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Articles 31 - 54 of 54
Full-Text Articles in Econometrics
New York Camp Econometrics Vii Program, Center For Policy Research
New York Camp Econometrics Vii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
New York Camp Econometrics Vi Program, Center For Policy Research
New York Camp Econometrics Vi Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
New York Camp Econometrics V Program, Center For Policy Research
New York Camp Econometrics V Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Trusts Versus Corporations: An Empirical Analysis Of Competing Organizational Forms, A. Joseph Warburton
Trusts Versus Corporations: An Empirical Analysis Of Competing Organizational Forms, A. Joseph Warburton
College of Law - Faculty Scholarship
This paper studies the effects of organizational form on managerial behavior and firm performance, from an empirical perspective. Managers of trusts are subject to stricter fiduciary responsibilities than managers of corporations. This paper examines the ramifications empirically, by exploiting data generated by a change in British regulations in the 1990s that allowed mutual funds to organize as either a trust or a corporation. I find evidence that trust law is effective in curtailing opportunistic behavior, as trust managers charge significantly lower fees than their observationally equivalent corporate counterparts. Trust managers also incur lower risk. However, evidence suggests that trust managers …
New York Camp Econometrics Iv Program, Center For Policy Research
New York Camp Econometrics Iv Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
New York Camp Econometrics Iii Program, Center For Policy Research
New York Camp Econometrics Iii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Testing For Heteroskedasticity And Spatial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Seuck Heun Song, Jae Hyeok Kwon
Testing For Heteroskedasticity And Spatial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Seuck Heun Song, Jae Hyeok Kwon
Center for Policy Research
A panel data regression model with heteroskedastic as well as spatially correlated disturbance is considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also derived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation, or spatial correlation in testing for homoskedasticity. Monte Carlo results show that these LM tests as well as their LR counterparts perform well even for small N and …
Testing For Random Effects And Spatial Lag Dependence In Panel Data Models, Badi H. Baltagi, Long Liu
Testing For Random Effects And Spatial Lag Dependence In Panel Data Models, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper derives a joint Lagrande Multiplier (LM) test which simultaneously tests for the absence of spatial lag dependence and random individual effects in a panel data regression model. It turns out that this LM statistic is the sum of two standard LM statistics. The first one tests for the absence of spatial lag dependence ignoring the random individual effects, and the second one tests for the absence of random individual effects ignoring the spatial lag dependence. This paper also derives two conditional LM tests. The first one tests for the absence of random individual effects without ignoring the possible …
Testing For Heteroskedasticity And Serial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Byoung Cheol Jung, Seuck Heun Song
Testing For Heteroskedasticity And Serial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Byoung Cheol Jung, Seuck Heun Song
Center for Policy Research
This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LM test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. It also derives a conditional LM test for homoskedasticity given serial correlation, as well as a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context of a random effects panel data model. Monte Carlo results show that these tests, along with their likelihood ratio alternatives, have good size and power under various forms …
Fitting Event-History Models To Uneventful Data, Douglas A. Wolf, Thomas M. Gill
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. …
New York Camp Econometrics Ii Program, Center For Policy Research
New York Camp Econometrics Ii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
A Monte Carlo Study Of Efficiency Estimates From Frontier Models, William Clinton Horrace, Seth O. Richards
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.
Panel Cointegration With Global Stochastic Trends, Jushan Bai, Chihwa Kao, Serena Ng
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 …
Testing For Instability In Factor Structure Of Yield Curves, Dennis Philip, Chihwa Kao, Giovanni Urga
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 …
Worldwide Econometrics Rankings: 1989-2005, Badi H. Baltagi
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 …
Copula-Based Tests For Cross-Sectional Independence In Panel Models, Chihwa Kao, Giovanni Urga
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.
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
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 …
New York Camp Econometrics I Program, Center For Policy Research
New York Camp Econometrics I Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
The Asymptotics For Panel Models With Common Shocks, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
The Asymptotics For Panel Models With Common Shocks, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
Center for Policy Research
This paper develops a novel asymptotic theory for panel models with common shocks. We assume that contemporaneous correlation can be generated by both the presence of common regressors among units and weak spatial dependence among the error terms. Several characteristics of the panel are considered: cross sectional and time series dimensions can either be fixed or large; factors can either be observable or unobservable; the factor model can describe either cointegration relationship or a spurious regression, and we also consider the stationary case. We derive the rate of convergence and the distribution limits for the ordinary least squares (OLS) estimates …
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach, Alfonso Flores-Lagunes, William Clinton Horrace, Kurt E. Schnier
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach, Alfonso Flores-Lagunes, William Clinton Horrace, Kurt E. Schnier
Center for Policy Research
There is a growing resource economics literature, concerning the estimation of the technical efficiency of fishing vessels utilizing the stochastic frontier model. In these models, vessel output is regressed on a linear function of vessel inputs and a random composed error. Using parametric assumptions on the regression residual, estimates of vessel technical efficiency are calculated as the mean of a truncated normal distribution and are often reported in a rank statistic as a measure of a captain's skill and used to estimate excess capacity within fisheries. We demonstrate analytically that these measures are potentially flawed, and extend the results of …
Panel Unit Root Tests And Spatial Dependence, Badi H. Baltagi, Georges Bresson, Alain Pirotte
Panel Unit Root Tests And Spatial Dependence, Badi H. Baltagi, Georges Bresson, Alain Pirotte
Center for Policy Research
This paper studies the performance of panel unit root tests when spatial effects are present that account for cross-section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error correlation. These tests are applied to a panel data set on net real income from the 1000 largest French communes observed over the period 1985-1998.
Simulation-Based Two-Step Estimation With Endogenous Regressors, Kamhon Kan, Chihwa Kao
Simulation-Based Two-Step Estimation With Endogenous Regressors, Kamhon Kan, Chihwa Kao
Center for Policy Research
This paper considers models with latent/discrete endogenous regressors and presents a simulation-based two-step (STS) estimator. The endogeneity is corrected by adopting a simulation-based control function approach. The first step consists of simulating the residuals of the reduced-form equation for endogenous regressors. The second step is a regression model (linear, latent or discrete) with the simulated residual as an additional regressor. In this paper we develop the asymptotic theory for the STS estimator and its rate of convergence.
On The Estimation And Inference Of A Panel Cointegration Model With Cross-Sectional Dependence, Jushan Bai, Chihwa Kao
On The Estimation And Inference Of A Panel Cointegration Model With Cross-Sectional Dependence, Jushan Bai, Chihwa Kao
Center for Policy Research
Most of the existing literature on panel data cointegration assumes cross-sectional independence, an assumption that is difficult to satisfy. This paper studies panel cointegration under cross-sectional dependence, which is characterized by a factor structure. We derive the limiting distribution of a fully modified estimator for the panel cointegrating coefficients. We also propose a continuous-updated fully modified (CUP-FM) estimator). Monte Carlo results show that the CUP-FM estimator has better small sample properties than the two-step FM (2S-FM) and OLS estimators.
Cox-Mcfadden Partial And Marginal Likelihoods For The Proportional Hazard Model With Random Effects, Jan Ondrich
Cox-Mcfadden Partial And Marginal Likelihoods For The Proportional Hazard Model With Random Effects, Jan Ondrich
Center for Policy Research
In survival analysis, Cox's name is associated with the partial likelihood technique that allows consistent estimation of proportional hazard scale parameters without specifying a duration dependence baseline. In discrete choice analysis, McFadden's name is associated with the generalized extreme-value (GEV) class of logistic choice models that relax the independence of irrelevant alternatives assumption. This paper shows that the mixed class of proportional hazard specifications allowing consistent estimation of scale and mixing parameters using partial likelihood is isomorphic to the GEV class. Independent censoring is allowed and I discuss approximations to the partial likelihood in the presence of ties. Finally, the …