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312
The local power of some unit root tests for panel data
 Advances in Econometrics, Vol. 15: Nonstationary Panels, Panel Cointegration, and Dynamic Panels, JAI
, 2000
"... To test the hypothesis of a di erence stationary time series against a trend stationary alternative, Levin and Lin (1993) and Im, Pesaran and Shin (1997) suggest bias adjusted tstatistics. Such corrections are necessary to account for the nonzero mean of the tstatistic in the case of an OLS detren ..."
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Cited by 250 (2 self)
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To test the hypothesis of a di erence stationary time series against a trend stationary alternative, Levin and Lin (1993) and Im, Pesaran and Shin (1997) suggest bias adjusted tstatistics. Such corrections are necessary to account for the nonzero mean of the tstatistic in the case of an OLS detrending method. In this paper the local power of panel unit root statistics against a sequence of local alternatives is studied. It is shown that the local power of the test statistics is a ected by two di erent terms. The rst term represents the asymptotic e ect on the bias due the detrending method and the second term is the usual location parameter of the limiting distribution under the sequence of local alternatives. It is argued that both terms can o set each other so that the test has no power against the sequence of local alternatives. This results suggest to construct test statistics based on alternative detrending methods. We consider a class of tstatistics that do not require a bias correction. The results of a Monte Carlo experiment suggest that avoiding the bias can improve the power of the test substantially. 1 1
Fully Modified OLS for Heterogeneous Cointegrated Panels and the Case of Purchasing Power Parity. Working paper No
, 1996
"... This chapter uses fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointeg ..."
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Cited by 202 (4 self)
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This chapter uses fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointegration studies. The asymptotic properties of various estimators are compared based on pooling along the ‘within ’ and ‘between ’ dimensions of the panel. By using Monte Carlo simulations to study the small sample properties, the group mean estimator is shown to behave well even in relatively small samples under a variety of scenarios. I.
Testing for a Unit Root in Panels with Dynamic Factors
 Journal of Econometrics
, 2002
"... This paper studies testing for a unit root for large n and T panels in which the crosssectional units are correlated. To model this crosssectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this environment a ..."
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Cited by 181 (6 self)
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This paper studies testing for a unit root for large n and T panels in which the crosssectional units are correlated. To model this crosssectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We show that these tests have significant asympotitic power when the model has no incidental trends. However, when there are incidental trends in the model and it is necessary to remove heterogeneous deterministic components, we show that these tests have no power against the same local alternatives. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests. 1
Dynamic panel estimation and homogeneity testing under cross section dependence. Cowles Foundation Discussion Paper #1362,
, 2002
"... Summary This paper deals with cross section dependence, homogeneity restrictions and small sample bias issues in dynamic panel regressions. To address the bias problem we develop a panel approach to median unbiased estimation that takes account of cross section dependence. The estimators given here ..."
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Cited by 166 (8 self)
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Summary This paper deals with cross section dependence, homogeneity restrictions and small sample bias issues in dynamic panel regressions. To address the bias problem we develop a panel approach to median unbiased estimation that takes account of cross section dependence. The estimators given here considerably reduce the effects of bias and gain precision from estimating cross section error correlation. This paper also develops an asymptotic theory for tests of coefficient homogeneity under cross section dependence, and proposes a modified Hausman test to test for the presence of homogeneous unit roots. An orthogonalization procedure, based on iterated method of moments estimation, is developed to remove cross section dependence and permit the use of conventional and meta unit root tests with panel data. Some simulations investigating the finite sample performance of the estimation and test procedures are reported.
Purchasing power parity tests in cointegrated panels
 The Review of Economics and Statistics
, 2001
"... Abstract—This paper employs recently developed techniques for testing hypotheses in cointegrated panels to test the strong version of purchasing power parity for a panel of post Bretton Woods data. We compare results using fully modi � ed and dynamic OLS approaches, and strongly reject the hypothesi ..."
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Cited by 155 (4 self)
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Abstract—This paper employs recently developed techniques for testing hypotheses in cointegrated panels to test the strong version of purchasing power parity for a panel of post Bretton Woods data. We compare results using fully modi � ed and dynamic OLS approaches, and strongly reject the hypothesis. We also introduce a new betweendimensio n dynamic OLS estimator and � nd that the betweendimensio n FMOLS and DOLS estimates of the longrun deviation from purchasing power parity are larger than the correspondin g withindimension estimates. Finally, we attempt to reconcile these rejections with the mixed � ndings that have been reported in panel unit root studies. I.
A PANIC Attack on Unit Roots and Cointegration
, 2003
"... This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of nonstationarity in the data. We refer to it as PANIC – a ‘Panel Analysis of Nonstationarity in Idiosyncratic and Common components’. PANIC consists of univariate and ..."
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Cited by 142 (3 self)
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This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of nonstationarity in the data. We refer to it as PANIC – a ‘Panel Analysis of Nonstationarity in Idiosyncratic and Common components’. PANIC consists of univariate and panel tests with a number of novel features. It can detect whether the nonstationarity is pervasive, or variablespecific, or both. It tests the components of the data instead of the observed series. Inference is therefore more accurate when the components have different orders of integration. PANIC also permits the construction of valid panel tests even when crosssection correlation invalidates pooling of statistics constructed using the observed data. The key to PANIC is consistent estimation of the components even when the regressions are individually spurious. We provide a rigorous theory for estimation and inference. In Monte Carlo simulations, the tests have very good size and power. PANIC is applied to a panel of inflation series.
On the Estimation and Inference of a Cointegrated Regression in Panel Data
 CENTRE FOR POLICY RESEARCH, SYRACUSE UNIVERSITY
, 1999
"... In this paper, we study the asymptotic distributions for leastsquares (OLS), fully modi ed (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic dist ..."
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Cited by 141 (5 self)
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In this paper, we study the asymptotic distributions for leastsquares (OLS), fully modi ed (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic distribution of the OLS estimator is shown to have a nonzero mean. Monte Carlo results examine the sampling behavior of the proposed estimators and show that (1) the OLS estimator has a nonnegligible bias in nite samples, (2) the FM estimator does not improve over the OLS estimator in general, and (3) the DOLS outperforms both the OLS and FM estimators.
Trade and the transmission of technology
, 1995
"... Marie Thursby, and an anonymous referee. Thanks also to Christian Langer for providing the data on trade flows, to Michael Craw for the US import inputoutput data, and to Jonathan Putnam for his help in obtaining the technology flow matrix used in the paper. ..."
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Cited by 94 (2 self)
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Marie Thursby, and an anonymous referee. Thanks also to Christian Langer for providing the data on trade flows, to Michael Craw for the US import inputoutput data, and to Jonathan Putnam for his help in obtaining the technology flow matrix used in the paper.
Cointegration Vector Estimation by Panel DOLS and LongRun Money Demand
 Oxford Bulletin of Economics and Statistics
, 2003
"... We study the panel dynamic ordinary least square (DOLS) estimator of a homogeneous cointegration vector for a balanced panel of N individuals observed over T time periods. Allowable heterogeneity across individuals include individualspecific time trends, individualspecific fixed effects and times ..."
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Cited by 92 (0 self)
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We study the panel dynamic ordinary least square (DOLS) estimator of a homogeneous cointegration vector for a balanced panel of N individuals observed over T time periods. Allowable heterogeneity across individuals include individualspecific time trends, individualspecific fixed effects and timespecific effects. The estimator is fully parametric, computationally convenient, and more precise than the single equation estimator. For fixed N as T fi 1, the estimator converges to a function of Brownian motions and the Wald statistic for testing a set of s linear constraints has a limiting v2(s) distribution. The estimator also has a Gaussian sequential limit distribution that is obtained first by letting T fi 1 and then letting N fi 1. In a series of MonteCarlo experiments, we find that the asymptotic distribution theory provides a reasonably close approximation to the exact finite sample distribution. We use panel DOLS to estimate coefficients of the longrun money demand function from a panel of 19 countries with annual observations that span from 1957 to 1996. The estimated income elasticity is 1.08 (asymptotic s.e. 0.26) and the estimated interest rate semielasticity is)0.02 (asymptotic s.e. 0.01). *This paper was previously circulated under the title ‘A Computationally Simple Cointegration
Testing for error correction in panel data
 Oxford Bulletin of Economics and Statistics
, 2007
"... This paper proposes new error correction based cointegration tests for panel data. The limiting distributions of the tests are derived and critical values are provided. Our simulation results suggest that the tests have good smallsample properties with small size distortions and high power relative ..."
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Cited by 90 (2 self)
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This paper proposes new error correction based cointegration tests for panel data. The limiting distributions of the tests are derived and critical values are provided. Our simulation results suggest that the tests have good smallsample properties with small size distortions and high power relative to other popular residualbased panel cointegration tests. In our empirical application, we present evidence suggesting that international health care expenditures and GDP are cointegrated once the possibility of an invalid common factor restriction has been accounted for.