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Articles 2251 - 2280 of 2838

Full-Text Articles in Economics

Transparency, Efficiency And The Distribution Of Economic Welfare In Pass-Through Investment Trust Games, Thomas A. Rietz, Roman M. Sheremeta, Timothy W. Shields, Vernon Smith Jan 2011

Transparency, Efficiency And The Distribution Of Economic Welfare In Pass-Through Investment Trust Games, Thomas A. Rietz, Roman M. Sheremeta, Timothy W. Shields, Vernon Smith

ESI Working Papers

We design an experiment to examine welfare and behavior in a multi-level trust game representing a pass through investment in an intermediated market. In a repeated game, an Investor invests via an Intermediary who lends to a Borrower. A pre-experiment one-shot version of the game serves as a baseline and to type each subject. We alter the transparency of exchanges between non-adjacent parties. We find transparency of the exchanges between the investor and intermediary does not significantly affect welfare. However, transparency regarding exchanges between the intermediary and borrower promotes trust on the part of the investor, increasing welfare. Further, this …

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Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung Jan 2011

Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung

Research Collection School Of Economics

We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …

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Assessing Post-Ada Employment: Some Econometric Evidence And Policy Considerations, Christopher L. Griffin Jr., John J. Donohue Iii, Michael Ashley Stein, Sascha Becker Jan 2011

Assessing Post-Ada Employment: Some Econometric Evidence And Policy Considerations, Christopher L. Griffin Jr., John J. Donohue Iii, Michael Ashley Stein, Sascha Becker

Faculty Scholarship

This article explores the relationship between the Americans with Disabilities Act (“ADA”) and the relative labor market outcomes for people with disabilities. Using individual-level longitudinal data from 1981 to 1996 derived from the previously unexploited Panel Study of Income Dynamics (“PSID”), we examine the possible effect of the ADA on (1) annual weeks worked; (2) annual earnings; and (3) hourly wages for a sample of 7120 unique male household heads between the ages of 21 and 65 as well as a subset of 1437 individuals appearing every year from 1981 to 1996. Our analysis of the larger sample suggests the …

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Nonparametric And Semiparametric Panel Econometric Models: Estimation And Testing, Liangjun Su, Aman Ullah Jan 2011

Nonparametric And Semiparametric Panel Econometric Models: Estimation And Testing, Liangjun Su, Aman Ullah

Research Collection School Of Economics

This paper gives a selective review on the recent developments of nonparametric and semiparametric panel data models. We focus on the conventional panel data models with one-way error component structure, partially linear panel data models, varying coefficient panel data models, nonparametric panel data models with multi-factor error structure, and nonseparable nonparametric panel data models. For each area, we discuss the basic models and ideas of estimation, and comment on the asymptotic properties of different estimators and specification tests. Much theoretical and empirical research is needed in this emerging area

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Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah Jan 2011

Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah

Research Collection School Of Economics

We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.

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Rhode Island Current Conditions Index — December 2010, Leonard Lardaro Dec 2010

Rhode Island Current Conditions Index — December 2010, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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Estimating A Small-Scale Macroeconometric Model (Ssmm) For Nigeria: A Dynamic Stochastic General Equilibrium (Dsge) Approach, Charlse N.O Mordi, Michael A. Adebiyi Dec 2010

Estimating A Small-Scale Macroeconometric Model (Ssmm) For Nigeria: A Dynamic Stochastic General Equilibrium (Dsge) Approach, Charlse N.O Mordi, Michael A. Adebiyi

CBN Occasional Papers

This paper attempts to develop a small scale macroeconometric model for the Nigerian economy using dynamic stochastic general equilibrium (DSGE) methodology. Particular attention is paid to using impulse responses to explain the dynamic properties of the model. This model incorporates expectation as an anchor in the forward-looking monetary policy objective of the Central Bank of Nigeria (CBN). It captures most of the channels through which policymakers believe monetary policy can influence a small open economy with a managed floating exchange rate. The model was taken to the data by means of Bayesian estimation with the following major findings. First, although …

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Testing Structural Change In Partially Linear Models, Liangjun Su, Halbert White Dec 2010

Testing Structural Change In Partially Linear Models, Liangjun Su, Halbert White

Research Collection School Of Economics

We consider two tests of structural change for partially linear time-series models. The first tests for structural change in the parametric component, based on the cumulative sums of gradients from a single semiparametric regression. The second tests for structural change in the parametric and nonparametric components simultaneously, based on the cumulative sums of weighted residuals from the same semiparametric regression. We derive the limiting distributions of both tests under the null hypothesis of no structural change and for sequences of local alternatives. We show that the tests are generally not asymptotically pivotal under the null but may be free of …

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Need Singapore Fear Floating? A Dsge-Var Approach, Hwee Kwan Chow, Paul D. Mcnelis Dec 2010

Need Singapore Fear Floating? A Dsge-Var Approach, Hwee Kwan Chow, Paul D. Mcnelis

Research Collection School Of Economics

This paper uses a DSGE-VAR model to examine the managed exchange-rate system at work in Singapore and asks if the country has any reason to fear floating the exchange rate with a Taylor rule inflation-targeting mechanism that uses the short term interest rate instead of the exchange rate as the benchmark monetary policy instrument. Our simulation results show that the use of a more flexible exchange rate system will reduce volatility in inflation and investment but consumption volatility will increase. Overall, there are neither signi…cant welfare gains or losses in the regime shift. Given the highly open and trade …

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Energy And Economic Growth: A State-Level Analysis, Nathanael D. Peach Nov 2010

Energy And Economic Growth: A State-Level Analysis, Nathanael D. Peach

Faculty Publications - College of Business

No abstract provided.

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Rhode Island Current Conditions Index — November 2010, Leonard Lardaro Nov 2010

Rhode Island Current Conditions Index — November 2010, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu Nov 2010

Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu

Research Collection Lee Kong Chian School Of Business

In this paper a Markov chain Monte Carlo (MCMC) technique is developed for the Bayesian analysis of structural credit risk models with microstructure noises. The technique is based on the general Bayesian approach with posterior computations performed by Gibbs sampling. Simulations from the Markov chain, whose stationary distribution converges to the posterior distribution, enable exact finite sample inferences of model parameters. The exact inferences can easily be extended to latent state variables and any nonlinear transformation of state variables and parameters, facilitating practical credit risk applications. In addition, the comparison of alternative models can be based on devian information criterion …

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Rhode Island Current Conditions Index — October 2010, Leonard Lardaro Oct 2010

Rhode Island Current Conditions Index — October 2010, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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New York Camp Econometrics V Program, Center For Policy Research Oct 2010

New York Camp Econometrics V Program, Center For Policy Research

Camp Econometrics-Programs

No abstract provided.

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Corporate Transparency, Private Information And Stock Price Synchronicity., Mohammed Sharaf Mohsen Shaiban Oct 2010

Corporate Transparency, Private Information And Stock Price Synchronicity., Mohammed Sharaf Mohsen Shaiban

Student Works (2010-2019)

The issue of stock price synchronicity as a measure of stock price informativeness has recently attracted much research attention. Using cross-country data from 40 countries, this study investigates the relationship between corporate transparency (measured by reporting timeliness, financial analyst following and credibility of disclosures) and stock price synchronicity. In addition, this study investigates the moderating effects of reporting timeliness on the relationship between financial analyst and credibility of disclosures and stock price synchronicity. Specifically, it examines whether the relationship between financial analysts and disclosure credibility and stock price synchronicity is stronger or weaker given the range of timeliness of financial …

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Border Metropolitan Water Forecast Accuracy, Thomas M. Fullerton Jr., Angel L. Molina Jr. Oct 2010

Border Metropolitan Water Forecast Accuracy, Thomas M. Fullerton Jr., Angel L. Molina Jr.

Border Region Modeling Project

Municipal water consumption planning is an active area of research due to infrastructure construction and maintenance costs, supply constraints, and water quality assurance. In spite of that, relatively few water forecast accuracy assessments have been completed to date, although some internal documentation may exist as part of the proprietary “grey literature.” This study utilizes a data set of previously published municipal consumption forecasts to partially fill that gap in the empirical water economics literature. Previously published municipal water econometric forecasts for three public utilities are examined for predictive accuracy against two random walk benchmarks commonly used in regional analyses. Descriptive …

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Estimating The Garch Diffusion: Simulated Maximum Likelihood In Continuous Time, Tore Selland Kleppe, Jun Yu, Hans J. Skaug Oct 2010

Estimating The Garch Diffusion: Simulated Maximum Likelihood In Continuous Time, Tore Selland Kleppe, Jun Yu, Hans J. Skaug

Research Collection School Of Economics

A new algorithm is developed to provide a simulated maximum likelihood estimation of the GARCH diffusion model of Nelson (1990) based on return data only. The method combines two accurate approximation procedures, namely, the polynomial expansion of Ait-Sahalia (2008) to approximate the transition probability density of return and volatility, and the Efficient Importance Sampler (EIS) of Richard and Zhang (2007) to integrate out the volatility. The first and second order terms in the polynomial expansion are used to generate a base-line importance density for an EIS algorithm. The higher order terms are included when evaluating the importance weights. Monte Carlo …

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Bayesian Hypothesis Testing In Latent Variable Models, Yong Li, Jun Yu Oct 2010

Bayesian Hypothesis Testing In Latent Variable Models, Yong Li, Jun Yu

Research Collection School Of Economics

Hypothesis testing using Bayes factors (BFs) is known to suffer from several problems in the context of latent variable models. The first problem is computational. Another problem is that BFs are not well defined under the improper prior. In this paper, a new Bayesian method, based on decision theory and the EM algorithm, is introduced to test a point hypothesis in latent variable models. The new statistic is a by-product of the Bayesian MCMC output and, hence, easy to compute. It is shown that the new statistic is appropriately defined under improper priors because the method employs a continuous loss …

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A Conversation With Eric Ghysels, Peter C. B. Phillips, Jun Yu Oct 2010

A Conversation With Eric Ghysels, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

Eric Ghysels is the Bernstein Distinguished Professor of Economics and Professor of Finance at University of North Carolina at Chapel Hill. In 2008, Eric Ghysels and Robert Engle (2003 Nobel co-Laureate in Economic Science with Clive Granger) founded the Society for Financial Econometrics (SoFiE), establishing a global network of academics and practitioners dedicated to the fast-growing field of financial econometrics. In June 2010, Eric visited the Centre for Financial Econometrics (CoFiE) and the Sim Kee Boon Institute (SKBI) of Financial Economics at Singapore Management University. During his visit we conversed with him about SoFiE and the growing toolroom of financial …

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Bias In Estimating Multivariate And Univariate Diffusions, Xiaohu Wang, Peter C. B. Phillips, Jun Yu Oct 2010

Bias In Estimating Multivariate And Univariate Diffusions, Xiaohu Wang, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

Multivariate continuous time models are now widely used in economics and finance. Empirical applications typically rely on some process of discretization so that the system may be estimated with discrete data. This paper introduces a framework for discretizing linear multivariate continuous time systems that includes the commonly used Euler and trapezoidal approximations as special cases and leads to a general class of estimators for the mean reversion matrix. Asymptotic distributions and bias formulae are obtained for estimates of the mean reversion parameter. Explicit expressions are given for the discretization bias and its relationship to estimation bias in both multivariate and …

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Measurement And High Finance, Peter C. B. Phillips, Jun Yu, Eric Ghysels Oct 2010

Measurement And High Finance, Peter C. B. Phillips, Jun Yu, Eric Ghysels

Research Collection School Of Economics

Turbulence in the world of banking and finance over the last two years has riveted media attention on the financial industry, exposing practices, products and risks in the industry to widespread public scrutiny. Questions continue to be asked about the management and regulation of an industry whose performance is now seen to affect the world’s financial health and its prospects as much as it does national savings and individual retirement funds.

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Simulation-Based Estimation Methods For Financial Time Series Models, Jun Yu Oct 2010

Simulation-Based Estimation Methods For Financial Time Series Models, Jun Yu

Research Collection School Of Economics

This paper overviews some recent advances on simulatio n-based methods of estimating time series models and asset pricing models that are widely used in finance. The simulation based methods have proven to be particularly useful when the likelihood function and moments do not have tractable forms and hence the maximum likelihood method (MLE) and the generalized method of moments (GMM) are difficult to use. They can also be useful for improving the finite sample performance of the traditional methods when financial time series are highly persistent and when the quantity of interest is a highly nonlinear function of system parameters.The …

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Asymptotic Distributions Of The Least Squares Estimator For Diffusion Processes, Qiankun Zhou, Jun Yu Oct 2010

Asymptotic Distributions Of The Least Squares Estimator For Diffusion Processes, Qiankun Zhou, Jun Yu

Research Collection School Of Economics

The asymptotic distributions of the least squares estimator of the mean reversion parameter (κ) are developed in a general class of diffusion models under three sampling schemes, namely, ongspan, in-fill and the combination of long-span and in-fill. The models have an affine structure in the drift function, but allow for nonlinearity in the diffusion function. The limiting distributions are quite different under the alternative sampling schemes. In particular, the in-fill limiting distribution is non-standard and depends on the initial condition and the time span whereas the other two are Gaussian. Moreover, while the other two distributions are discontinuous at κ …

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Bias-Corrected Estimation For Spatial Autocorrelation, Zhenlin Yang Oct 2010

Bias-Corrected Estimation For Spatial Autocorrelation, Zhenlin Yang

Research Collection School Of Economics

The biasedness issue arising from the maximum likelihood estimation of the spatial autoregressive model (SAR) is further investigated under a broader set-up than that in Bao and Ullah (2007a). A major difficulty in analytically evaluating the expectations of ratios of quadratic forms is overcome by a simple bootstrap procedure. With that, the corrections on bias and variance of the spatial estimator can easily be made up to third-order, and once this is done, the estimators of other model parameters become nearly unbiased. Compared with the analytical approach, the new approach is much simpler, and can easily be extended to other …

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A Study Of Price Evolution In Online Toy Market, Zhenlin Yang, Lydia L Gan, Fang-Fang Tang Oct 2010

A Study Of Price Evolution In Online Toy Market, Zhenlin Yang, Lydia L Gan, Fang-Fang Tang

Research Collection School Of Economics

We study and contrast pricing and price evolution of online only (Dotcom) and online branch of multi-channel retailers (OBMCRs) based on two panel data sets collected from online toy markets. Panel data regression analyses reveal several interesting empirical results: over time, OBMCRs and Dotcoms charge similar prices on average but Dotcoms significantly increase their shipping costs that eventually drive the overall average price of Dotcoms higher than that of OBMCRs. Price dispersions of both types of retailers are persistent. The price dispersion of OBMCRs is higher than that of Dotcoms at the beginning and does not change much over time, …

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Standardized Lm Tests For Spatial Error Dependence In Linear Or Panel Regressions, Badi H. Baltagi, Zhenlin Yang Oct 2010

Standardized Lm Tests For Spatial Error Dependence In Linear Or Panel Regressions, Badi H. Baltagi, Zhenlin Yang

Research Collection School Of Economics

The robustness of the LM tests for spatial error dependence of Burridge (1980) for the linear regression model and Anselin (1988) for the panel regression model are examined. While both tests are asymptotic ally robust against distributional misspecification, their finite sample behavior can be sensitive to the spatial layout. To overcome this shortcoming, standardized LM tests are suggested. Monte Carlo results show that the new tests possess good finite sample properties. An important observation made throughout this study is that the LM tests for spatial dependence need to be both mean- and variance-adjusted for good finite sample performance to be …

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A New Bayesian Unit Root Test In Stochastic Volatility Models, Yong Li, Jun Yu Oct 2010

A New Bayesian Unit Root Test In Stochastic Volatility Models, Yong Li, Jun Yu

Research Collection School Of Economics

A new posterior odds analysis is proposed to test for a unit root in volatility dynamics in the context of stochastic volatility models. This analysis extends the Bayesian unit root test of So and Li (1999, Journal of Business Economic Statistics) in two important ways. First, a numerically more stable algorithm is introduced to compute the Bayes factor, taking into account the special structure of the competing models. Owing to its numerical stability, the algorithm overcomes the problem of diverged “size” in the marginal likelihood approach. Second, to improve the “power” of the unit root test, a mixed prior specification …

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Smoothing Local-To-Moderate Unit Root Theory, Peter C. B. Phillips, Tassos Magdalinos, Liudas Giraitis Oct 2010

Smoothing Local-To-Moderate Unit Root Theory, Peter C. B. Phillips, Tassos Magdalinos, Liudas Giraitis

Research Collection School Of Economics

A limit theory is established for autoregressive time series that smooths the transition between local and moderate deviations from unity and provides a transitional form that links conventional unit root distributions and the standard normal. Edgeworth expansions of the limit theory are given. These expansions show that the limit theory that holds for values of the autoregressive coefficient that are closer to stationarity than local (i.e. deviations of the form rho = 1 + c/n, where n is the sample size and c < 0) holds up to the second order. Similar expansions around the limiting Cauchy density are provided for the mildly explosive case. (C) 2010 Elsevier B.V. All rights reserved.

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Rhode Island Current Conditions Index — September 2010, Leonard Lardaro Sep 2010

Rhode Island Current Conditions Index — September 2010, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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A Robust Lm Test For Spatial Error Components, Zhenlin Yang Sep 2010

A Robust Lm Test For Spatial Error Components, Zhenlin Yang

Research Collection School Of Economics

This paper presents previous termanext term modified previous termLM test of spatial error components,next term which is shown to be previous termrobustnext term against distributional misspecifications and previous termspatialnext term layouts. The proposed previous termtestnext term differs from the previous termLM testnext term of Anselin (2001) by previous termanext term term in the denominators of the previous termtestnext term statistics. This term disappears when either the previous termerrorsnext term are normal, or the variance of the diagonal elements of the product of previous termspatialnext term weights matrix and its transpose is zero or approaches to zero as sample size goes …

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