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.

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.

Christopher Baum (Economics)

This project evaluates the role of college quality in explaining lower economic pay-offs to adult education. While delaying education is costly and is associated with substantial wage penalties, currently over 35 percent of American university students are 25 and older. The first part of the project will examine the relationship between college quality, ability, and timing of education. The second part will explicitly model enrollment and college quality decisions to determine their impact on wages. As a source of data on college quality, this project uses the information available from restricted use supplement to the National Longitudinal Survey of Youth.

Andrew Beauchamp (Economics)

My work involves estimating equilibrium models of individual and market behavior.  I apply methods across labor economics and industrial organization that use the latest cutting edge technical tools, which allows models to be more flexibly specified  and better simulate real world responses to changes in policy.  One example of my work is on the interactions between men and women when deciding on matching with one-another romantically.  This problem involves a complex choice which depends on all the other choices of individuals looking to match; this feature is the essence of equilibrium, and the reason for the computational complexity in estimating the model. Another line of research seeks to understand markets for fertility control by understanding how firms interact and compete in the market over the course of time.  This game between firms constitutes a difficult problem to solve, i.e. the optimal choices are highly non-linear functions of the choices of other firms, and estimation requires solving the problem many times. Finally, I also study individual labor market behavior which constitutes individual choices over what type of work to engage in in rural villages in Bolivia. This model focuses on the accumulation of experience in different sectors and how the related productivity translates into nutritional gains among poor households.  Controlling for childbearing, investment, risk sharing,and many other factors allows me to separate the effects of experience as opposed to other factors, but makes the computational burden significantly lager.

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.

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

David A. Chapman (Finance)

We examine the implications of career concerns for the portfolio strategy of an equity mutual fund manager who times the market with valuable private information. The manager solves a dynamic lifetime portfolio/consumption choice problem with endogenous stochastic income, generated by fund management fees, in a setting without learning. Career concerns are defined as endogenous effect of the manager's actions on both fund flows and the probability of "demotion", which is defined as a discrete drop in the assets under management.

Jeffrey Chuang (Biology)

Our lab is interested in the fields of computational biology and bioinformatics. In particular, we use computational and statistical techniques to study problems in comparative genomics, gene regulation, and molecular evolution. It is well known that codon usage bias correlates well with gene expression in bacteria and lower eukaryotes such as yeast, suggesting that codon bias determines gene expression level in these organisms.  However, due to the multiple tissues of higher eukaryotes, it's not clear how codon bias is related to gene expression in more complex species.  We are interested in addressing codon bias patterns in higher eukaryotes (human, mouse and others) to analyze tissue-specific and condition-specific gene expression on a large scale.

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.

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.

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.

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.

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. 

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.

Alan Kafka and John Ebel (Geology and Geophysics)

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.

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.

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.

 Jason Kingsbury (Chemistry)

Through research spanning over a century, the one–carbon reagent diazomethane has assumed a position of central importance and utility in chemical synthesis.  Though volatile, toxic, and unstable, the reagent is now safely produced on metric ton scale and applied to complex, multistep processes, especially those relevant to the commercial synthesis of pharmaceutical agents.  Our program seeks to dramatically improve the power and scope of diazoalkyl carbon insertion reactions.  Starting from inexpensive aldehydes and ketones, more stable mono– and disubstituted diazomethanes will be prepared by practical modern procedures and applied to the enantio- and diastereoselective homologation of the carbonyl group with catalysts recently discovered in these laboratories.  Our use of high-power computational chemistry includes modeling of both starting and substrate-bound chiral scandium(III) bis(oxazoline) complexes as well as the mechanism of Sc-catalyzed carbon insertion reactions.

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.

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. 

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.

Vidya Madhavan (Physics)

Our research is focused on understanding the fundamental physics of complex materials like high temperature superconductors and magnetic semiconductors. We use a unique probe called the scanning tunneling microscope (STM) to examine the electronic properties of these systems at nanometer length scales. Our experiment generates thousands of spectra that are analyzed for patterns in energy and spatial positon at various temperatures. Fitting the data from our STM with different theoretical models will allow us to discriminate between them, eventually leading to a deeper understanding of the nanoscale properties of these materials.

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.

Gabor Marth (Biology)

The Marth lab  investigates genetic sequence variations. From a functional point of view, some of these variations cause phenotypic differences, and can lead to hereditary human diseases. From a basic scientific perspective, sequence variations are landmarks that allow us to track how segments of DNA have been passed down through past generations. My laboratory is interested in various aspects of sequence variations: single-nucleotide polymorphism (SNP) discovery, population genetic theory, particularly the effects of long-term demography on the patterns observed in genome-wide SNP distributions, human haplotpe structure, the functional effects of sequence variations, and the medical applications of population genetics.

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.

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. 

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.

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. 

Erik Owens (Theology)

9/11 Reflections is a web-based project of reflection and remembrance, presented by the Boisi Center for Religion and American Public Life on the occasion of the tenth anniversary of the September 11, 2001 terror attacks. The extended Boston College community -- past and present students, faculty and staff -- is invited to submit 150-word responses to the question "What have you learned since 9/11?" A suite of SAS data mining and sentiment analysis tools will examine text and metadata submitted through a web interface. Users will be able to interact with the submissions by searching or browsing, using metadata fields or any number of SAS-generated keywords; data visualization tools will use phrase clouds, diagrams or charts to direct readers to selected essays. As both a touch stone for conversation this fall and a lasting online memorial, we hope the project will reflect the thoughtful, spiritual and serious tone the topic deserves.

Willie Padilla (Physics)

The project focuses on perfectly absorbing metamaterials and ultra-small magnetic resonators. The structures being considered in the simulation we perform consist of a large array of a repeating metamaterial pattern. By alternating the size of the array we can study how the individual metamaterial elements interact with their neighbors to create an effective material response. These in-depth simulations also let us examine other useful properties such as surface wave excitation/propagation and the use of metamaterial perfect absorbers in imaging systems.

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 (GSSW 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.

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)

Our research project explores the importance of resource (mis)allocation  as an explanation of underdevelopment. In particular we intend to assess how the allocation of labour and capital is affected by the institutional environment of each country, including product market regulation, labour market regulation, financial development, and general  quality of governance. The research project involves the use of firm level data sets for many countries and the application of econometric techniques to those data.

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.

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.

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.

Kian Tang (Chemistry)

Our research group focuses on the development and mechanistic study of transition metal-catalyzed reactions for the formation of new carbon-carbon and carbon-heteroatom bonds.  A critical challenge for synthetic chemists is control of the regio-, diastereo-, and enantioselectivity of organic transformations.  Our group is currently developing a general strategy for controlling these elements through the use of a scaffolding ligand.  We are currently using computational chemistry to predict the properties of these new ligands.  In particular computational chemistry provides important structural information as well as the relative stabilities of newly designed ligands.  With the aid of computational chemistry we aim to improve both the efficiency and activity of the scaffolding ligands.

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.

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.

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.