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Social and Behavioral Sciences Commons™

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Econometrics

Syracuse University

2007

Articles 1 - 8 of 8

Full-Text Articles in Social and Behavioral Sciences

Fitting Event-History Models To Uneventful Data, Douglas A. Wolf, Thomas M. Gill Dec 2007

Fitting Event-History Models To Uneventful Data, Douglas A. Wolf, Thomas M. Gill

Center for Policy Research

Data with which to study disability dynamics usually take the form of successive current-status measures of disability rather than a record of events or spell durations. One recent paper presented a semi-Markov model of disability dynamics in which spell durations were inferred from sequences of current-status measures taken at 12-month intervals. In that analysis, it was assumed that no unobserved disablement transitions occurred between annual interviews. We use data from a longitudinal survey in which participants' disability was measured at monthly intervals, and simulate the survival curves for remaining disabled that would be obtained with 1- and 12-month follow-up intervals. …

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New York Camp Econometrics Ii Program, Center For Policy Research Mar 2007

New York Camp Econometrics Ii Program, Center For Policy Research

Camp Econometrics-Programs

No abstract provided.

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Testing For Instability In Factor Structure Of Yield Curves, Dennis Philip, Chihwa Kao, Giovanni Urga Jan 2007

Testing For Instability In Factor Structure Of Yield Curves, Dennis Philip, Chihwa Kao, Giovanni Urga

Center for Policy Research

A widely relied upon but a formally untested consideration is the issue of stability in actors underlying the term structure of interest rates. In testing for stability, practitioners as well as academics have employed ad hoc techniques such as splitting the sample into a few sub-periods and determining whether the factor loadings have appeared to be similar over all sub-periods. Various authors have found mixed evidence on stability in the actors. In this paper we develop a formal testing procedure to evaluate the factor structure stability of the US zero coupon yield term structure. We find the factor structure of …

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Copula-Based Tests For Cross-Sectional Independence In Panel Models, Chihwa Kao, Giovanni Urga Jan 2007

Copula-Based Tests For Cross-Sectional Independence In Panel Models, Chihwa Kao, Giovanni Urga

Center for Policy Research

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

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Worldwide Econometrics Rankings: 1989-2005, Badi H. Baltagi Jan 2007

Worldwide Econometrics Rankings: 1989-2005, Badi H. Baltagi

Center for Policy Research

This paper updates Baltagi's (2003, Econometric Theory 19, 165-224) rankings of academic institutions by publication activity in econometrics from 1989-1999 to 1989-2005. This ranking is based on 16 leading international journals that publish econometrics articles. It is compared with the prior rankings by Hall (1980, 1987) for the period 1980-1988. In addition, a list of the top 150 individual producers of econometrics in these 16 journals over this 17-year period is provided. This is done for theoretical econometrics as well as all contributions in econometrics. Sensitivity analysis is provided using (i) alternative weighting factors given to the 16 journals taking …

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Panel Cointegration With Global Stochastic Trends, Jushan Bai, Chihwa Kao, Serena Ng Jan 2007

Panel Cointegration With Global Stochastic Trends, Jushan Bai, Chihwa Kao, Serena Ng

Center for Policy Research

This paper studies estimation of panel cointegration models with cross-sectional dependence generated by unobserved global stochastic trends. The standard least squares estimator is, in general, inconsistent owing to the spuriousness induced by the unobservable I(1) trends. We propose two iterative procedures that jointly estimate the slope parameters and the stochastic trends. The resulting estimators are referred to respectively as CupBC (continuously updated and bias-corrected) and the CupFM (continuously updated and fully modified) estimators. We establish their consistency and derive their limiting distributions. Both are asymptotically unbiased and asymptotically normal and permit inference to be conducted using standard test statistics. The …

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A Monte Carlo Study Of Efficiency Estimates From Frontier Models, William Clinton Horrace, Seth O. Richards Jan 2007

A Monte Carlo Study Of Efficiency Estimates From Frontier Models, William Clinton Horrace, Seth O. Richards

Center for Policy Research

Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimated (a) the conditional means of inefficiency and (b) probabilities that firms are most or least efficient. Monte Carlo experiments suggest that the efficiency probabilities are more reliable in terms of mean absolute percent error when inefficiency has large variation across firms. Along the way we tackle some interesting problems associated with simulating and assessing estimator performance in the stochastic frontier environment.

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A Monte Carlo Study For Pure And Pretest Estimators Of A Panel Data Model With Spatially Auto Correlated Disturbances, Badi H. Baltagi, Peter Egger, Michael Pfaffermayr Jan 2007

A Monte Carlo Study For Pure And Pretest Estimators Of A Panel Data Model With Spatially Auto Correlated Disturbances, Badi H. Baltagi, Peter Egger, Michael Pfaffermayr

Center for Policy Research

This paper examines the consequences of model misspecification using a panel data model with spatially auto correlated disturbances. The performance of several maximum likelihood estimators assuming different specifications for this model are compared using Monte Carlo experiments. These include (i) MLE of a random effects model that ignore the spatial correlation; (ii) MLE described in Anselin (1988) which assumes that the individual effects are not spatially auto correlated; (iii) MLE described in Kapoor et al. (2006) which assumes that both the individual effects and the remainder error are governed by the same spatial autocorrelation; (iv) MLE described in Baltagi et …

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