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Improved GMM estimation of panel VAR models. (English) Zbl 1466.62089

Summary: Improved IV/GMM estimators for panel vector autoregressive models (VAR) are proposed. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias-corrected fixed effects estimator in the VAR(1) case when both the sample sizes of cross section and time series are large. Since the proposed estimator is simply to change the form of instruments, it is very easy to implement in practice. As applications of the proposed estimators, a panel Granger causality test and panel impulse response analysis in which the asymptotic distribution of generalized impulse response functions is newly derived are considered. Monte Carlo simulation results show that the proposed estimators have comparable or better finite sample properties than the conventional IV/GMM estimators using instruments in levels for moderate or long time periods.

MSC:

62-08 Computational methods for problems pertaining to statistics
62P05 Applications of statistics to actuarial sciences and financial mathematics
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
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[1] Abadir, K. M.; Magnus, J. R., Matrix algebra, (2005), Cambridge University Press · Zbl 1084.15001
[2] Ahn, S. C.; Lee, Y. H.; Schmidt, P., Panel data models with multiple time-varying individual effects, J. Econometrics, 174, 1-14, (2013) · Zbl 1277.62202
[3] Alvarez, J.; Arellano, M., The time series and cross-section asymptotics of dynamic panel data estimators, Econometrica, 71, 1121-1159, (2003) · Zbl 1153.62353
[4] Anderson, T. W.; Hsiao, C., Estimation of dynamic models with error components, J. Amer. Statist. Assoc., 76, 598-606, (1981) · Zbl 0491.62080
[5] Arellano, M., 2003. Modelling optimal instrumental variables for dynamic panel data models. CEMFI Working Paper No. 0310.
[6] Arellano, M.; Bond, S., Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Rev. Econom. Stud., 58, 277-297, (1991) · Zbl 0719.62116
[7] Arellano, M.; Bover, O., Another look at the instrumental variable estimation of error-components models, J. Econometrics, 68, 29-51, (1995) · Zbl 0831.62099
[8] Aspachs, O.; Goodhart, C. A.E.; Tsomocos, D. P.; Zicchino, L., Towards a measure of financial fragility, Ann. Financ., 3, 37-74, (2007)
[9] Binder, M.; Hsiao, C.; Pesaran, M. H., Estimation and inference in short panel vector autoregressions with unit roots and cointegration, Econometric Theory, 21, 795-837, (2005) · Zbl 1082.62072
[10] Blundell, R.; Bond, S., Initial conditions and moment restrictions in dynamic panel data models, J. Econometrics, 87, 115-143, (1998) · Zbl 0943.62112
[11] Blundell, R.; Bond, S.; Windmeijer, F., Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator, (Baltagi, B. H., Nonstationary Panels, Panel Cointegration and Dynamic Panels, Advances in Econometrics, vol. 15, (2000), JAI Press Amsterdam), 53-91
[12] Buch, C. M.; Döpke, J.; Pierdzioch, C., Financial openness and business cycle volatility, J. Int. Money Finance, 24, 744-765, (2005)
[13] Bun, M. J.G.; Windmeijer, F., The weak instrument problem of the system GMM estimator in dynamic panel data models, Econom. J., 13, 95-126, (2010) · Zbl 1187.62139
[14] Cao, B.; Sun, Y., Asymptotic distributions of impulse response functions in short panel vector autoregressions, J. Econometrics, 163, 127-143, (2011) · Zbl 1441.62628
[15] Choe, J. I., Do foreign direct investment and Gross domestic investment promote economic growth?, Rev. Dev. Econ., 7, 44-57, (2003)
[16] Chong, A.; Gradstein, M., Inequality and institutions, Rev. Econ. Stat., 89, 454-465, (2007)
[17] Gilchrist, S.; Himmelberg, C. P.; Huberman, G., Do stock price bubbles influence corporate investment?, J. Monetary Econ., 52, 805-827, (2005)
[18] Granger, C. W.J., Investigating causal relations by econometric models and cross-spectral methods, Econometrica, 37, 424-438, (1969) · Zbl 1366.91115
[19] Hahn, J.; Kuersteiner, G., Asymptotically unbiased inference for a dynamic panel model with fixed effects when both \(n\) and \(T\) are large, Econometrica, 70, 1639-1657, (2002) · Zbl 1099.62100
[20] Hayakawa, K., Small sample bias properties of the system GMM estimator in dynamic panel data models, Econom. Lett., 95, 32-38, (2007) · Zbl 1255.62353
[21] Hayakawa, K., On the effect of mean-nonstationarity in dynamic panel data models, J. Econometrics, 153, 133-135, (2009) · Zbl 1431.62622
[22] Hayakawa, K., A simple efficient instrumental variable estimator in panel AR(p) models when both \(N\) and \(T\) are large, Econometric Theory, 25, 873-890, (2009) · Zbl 1253.62061
[23] Hayakawa, K.; Pesaran, M. H., Robust standard errors in transformed likelihood estimation of dynamic panel data models with cross-sectional heteroskedasticity, J. Econometrics, 188, 8, 111-134, (2015) · Zbl 1337.62265
[24] Hoffmann, R.; Lee, C. G.; Ramasamy, B.; Yeung, M., FDI and pollution: A Granger causality test using panel data, J. Int. Dev., 17, 311-317, (2005)
[25] Holtz-Eakin, D.; Newey, W. K.; Rosen, H. S., Estimating vector autoregressions with panel data, Econometrica, 56, 1371-1395, (1988) · Zbl 0654.62091
[26] Hsiao, C., Analysis of panel data, (2003), Cambridge University Press Cambridge, New York
[27] Hsu, N. J.; Hung, H. L.; Chang, Y. M., Subset selection for vector autoregressive processes using lasso, Comput. Statist. Data Anal., 52, 3645-3657, (2008), August · Zbl 1359.62296
[28] Huang, B.; Hwang, M. J.; Yang, C. W., Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach, Ecol. Econ., 67, 41-54, (2008), August
[29] Iwakura, H., Okui, R., 2014. Asymptotic efficiency in factor models and dynamic panel data models. KIER Discussion Paper, No. 887.
[30] Juodis, A., 2013. First difference transformation in panel VAR models: Robustness, estimation and inference. UvA-Econometrics Discussion Paper 2013/06. · Zbl 1284.62561
[31] Koop, G.; Pesaran, M. H.; Potter, S. M., Impulse response analysis in nonlinear multivariate models, J. Econometrics, 74, 119-147, (1996) · Zbl 0865.62086
[32] Love, I.; Zicchino, L., Financial development and dynamic investment behavior: evidence from panel VAR, Q. Rev. Econ. Finance, 46, 190-210, (2006), May
[33] Moon, H. R.; Phillips, P. C.B., Estimation of autoregressive roots near unity using panel data, Econometric Theory, 16, 927-997, (2000) · Zbl 1179.62126
[34] Nair-Reichert, U.; Weinhold, D., Causality tests for cross-country panels: a new look at FDI and economic growth in developing countries, Oxford Bull. Econ. Stat., 63, 153-171, (2001)
[35] Pesaran, M. H.; Shin, Y., Generalized impulse response analysis in linear multivariate models, Econom. Lett., 58, 17-29, (1998) · Zbl 0903.90028
[36] Phillips, P. C.B.; Moon, H. R., Linear regression limit theory for nonstationary panel data, Econometrica, 67, 1057-1111, (1999) · Zbl 1056.62532
[37] Rousseau, P. L.; Wachtel, P., Equity markets and growth: cross-country evidence on timing and outcomes, 1980-1995, J. Banking Finance, 24, 1933-1957, (2000), December
[38] Sims, C. A., Macroeconomics and reality, Econometrica, 48, 1-48, (1980)
[39] So, B. S.; Shin, D. W., Recursive mean adjustment in time series inferences, Statist. Probab. Lett., 43, 65-73, (1999) · Zbl 0914.62069
[40] Tibshirani, R., Regression shrinkage and selection via the lasso, J. R. Stat. Soc. Ser. B, 58, 267-288, (1996) · Zbl 0850.62538
[41] Windmeijer, F., A finite sample correction for the variance of linear efficient two-step GMM estimators, J. Econometrics, 126, 25-51, (2005) · Zbl 1334.62136
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