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247
Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure
, 2004
"... This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individualspecific regressors, and the factor loadings differ over the cross section units. The ..."
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Cited by 383 (44 self)
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This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individualspecific regressors, and the factor loadings differ over the cross section units. The basic idea behind the proposed estimation procedure is to filter the individualspecific regressors by means of (weighted) crosssection aggregates such that asymptotically as the crosssection dimension ( N) tends to infinity the differential effects of unobserved common factors are eliminated. The estimation procedure has the advantage that it can be computed by OLS applied to an auxiliary regression where the observed regressors are augmented by (weighted) cross sectional averages of the dependent variable and the individual specific regressors. Two different but related problems are addressed: one that concerns the coefficients of the individualspecific regressors, and the other that focusses on the mean of the individual coefficients assumed random. In both cases appropriate estimators, referred to as common correlated effects (CCE) estimators, are proposed and their asymptotic distribution as N →∞, with T (the timeseries dimension) fixed or as N and T →∞(jointly) are derived under different regularity conditions. One important feature of the proposed CCE mean group (CCEMG) estimator is its invariance to the (unknown but fixed) number of unobserved common factors as N and T →∞(jointly). The small sample properties of the various pooled estimators are investigated by Monte Carlo experiments that confirm the theoretical derivations and show that the pooled estimators have generally satisfactory small sample properties even for relatively small values of N and T.
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.
Unit Roots and Cointegration in Panels
, 2007
"... This paper provides a review of the literature on unit roots and cointegration in panels where the time dimension (T), and the cross section dimension (N) are relatively large. It distinguishes between the first generation tests developed on the assumption of the cross section independence, and the ..."
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Cited by 54 (3 self)
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This paper provides a review of the literature on unit roots and cointegration in panels where the time dimension (T), and the cross section dimension (N) are relatively large. It distinguishes between the first generation tests developed on the assumption of the cross section independence, and the second generation tests that allow, in a variety of forms and degrees, the dependence that might prevail across the different units in the panel. In the analysis of cointegration the hypothesis testing and estimation problems are further complicated by the possibility of cross section cointegration which could arise if the unit roots in the different cross section units are due to common random walk components.
Large panels with common factors and spatial correlations
 IZA DISCUSSION PAPER
, 2007
"... This paper considers the statistical analysis of large panel data sets where even after conditioning on common observed effects the cross section units might remain dependently distributed. This could arise when the cross section units are subject to unobserved common effects and/or if there are spi ..."
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Cited by 52 (5 self)
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This paper considers the statistical analysis of large panel data sets where even after conditioning on common observed effects the cross section units might remain dependently distributed. This could arise when the cross section units are subject to unobserved common effects and/or if there are spill over effects due to spatial or other forms of local dependencies. The paper provides an overview of the literature on cross section dependence, introduces the concepts of timespecific weak and strong cross section dependence and shows that the commonly used spatial models are examples of weak cross section dependence. It is then established that the Common Correlated Effects (CCE) estimator of panel data model with a multifactor error structure, recently advanced by Pesaran (2006), continues to provide consistent estimates of the slope coefficient, even in the presence of spatial error processes. Small sample properties of the CCE estimator under various patterns of cross section dependence, including spatial forms, are investigated by Monte Carlo experiments. Results show that the CCE approach works well in the presence of weak and/or strong cross sectionally correlated errors. We also explore the role of certain characteristics of spatial processes in determining the performance of CCE estimators, such as the form and intensity of spatial dependence, and the sparseness of the spatial weight matrix.
Lumpy price adjustments: a microeconometric analysis", by
, 2006
"... This paper presents a simple model of statedependent pricing that allows identi cation of the relative importance of the degree of price rigidity that is inherent to the price setting mechanism (intrinsic) and that which is due to the prices driving variables (extrinsic). Using two data sets consi ..."
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Cited by 49 (4 self)
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This paper presents a simple model of statedependent pricing that allows identi cation of the relative importance of the degree of price rigidity that is inherent to the price setting mechanism (intrinsic) and that which is due to the prices driving variables (extrinsic). Using two data sets consisting of a large fraction of the price quotes used to compute the Belgian and French CPI, we are able to assess the role of intrinsic and extrinsic price stickiness in explaining the occurrence and magnitude of price changes at the outlet level. We
nd that infrequent price changes are not necessarily associated with large adjustment costs. Indeed, extrinsic rigidity appears to be signi
cant in many cases. We also
nd that asymmetry in the price adjustment could be due to trends in marginal costs and/or desired markups rather than asymmetric cost of adjustment bands. JEL Classi
cations: C51, C81, D21.
What do we really know about fiscal sustainability in the EU? A panel data diagnostic
, 2007
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Panel Data Econometrics in R: The plm Package
 Journal of Statistical Software
, 2008
"... This introduction to the plm package is a slightly modified version of Croissant and Millo (2008), published in the Journal of Statistical Software. Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a p ..."
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Cited by 30 (1 self)
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This introduction to the plm package is a slightly modified version of Croissant and Millo (2008), published in the Journal of Statistical Software. Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a package for R which intends to make the estimation of linear panel models straightforward. plm provides functions to estimate a wide variety of models and to make (robust) inference. Keywords:˜panel data, covariance matrix estimators, generalized method of moments, R. 1.
European Central Bank
, 2008
"... New Keynesian Phillips Curves (NKPC) have been extensively used in the analysis of monetary policy, but yet there are a number of issues of concern about how they are estimated and then related to the underlying macroeconomic theory. The first is whether such equations are identified. To check ident ..."
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Cited by 29 (0 self)
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New Keynesian Phillips Curves (NKPC) have been extensively used in the analysis of monetary policy, but yet there are a number of issues of concern about how they are estimated and then related to the underlying macroeconomic theory. The first is whether such equations are identified. To check identification requires specifying the process for the forcing variables (typically the output gap) and solving the model for inflationintermsoftheobservables. Inpractice,theequationisestimatedby GMM, relying on statistical criteria to choose instruments. This may result in failure of identification or weak instruments. Secondly, the NKPC is usually derived as a part of a DSGE model, solved by loglinearising around a steady state and the variables are then measured in terms of deviations from the steady state. In practice the steady states, e.g. for output, are usually estimated by some statistical procedure such as the HodrickPrescott (HP) filter that might not be appropriate. Thirdly, there are arguments that other variables, e.g. interest rates, foreign inflation and foreign output gaps should enter the Phillips curve. This paper examines these three issues and argues that all three benefit from a global perspective. The global perspective provides additional instruments to alleviate the weak instrument problem, yields a theoretically consistent measure of the steady state and provides a natural route for foreign inflation or output gap to enter the NKPC. Keywords: Global VAR (GVAR), identification, New Keynesian Phillips Curve, TrendCycle decomposition.
2011a). Growth, Development and Natural Resources: New Evidence Using a Heterogeneous Panel Analysis. The Quarterly Review of Economics and Finance 51
"... This paper explores whether natural resource abundance is a curse or a blessing. To do so, we …rstly develop a theory consistent econometric model, in which we show that there is a long run relationship between real income, the investment rate, and the real value of oil production. Secondly, we inve ..."
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Cited by 23 (11 self)
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This paper explores whether natural resource abundance is a curse or a blessing. To do so, we …rstly develop a theory consistent econometric model, in which we show that there is a long run relationship between real income, the investment rate, and the real value of oil production. Secondly, we investigate the longrun (level) impacts of natural resource abundance on domestic output as well as the shortrun (growth) e¤ects. Thirdly, we explicitly recognize that there is a substantial crosssectional dependence and crosscountry heterogeneity in our sample, which covers 53 oil exporting and importing countries with very di¤erent historical and institutional backgrounds, and adopt the nonstationary panel methodologies developed by Pesaran (2006) and Pedroni (2000) for estimation. Our results, using the real value of oil production, rent or reserves as a proxy for resource endowment, reveal that oil abundance has a positive e¤ect on both income levels and economic growth. While we accept that oil rich countries could bene…t more from their natural wealth by adopting growth and welfare enhancing policies and institutions, we challenge the common view that oil abundance a¤ects economic growth negatively.