| dc.contributor.author | Lütkepohl, Helmut | |
| dc.contributor.author | Staszewska-Bystrova, Anna | |
| dc.contributor.author | Winker, Peter | |
| dc.date.accessioned | 2018-10-05T07:34:36Z | |
| dc.date.available | 2018-10-05T07:34:36Z | |
| dc.date.issued | 2018-09-30 | |
| dc.identifier.uri | http://hdl.handle.net/11089/25920 | |
| dc.description.abstract | Methods for constructing joint confidence bands for impulse response functions
which are commonly used in vector autoregressive analysis are reviewed.
While considering separate intervals for each horizon individually still seems
to be the most common approach, a substantial number of methods have been
proposed for making joint inferences about the complete impulse response
paths up to a given horizon. A structured presentation of these methods is
provided. Furthermore, existing evidence on the small-sample performance
of the methods is gathered. The collected information can help practitioners
to decide on a suitable confidence band for a structural VAR analysis. | pl_PL |
| dc.description.sponsorship | Part of the work on this paper was conducted while the first author was a
Fernand Braudel Fellow at the European University Institute in Florence.
Financial support from the National Science Center (NCN) through MAESTRO
4: DEC-2013/08/A/HS4/00612 is gratefully acknowledged. | pl_PL |
| dc.language.iso | en | pl_PL |
| dc.relation.ispartofseries | Lodz Economics Working Papers;4 | |
| dc.subject | Impulse responses | pl_PL |
| dc.subject | vector autoregressive model | pl_PL |
| dc.subject | joint confidence bands | pl_PL |
| dc.title | Constructing Joint Confidence Bands for Impulse Response Functions of VAR Models - A Review | pl_PL |
| dc.type | Working Paper | pl_PL |
| dc.contributor.authorAffiliation | DIW Berlin and Freie Universität Berlin | pl_PL |
| dc.contributor.authorAffiliation | University of Lodz | pl_PL |
| dc.contributor.authorAffiliation | University of Giessen | pl_PL |
| dc.references | Alt, F. & Spruill, C. (1977). A comparison of confidence intervals generated by the Scheffe and Bonferroni methods, Communications in Statistics - Theory and Methods A6(15): 1503–1510. | pl_PL |
| dc.references | Andrews, D. W. K. (1987). Asymptotic results for generalized Wald tests, Econometric Theory 3: 348–358. | pl_PL |
| dc.references | Bagliano, F. C. & Favero, C. A. (1998). Measuring monetary policy with VAR models: An evaluation, European Economic Review 42(6): 1069–1112. | pl_PL |
| dc.references | Benkwitz, A., Lütkepohl, L. & Neumann, M. (2000). Problems related to bootstrapping impulse responses of autoregressive processes, Econometric Reviews 19: 69–103. | pl_PL |
| dc.references | Bruder, S. (2014). Comparing several methods to compute joint prediction regions for path forecasts generated by vector autoregressions, ECON - Working Papers 181, University of Zurich, Department of Economics. Revised 2015. | pl_PL |
| dc.references | Bruder, S. & Wolf, M. (2018). Balanced bootstrap joint confidence bands for structural impulse response functions, Journal of Time Series Analysis (forthcoming). | pl_PL |
| dc.references | Brüggemann, R., Jentsch, C. & Trenkler, C. (2016). Inference in VARs with conditional volatility of unknown form, Journal of Econometrics 191: 69–85. | pl_PL |
| dc.references | Deutsche Bundesbank (2005). Finanzmarktstabilitätsbericht 2005, Deutsche Bundesbank, Frankfurt a.M. | pl_PL |
| dc.references | Fisher, L. A. & Huh, H.-S. (2016). Monetary policy and exchange rates: Further evidence using a new method for implementing sign restrictions, Journal of Macroeconomics 49: 177–191. | pl_PL |
| dc.references | Gertler, M. & Karadi, P. (2015). Monetary policy surprises, credit costs, and economic activity, American Economic Journal: Macroeconomics 7(1): 44–76. | pl_PL |
| dc.references | Grabowski, D., Staszewska-Bystrova, A. & Winker, P. (2017). Generating prediction bands for path forecasts from SETAR models, Studies in Nonlinear Dynamics & Econometrics 21(5). | pl_PL |
| dc.references | Hamilton, J. D. (2009). Causes and consequences of the oil shock of 2007-08, Brookings Papers on Economic Activity 40: 215–283. | pl_PL |
| dc.references | Hyndman, R. (1995). Highest-density forecast regions for nonlinear and nonnormal time series models, Journal of Forecasting 14(5): 431–441. | pl_PL |
| dc.references | Hyndman, R. (1996). Computing and graphing highest density regions, The American Statistician 50(2): 120–126. | pl_PL |
| dc.references | Inoue, A. & Kilian, L. (2013). Inference on impulse response functions in structural VAR models, Journal of Econometrics 177: 1–13. | pl_PL |
| dc.references | Inoue, A. & Kilian, L. (2016). Joint confidence sets for structural impulse responses, Journal of Econometrics 192(2): 421–432. | pl_PL |
| dc.references | Jorda, O. (2009). Simultaneous confidence regions for impulse responses, The Review of Economics and Statistics 91(3): 629–647. | pl_PL |
| dc.references | Jorda, O. & Marcellino, M. (2010). Path forecast evaluation, Journal of Applied Econometrics 25: 635–662. | pl_PL |
| dc.references | Kapetanios, G., Price, S. & Young, G. (2018). A UK financial conditions index using targeted data reduction: Forecasting and structural identification, Econometrics and Statistics (forthcoming). | pl_PL |
| dc.references | Kilian, L. (1998a). Accounting for lag order uncertainty in autoregressions: The endogenous lag order bootstrap algorithm, Journal of Time Series Analysis 19: 531–548. | pl_PL |
| dc.references | Kilian, L. (1998b). Small-sample confidence intervals for impulse response functions, Review of Economics and Statistics 80: 218–230. | pl_PL |
| dc.references | Kilian, L. (1999). Finite-sample properties of percentile and percentile-t bootstrap confidence intervals for impulse responses, Review of Economics and Statistics 81: 652–660. | pl_PL |
| dc.references | Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market, American Economic Review 99(3): 1053–1069. | pl_PL |
| dc.references | Kilian, L. (2013). Structural vector autoregressions, in N. Hashimzade & M. Thornton (eds), Handbook of Research Methods and Applications on Empirical Macroeconomics, Edward Elger, Cheltenham, UK, pp. 515– 554. | pl_PL |
| dc.references | Kilian, L. & Lütkepohl, H. (2017). Structural Vector Autoregressive Analysis, Cambridge University Press, Cambridge. | pl_PL |
| dc.references | Kilian, L. & Murphy, D. P. (2012). Why agnostic sign restrictions are not enough: Understanding the dynamics of oil market VAR models, Journal of the European Economic Association 10(5): 1166–1188. | pl_PL |
| dc.references | Kolsrud, D. (2007). Time-simultaneous prediction band for a time series, Journal of Forecasting 26(3): 171–188. | pl_PL |
| dc.references | Kolsrud, D. (2015). A time-simultaneous prediction box for a multivariate time series, Journal of Forecasting 34(8): 675–693. | pl_PL |
| dc.references | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis, Springer-Verlag, Berlin. | pl_PL |
| dc.references | Lütkepohl, H., Staszewska-Bystrova, A. & Winker, P. (2015a). Comparison of methods for constructing joint confidence bands for impulse response functions, International Journal for Forecasting 31: 782–798. | pl_PL |
| dc.references | Lütkepohl, H., Staszewska-Bystrova, A. & Winker, P. (2015b). Confidence bands for impulse responses: Bonferroni versus Wald, Oxford Bulletin of Economics and Statistics 77: 800–821. | pl_PL |
| dc.references | Lütkepohl, H., Staszewska-Bystrova, A. & Winker, P. (2017). Calculating joint confidence bands for impulse response functions using highest density regions, Empirical Economics (forthcoming). | pl_PL |
| dc.references | Montiel Olea, J. & Plagborg-Møller, M. (2017). Simultaneous confidence bands: Theoretical comparisons and recommendations for practice, Unpublished manuscript, Harvard University. | pl_PL |
| dc.references | Montiel Olea, J. & Plagborg-Møller, M. (2018). Simultaneous confidence bands: Theorym implementation, and an application to svars, Journal of Applied Econometrics (forthcoming). | pl_PL |
| dc.references | Nicholls, D. F. & Pope, A. L. (1988). Bias in estimation of multivariate autoregression, Australian Journal of Statistics 30A: 296–309. | pl_PL |
| dc.references | Pope, A. L. (1990). Biases for estimators in multivariate non-Gaussian autoregressions, Journal of Time Series Analysis 11: 249–258. | pl_PL |
| dc.references | Romano, J. P. &Wolf, M. (2010). Balanced control of generalized error rates, Annals of Statistics 38: 598–633. | pl_PL |
| dc.references | Royen, T. (2014). A simple proof of the Gaussian correlation conjecture extended to some multivariate Gamma distributions, Far East Journal of Theoretical Statistics 48: 139–145. | pl_PL |
| dc.references | Scheffe, H. (1953). A method for judging all contrasts in the analysis of variance, Biometrika 49: 87–104. | pl_PL |
| dc.references | Schüssler, R. & Trede, M. (2016). Constructing minimum-width confidence bands, Economics Letters 145: 182–185. | pl_PL |
| dc.references | Sims, C. A. (1980). Macroeconomics and reality, Econometrica 48: 1–48. | pl_PL |
| dc.references | Sims, C. A. & Zha, T. (1999). Error bands for impulse responses, Econometrica 67(5): 1113–1155. | pl_PL |
| dc.references | Staszewska, A. (2007). Representing uncertainty about impulse response paths: The use of heuristic optimization methods, Computational Statistics & Data Analysis 52: 121–132. | pl_PL |
| dc.references | Staszewska-Bystrova, A. (2011). Bootstrap prediction bands for forecast paths from vector autoregressive models, Journal of Forecasting 30: 721– 735. | pl_PL |
| dc.references | Staszewska-Bystrova, A. (2013). Modified Scheffe’s prediction bands, Journal of Economics and Statistics 233(5-6): 680–690. | pl_PL |
| dc.references | Staszewska-Bystrova, A. & Winker, P. (2013). Constructing narrowest pathwise bootstrap prediction bands using threshold accepting, International Journal of Forecasting 29: 221–233. | pl_PL |
| dc.references | Staszewska-Bystrova, A. & Winker, P. (2014). Measuring forecats uncertainty of corporate bond spreads by Bonferroni-type prediction bands, Central European Journal of Economic Modeling and Econometrics 6(2): 89–104. | pl_PL |
| dc.references | Stock, J. & Watson, M. (2005). Understanding changes in international business cycle dynamics, Journal of the European Economic Association 3(5): 968–1006. | pl_PL |
| dc.references | Sidak, Z. (1967). Rectangular confidence regions for the means of multivariate normal distributions, Journal of the American Statistical Association 62: 626–633. | pl_PL |
| dc.references | Wolf, M. & Wunderli, D. (2015). Bootstrap joint prediction regions, Journal of Time Series Analysis 36(3): 352–376. | pl_PL |
| dc.contributor.authorEmail | hluetkepohl@diw.de | pl_PL |
| dc.contributor.authorEmail | anna.bystrova@uni.lodz.pl | pl_PL |
| dc.contributor.authorEmail | Peter.Winker@wirtschaft.uni-giessen.de | pl_PL |
