On modeling panels of time series *

This paper reviews research issues in modeling panels of time series. Examples of this type of data are annually observed macroeconomic indicators for all countries in the world, daily returns on the individual stocks listed in the S&P500, and the sales records of all items in a retail store. A panel of time series usually concerns the case where the cross-section dimension and the time dimension are large. Usually, there is no a priori reason to select a few series or to aggregate the series over the cross-section dimension. In that case, however, the use of for example a vector autoregression or other types of multivariate systems becomes cumbersome. Panel models and associated estimation techniques are more useful. This paper discusses representation, estimation and inference in case the data have trends, seasonality, outliers, or nonlinearity. Various examples illustrate the various models.

[1]  David H. Papell.  Searching for stationarity: Purchasing power parity under the current float , 1997 .

[2]  M. Hashem Pesaran,et al.  Pooled Mean Group Estimation of Dynamic Heterogeneous Panels , 1999 .

[3]  Dag Tjøstheim,et al.  Modelling panels of intercorrelated autoregressive time series , 1999 .

[4]  Gerard A. Pfann,et al.  Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates , 2000 .

[5]  Elias Tzavalis,et al.  Inference for unit roots in dynamic panels where the time dimension is fixed , 1999 .

[6]  Jinyong Hahn,et al.  Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects When Both N and T are Large , 2000 .

[7]  Clive W. J. Granger,et al.  Extracting information from mega‐panels and high‐frequency data , 2008 .

[8]  R. Engle,et al.  Common Seasonal Features: Global Unemployment , 1996 .

[9]  J. Stock,et al.  Macroeconomic Forecasting Using Diffusion Indexes , 2002 .

[10]  Andrew T. Levin,et al.  Unit root tests in panel data: asymptotic and finite-sample properties , 2002 .

[11]  R. Blundell,et al.  What Do We Learn About Consumer Demand Patterns from Micro Data , 1993 .

[12]  P. O'Connell.  The overvaluation of purchasing power parity , 1998 .

[13]  P. Franses,et al.  An Empirical Study of Cash Payments , 2003 .

[14]  Robert C. Blattberg,et al.  Shrinkage Estimation of Price and Promotional Elasticities: Seemingly Unrelated Equations , 1991 .

[15]  BAYESIAN MODELING OF ECONOMIES AND DATA REQUIREMENTS , 2001, Macroeconomic Dynamics.

[16]  Peter C. B. Phillips,et al.  ESTIMATION OF AUTOREGRESSIVE ROOTS NEAR UNITY USING PANEL DATA , 1999, Econometric Theory.

[17]  Philip Hans Franses,et al.  Testing for common deterministic trend slopes , 2001 .

[18]  Stephen Nickell,et al.  Biases in Dynamic Models with Fixed Effects , 1981 .

[19]  W. Newey,et al.  Estimating vector autoregressions with panel data , 1988 .

[20]  P. Swamy.  Efficient Inference in a Random Coefficient Regression Model , 1970 .

[21]  P. Phillips,et al.  Linear Regression Limit Theory for Nonstationary Panel Data , 1999 .

[22]  R. Paap.  What are the advantages of MCMC based inference in latent variable models? , 2002 .

[23]  Frank Kleibergen,et al.  Likelihood-Based Cointegration Analysis in Panels of Vector Error-Correction Models , 2003 .

[24]  Philip Hans Franses,et al.  Selective Sampling for Binary Choice Models , 2003 .