Bootstrap bias-correction procedure in estimating long-run relationships from dynamic panels, with an application to money demand in the euro area

In dynamic panel data models, which are particularly well-suited to cross-country analysis, the Mean Group estimator (Pesaran and Smith, 1995) is under certain quite strong conditions consistent, but theoretical and empirical evidence indicates that it can be biased when the number of time observations is small. Possible explanations are sample-size bias and omitted variables or measurement errors that are correlated with the regressors. I find support for both hypotheses using a Monte Carlo experiment which analyzes cointegrated systems. A possible solution for the MG estimator bias is a bootstrap bias-correction procedure, but Pesaran and Zhao (1999) show that it performs well only when the true coefficient of the lagged dependent variable is small. In this paper, I test three different bootstrap procedures and obtain an appreciable reduction in the MG estimator bias, especially when the suggestions of Li and Maddala (1997) are applied. Finally, I use bootstrap bias-corrected estimators to investigate the long-run properties of money demand in the euro area.

[1]  A. Generale,et al.  New Findings on Firm Investment and Monetary Transmission in the Euro Area , 2001 .

[2]  Patrick Sevestre,et al.  The Econometrics of Panel Data , 1993 .

[3]  D. Andrews.  Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation , 1991 .

[4]  A. Generale,et al.  Does Monetary Policy Have Asymmetric Effects? A Look at the Investment Decisions of Italian Firms , 2001, SSRN Electronic Journal.

[5]  Luca Dedola,et al.  Money Demand in theEuroArea: Do National Differences Matter? , 2001 .

[6]  Jeremy Berkowitz,et al.  Recent developments in bootstrapping time series , 1996 .

[7]  Modeling the Demand for M3 in the Euro Area , 2000 .

[8]  H. Künsch.  The Jackknife and the Bootstrap for General Stationary Observations , 1989 .

[9]  F. Busetti.  The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model , 2001 .

[10]  A. Staderini.  Tax reforms to influence corporate financial policy: the case of the Italian business tax reform of 1997-98 , 2001 .

[11]  G. Tomat.  Durable Goods, Price Indexes and Quality Change: An Application to Automobile Prices in Italy, 1988-1998 , 2002, SSRN Electronic Journal.

[12]  Ronald Smith,et al.  Dynamic Linear Models for Heterogenous Panels , 1996 .

[13]  Filippo Altissimo,et al.  The construction of coincident and leading indicators for the euro area business cycler of the euro area business cycle , 2001 .

[14]  J. Henry,et al.  Long run money demand in the EU: Evidence for area-wide aggregates , 1998 .

[15]  Bruce E. Hansen,et al.  Tests for Parameter Instability in Regressions with I(1) Processes , 1992 .

[16]  M. Pesaran,et al.  Estimating Long-Run Relationships From Dynamic Heterogeneous Panels , 1995 .

[17]  Sandro Trento,et al.  Nuove tecnologie e cambiamenti organizzativi: alcune implicazioni per le imprese italiane , 2001 .

[18]  Günter Coenen,et al.  The Demand for M3 in the Euro Area , 1999, SSRN Electronic Journal.

[19]  G. S. Hongyi Li,et al.  Bootstrapping time series models , 1996 .

[20]  L. Papi,et al.  European Integration, Monetary Co-ordination, and the Demand for Money , 1996 .

[21]  S. Pastorello,et al.  Modelling the demand for M3 in the Euro area , 2002 .

[22]  Patrick Sevestre,et al.  Financial Systems and the Role of Banks in Monetary Policy Transmission in the Euro Area , 2001, SSRN Electronic Journal.

[23]  Paolo Sestito,et al.  Earnings Dispersion, Low Pay and Household Poverty in Italy, 1977-1998 , 2001 .

[24]  S. Ahsan,et al.  The design of a consumption tax under capital risk , 1998 .

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

[26]  Giovanni Iuzzolino.  Struttura dell�offerta e divari territoriali nella filiera dell�information and communication technologies in Italia , 2001 .

[27]  S. Neri.  Assessing the effects of monetary and fiscal policy , 2001 .

[28]  Peter C. B. Phillips,et al.  Statistical Inference in Instrumental Variables Regression with I(1) Processes , 1990 .

[29]  F. Schivardi,et al.  Ingredients for the New Economy: How Much does Finance Matter? , 2001 .

[30]  Riccardo Cristadoro,et al.  A Core Inflation Index for the Euro Area , 2001 .

[31]  M. Pesaran,et al.  Bias Reduction in Estimating Long-run Relationships from Dynamic Heterogenous Panels , 1998 .

[32]  Z. Kontolemis.  Money Demand in the Euro Area , 2002 .

[33]  Yongcheol Shin,et al.  Pooled Estimation of Long-run Relationships in Dynamic Heterogeneous Panels , 1997 .

[34]  Regina Y. Liu.  Moving blocks jackknife and bootstrap capture weak dependence , 1992 .

[35]  Donald W. K. Andrews,et al.  An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator , 1992 .

[36]  L. Gambacorta.  Bank-Specific Characteristics and Monetary Policy Transmission: The Case of Italy , 2001, SSRN Electronic Journal.

[37]  K. Song,et al.  Bootstrapping cointegrating regressions , 2006 .

[38]  The stability-oriented monetary policy strategy of the Eurosystem , 2007 .

[39]  Jan F. Kiviet,et al.  On bias, inconsistency and efficiency of various estimators in dynamic panel data models , 1995 .

[40]  Paola Caselli,et al.  ICT accumulation and productivity growth in the United States: an analysis based on industry data , 2001 .

[41]  A. Locarno,et al.  Monetary Policy Transmission in the Euro Area: What Do Aggregate and National Structural Models Tell Us? , 2001, SSRN Electronic Journal.

[42]  Hongyi Li,et al.  15 Bootstrap based tests in financial models , 1996 .

[43]  Enrico Saltari,et al.  Consumption and fiscal policies: medium-run non-Keynesian effects , 2001 .

[44]  C. Fuest,et al.  Efficiency wages, employment, and the marginal income-tax rate: A note , 1998 .