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19
Estimating standard errors in finance panel data sets: comparing approaches.
 Review of Financial Studies
, 2009
"... Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solut ..."
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Cited by 890 (7 self)
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Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the FamaMacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use.
The local bootstrap for Markov processes
 J. Statist. Plann. Inference
, 2002
"... A nonparametric bootstrap procedure is proposed for stochastic processes which follow a general autoregressive structure. The procedure generates bootstrap replicates by locally resampling the original set of observations reproducing automatically its dependence properties. It avoids an initial non ..."
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Cited by 18 (3 self)
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A nonparametric bootstrap procedure is proposed for stochastic processes which follow a general autoregressive structure. The procedure generates bootstrap replicates by locally resampling the original set of observations reproducing automatically its dependence properties. It avoids an initial nonparametric estimation of process characteristics in order to generate the pseudotime series and the bootstrap replicates mimic several of the properties of the original process. Applications of the procedure in nonlinear time series analysis are considered and theoretically justi ed; some simulated and real data examples are discussed.
Original Article
, 2011
"... Adaptive wavelet filtering for bearing monitoring based on block bootstrapping and white noise test ..."
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Adaptive wavelet filtering for bearing monitoring based on block bootstrapping and white noise test
Original Article Adaptive
, 2011
"... wavelet filtering for bearing monitoring based on block bootstrapping and white noise test ..."
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wavelet filtering for bearing monitoring based on block bootstrapping and white noise test
Psychosocial Mediators of a Nurse Intervention to Increase Skin Selfexamination in Patients at High Risk for Melanoma
"... This prospective study examines psychosocialmediators of an efficacious skin selfexamination (SSE) intervention that includes provision of a wholebody digital photography book depicting the entire skin surface. Individuals (n = 100) with established risk factors for melanoma were recruited from th ..."
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This prospective study examines psychosocialmediators of an efficacious skin selfexamination (SSE) intervention that includes provision of a wholebody digital photography book depicting the entire skin surface. Individuals (n = 100) with established risk factors for melanoma were recruited from the Memorial SloanKettering Cancer Center Pigmented Lesion Clinic during their initial dermatologist visit and were randomized to receive a photobook immediately (n = 49) or 4 months after intervention delivery (n = 51). Potential mediators included selfefficacy and response efficacy drawn from Social Cognitive Theory, melanoma worry, and SSE anxiety drawn from SelfRegulation Theory, and skin cancer knowledge, and skin awareness. Only selfefficacy was a significant mediator, accounting for 8 % of the total effect of photobook enhancement on SSE adherence at 4 months. (Cancer Epidemiol Biomarkers Prev 2006;15(6):1212–6)
On Boostrap Prediction Intervals for Autoregressive Model
"... Keywords: Bootstrap method, Standard error, bias, bootstrap confidence t interval, prediction error rate, and autoregressive model. Background:Frequently, an estimated mean squared error is the only indicator or yardstick of measuring error in a prediction. However, the statement that the future va ..."
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Keywords: Bootstrap method, Standard error, bias, bootstrap confidence t interval, prediction error rate, and autoregressive model. Background:Frequently, an estimated mean squared error is the only indicator or yardstick of measuring error in a prediction. However, the statement that the future values falls in an interval with a specified probability is more informative. Prediction intervals have this probabilistic interpretation, which is similar to that of tolerance intervals . Two resampling methods yield prediction intervals that obtain some types of asymptotic invariance to the sampling distribution. The resampling procedure proposed here utilizes the bootstrap method. The bootstrap interval derives from an empirical distribution generated using bootstrap resampling. The bootstrap is a resampling technique whose aim is to gain information on the distribution of an estimator. Objective: The bootstrap method for measures of Statistical accuracy such as standard error, bias, prediction error and to complicated data structures such as autoregressive models are considered. We estimated the parameters and the bootstrap t confidence interval with an autoregressive model fitted to the real data. Results:Bootstrap prediction intervals provide a non parametric measure of the probable error of forecast from a standard linear autoregressive model. Empirical measure prediction error rate motivate the choice of these intervals, which are calculated by an application of the bootstrap methods, to a time series data. Conclution: Bootstrap prediction intervals represent a useful addition to the traditional set of measures to assess the accuracy of forecast. The asymptotic properties of the intervals do not depend upon the sampling distribution, and the bootstrap results suggest that the invariance approximately holds for relatively all sample sizes.
10.1177/0272989X04268960MEDICAL DECISION MAKING/???–??? 2004NOYES AND OTHERSCLIN APPLICATIONSSTEFFECTIVENE S OF PRAMIPEXOLE IN PARKINSON’S DISEASESEP–OCT Pramipexole v. Levodopa as Initial Treatment for Parkinson’s Disease:
"... Parkinson’s disease (PD) is a chronic neurodegenerative condition characterized by rigidity, bradykinesia, resting tremor, and postural instability. Prevalence rates increase with age and its slow progressive course is characterized by increasing morbidity and mortality.1 PD is most commonly treat ..."
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Parkinson’s disease (PD) is a chronic neurodegenerative condition characterized by rigidity, bradykinesia, resting tremor, and postural instability. Prevalence rates increase with age and its slow progressive course is characterized by increasing morbidity and mortality.1 PD is most commonly treated with levodopa, and its effectiveness in the early stages of disease is well established. However, with prolonged use, the effectiveness of levodopa diminishes and can adversely affect the course of disease by leading to disabling dyskinesias and motor fluctuations.2 Recently, 3 large multicenter randomized controlled studies directly comparing a dopamine agonist with levodopa as initial therapy in early PD have been published.3–5 These studies show that initiating treatment with a dopamine agonist results in less dopaminergic
A Finite Mixture Analysis of BeautyContest Data Using Generalized Beta Distributions ∗
, 2010
"... We thank the editor and two referees for insightful comments that helped improve the manuscript. Thanks are also due to the Spanish Ministerio de Educación y Ciencia for financial help under research projects SEJ200503891/ECON (ABD), SEJ2006135 and SEJ200764340, and by the Barcelona GSE research ..."
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We thank the editor and two referees for insightful comments that helped improve the manuscript. Thanks are also due to the Spanish Ministerio de Educación y Ciencia for financial help under research projects SEJ200503891/ECON (ABD), SEJ2006135 and SEJ200764340, and by the Barcelona GSE research network, Generalitat de Catalunya. This paper introduces a mixture model based on the beta distribution, without preestablished means and variances, to analyze a large set of BeautyContest data obtained from diverse groups of experiments (BoschDomènech et al. 2002). This model gives a better fit of the experimental data, and more precision to the hypothesis that a large proportion of individuals follow a common pattern of reasoning, described as iterated best reply (degenerate), than mixture models based on the normal distribution. The analysis shows that the means of the distributions across the groups of experiments are pretty stable, while the proportions of choices at different levels of reasoning vary across groups.
Barcelona Economics Working Paper Series Working Paper nº 455A Finite Mixture Analysis of BeautyContest Data Using Generalized Beta Distributions ∗
, 2010
"... We thank the editor and two referees for insightful comments that helped improve the manuscript. Thanks are also due to the Spanish Ministerio de Educación y Ciencia for financial help under research projects SEJ200503891/ECON (ABD), SEJ2006135 and SEJ200764340, and by the Barcelona GSE research ..."
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We thank the editor and two referees for insightful comments that helped improve the manuscript. Thanks are also due to the Spanish Ministerio de Educación y Ciencia for financial help under research projects SEJ200503891/ECON (ABD), SEJ2006135 and SEJ200764340, and by the Barcelona GSE research network, Generalitat de Catalunya. This paper introduces a mixture model based on the beta distribution, without preestablished means and variances, to analyze a large set of BeautyContest data obtained from diverse groups of experiments (BoschDomènech et al. 2002). This model gives a better fit of the experimental data, and more precision to the hypothesis that a large proportion of individuals follow a common pattern of reasoning, described as iterated best reply (degenerate), than mixture models based on the normal distribution. The analysis shows that the means of the distributions across the groups of experiments are pretty stable, while the proportions of choices at different levels of reasoning vary across groups.
The anticipated effects of EU enlargement: exchange rate volatility, institutions and conditional convergence 1
"... Improvement (and reduced heterogeneity) of economic policies and institutions and reduced exchange rate volatility are two expected effects arising when candidates develop prerequisites needed to qualify for EU membership. In this paper we evaluate whether these two effects apply to Eastern European ..."
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Improvement (and reduced heterogeneity) of economic policies and institutions and reduced exchange rate volatility are two expected effects arising when candidates develop prerequisites needed to qualify for EU membership. In this paper we evaluate whether these two effects apply to Eastern European countries by inspecting the volatility of real effective exchange rates (REER) and of different indicators of quality of institutional rules and macroeconomic policies before and after the negotiation period. We finally evaluate the impact of both effects on levels and growth of real per capita GDP. By comparing dynamics of the above mentioned variables for transition candidates and a group of control countries, including transition non candidates, we find that the positive effects of accession to the EU materialise much before accession and even before the beginning of the negotiating process with significant effects on levels and growth.