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210
Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests, With an Application to the PPP Hypothesis; New Results. Working paper
, 1997
"... We examine properties of residualbased tests for the null of no cointegration for dynamic panels in which both the shortrun dynamics and the longrun slope coefficients are permitted to be heterogeneous across individual members of the panel+ The tests also allow for individual heterogeneous fixed ..."
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Cited by 529 (13 self)
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We examine properties of residualbased tests for the null of no cointegration for dynamic panels in which both the shortrun dynamics and the longrun slope coefficients are permitted to be heterogeneous across individual members of the panel+ The tests also allow for individual heterogeneous fixed effects and trend terms, and we consider both pooled within dimension tests and group mean between dimension tests+ We derive limiting distributions for these and show that they are normal and free of nuisance parameters+ We also provide Monte Carlo evidence to demonstrate their small sample size and power performance, and we illustrate their use in testing purchasing power parity for the post–Bretton Woods period+ 1.
A Simple Panel Unit Root Test in the Presence of Cross Section Dependence
 JOURNAL OF APPLIED ECONOMETRICS
, 2006
"... A number of panel unit root tests that allow for cross section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross dependence of the series before standard panel unit root tests are applied to the transformed series. In thi ..."
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Cited by 372 (16 self)
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A number of panel unit root tests that allow for cross section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross dependence of the series before standard panel unit root tests are applied to the transformed series. In this paper we propose a simple alternative where the standard ADF regressions are augmented with the cross section averages of lagged levels and firstdifferences of the individual series. New asymptotic results are obtained both for the individual cross sectionally augmented ADF (CADF) statistics, and their simple averages. It is shown that the individual CADF statistics are asymptotically similar and do not depend on the factor loadings. The limit distribution of the average CADF statistic is shown to exist and its critical values are tabulated. Small sample properties of the proposed test are investigated by Monte Carlo experiments. The proposed test is applied to a panel of 17 OECD real exchange rate series as well as to log real earnings of households in the PSID data.
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
Implications of dynamic factor models for VAR analysis
 NBER, WORKING PAPER
, 2005
"... This paper considers VAR models incorporating many time series that interact through a few dynamic factors. Several econometric issues are addressed including estimation of the number of dynamic factors and tests for the factor restrictions imposed on the VAR. Structural VAR identification based on ..."
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Cited by 162 (5 self)
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This paper considers VAR models incorporating many time series that interact through a few dynamic factors. Several econometric issues are addressed including estimation of the number of dynamic factors and tests for the factor restrictions imposed on the VAR. Structural VAR identification based on timing restrictions, long run restrictions, and restrictions on factor loadings are discussed and practical computational methods suggested. Empirical analysis using U.S. data suggest several (7) dynamic factors, rejection of the exact dynamic factor model but support for an approximate factor model, and sensible results for a SVAR that identifies money policy shocks using timing restrictions.
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.
Nowcasting: the realtime informational content of macroeconomic data
 Journal of Monetary Economics
, 2008
"... A formal method is developed for evaluating the marginal impact that intramonthly data releases have on currentquarter forecasts (nowcasts) of real GDP growth. The method can track the realtime flow of the type of information monitored by central banks because it can handle large data sets with s ..."
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Cited by 128 (12 self)
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A formal method is developed for evaluating the marginal impact that intramonthly data releases have on currentquarter forecasts (nowcasts) of real GDP growth. The method can track the realtime flow of the type of information monitored by central banks because it can handle large data sets with staggered datarelease dates. Each time new data are released, the nowcasts are updated on the basis of progressively larger data sets that, reflecting the unsynchronized datarelease dates, have a “jagged edge” across the most recent months.
Panel Data Models with Interactive Fixed Effects
, 2005
"... This paper considers large N and large T panel data models with unobservable multiple interactive effects. These models are useful for both micro and macro econometric modelings. In earnings studies, for example, workers ’ motivation, persistence, and diligence combined to influence the earnings in ..."
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Cited by 125 (6 self)
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This paper considers large N and large T panel data models with unobservable multiple interactive effects. These models are useful for both micro and macro econometric modelings. In earnings studies, for example, workers ’ motivation, persistence, and diligence combined to influence the earnings in addition to the usual argument of innate ability. In macroeconomics, the interactive effects represent unobservable common shocks and their heterogeneous responses over cross sections. Since the interactive effects are allowed to be correlated with the regressors, they are treated as fixed effects parameters to be estimated along with the common slope coefficients. The model is estimated by the least squares method, which provides the interactiveeffects counterpart of the within estimator. We first consider model identification, and then derive the rate of convergence and the limiting distribution of the interactiveeffects estimator of the common slope coefficients. The estimator is shown to be √ NT consistent. This rate is valid even in the presence of correlations and heteroskedasticities in both dimensions, a striking contrast with fixed T framework in which serial correlation and heteroskedasticity imply unidentification. The asymptotic distribution is not necessarily centered at zero. Biased corrected estimators are derived. We also derive the constrained estimator and its limiting distribution, imposing additivity coupled with interactive effects. The problem of testing additive versus interactive effects is also studied. We also derive identification conditions for models with grand mean, timeinvariant regressors, and common regressors. It is shown that there exists a set of necessary and sufficient identification conditions for those models. Given identification, the rate of convergence and limiting results continue to hold. Key words and phrases: incidental parameters, additive effects, interactive effects, factor
Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets.”Journal of Monetary Economics
, 2009
"... To identify disruptions in credit markets, research on the role of asset prices in economic fluctuations has focused on the information content of various corporate credit spreads. We reexamine this evidence using a broad array of credit spreads constructed directly from the secondary bond prices o ..."
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Cited by 105 (14 self)
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To identify disruptions in credit markets, research on the role of asset prices in economic fluctuations has focused on the information content of various corporate credit spreads. We reexamine this evidence using a broad array of credit spreads constructed directly from the secondary bond prices on outstanding senior unsecured debt issued by a large panel of nonfinancial firms. An advantage of our “groundup ” approach is that we are able to construct matched portfolios of equity returns, which allows us to examine the information content of bond spreads that is orthogonal to the information contained in stock prices of the same set of firms, as well as in macroeconomic variables measuring economic activity, inflation, interest rates, and other financial indicators. Our portfoliobased bond spreads contain substantial predictive power for economic activity and outperform—especially at longer horizons—standard defaultrisk indicators. Much of the predictive power of bond spreads for economic activity is embedded in securities issued by intermediaterisk rather than highrisk firms. According to impulse responses from a structural factoraugmented vector autoregression, unexpected increases in bond spreads cause large and persistent contractions in economic activity. Indeed, shocks emanating from the corporate bond market account for more than 20 percent of the forecast error variance in economic activity at the two to fouryear horizon. Overall, our results imply that credit market shocks have contributed significantly to U.S. economic fluctuations during the 1990–2007 period.
2006, A quasi maximum likelihood approach for large approximate dynamic factor models based on the Kalman filter, ECB Working Paper 674
"... Is maximum likelihood suitable for factor models in large crosssections of time series? We answer this question from both an asymptotic and an empirical perspective. We show that estimates of the common factors based on maximum likelihood are consistent for the size of the crosssection (n) and th ..."
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Cited by 101 (12 self)
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Is maximum likelihood suitable for factor models in large crosssections of time series? We answer this question from both an asymptotic and an empirical perspective. We show that estimates of the common factors based on maximum likelihood are consistent for the size of the crosssection (n) and the sample size (T) going to infinity along any path of n and T and that therefore maximum likelihood is viable for n large. The estimator is robust to misspecification of the crosssectional and time series correlation of the the idiosyncratic components. In practice, the estimator can be easily implemented using the Kalman smoother and the EM algorithm as in traditional factor analysis. JEL Classification: C51, C32, C33.