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Articles 1711 - 1740 of 2835

Full-Text Articles in Econometrics

Economic Growth And Development In Sub-Saharan Africa, Asia, And Latin America: The Impact Of Human Capital, Angui D. Macham May 2015

Economic Growth And Development In Sub-Saharan Africa, Asia, And Latin America: The Impact Of Human Capital, Angui D. Macham

Applied Economics Theses

My thesis is that human capital has been important to growth, but has had differential impact in three areas: Sub-Sahara Africa; Asia; and Latin America. I estimated three regional models to determine the impact of human capital on the growth of gross domestic product (GDP) per capita. Each model was estimated using the pooled OLS approach with a sample of 10 countries within each region. I make use of data from the Penn World Table- international comparisons of production data bank. I found that only the African region had statistically significant coefficients for both physical and human capital. For the …

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Averaged Instrumental Variables Estimators, Yoonseok Lee, Yu Zhou May 2015

Averaged Instrumental Variables Estimators, Yoonseok Lee, Yu Zhou

Center for Policy Research

We develop averaged instrumental variables estimators as a way to deal with many weak instruments. We propose a weighted average of the preliminary k-class estimators, where each estimator is obtained using different subsets of the available instrumental variables. The averaged estimators are shown to be consistent and to satisfy asymptotic normality. Furthermore, its approximate mean squared error reveals that using a small number of instruments for each preliminary k-class estimator reduces the finite sample bias, while averaging prevents the variance from inflating. Monte Carlo simulations find that the averaged estimators compare favorably with alternative instrumental-variable-selection approaches when the strength levels …

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Downtown Parking Meter Demand In El Paso, Thomas M. Fullerton Jr., E. Pallarez, Adam G. Walke May 2015

Downtown Parking Meter Demand In El Paso, Thomas M. Fullerton Jr., E. Pallarez, Adam G. Walke

Border Region Modeling Project

Prior research establishes that the price of parking in the city centre often impacts the decision to travel downtown and the mode of transportation utilized. Other factors that influence the decision to drive and park downtown have received less attention. This study uses time series data to analyse the demand for metered parking spaces in El Paso, Texas, USA. In addition to meter rates, the determinants of demand include personal income, gasoline prices, and the price of a substitute good, parking garage spaces. Because international bridges connect downtown El Paso to neighbouring Ciudad Juárez, Chihuahua, Mexico, the impacts of trans-boundary …

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Asymptotic Distribution And Finite-Sample Bias Correction Of Qml Estimators For Spatial Dependence Model, Shew Fan Liu, Zhenlin Yang May 2015

Asymptotic Distribution And Finite-Sample Bias Correction Of Qml Estimators For Spatial Dependence Model, Shew Fan Liu, Zhenlin Yang

Research Collection School Of Economics

In studying the asymptotic and finite sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model. In particular, the effect of spatial dependence on the convergence rate of the QML estimators has not been formally studied, and methods for correcting finite sample bias of the QML estimators have not been given. This paper fills in these gaps. Of the two, bias correction is particularly important to the applications of this model, as …

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Limit Theory For Vars With Mixed Roots Near Unity, Peter C. B. Phillips, Ji Hyung Lee May 2015

Limit Theory For Vars With Mixed Roots Near Unity, Peter C. B. Phillips, Ji Hyung Lee

Research Collection School Of Economics

Limit theory is developed for nonstationary vector autoregression (VAR) with mixed roots in the vicinity of unity involving persistent and explosive components. Statistical tests for common roots are examined and model selection approaches for discriminating roots are explored. The results are useful in empirical testing for multiple manifestations of nonstationarity - in particular for distinguishing mildly explosive roots from roots that are local to unity and for testing commonality in persistence.

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Modified Qml Estimation Of Spatial Autoregressive Models With Unknown Heteroskedasticity And Nonnormality, Shew Fan Liu, Zhenlin Yang May 2015

Modified Qml Estimation Of Spatial Autoregressive Models With Unknown Heteroskedasticity And Nonnormality, Shew Fan Liu, Zhenlin Yang

Research Collection School Of Economics

In the presence of heteroskedasticity, Lin and Lee (2010) show that the quasi-maximum likelihood (QML) estimator of the spatial autoregressive (SAR) model can be inconsistent as a ‘necessary’ condition for consistency can be violated, and thus propose robust GMM estimators for the model. In this paper, we first show that this condition may hold in certain situations and when it does the regular QML estimator can still be consistent. In cases where this condition is violated, we propose a simple modified QML estimation method robust against unknown heteroskedasticity. In both cases, asymptotic distributions of the estimators are derived, and methods …

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Testing Additive Separability Of Error Term In Nonparametric Structural Models, Liangjun Su, Yundong Tu, Aman Ullah May 2015

Testing Additive Separability Of Error Term In Nonparametric Structural Models, Liangjun Su, Yundong Tu, Aman Ullah

Research Collection School Of Economics

This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively. We propose a test statistic under a set of identification conditions considered by Hoderlein, Su and White (2012), which require the existence of a control variable such that the regressor is independent of the error term given the control variable. The test statistic is motivated from the observation that, under the additive error structure, the partial derivative of the nonparametric structural function with respect to the error term is one under identification. The asymptotic distribution …

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Specification Test For Panel Data Models With Interactive Fixed Effects, Liangjun Su, Sainan Jin, Yonghui Zhang May 2015

Specification Test For Panel Data Models With Interactive Fixed Effects, Liangjun Su, Sainan Jin, Yonghui Zhang

Research Collection School Of Economics

In this paper, we propose a consistent nonparametric test for linearity in panel data models with interactive fixed effects. To construct the test statistic, we need to estimate the model under the null hypothesis of linearity and then obtain the restricted residuals. We show that after being appropriately centered and standardized, the test statistic is asymptotically normally distributed both under the null hypothesis and a sequence of Pitman local alternatives. To improve the finite sample performance, we propose a bootstrap procedure to obtain the bootstrap p-values. A small set of Monte Carlo simulations illustrates that our test performs well in …

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A General Method For Third-Order Bias And Variance Corrections On A Nonlinear Estimator, Zhenlin Yang May 2015

A General Method For Third-Order Bias And Variance Corrections On A Nonlinear Estimator, Zhenlin Yang

Research Collection School Of Economics

Motivated by a recent study of Bao and Ullah (2007a) on finite sample properties of MLE in the pure SAR (spatial autoregressive) model, a general method for third-order bias and variance corrections on a nonlinear estimator is proposed based on stochastic expansion and bootstrap. Working with concentrated estimating equation simplifies greatly the high-order expansions for bias and variance; a simple bootstrap procedure overcomes a major difficulty in analytically evaluating expectations of various quantities in the expansions. The method is then studied in detail using a more general SAR model, with its effectiveness in correcting bias and improving inference fully demonstrated …

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On Time-Varying Factor Models: Estimation And Testing, Liangjun Su, Xia Wang May 2015

On Time-Varying Factor Models: Estimation And Testing, Liangjun Su, Xia Wang

Research Collection School Of Economics

Conventional factor models assume that factor loadings are fixed over a long horizon of time, which appears overly restrictive and unrealistic in applications. In this paper, we introduce a time-varying factor model where factor loadings are allowed to change smoothly over time. We propose a local version of the principal component method to estimate the latent factors and time-varying factor loadings simultaneously. We establish the limiting distributions of the estimated factors and factor loadings in the standard large N and large T framework. We also propose a BIC-type information criterion to determine the number of factors, which can be used …

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A Bayesian Specification Test, Yong Li, Tao Zeng, Jun Yu May 2015

A Bayesian Specification Test, Yong Li, Tao Zeng, Jun Yu

Research Collection School Of Economics

A Bayesian test statistic is proposed to assess the model specification after the model is estimated by Bayesian MCMC methods. The proposed approach does not require an alternative model to be specified and is applicable to a variety of models, including latent variable models, structural dynamic choice models, and dynamics stochastic general equilibrium (DSGE) models, for which frequentist methods are difficult to use. The properties of the test statistic are established and its implementation is discussed. The test is easy to use and the test statistic can be calculated from MCMC outputs even when there are latent variables. The method …

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Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors, Riley K. Acton Apr 2015

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.

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A Different Approach To Jensen’S Alpha And Its Relationship With Returning Ranking, Tingyu Du Ms. Apr 2015

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.

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New York Camp Econometrics X Program, Center For Policy Research Apr 2015

New York Camp Econometrics X Program, Center For Policy Research

Camp Econometrics-Programs

No abstract provided.

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Evaluating The Impact Of The American Recovery And Reinvestment Act’S Btop Program On Broadband Adoption, James Prieger, Janice A. Hauge Apr 2015

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 …

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Rhode Island Current Conditions Index -- April 2015, Leonard Lardaro Apr 2015

Rhode Island Current Conditions Index -- April 2015, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin Apr 2015

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 …

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Optimal Jackknife For Unit Root Models, Ye Chen, Jun Yu Apr 2015

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.

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A Combined Approach To The Inference Of Conditional Factor Models, Yan Li, Liangjun Su, Yuewa Xu Apr 2015

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 …

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Nonparametric Predictive Regression, Ioannis Kasparis, Elena Andreou, Peter C. B. Phillips Apr 2015

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. …

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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 Apr 2015

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 …

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Economic Analysis Of Flight Delay, Nathan D. Boettcher Mar 2015

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 …

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Analyzing Options Market Toxicity And The Black-Scholes Formula In The Presence Of Jump Diffusion As Simulated With Agent-Based Modeling, William D. Elliott Mar 2015

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.

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Rhode Island Current Conditions Index -- March 2015, Leonard Lardaro Mar 2015

Rhode Island Current Conditions Index -- March 2015, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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Estimation Of Heterogeneous Panels With Structural Breaks, Badi Baltagi Mar 2015

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 …

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Qml Estimation Of Dynamic Panel Data Models With Spatial Errors, Liangjun Su, Zhenlin Yang Mar 2015

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 …

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Enriching Surveys With Supplementary Data And Its Application To Studying Wage Regression, Denis H. Y. Leung, Ken Yamada, Biao Zhang Mar 2015

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 …

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Enriching Surveys With Supplementary Data And Its Application To Studying Wage Regression, Denis H. Y. Leung, Ken Yamada, Biao Zhang Mar 2015

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 …

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Asymptotic Theory For Linear Diffusions Under Alternative Sampling Scheme, Qiankun Zhou, Jun Yu Mar 2015

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.

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Lm Tests Of Spatial Dependence Based On Bootstrap Critical Values, Zhenlin Yang Mar 2015

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 …

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