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Social and Behavioral Sciences Commons™
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- Fixed Effects (2)
- Panel Data (2)
- Random Effects (2)
- AR(p) (1)
- Bad leverage points (1)
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- Bootstrap; Distributional misspecification; Group interaction; LM test; Moran’s I (1)
- CUSUM statistic (1)
- Changepoint (1)
- Common trends (1)
- Covariance Matrix (1)
- Cross-sectional Dependence (1)
- Eigensystem (1)
- Hausman-Taylor (1)
- Hausman-Taylor estimator; Spatial random effects; Small sample properties (1)
- High Dimensional Inference (1)
- Instrumental Variables (1)
- LM Test (1)
- Panel cointegration (1)
- Panel data (1)
- Prediction (1)
- Serial (1)
- Serial Correlation (1)
- Structural change (1)
- Term Structure of Interest Rates (1)
- Two stage generalized MS (1)
- Weak Instrument; Panel Data; fixed effects; Pitman drift local-to-zero (1)
Articles 1 - 19 of 19
Full-Text Articles in Social and Behavioral Sciences
Still Unknown: The Impact Of School Capital On Student Performance, John Yinger
Still Unknown: The Impact Of School Capital On Student Performance, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
A Missed Opportunity In California, John Yinger
A Missed Opportunity In California, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
Holding Tax Shares Constant Is A Bad Idea: What The Homestead Tax Option In New York Can Teach Us About Romney’S Income Tax Proposal, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
Reforming State Education Aid In New York State, John Yinger
Reforming State Education Aid In New York State, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
On The Estimation And Testing Of Fixed Effects Panel Data Models With Weak Instruments, Badi Baltagi, Chihwa Kao, Long Liu
On The Estimation And Testing Of Fixed Effects Panel Data Models With Weak Instruments, Badi Baltagi, Chihwa Kao, Long Liu
Center for Policy Research
This paper studies the asymptotic properties of within groups k-class estimators in a panel data model with weak instruments. Weak instruments are characterized by the coefficients of the instruments in the reduced form equation shrinking to zero at a rate proportional to nTδ ; where n is the dimension of the cross-section and T is the dimension of the time series. Joint limits as (n,T )→∞show that this within group k-class estimator is consistent if 0 ≤δ ≤ ½ and inconsistent if ½ ≤δ ≤ ∞.
A Robust Hausman-Taylor Estimator, Badi Baltagi, Georges Bresson
A Robust Hausman-Taylor Estimator, Badi Baltagi, Georges Bresson
Center for Policy Research
This paper suggests a robust Hausman and Taylor (1981) estimator, here-after HT that deals with the possible presence of outliers. This entails two modifications of the classical HT estimator. The first modification uses the Bramati and Croux (2007) robust Within MS estimator instead of the Within estimator in the first stage of the HT estimator. The second modification uses the robust Wagenvoort and Waldmann (2002) two stage generalized MS estimator instead of the 2SLS estimator in the second step of the HT estimator. Monte Carlo simulations show that, in the presence of vertical outliers or bad leverage points, the robust …
Small Sample Properties And Pretest Estimation Of A Spatial Hausman-Taylor Model, Badi Baltagi, Peter H. Egger, Michaela Kesina
Small Sample Properties And Pretest Estimation Of A Spatial Hausman-Taylor Model, Badi Baltagi, Peter H. Egger, Michaela Kesina
Center for Policy Research
This paper considers a Hausman and Taylor (1981) panel data model that exhibits a Cliff and Ord (1973) spatial error structure. We analyze the small sample properties of a generalized moments estimation approach for that model. This spatial Hausman-Taylor estimator allows for endogeneity of the time-varying and time-invariant variables with the individual effects. For this model, the spatial effects estimator is known to be consistent, but its disadvantage is that it wipes out the effects of time-invariant variables, which are important for most empirical studies. Monte Carlo results show that the spatial Hausman-Taylor estimator performs well in small samples.
Standardized Lm Test For Spatial Error Dependence In Linear Or Panel Regressions, Badi Baltagi, Zhenlin Yankg
Standardized Lm Test For Spatial Error Dependence In Linear Or Panel Regressions, Badi Baltagi, Zhenlin Yankg
Center for Policy Research
The robustness of the LM tests for spatial error dependence of Burridge (1980) and Born and Breitung (2011) for the linear regression model, and Anselin (1988) and Debarsy and Ertur (2010) for the panel regression model with random or fixed effects are examined. While all tests are asymptotically robust against distributional misspecification, their finite sample behavior may 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 …
Quality Of Life For All Ages, By Design. A Conversation With Patricia Moore, Patricia Moore
Quality Of Life For All Ages, By Design. A Conversation With Patricia Moore, Patricia Moore
Center for Policy Research
On November 3, 2011, Patricia Moore presented the Syracuse Seminar on Aging to a packed audience of over 250 faculty, students, and community members. She delivered an engaging lecture on “Quality of life for all ages, by design”. Afterwards Janet Wilmoth, Director of the Syracuse University Aging Studies Institute, and Patricia Moore had a chance to sit down and talk about her path-breaking career, ability-based design, and aging in America.
Four Flaws In New York State’S Property Taxes And How To Fix Them: Small Assessment Units, John Yinger
Four Flaws In New York State’S Property Taxes And How To Fix Them: Small Assessment Units, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
Integrating Care: Improving Overall Health By Integrating Behavioral/Mental Health Care Into Primary Care, Macaran A. Baird
Integrating Care: Improving Overall Health By Integrating Behavioral/Mental Health Care Into Primary Care, Macaran A. Baird
Center for Policy Research
Hippocrates noted that the patient must be attended in light of “his” diet, work, home, and community setting. Since that time, we have struggled with the dilemma of how to put the patient’s presenting problems in the context of the patient’s life circumstances. That goal has proven elusive. So how do we sort out where to put the emphasis with our healing arts?
Four Flaws In New York State’S Property Taxes And How To Fix Them: The Homestead Option, John Yinger
Four Flaws In New York State’S Property Taxes And How To Fix Them: The Homestead Option, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
Estimation And Prediction In The Random Effects Model With Ar(P) Remainder Disturbances, Badi Baltagi, Long Liu
Estimation And Prediction In The Random Effects Model With Ar(P) Remainder Disturbances, Badi Baltagi, Long Liu
Center for Policy Research
This paper considers the problem of estimation and forecasting in a panel data model with random individual effects and AR(p) remainder disturbances. It utilizes a simple exact transformation for the AR(p) time series process derived by Baltagi and Li (1994) and obtains the generalized least squares estimator for this panel model as a least squares regression. This exact transformation is also used in conjunction with Goldberger’s (1962) result to derive an analytic expression for the best linear unbiased predictor. The performance of this predictor is investigated using Monte Carlo experiments and illustrated using an empirical example.
Four Flaws In New York State’S Property Taxes And How To Fix Them: Levy Limits, John Yinger
Four Flaws In New York State’S Property Taxes And How To Fix Them: Levy Limits, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
Four Flaws In New York State’S Property Taxes And How To Fix Them: Star, John Yinger
Four Flaws In New York State’S Property Taxes And How To Fix Them: Star, John Yinger
Center for Policy Research
It’s Elementary is a series of essays on topics in education and education policy. The main focus is on education finance in New York State, but general research findings in education and education policy issues in several other states are also discussed. John Yinger, Professor of Economics and Public Administration at the Maxwell School, Syracuse University is the author of most of these essays, although a few are written by or co-authored with other scholars.
A Lagrange Multiplier Test For Cross-Sectional Dependence In A Fixed Effects Panel Data Model, Badi Baltagi, Qu Feng, Chihwa Kao
A Lagrange Multiplier Test For Cross-Sectional Dependence In A Fixed Effects Panel Data Model, Badi Baltagi, Qu Feng, Chihwa Kao
Center for Policy Research
It is well known that the standard Breusch and Pagan (1980) LM test for cross-equation correlation in a SUR model is not appropriate for testing cross-sectional dependence in panel data models when the number of cross-sectional units (n) is large and the number of time periods (T) is small. In fact, a scaled version of this LM test was proposed by Pesaran (2004) and its finite sample bias was corrected by Pesaran, Ullah and Yamagata (2008). This was done in the context of a heterogeneous panel data model. This paper derives the asymptotic bias of this scaled version of the …
Testing For Instability In Covariance Sturctures, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
Testing For Instability In Covariance Sturctures, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
Center for Policy Research
We propose a test for the stability over time of the covariance matrix of multivariate time series. The analysis is extended to the eigensystem to ascertain changes due to instability in the eigenvalues and/or eigenvectors. Using strong Invariance Principle and Law of Large Numbers, we normalize the CUSUM-type statistics to calculate their supremum over the whole sample. The power properties of the test versus local alternatives and alternatives close to the beginning/end of sample are investigated theoretically and via simulation. The testing procedure is validated through an application to 18 US interest rates over 1997-2011, finding instability at the end-2007/beginning-2008.
The Hausman-Taylor Panel Data Model With Serial Correlation, Badi Baltagi, Long Liu
The Hausman-Taylor Panel Data Model With Serial Correlation, Badi Baltagi, Long Liu
Center for Policy Research
This paper modifies the Hausman and Taylor (1981) panel data estimator to allow for serial correlation in the remainder disturbances. It demonstrates the gains in efficiency of this estimator versus the standard panel data estimators that ignore serial correlation using Monte Carlo experiments.
Testing For Breaks In Cointegrated Panels, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
Testing For Breaks In Cointegrated Panels, Chihwa Kao, Lorenzo Trapani, Giovanni Urga
Center for Policy Research
We investigate the issue of testing for structural breaks in large cointegrated panels with common and idiosyncratic regressors. We prove a panel Functional Central Limit Theorem. We show that the estimated coefficients of the common regressors have a mixed normal distribution, whilst the estimated coefficients of the idiosyncratic regressors have a normal distribution. We consider strong dependence across the idiosyncratic regressors by allowing for the presence of (stationary and nonstationary) common factors. We show that tests based on transformations of Wald-type statistics have power versus alternatives of order