation of the results.
Eyal Dvir (Economics)
Recent empirical work has shown that incomplete exchange rate pass-through is found overwhelmingly at the wholesale level. This unexpected finding, which holds in a variety of industries, raises again the question: how are wholesale prices set, relative to retail prices? I focus on large retailers, such as Wal-Mart, who source goods from a worldwide pool of suppliers. This paper presents a model of international trade, where these retailers must decide how best to procure production services in a Ricardian environment. Under certain conditions, it can be shown that these importers choose suppliers by means of a discriminatory procurement auction at the wholesale level. A main result of the model is that importers will respond to shocks which affect any one of their suppliers by smoothing the shock across all of their suppliers. Essentially, importers will change the discrimination rules governing their auctions in favor of the adversely affected suppliers, thus forcing the unaffected suppliers to share the cost of the shock by lowering their bids. This novel mechanism of shock accommodation explains how by appropriately changing the rules of their procurement auctions, large retailers can effectively insulate themselves from cost shocks, including exchange rate shocks. This implies incomplete pass-through at the wholesale level. Another implication is that low exchange rate pass-through to import prices, a feature of international price data, need not indicate excessive vulnerability of exporters' profits to these shocks.
Jan Engelbrecht (Physics)
Our research explores emergent phenomena in both physical and biological contexts where many simple interacting "entities" develop novel collective behaviour not found in the original building blocks. Our work in physics considers correlated electrons cooperating to exhibit strange behaviour in high-temperature superconductors. We have a new program in neuroscience where we extend some of the ideas of emergence in physics to consider how populations of `interacting' neurons develop collective behaviour that performs function. Specifically we consider how the dynamics of the development of synchrony in neural spike times can realize algorithms for sensory pattern recognition and binding.
Maksym Fedorchuk (Mathematics)
I plan to use the account to run computations in SAGE and Python with the goal of understanding the geometry of moduli spaces of algebraic curves. My main interest is in computing cones of nef and effective divisors on these moduli spaces, with the eventual goal of resolving several long standing conjectures regarding these cones.
Scott Fulford (Economics)
My work examines the consequences of changes in financial access in developing economies. I model and simulate the changes that occur as communities gain access to new financial services. These simulations provide hypotheses concerning what should happen to consumption and wealth over time according to a given model, which I test using data from large surveys. In addition, I use the method of simulated moments to help choose the parameters of the model which best fit the data, and to help distinguish between competing models of investment and consumption.
Brian Galle (Law)
State nonprofit law is almost never enforced publicly, and is often unenforceable by any interested private party. Does nonprofit law really matter? We test that proposition by examining the impact of rolling state enactment of UPMIFA, a model statute that governs, among other things, nonprofit corporate spending out of restricted funds. UPMIFA liberalizes spending rules, while a prior set of reforms had granted increased spending flexibility for nonprofit trusts. Accordingly, we employ a triple-difference design to estimate the incremental impact of UPMIFA on corporate spending in enacting states.
Jiaming Gao (Chemistry)
The Gao group will use the Cluster for computational modeling of macrocyclic peptides. A major goal of our research is to develop synthetic molecules that target specific lipids in cell membranes. Molecules as such allow one to target particular cell types, which is highly desirable in medicinal chemistry. For instance, facile differentiation of bacterial and mammalian cells would enable development of novel antibiotics. We hypothesize that lipid recognition can be achieved with peptide macrocycles. Computational modeling (with Amber) of these molecules may enable prediction of their preferred conformations, therefore greatly facilitate the design and optimization process.
Peter Gottschalk (Economics)
Our work examines individuals' earnings mobility and family income mobility over the course of three decades. In addition to studying the current levels of mobility in the United States, our work examines how patterns of mobility have changed over time and how these patterns are affected when some individual and family characteristics are controlled. Making use of transition matrices, quantile regressions, and various nonparametric and semiparametric regressions, we study how mobility varies both over time and within the income distribution.
Michael Graf (Physics)
Our group focus is on measurements of strongly correlated electron and magnetic systems at low temperatures. These works encompass materials that are at the forefront of modern condensed matter physics, and involve exotic low temperature phases and are a result of complex many-body interactions. One prominent technique in our research is Muon Spin Resonance (MuSR or μSR), used to probe the local distribution of magnetic fields. As a part of this technique, numerical fitting routines must be performed on the data to extract parameters based on analytical models. At present we are not able to utilize the software to its full potential based on the limited computational speed of desktop machines. The Scorpio cluster will be used to implement the more powerful and thorough routines of the software and thus extract much more detailed information than currently obtainable.
Rob Gross (Mathematics)
Our research group is investigating new algorithms to find efficientlattice packings in moderately high dimensions (20<n<99). We hope to improve on some known bounds by using parallel methods.
Michael Grubb (Economics)
My research focuses on topics in behavioral industrial organization. In ongoing work I use historical cellular phone and electricity billing data to investigate the potential effect of bill-shock regulation on consumers. Bill-shock regulation seeks to inform consumers by requiring firms to alert consumers when high usage triggers an increase in marginal price. Importantly, the work seeks to predict how firms would change prices in response to such regulation and takes these predicted price changes into account when evaluating the policy’s impact on consumers.
Fredrik Haeffner (Chemistry)
I collaborate with several research groups at the Department of Chemistry, where I use quantum chemistry in an effort to better understand chemical reactivity and selectivity of a variety of organic and organometallic catalyzed transformations. Examples of past and current research involve olefin metathesis, N-heterocyclic carbene catalyzed addition and substitution reactions, Pt-catalyzed enantioselective diboration of monosubstituted alkenes, chemical and spectroscopic properties of azaborines. Other interests of mine are enzyme mimics and in-silico design and optimization of catalysts for a variety of reactions.
Joshua Hartshorne ( Psychology)
Our research is focused on learning the structure of the syntax and semantics of English verbs, specifically in verb argument structure and verb classes, using data from both existing lexical resources and large web-based experiments. We take a computational approach to analysis, using non-parametric Bayesian models and artificial neural networks.
Summer Hawkins (Social Work)
This program of research will utilize routinely-collected data from the birth certificate to examine the impact of state-level policies and economic conditions on maternal smoking during pregnancy. The National birth files contain information on every birth in 29 states from 2000 through 2009 for a total of 18 million births. For our first project we will examine the impact of cigarette taxes and smoke-free legislation on maternal smoking during pregnancy and test whether these relationships vary across different subgroups of the population. For our second project we will examine the effect of economic conditions, including recessions, on maternal smoking behaviors and determine whether the economic climate impacts mothers differently across racial/ethnic and socioeconomic groups.
Stefan Hoderlein (Economics)
A new estimator based on Radon inverse is suggested to estimate treatment effect parameters in a triangular treatment effect model with random coefficients in the selection equation. This non-parametric estimator relies on certain smoothing parameters, which need to be chosen by running a series of simulations and computing various types of optimality criterion.
Amir H. Hoveyda (Chemistry)
The research in our group is centered on the design and synthesis of new organometallic and metal-free catalysts for practical applications in asymmetric synthesis. Although our group focuses on experimental solutions to the major problems in asymmetric catalysis, quantum-mechanical calculations (Gaussian) are a valuable aid for us in the pursuit for more efficient and selective catalytic systems. Theoretical analysis of the catalysts developed in our group helps us understand their reactivity profile and identify promising structures for future experimental studies. Our current theoretical studies involve investigation of the reactive intermediates in the catalytic cycles of the chiral Ru-based and Mo-based metathesis catalysts. The insight gained from our experimental and computational studies is employed towards design of new metathesis catalysts. Future investigations will include other methods under development in our group, for example, asymmetric conjugate additions and asymmetric ketone and imine alkylations.
Amy Hutton (Finance)
We are examining the relation between firm's idiosyncratic risk and the level of transparency in their financial reports. We expect to demonstrate that greater transparency leads to greater information flow and thereby greater idiosyncratic risk. The ultimate question we hope to address is whether greater transparency results in less mis-pricing of firms' traded shares.
Peter Ireland (Economics)
We are constructing and analyzing a set of dynamic, stochastic, general equilibrium macroeconomic models in which heterogeneous agents possess imperfect information either about the true structure of the economy or the set of shocks impacting on the economy. As these models are computationally intensive, our efforts focus partly on developing and implementing numerical procedures to solve them. From a substantive viewpoint, we are investigating how the actions of imperfectly informed agents propagate shocks through the economy and how government policies can be designed to mitigate the distortions and welfare losses that result from private agents' imperfect information.
Hao Jiang (Computer Science)
This project focuses on convex methods for human movement understanding, the task of estimating and quantifying human motion and movement in videos. Compared with previous approaches, the convex methods explicitly model complex inter-component correlations and
global constraints and are able to achieve more reliable results. The convex formulations are automatically generated using learning methods. By taking advantage of their special structures, efficient algorithms are devised. This project studies human movement understanding from different perspectives and provides convex solutions to global movement estimation, body part tracking, and local patch motion trajectory estimation. The key research components include convex articulated graph matching with complexity decoupled
from the sizes of target candidate sets, convex structure learning and efficient decomposition methods for solving large-scale problems. With robust movement estimation, this project further addresses performance recognition, a new application that quantifies the style and
performance of action.
Alan Kafka and John Ebel (Earth and Environmental Sciences)
Although earthquake prediction remains an elusive goal, it is possible to forecast the general characteristics of future earthquakes at some level of detail. Seismologists use the term "earthquake forecast" to refer to a statement of the long-term probability of one or more earthquakes occurring in a region. Our research on earthquake forecasting is focused on discerning the level of detail that can be known about the spatial and temporal characteristics of future earthquake processes. We are investigating the extent to which the distribution of seismicity in a region delineates where future earthquakes are likely to occur, as well as the extent to which non-random patterns in the temporal distribution of seismicity might indicate increased probability of earthquakes occurring.
Gabor Kalman (Physics)
Our research focuses on the theoretical analysis combined with computer simulation of the properties of strongly coupled plasmas, complex (dusty) plasmas in particular . Complex (dusty) plasmas consist of mesoscopic grains immersed in the background of gaseous plasma of electrons, ions and neutral atoms. Such systems occur in a variety of situations. Our aim is the study of the collective behavior in such systems: i.e. phenomena resulting from the cooperative participation of many particles. Such a collective behavior is the hallmark of strongly coupled systems. Six major areas are proposed for study: (i) magnetic interaction between grains carrying a magnetic dipole moment; (ii) propagation of waves in complex plasmas in two dimensional and three-dimensional configurations; (iii) micro-instabilities generated by beams of ions or grains penetrating into the complex plasma; (iv) stochastic and disordered behavior in complex plasmas; (v) phase transitions in complex plasmas; (vi) feasibility study for the cryogenic generation of complex plasmas on the surface of liquid helium. One of the principal approaches to be used in the proposed investigations relies on an analytic method referred to as the Quasi Localized Charge Approximation that has been successfully used previously.
Broader impacts of the research will contribute to improved understanding of problems of fundamental importance in plasma and condensed matter physics. Establishing techniques suitable for the manipulation of mesoscopic structures will also have impact on engineering applications.
Evan Kantrowitz (Chemistry)
Work in my laboratory is centered around an understanding of the relationship between protein structure and function and in particular, how protein structure relates to catalysis, metal binding, and cooperativity in enzyme systems. The BC research cluster will be used for: (1) Calculations involved in protein structure determination by X-ray crystallography. For this work will be make use of software such as CNS and XPLOR. (2) Calculations of how small molecules bind to receptor targets for drug design. For this work we have written a series of scripts that interface to a proprietary MySQL database. Software for these calculations includes AUTODOCK, DOCK5, GOLD, GLIDE and SURFLEX. (3) Molecular dynamics and molecular mechanisms calculations on our systems will be used to better understand their mechanism of action. For this work we will make use of software such as GROMACS and NAMD. For the knowledge gained from these studies we hope to develop new classes of inhibitors that can potentially become drugs from the treatment of viral infections, malaria, diabetes and cancer.
Oguzhan Karakas (Finance)
Our research examines the shareholder control premiums using option prices. We expect to have a better understanding of the determinants and consequences of the control in firms.
Krzysztof (Kris) Kempa (Physics)
Electromagnetic properties of nanostructures determine the behavior of sensors, solar cells and other novel devices. The research activity in the Physics Department at BC has been, in part, devoted to making and studies of nanostructures. As a part of this effort, the theory group developed advanced computer simulations of the nanostructures. These simulations involve numerical solutions of Maxwells equations, in various domains (time, space, frequency and momentum), and with realistic parameters for the materials employed. These simulations guide the experimental groups involved in studies of the nanostructures.
Elizabeth A. Kensinger (Psychology)
Our research examines the neural activity associated with memory processes. We are particularly interested in understanding how neural activity differs when information is successfully remembered versus when it is forgotten, and how the neural processes that correspond with accurate memory differ for emotionally meaningful experiences versus for more mundane ones. To examine these questions we use Matlab-based software in order to analyze the hemodynamic (blood-flow) responses throughout the brain as individuals are remembering events.
Marios Kokkodis (Information Systems, CSOM)
My research focuses on understanding and optimizing design aspects of online marketplaces. I analyze massive amounts of data from multiple sources and propose technical/econometric models/algorithms that increase the transactional efficiency of these marketplaces. I will use the cluster to store, query and process data, and to train and evaluate predictive/econometric models.
Sergei Koulayev (Economics)
I'm using cluster primarily for my work on Matlab. I'm estimating structural models of consumer search, where both search and purchase decisions are explained through rationality conditions imposed by the economic theory. My dataset consists of online searches made by consumers who were booking a hotel on the internet. I'm exploring various sources of identification of the search cost distribution, together with consumer preferences.
Tzuo Hann Law (Economics)
I work macroeconomic models that are consistent with micro level data of varying degrees. The cluster will be used to study (a) income inequality in Germany (b) inequality and entrepreneurship in China in the face of corporatization of formerly state owned enterprises (c) finance and banking in the US and (d) the application of machine learning methods to equilibrium labor market models.
Deishin Lee (CSOM)
This research studies how supply chain structure affects customer service level and raw material utilization. We investigate the tradeoffs between the cost of labor and capital resources and the cost of under-utilizing raw material (natural) resources.
Lian Fen Lee (CSOM)
This project examines the relative accuracy of management and analyst forecasts. We predict that analysts’ information advantage resides at the macroeconomic level. They provide more accurate long-horizon earnings forecast than management when a firm’s fortunes move in concert with macroeconomic factors such as gross domestic product and energy costs. In contrast, we expect management’s information advantage to reside at the firm level. Their forecasts are more accurate than analysts when management’s actions, which affect reported earnings, are difficult to anticipate by outsiders. Examples include when the firm’s inventories are abnormally high, the firm has excess capacity, or is experiencing a loss. Last, while analysts are commonly viewed as industry specialists, it is unclear whether analysts have an information advantage over managers at the industry level. Managers are also likely to have significant industry expertise and knowledge. They need to understand industry dynamics and demand to effectively run an operating firm.
Jacqueline V. Lerner (LSOE)
We will be conducting analyses of survey data from the Connecting Adolescents’ Beliefs and Behaviors (CABB) Study, a 3-year study with adolescents from the New England area. Our main research question is whether intentional self-regulation is the process through which adolescents who report positive virtues are able to turn them into behaviors consistent with that character; i.e., whether it helps them “do the right thing.” The study was funded by a grant to Jacqueline V. Lerner, Ph.D. and Sara K. Johnson, Ph.D. from the John Templeton Foundation.
Rebekah Levine Coley (LSOE)
Using Add Health data on a representative sample of Americans followed through adolescence (3 waves of data covering ages 12 through 26; n = 20,745), this research will assess rich, multi-reporter measures of social norms, gender roles, and parenting processes as well as genetic polymorphisms. Data analyses will employ multilevel growth modeling as well as semiparametric mixture models and regression models. This research offers the potential to understand causes and correlates of youth risk behaviors and to identify high risk youth. Results will inform development of effective intervention programs and policies to diminish adolescent engagement in health risk behaviors.
Arthur Lewbel (Economics)
This project deals with nonparametric identification and estimation of binary games with incomplete information, using excluded regressors. A typical example of this type of game is the decisions competing firms make on whether to enter a particular market or not. Given data on the outcomes of such games (e.g. attributes of the firms and whether they entered or not), the goal is to recover the distribution of probabilities of entry for each player, and each player's payoff functions, corresponding to the utility each player would get given each possible market outcome. An excluded regressor for player i is a state variable that does not affect other players' utility and is additively separable from other components in i's payoff. When excluded regressors satisfy certain properties, we can show that the interaction effects between players, each player's payoff function, and the distribution of private information for all players are nonparametrically identified. We show that this approach can be extended to accommodate the existence of multiple Bayesian Nash equilibria in the data-generating process, without equilibrium selection rules. Nonparametric estimation based on these identification results can be computationally demanding. We use the cluster to evaluate the accuracy and performance of our estimators based on these results.
Ben Li (Economics)
This project aims to examine price and quantity decisions in offshoring production. I am currently employing transaction-level data to estimate deep parameters in the production process. Because of the huge volume of the data, I face a bottleneck in computational power. The project will shed light on a number of questions about offshoring production in the global economy, including but not limited to 1) how differently it responds to exchange-rate fluctuations in comparison with conventional production, 2) what is the role of contracts in offshore production, and 3) how offshoring affects bilateral international trade.
Zhuoxin Li (Information Systems, CSOM)
I expect to use the cluster for running computation-intensive statistical analysis with large datasets, using software packages R, Matlab, and Stata. Ongoing projects include Bayesian estimation of large-scale consumer decision marking problems. If feasible, I may utilize parallel computing to speed up data processing and analysis.
Shih-Yuan Liu (Chemistry)
The research in the Liu group is focused on the development of boron(B)–nitrogen(N)- containing heterocycles, specifically azaborines, for potential applications in biomedical research and materials science. Azaborines are structures resulting from the replacement of two carbon atoms in benzene with a boron and a nitrogen atom. Azaborines closely match the size and shape of ordinary benzene rings, but most of their other physical, chemical, and spectroscopic properties are significantly altered. Computational studies will be invaluable to our efforts in understanding the electronic structure and spectroscopic features of azaborines, and the mechanism of reactions they undergo.
Sean MacEvoy (Psychology)
We study human object recognition and learning using a combination of behavioral and brain imaging techniques. Our present goal is to understand the brain mechanisms supporting the recognition of multiple simultaneously-viewed objects, and how these mechanisms tolerate relationships between newly-recognized objects. Real-world objects are difficult to use in this paradigm, owing to variability between observers expertise with each object. Instead, we will generate large families of novel "nonsense" objects that must be screened by several strict criteria.
Alan Marcus (Finance)
Our project aims to identify the factors that affect explanatory power in regressions of stock return time series against several market indexes. In general, market models show poor performance in explaining variation in stock returns, resulting in surprisingly low R-squares. However, the variation in R-square itself is considerable, a result that may indicate that R-square may be a proxy for other risk factors, reflect firm-specific information, or simply reflect noise. Using all the U.S. stock returns available since the 1930s we try to infer the determinants of R-square and their effects on asset prices.
Michael O. Martin and Ina V.S. Mullis (Education)
The TIMSS & PIRLS International Study Center at the Lynch School of Education conducts two major ongoing programs of international assessment of student achievement. TIMSS (Trends in International Mathematics and Science Study) involves more than 60 countries, and has been reporting on fourth- and eighth-grade student achievement in mathematics and science on a four-year cycle since 1995. Beginning in 2001, PIRLS (Progress in International Reading Literacy Study), with more than 40 countries participating, reports fourth-grade students' reading achievement on a five-year cycle. TIMSS and PIRLS use sophisticated multiple-imputation techniques to derive student achievement measures in mathematics, science, and reading, and the resulting data require computer-intensive statistical procedures to estimate population statistics and their standard errors.
Christopher Maxwell (Economics)
This projects studies the extent to which closed-access criminal records policies impact employment opportunities of ex-offenders. The hypothesis to be tested is that in the absence of public access to criminal records, employers will statistically discriminate against applicants who demonstrate attributes similar to the perceived criminal such as ethnicity, geographic location, age, sex, socio-economic status and gaps in employment history. And to that extent, access policies will have at best a marginal impact on employment opportunities for ex-offenders. The analysis, which builds on earlier work by Finlay, will focus on the 1997 National Youth Longitudinal Survey data and look closely at the differential employment impacts of policies among states that allow for more open or closed access to criminal records.
Michelle Meyer (Biology)
The biological roles of RNA, beyond encoding proteins, have expanded in the last decade to include a diversity of important gene regulatory functions in nearly all living things. At the same time, genome sequencing efforts have produced a wealth of data that can be mined tostudy the evolution of non-coding RNAs (ncRNAs), as well as identify previously unknown non-coding RNAs. We are particularly interested in RNA structures that bind proteins to control gene expression. The predominant methodology for the discovery of ncRNAs is comparative genomics. Using the massive amounts of sequence information generated by microbial sequencing projects, and various metagenomic projects(such as the Human Microbiome Project) we apply a variety of computational tools to discover new structured mRNA elements that are hypothesized to control gene expression. In particular, we use RNA structure alignment searches using programs built on stochastic context free grammars.
Robert Meyerhoff (Mathematics)
This project enumerates and analyzes families of one-cusped complete hyperbolic 3-manifolds with low-area cusp neighborhoods. We build upon computational techniques that were used to analyze small-volume compact hyperbolic 3-manifolds and to establish the Weeks manifold as the minimum-volume compact hyperbolic 3-manifold. Advanced precision and error-bound techniques help provide for empirical results and rigorous results. We intend to use these results, the theory of Dehn fillings, and the theory of Mom technology to analyze certain classes of low-volume one-cusped hyperbolic 3-manifolds.
Udayan Mohanty (Chemistry)
Electrostatic interactions between charges in solution and between the charges along the backbone of RNA play a delicate role in determining its overall stability. The importance of electrostatic interactions is apparent from the fact that magnesium influences the biological activity of tRNA and Tetrahymena group I intron, for example. We are studying the nature of interaction of magnesium ions with RNA bases. The approach combines Grand Monte Carlo simulations, Poisson-Boltzmann calculation and high-level ab initio theory to determine the binding free energy for magnesium ions with RNA bases. Another goal of the project is to use Monte Carlo simulations to quantitatively determine the effects of phosphate-phosphate repulsion on DNA stiffness in vitro. Finally, we will investigate by Brownian dynamic simulations the effects on the end-to-end contact probabilities for 200-bp DNAs of binding at different degrees of saturation for HMGB proteins.
Babak Momeni (Biology)
Communities of interacting microbes are abundant in nature. They playimportant roles in ecosystems (e.g. by cycling carbon), in human health (e.g. by causing infections), and in industry (e.g. by degrading toxic waste). We build mathematical models to study how cell-level properties of members shape the overall functions of multispecies microbial communities.
Sara Moorman (Sociology)
I am using data from the National Social Life, Health, and Aging Project (NSHAP) to examine dyadic effects of marital quality on older adults' well-being, including whether there are any differences according to gender.
James P. Morken (Chemistry)
Research in the Morken group focuses on the development of new catalytic enantioselective processes and their application to natural products synthesis. Our current work in asymmetric catalysis focuses on the design and study of rhodium and palladium complexes for enantioselective allylation and dimetallation of alkenes. Computational studies (Gaussian and MacroModel) of reaction mechanisms and catalyst structures often complement experimental studies. Combined, the two approaches enhance our ability to design effective new reactions. Our most recent DFT studies on the Pd-catalyzed addition of organometallic reagents to enones, revealed an unprecedented and unexpected reaction mechanism, which is forming the basis for many of our research directions.
Julie Holland Mortimer (Economics)
Incomplete product availability is an important feature of many markets, and ignoring changes in availability may bias demand estimates. We study a new dataset from a wireless inventory system on vending machines to track product availability every four hours. The data allow us to account for product availability when estimating demand, and provide a valuable source of variation for identifying substitution patterns when products stock-out. We develop a procedure that allows for changes in product availability when availability is only observed periodically. We find significant differences in demand estimates: the corrected model predicts significantly larger impacts of stock-outs on profitability.
Alicia Munnell (Carroll School of Management)
We are currently working on a project to estimate 401(k) fees using common options in mutual funds from the Thomson Financial Ownership and the New York Stock Exchange’s Trade and Quote databases, both available through Wharton Research Database Services. These data sets are large (generally about 60GB per month of data for 5 years of data), so basic manipulations must be done to reduce the size then analyze the data.
Dmitriy Muravyev (Finance)
I want to study why option prices change during a trading day. While there is an extensive literature about intraday stock returns, little is known about intraday returns in the options market. The research is scarce because intraday options data are hard to obtain and process. Many basic questions are still open. Do intraday option returns have crossectional patterns? Do changes in option prices reflect changes in volatility expectations? How important is the inventory risk faced by option market makers? What part of the volatility discovery is produced by the underlying stock market and what by the options market? What is the relative importance of market-wide and stock-specific factors? How much information is contained in option trades compared to quote revisions?
Jordan Nickerson (Finance)
Using a structural model, I examine the distortionary effects of frictions in the CEO labor market. Firms experience productivity shocks over time and either outgrow or underutilize their incumbent CEO's talent, but keep their manager to avoid a switching cost. The decision to replace a manager depends on the magnitude of the cost and dispersion of CEO talent. This results in an endogenous supply of available CEO labor which must be determined simultaneously with the optimal policy function of the firm.
Ashutosh Patil (CSOM)
This research looks into whether Bayesian principles can be utilizedto execute moderated multiple regression (MMR), which inherently hasvery low statistical power. The focus will on analyzing data createdby on executing several thousand monte carlo simulations for thousandsof conditions.
Marcie Pitt-Catsouphes (Social Work and CSOM)
The Linux Cluster is used for work with the Generations of Talent study conducted by the Sloan Center on Aging & Work (reporting into the GSSW). The Generations of Talent Study examines the priorities and needs of employees of different ages who work in different countries. We assess employees’ past and current quality of employment and their future work-related transitions. Three key research questions are:
- Do employees’ priorities and use of workplace-based resources for quality of employment vary by age, career stage, and life stage?
- How do organizational policies, programs, and practice influence employee engagement, job satisfaction, work productivity, and career transitions in different countries?
- How does country context, such as public policies and cultural orientations, influence employees’ quality of employment?
Jeffrey Pontiff (Finance)
Most investments research uses Fama-Macbeth (1973) t-statistics to test whether or not an independent variable is related to future stock returns. Fama-Macbeth use a two-step procedure that is robust to cross-sectional correlation. Pontiff (1996) proposes an extension of Fama-Macbeth's procedure that is also robust to time-series correlation. Pontiff's method is based on modeling Fama-Macbeth slope coefficients with a moving-average process. We propose to compare the performance of Pontiff's statistic to other corrections by using simulations.
Ying Ran (Physics)
Our research group studies quantum condensed matter materials including frustrated quantum magnets, high temperature superconductors, quantum hall systems and topological phases of matters. Close to zero temperature, the electronic motion in these systems are described by quantum mechanics. However because of the strong interactions between
the vast number of electrons, some novel behaviors in these materials are so striking that they cannot be described in terms of the original electronic degrees of freedom; instead they are described by completely new emergent collective degrees of freedoms. The novel physics of these emergent degrees of freedoms sometimes are in analogy of the quack, lepton, and gauge fields in the high-energy physics context, but are now realized in a condensed matter compound. To study these emergent physics qualitatively and quantitatively, we use numerical methods such as functional renormalization group, variational quantum Monte Carlo, and exact diagonalization of large sparse matrices.
Sam Ransbotham (Information Systems, CSOM)
Our research introduces a new disaggregated formulation of the Generalized Assignment Problem. Based on the reformulation, we are able to introduce unique strong inequalities. We test the strength of this formulation on a set of standard benchmark problems and show the new formulation to be significantly stronger than other known formulations.
Jonathan Reuter (Finance)
Using detailed over-the-counter bond transactions and holdings of mutual funds, we plan to investigate the effect of liquidity shocks to mutual funds on their holdings. We hope to better understand how the behavior of mutual funds affects the prices and liquidity of their holdings.
Ronnie Sadke (Finance)
This research presents a new pattern in the cross-section of expected stock returns. Stocks tend to have relatively high (or low) returns every year in the same calendar month. We recognize the annual cross-sectional autocorrelation pattern documented in Jegadeesh (1990 at lags of 12, 24, and 36 months as part of a general pattern that lasts up to 20 annual lags, superimposed on the general momentum/reversal patterns. This pattern explains an economically and statistically significant magnitude of the cross-sectional variation in average stock returns. Volume and volatility exhibit similar seasonal patterns but they do not explain the seasonality in returns. The pattern is independent of size, industry, earnings announcements, dividends, and fiscal year. The results are consistent with the existence of a persistent seasonal effect in stock returns.
Natalia Sarkisian (Sociology)
I am using data from the Health and Retirement Study to examine the reciprocal relationship between employment and caregiving to parents and the variations in that relationship by race and gender.
Fabio Schiantarelli (Economics)
We explore the evolution of attitudes of European immigrants to the US using the General Social Survey and, more specifically we examine how they vary across generations. We examine whether they converge(or not) to the US prevailing norm. We do this for various attitudes concerning religion, morality, gender issues, sexual mores, political orientation, etc.. We also intend to link the attitudinal data from the GSS to census data. The census data will be used to examine the evolving ethnic composition of US counties.
Lawrence T. Scott (Chemistry)
The Linux computational cluster is used by our research group primarily for the study of geodesic polycyclic aromatic hydrocarbons (PAHs) and synthetic intermediates used in their preparation. Using the Gaussian modeling software, we perform high level density functional theory calculations to optimize the geometries of these molecules and accurately predict their properties, including NMR and UV-vis absorption spectra.
Ce Shen (Social Work)
Our research projects focus on cross-country analysis. A special emphasis is given to the study of people's values and beliefs over time. In ongoing work, we use data from large scale global surveys, such as World Values Survey and barometer surveys from several countries.
Ewa Sletten (Accounting)
We compare earnings' informativeness in bad-news and good-news quarters. We predict that when the news reaching the market during a quarter is negative, a greater proportion of it is released through earnings than when the news is positive, because of various factors that prompt managers to delay bad-news disclosures and because of the nature of the earnings reporting process. Using returns to measure news, we find, consistent with our prediction, that earnings' informativeness relative to other sources is higher in bad-news quarters than in good-news quarters. Further, cross-sectional tests indicate that earnings' differential informativeness in bad-news quarters is more pronounced when managers do not issue short-horizon forecasts, information asymmetry is stronger, and managers are net sellers of stock. Our findings highlight that when factors such as litigation risk are not high enough to induce voluntary disclosures, earnings release the negative information that has not reached the market via alternative sources.
Marc Snapper (Chemistry)
Our research focus is on introducing new chemical transforma¬tions, using these reactions to build complex molecules, and then using these compounds to study cellular function. To maintain competitiveness in the global chemical community, the introduction of new, more powerful chemical reactions continues to be an important endeavor in organic chemistry. Our efforts have been directed toward discovering better ways of constructing medium-ring-containing compounds. Using novel transformations that build molecular complexity rapidly have allowed for the efficient construction of seven- and eight-membered ring, containing natural products. Computational studies will be used to help predict the outcome of various synthetic approaches towards our target structures.
Philip E. Strahan (Finance)
Non financial firms have increased cash sharply following the financial crisis. Large firms and firms with access to bond markets have increased cash more than other firms, suggesting that financial constraints coupled with an increase in demand for liquidity helps explain these patterns.
Georg Strasser (Economics)
The project estimates and compares international relocation costs of consumption goods and capital goods. I estimate a continuous-time model by indirect inference, which uses the time variation of both mean and variance of the real exchange rate process for identifying the parameters. This procedure requires at each step the solution of several second-order differential equations and the repeated simulation of a large number of time paths of the real exchange rate.
Richard Sweeney (Psychology)
This research project uses confidential microdata from the Energy Information Administration to study energy and environmental policy in US petroleum markets. One project looks at the impact of fuel content regulations stemming from the 1990 Clean Air Act Amendments on the US oil refining industry. A key feature of this industry is that economically interrelated markets experience differential regulation under the new rules, making estimation their impact complicated. We overcome this challenge by estimating a structural model of the industry and simulating policy counterfactuals for both regulated and unregulated markets simultaneously. A second project looks at the effects of the US crude oil export ban. The advent of fracking abruptly reversed a decades long decline in domestic oil production, yet physical and regulatory impediments have severely limited the transmission of this new crude. We estimate who benefited most from the fracking boom and compare the current regime to a world where these impediments are removed.
Jérôme Taillard (Finance)
In this study, we revisit the managerial ownership and firm performance relationship. We take a novel approach and condition the relationship on the past liquidity of a firm’s stock. We posit that market frictions affect the level of insider ownership over time and, as a consequence, might also affect the link between managerial ownership and firm performance. Previous studies have not taken into account these liquidity effects and as such might have documented spurious correlations.
Thanh Tran (Social Work)
The research team has on-going projects using large scale, nationally representative data to investigate wellness outcomes such as disability, self-rated health, depression, and other health and mental health indicators for Asian American populations. Key social determinants such as acculturation, lifestyle behaviors and other factors are examined across ethnic groups to determine how to best address health disparities and services in social work research and practice with this under-served population.
Chia-Kuang Tsung (Chemistry)
One strategy to mitigate anthropogenic climate change is to develop methods to transform carbon dioxide into value-added chemicals and fuels to help incentivize its capture. The hydrogenation of carbon dioxide to formic acid is an attractive route because of formic acid's potential use as both a fuel cell feedstock and as a C1 building block for more complex molecules; however requirements of high CO2 partial pressure and expensive noble metal catalysts prevent this reaction from reaching large scale implementation. A recently discovered pincer complex was found to have high activity for CO2 reduction at low pressure and using earth-abundant iron as its metal center. The catalyst is effective in an atmosphere of CO2 and nitrogen, but for real world implementation it must be resistant to oxygen, which presently degrades the catalyst. Encasing the complex in a porous metal organic framework (MOF) that allows the passage of CO2 but not of O2, such as ZIF-78 or CID-3, would provide the desired durability without impacting the catalysts inherent activity. Selection of an appropriate MOF material requires knowledge of not only spatially how the iron complex catalyst will fit within the pore cavities but also how it will interact chemically with functional groups in the MOF structure. A initio calculations with Gaussian software will allow us to screen many MOF candidates and identify the best material for making this multifunctional catalyst.
Rosen Valchev (Economics)
This project seeks to understand the origins of nominal price stickiness, which is both a pervasive feature of the data, and a crucial ingredient in modern macroeconomic theoretical models Yet, standard models of price stickiness are at odds with certain robust empirical facts from micro price datasets. To address this, we explore a new, parsimonious theory of price rigidity, built around the idea of demand uncertainty, that is consistent with a number of salient micro facts. In the model, firms faces Knightian uncertainty about their competitive environment. They learn non-parametrically about the underlying, uncertain demand and make robust pricing decisions. The non-parametric learning leads to kinks in the expected profit function at previously observed prices, which generate price stickiness and a discrete price distribution. In addition, we show that when the ambiguity-averse firm worries that aggregate inflation is an ambiguous signal of the prices of its direct competitors in the short run, the rigidity becomes explicitly nominal in nature.
Mathis Wagner (Economics)
My work focuses on using individual level Austrian social security data (for all private sector workers, starting in 1972) to answer a number of questions in labor and public economics. On-going projects include the impact of immigration on native labor market outcomes, the determinants of workers' hazard rates out of employment and unemployment, and the effect of changes in publicly provided pensions on retirement behavior.
Dunwei Wang (Chemistry)
The Wang group's research is centered around artificial photosynthesis to mitigate problems caused by the usage of fossil fuels. We will use the cluster to understand the nature of charge transfer between catalyst and photoelectrodes. The understanding is an important piece of our effort to mimic photosynthesis in the lab, which will pave the way toward a green, sustainable solution to our energy needs.
Ziqiang Wang (Physics)
Our research group studies the fundamental physics of strongly correlated electronic materials with a special focus on that of the high temperature superconductors. Understanding the unconventional, complex, and emergent physical properties in these materials represents both the challenge and the vitality of condensed matter physics. The strong many-body correlations in these systems render the problem nonperturbative and the investigation of the possible electronic states of matter and the low energy excitations defies conventional perturbation approaches that use noninteracting electrons as a starting point. As a result, it is very difficult to study these materials by purely analytical means and numerical computations have played and continue to play a key role in this rapidly developing field. The computational component of the research projects in our group involves exact diagonalization, variational and quantum Monte Carlo simulations, and manipulations of large random matrices.
Eranthie Weerapana (Chemistry)
Our lab utilizes mass spectrometry to identify and quantify proteins from complex mixtures. We apply chemical probes to specifically enrich subsets of proteins based on activity or posttranslational modification-state for analysis by mass spectrometry using an LTQ-Orbitrap instrument. We are particularly interested in the functional significance of protein oxidation and glycosylation and seek to develop novel chemical proteomic technologies for quantitatively profiling these protein modifications. The BC research cluster will be used for data analysis software programs that correlate tandem mass spectra of peptides with amino acid sequences from protein databases. One such search algorithm, known as SEQUEST, cross correlates the observed tandem mass spectrum to theoretical spectra to identify the best candidate sequence match. Using a combination of chemistry, biology, mass spectrometry and bioinformatics, we hope to identify novel dysregulated protein activities implicated in a variety of patho physiological states.
Hao Wu (Psychology)
The linux cluster will be used for various simulation studies concerning models used in psychometrics. Examples include factor analysis models for ordered categorical data (e.g. 5-point rating scales), variance component models used in twin studies, nonparametric Bayesian models, among others. These studies focus on theoretical issues of model evaluation and selection.
Zhijie Xiao (Economics)
Bootstrapping has attracted a lot of research attention in the last twenty years. It provides a convenient way of estimating the distribution of an estimator or test statistic by resampling the original data. In this project, we consider a prewhitened block bootstrap (PBB) method. The prewhitened block bootstrap combines the ideas of the parametric residual-based bootstrap and the nonparametric blockwise bootstrap. The stated idea of prewhitened block bootstrap is as follows: First, one prewhitens (prefilters) the original data to obtain a less dependent series; then block bootstrap is applied to the prewhitened (filtered) data, which has less dependence; finally the (block) bootstrapped data is recolored to produce a bootstrapped data set for the original series, and bootstrap estimation and inference procedures can be constructed based on the recolored data. Bootstrap is a very computational intensive method, high power computers are needed for this research project.
Liane Young (Psychology)
Our research group studies the cognitive and neural basis of human moral judgment. Our current research focuses on the role of theory of mind, mind attribution, and emotions in moral judgment and behavior, as well as individual and cultural differences in moral cognition. We employ methods of social psychology and cognitive neuroscience, including functional magnetic resonance imaging (fMRI).
Jianer Zhou (CSOM)
The project is to empirically examine how intangible capability influences inventory turnover performance using U.S. public firms’ financial and patent data in 1976-2006. In particular, we investigate two types of capabilities driven by intangible resources: innovation efficiency and labor productivity. Firms have been investing in their tangible and intangible resources to build sustained competitive advantage in the market. Though previous work has shown that tangible resources are associated with inventory turnover performance, little is known about this link between intangible resources and inventory turnover. To address this issue, we intend to run panel regressions of a large dataset.