Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors,
2015
Ursinus College
Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors, Riley K. Acton
Business and Economics Honors Papers
Producing more graduates in Science, Technology, Engineering, and Mathematics (STEM), as well as ensuring students complete college in a timely manner are both areas of national public policy interest. In order to improve these two outcomes, it is imperative to understand what factors lead undergraduate students to persist in, and ultimately graduate with STEM degrees. This paper uses data from the Beginning Postsecondary Students Longitudinal Study, provided by The National Center of Education Statistics, to model the time to baccalaureate degree among STEM majors using a Cox proportional hazard model.
A Different Approach To Jensen’S Alpha And Its Relationship With Returning Ranking,
2015
Washington University in St. Louis
A Different Approach To Jensen’S Alpha And Its Relationship With Returning Ranking, Tingyu Du Ms.
Undergraduate Economic Review
Based on Michael C. Jensen’s CAPM model (1968), this paper refines it with dummy variables included. It examines if fund manager’s skill is contributing to fund’s performance within a five-year span from June 2009 to June 2014, and if high total return ranking is related to outstanding Jensen’s Alpha. The findings coincide with Jensen’s research results.
New York Camp Econometrics X Program,
2015
Syracuse University
New York Camp Econometrics X Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Evaluating The Impact Of The American Recovery And Reinvestment Act’S Btop Program On Broadband Adoption,
2015
Pepperdine University
Evaluating The Impact Of The American Recovery And Reinvestment Act’S Btop Program On Broadband Adoption, James Prieger, Janice A. Hauge
School of Public Policy Working Papers
The American Recovery and Reinvestment Act’s Broadband Technology Opportunities Program (BTOP) spent $4.7B during 2009-2013 to, int. al, increase broadband adoption in underserved communities. We characterize the BTOP grants and examine the impact of the awards on broadband adoption. Econometric specifications controlling for award endogeneity related to observed and unobserved county-level factors find that spending is apparently associated with increased broadband adoption. Further investigation, however, reveals that the impacts of spending are nonlinear and even nonmonotonic over the range of county-level BTOP spending in the data. Controlling for trends to reduce the potential for spurious correlation between spending and outcomes …
Rhode Island Current Conditions Index -- April 2015,
2015
University of Rhode Island
Rhode Island Current Conditions Index -- April 2015, Leonard Lardaro
The Rhode Island Current Conditions Index
No abstract provided.
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures,
2015
Singapore Management University
Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin
Research Collection School Of Economics
We consider the problem of determining the number of factors and selecting the proper regressors in linear dynamic panel data models with interactive fixed effects. Based on the preliminary estimates of the slope parameters and factors a la Bai and Ng (2009) and Moon andWeidner (2014a), we propose a method for simultaneous selection of regressors and factors and estimation through the method of adaptive group Lasso (least absolute shrinkage and selection operator). We show that with probability approaching one, our method can correctly select all relevant regressors and factors and shrink the coefficients of irrelevant regressors and redundant factors to …
Optimal Jackknife For Unit Root Models,
2015
Capital University of Economics and Business
Optimal Jackknife For Unit Root Models, Ye Chen, Jun Yu
Research Collection School Of Economics
A new jackknife method is introduced to remove the first order bias in unit root models. It is optimal in the sense that it minimizes the variance among all the jackknife estimators of the form considered in Phillips and Yu (2005) and Chambers and Kyriacou (2013) after the number of subsamples is selected. Simulations show that the new jackknife reduces the variance of that of Chambers and Kyriacou by about 10% for any selected number of subsamples without compromising bias reduction. The results continue to hold true in near unit root models. (C) 2014 Elsevier B.V. All rights reserved.
A Combined Approach To The Inference Of Conditional Factor Models,
2015
Temple University
A Combined Approach To The Inference Of Conditional Factor Models, Yan Li, Liangjun Su, Yuewa Xu
Research Collection School Of Economics
This article develops a new methodology for estimating and testing conditional factor models in finance. We propose a two-stage procedure that naturally unifies the two existing approaches in the finance literature-the parametric approach and the nonparametric approach. Our combined approach possesses important advantages over both methods. Using our two-stage combined estimator, we derive new test statistics for investigating key hypotheses in the context of conditional factor models. Our tests can be performed on a single asset or jointly across multiple assets. We further propose a novel test to directly check whether the parametric model used in our first stage is …
Nonparametric Predictive Regression,
2015
University of Cyprus
Nonparametric Predictive Regression, Ioannis Kasparis, Elena Andreou, Peter C. B. Phillips
Research Collection School Of Economics
A unifying framework for inference is developed in predictive regressions where the predictor has unknown integration properties and may be stationary or nonstationary. Two easily implemented nonparametric F-tests are proposed. The limit distribution of these predictive tests is nuisance parameter free and holds for a wide range of predictors including stationary as well as non-stationary fractional and near unit root processes. Asymptotic theory and simulations show that the proposed tests are more powerful than existing parametric predictability tests when deviations from unity are large or the predictive regression is nonlinear. Empirical illustrations to monthly SP500 stock returns data are provided. …
Lag Length Selection For Unit Root Tests In The Presence Of Nonstationary Volatility,
2015
University of Bologna
Lag Length Selection For Unit Root Tests In The Presence Of Nonstationary Volatility, Giuseppe Cavaliere, Peter C. B. Phillips, Stephan Smeekes, A. M. Robert Taylor
Research Collection School Of Economics
A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey–Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency …
Economic Analysis Of Flight Delay,
2015
Pepperdine University
Economic Analysis Of Flight Delay, Nathan D. Boettcher
Seaver College Research And Scholarly Achievement Symposium
Our project began as an investigation into the phenomenon of flight delay. We approached this problem with two goals in mind. First, we used mathematical statistics and econometric methods to develop a predictive model of flight delay. An improved forecasting process has obvious benefits for customers, and would additionally shed light on the factors which airports and airlines should seek to change in order to reduce flight delay. Our secondary goal was to complement this predictive research with a theoretical analysis of the incentive structure that consumers and producers face. We limited the scope of this model to delayed flights …
Analyzing Options Market Toxicity And The Black-Scholes Formula In The Presence Of Jump Diffusion As Simulated With Agent-Based Modeling,
2015
Collin County Community College District
Analyzing Options Market Toxicity And The Black-Scholes Formula In The Presence Of Jump Diffusion As Simulated With Agent-Based Modeling, William D. Elliott
Undergraduate Economic Review
This paper presents new and significant research on the Black-Scholes Formula using the agent-based modeling software NetLogo. The software was used to simulate an options market subject to jump diffusion. Since the widely-used Black-Scholes Formula has at times proven unreliable, this research sought to understand circumstances that render the formula ineffective. It was hypothesized that markets would become difficult to trade in or “toxic” at low price volatility but high jump volatility. Further, it was predicted that kurtosis would alert the presence of toxic markets by accurately and consistently conveying whether jump diffusion was present.
Rhode Island Current Conditions Index -- March 2015,
2015
University of Rhode Island
Rhode Island Current Conditions Index -- March 2015, Leonard Lardaro
The Rhode Island Current Conditions Index
No abstract provided.
Estimation Of Heterogeneous Panels With Structural Breaks,
2015
Syracuse University
Estimation Of Heterogeneous Panels With Structural Breaks, Badi Baltagi
Center for Policy Research
This paper extends Pesaran's (2006) work on common correlated effects (CCE) estimators for large heterogeneous panels with a general multifactor error structure by allowing for unknown common structural breaks. Structural breaks due to new policy implementation or major technological shocks, are more likely to occur over a longer time span. Consequently, ignoring structural breaks may lead to inconsistent estimation and invalid inference. We propose a general framework that includes heterogeneous panel data models and structural break models as special cases. The least squares method proposed by Bai (1997a, 2010) is applied to estimate the common change points, and the consistency …
Qml Estimation Of Dynamic Panel Data Models With Spatial Errors,
2015
Singapore Management University
Qml Estimation Of Dynamic Panel Data Models With Spatial Errors, Liangjun Su, Zhenlin Yang
Research Collection School Of Economics
We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models, and prove consistency and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residual-based bootstrap method for estimating the standard errors of the QML estimators. Monte Carlo simulation shows that both the QML estimators and the bootstrap standard errors perform well in finite samples under a correct assumption on initial observations, but may …
Enriching Surveys With Supplementary Data And Its Application To Studying Wage Regression,
2015
Singapore Management University
Enriching Surveys With Supplementary Data And Its Application To Studying Wage Regression, Denis H. Y. Leung, Ken Yamada, Biao Zhang
Research Collection School Of Economics
We consider the problem of supplementing survey data with additional information from a population. The framework we use is very general; examples are missing data problems, measurement error models and combining data from multiple surveys. We do not require the survey data to be a simple random sample of the population of interest. The key assumption we make is that there exists a set of common variables between the survey and the supplementary data. Thus, the supplementary data serve the dual role of providing adjustments to the survey data for model consistencies and also enriching the survey data for improved …
Enriching Surveys With Supplementary Data And Its Application To Studying Wage Regression,
2015
Singapore Management University
Enriching Surveys With Supplementary Data And Its Application To Studying Wage Regression, Denis H. Y. Leung, Ken Yamada, Biao Zhang
Research Collection School Of Economics
We consider the problem of supplementing survey data with additional information from a population. The framework we use is very general; examples are missing data problems, measurement error models and combining data from multiple surveys. We do not require the survey data to be a simple random sample of the population of interest. The key assumption we make is that there exists a set of common variables between the survey and the supplementary data. Thus, the supplementary data serve the dual role of providing adjustments to the survey data for model consistencies and also enriching the survey data for improved …
Asymptotic Theory For Linear Diffusions Under Alternative Sampling Scheme,
2015
University of Southern California
Asymptotic Theory For Linear Diffusions Under Alternative Sampling Scheme, Qiankun Zhou, Jun Yu
Research Collection School Of Economics
The asymptotic distributions of the maximum likelihood estimator of the persistence parameter are developed in a linear diffusion model under three sampling schemes, long-span, in-fill and double. Simulations suggest that the in-fill asymptotic distribution gives a more accurate approximation to the finite sample distribution than the other two distributions. An empirical application highlights the difference in unit root testing based on the alternative asymptotic distributions.
Lm Tests Of Spatial Dependence Based On Bootstrap Critical Values,
2015
Singapore Management University
Lm Tests Of Spatial Dependence Based On Bootstrap Critical Values, Zhenlin Yang
Research Collection School Of Economics
To test the existence of spatial dependence in an econometric model, a convenient test is the Lagrange Multiplier (LM) test. However, evidence shows that, in finite samples, the LM test referring to asymptotic critical values may suffer from the problems of size distortion and low power, which become worse with a denser spatial weight matrix. In this paper, residual-based bootstrap methods are introduced for asymptotically refined approximations to the finite sample critical values of the LM statistics. Conditions for their validity are clearly laid out and formal justifications are given in general, and in detail under several popular spatial LM …
Bias Correction For Fixed Effects Spatial Panel Data Models,
2015
Singapore Management University
Bias Correction For Fixed Effects Spatial Panel Data Models, Zhenlin Yang, Jihai Yu, Shew Fan Liu
Research Collection School Of Economics
This paper examines the finite sample properties of the quasi maximum likelihood (QML) estimators of the fixed effects spatial panel data (FE-SPD) models of Lee and Yu (2010). Following the general bias correction methods recently developed by Yang (2015), we derive up to third-order bias corrections for the QML estimators of the FE-SPD model, and propose a simple bootstrap method for their practical implementation. Monte Carlo results reveal that the QML estimators of the spatial parameters can be quite biased and that a second-order bias correction effectively removes the bias. The validity of the bootstrap method is established. Variance corrections …
