References
- Anderson, T. W., and Rubin, H. (1949), “Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations,” Annals of Mathematical Statistics, 20, 46–63. DOI: 10.1214/aoms/1177730090.
- Andrews, D. W. K. (1991), “Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation,” Econometrica, 59, 817–858. DOI: 10.2307/2938229.
- Andrews, D. W. K., and Cheng, X. (2012), “Estimation and Inference with Weak, Semi-Strong, and Strong Identification,” Econometrica, 80, 2153–2211.
- Andrews, I., Stock, J. H., and Sun, L. (2019), “Weak Instruments in Instrumental Variables Regression: Theory and Practice,” Annual Review of Economics, 11, 727–753. DOI: 10.1146/annurev-economics-080218-025643.
- Angelini, G., and Fanelli, L. (2019), “Exogenous Uncertainty and the Identification of Structural Vector Autoregressions with External Instruments,” Journal of Applied Econometrics, 34, 951–971. DOI: 10.1002/jae.2736.
- Arias, J. E., Rubio-Ramírez, J. F., and Waggoner, D. F. (2018), “Inference in Bayesian Proxy-SVARs,” Federal Reserve Bank of Atlanta Working Paper 2018-16.
- Brillinger, D. R. (1981), Time Series: Data Analysis and Theory, San Francisco, CA: Holden-Day.
- Brüggemann, R., Jentsch, C., and Trenkler, C. (2014), “Inference in VARs with Conditional Heteroskedasticity of Unknown Form,” University of Konstanz Working Paper 2014-13.
- Brüggemann, R., Jentsch, C., and Trenkler, C. (2016), “Inference in VARs With Conditional Heteroskedasticity of Unknown Form,” Journal of Econometrics, 191, 69–85.
- Caldara, D., and Herbst, E. (2019), “Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs,” American Economic Journal: Macroeconomics, 11, 157–192. DOI: 10.1257/mac.20170294.
- Carriero, A., Mumtaz, H., Theodoridis, K., and Theophilopoulou, A. (2015), “The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR Approach,” Journal of Money, Credit and Banking, 47, 1223–1238. DOI: 10.1111/jmcb.12243.
- Christiano, L. J., Eichenbaum, M., and Evans, C. L. (1999), “Monetary Policy Shocks: What Have We Learned and to What End?” in Handbook of Macroeconomics, eds. John B. Taylor and Michael Woodford, chap. 2. Amsterdam, The Netherlands: Elsevier Science B.V., pp. 65–148.
- Clark, T. E., and Ravazzolo, F. (2015), “Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility,” Journal of Applied Econometrics, 30, 551–575. DOI: 10.1002/jae.2379.
- Davis, R. A., and Mikosch, T. (2009), “Probabilistic Properties of Stochastic Volatility Models,” in Handbook of Financial Time Series, eds. Torben G. Andersen, Richard A. Davis, Jens-Peter Kreiß, and Thomas Mikosch. Berlin, Heidelberg: Springer-Verlag, pp. 255–267.
- Dolado, J. J., and Lütkepohl, H. (1996), “Making Wald Tests Work for Cointegrated VAR Systems,” Econometric Reviews, 15, 369–386. DOI: 10.1080/07474939608800362.
- Fernández-Villaverde, J., Guerrón-Quintana, P., and Rubio-Ramírez, J. F. (2010), “Reading the Recent Monetary History of the United States, 1959-2007,” Federal Reserve Bank of St. Louis Review, 92, 311–338. DOI: 10.20955/r.92.311-38.
- Gertler, M., and Karadi, P. (2015), “Monetary Policy Surprises, Credit Costs, and Economic Activity,” American Economic Journal: Macroeconomics, 7, 44–76. DOI: 10.1257/mac.20130329.
- Gonçalves, S., and Kilian, L. (2004), “Bootstrapping Autoregressions With Conditional Heteroskedasticity of Unknown Form,” Journal of Econometrics, 123, 89–120. DOI: 10.1016/j.jeconom.2003.10.030.
- Gonçalves, S., and Kilian, L. (2007), “Asymptotic and Bootstrap Inference for AR(∞ ) Processes With Conditional Heteroskedasticity,” Econometric Reviews, 26, 609–641.
- Hachula, M., and Nautz, D. (2018), “The Dynamic Impact of Macroeconomic News on Long-Term Inflation Expectations,” Economics Letters, 165, 39–43. DOI: 10.1016/j.econlet.2018.01.015.
- Hall, P. (1992), The Bootstrap and Edgeworth Expansion, New York: Springer.
- Hansen, B. E. (1999), “The Grid Bootstrap and the Autoregressive Model,” Review of Economics and Statistics, 81, 594–607. DOI: 10.1162/003465399558463.
- Inoue, A., and Kilian, L. (2020), “The Uniform Validity of Impulse Response Inference in Autoregressions,” Journal of Econometrics, 215, 450–472. DOI: 10.1016/j.jeconom.2019.10.001.
- Jarociński, M., and Karadi, P. (2020), “Deconstructing Monetary Policy Surprises – The Role of Information Shocks,” American Economic Journal: Macroeconomics, 12, 1–43. DOI: 10.1257/mac.20180090.
- Jentsch, C., and Lunsford, K. G. (2016), “Proxy SVARs: Asymptotic Theory, Bootstrap Inference, and the Effects of Income Tax Changes in the United States,” Federal Reserve Bank of Cleveland, Working Paper No. 16-19.
- Jentsch, C., and Lunsford, K. G. (2019a), “Asymptotically Valid Bootstrap Inference for Proxy SVARs,” Federal Reserve Bank of Cleveland, Working Paper No. 19-08.
- Jentsch, C., and Lunsford, K. G. (2019b), “The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States: Comment,” American Economic Review, 109, 2655–2678.
- Kerssenfischer, M. (2019), “The Puzzling Effects of Monetary Policy in VARs: Invalid Identification or Missing Information?” Journal of Applied Econometrics, 34, 18–25. DOI: 10.1002/jae.2647.
- Kilian, L. (1998), “Small-Sample Confidence Intervals for Impulse Response Functions,” Review of Economics and Statistics, 80, 218–230. DOI: 10.1162/003465398557465.
- Kilian, L. (1999), “Finite-Sample Properties of Percentile and Percentilet Bootstrap Confidence Intervals for Impulse Responses,” Review of Economics and Statistics, 81, 652–660.
- Künsch, H. R. (1989), “The Jackknife and the Bootstrap for General Stationary Observations,” Annals of Statistics, 17, 1217–1241.
- Lunsford, K. G. (2015), “Identifying Structural VARs with a Proxy Variable and a Test for a Weak Proxy,” Federal Reserve Bank of Cleveland Working Paper No. 15-28.
- Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis, Berlin, Heidelberg: Springer-Verlag.
- Mertens, K., and Ravn, M. O. (2013), “The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States,” American Economic Review, 103, 1212–1247. DOI: 10.1257/aer.103.4.1212.
- Mertens, K., and Ravn, M. O. (2014), “A Reconciliation of SVAR and Narrative Estimates of Tax Multipliers,” Journal of Monetary Economics, 68, S1–S19.
- Mikusheva, A. (2012), “One-Dimensional Inference in Autoregressive Models With the Potential Presence of a Unit Root,” Econometrica, 80, 173–212.
- Miranda-Agrippino, S. (2016), “Unsurprising Shocks: Information, Premia, and the Monetary Transmission,” Bank of England Staff Working Paper No. 626.
- Monteil Olea, J. L., Stock, J. H., and Watson, M. W. (2021), “Inference in Structural Vector Autoregressions Identified With an External Instrument,” Journal of Econometrics, 225, 74–87. DOI: 10.1016/j.jeconom.2020.05.014.
- Passari, E., and Rey, H. (2015), “Financial Flows and the International Monetary System,” Economic Journal 125, 675–698. DOI: 10.1111/ecoj.12268.
- Piffer, M., and Podstawski, M. (2018), “Identifying Uncertainty Shocks Using the Price of Gold,” Economic Journal, 128, 3266–3284. DOI: 10.1111/ecoj.12545.
- Ramey, V. A. (2016), “Macroeconomic Shocks and Their Propagation,” in Handbook of Macroeconomics, eds. John B. Taylor and Harald Uhlig, chap. 2. Amsterdam, The Netherlands: Elsevier B.V., pp. 71–162.
- Rey, H. (2016), “International Channels of Transmission of Monetary Policy and the Mundellian Trilemma,” IMF Economic Review 64, 6–35. DOI: 10.1057/imfer.2016.4.
- Sims, C. A. (1980), “Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered,” American Economic Review 70, 250–257.
- Stock, J. H., and Watson, M. W. (2008), “Lecture 7 – Recent Developments in Structural VAR Modeling,” Presented at the NBER Summer Institute Econometrics Lectures: What’s New in Economics – Time Series, July 15.
- Stock, J. H., and Watson, M. W. (2012), “Disentangling the Channels of the 2007-09 Recession,” Brookings Papers on Economic Activity, Spring, 81–135.
- Stock, J. H., and Watson, M. W. (2016), “Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics,” in Handbook of Macroeconomics, eds. John B. Taylor and Harald Uhlig, chap. 8. Amsterdam, The Netherlands: Elsevier B.V., pp. 415–525.
- Stock, J. H., Wright, J. H., and Yogo, M. (2002), “A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments,” Journal of Business & Economic Statistics, 20, 518–529.
- Toda, H. Y., and Yamamoto, T. (1995), “Statistical Inference in Vector Autoregressions With Possibly Integrated Processes,” Journal of Econometrics 66, 225–250. DOI: 10.1016/0304-4076(94)01616-8.