RDP 2022-04: The Unit-effect Normalisation in Set-identified Structural Vector Autoregressions References

Amir-Ahmadi P and T Drautzburg (2021), ‘Identification and Inference with Ranking Restrictions’, Quantitative Economics, 12(1), pp 1–39.

Antolín-Díaz J and JF Rubio-Ramírez (2018), ‘Narrative Sign Restrictions for SVARs’, The American Economic Review, 108(10), pp 2802–2829.

Arias JE, D Caldara and JF Rubio-Ramírez (2019), ‘The Systematic Component of Monetary Policy in SVARs: An Agnostic Identification Procedure’, Journal of Monetary Economics, 101, pp 1–13.

Arias JE, JF Rubio-Ramírez and DF Waggoner (2018), ‘Inference Based on Structural Vector Autoregressions Identified with Sign and Zero Restrictions: Theory and Applications, Econometrica, 86(2), pp 685–720.

Arias JE, JF Rubio-Ramírez and DF Waggoner (2022), ‘Uniform Priors for Impulse Responses’, Federal Reserve Bank of Philadelphia Working Paper WP 22-30.

Bacchiocchi E and T Kitagawa (2021), ‘A Note on Global Identification in Structural Vector Autoregressions’, Centre for Microdata Methods and Practice, cemmap Working Paper CWP03/21.

Baumeister C and JD Hamilton (2015), ‘Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information’, Econometrica, 83(5), pp 1963–1999.

Baumeister C and JD Hamilton (2018), ‘Inference in Structural Vector Autoregressions When the Identifying Assumptions Are Not Fully Believed: Re-Evaluating the Role of Monetary Policy in Economic Fluctuations’, Journal of Monetary Economics, 100, pp 48–65.

Baumeister C and JD Hamilton (2019), ‘Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks’, The American Economic Review, 109(5), pp 1873–1910.

Baumeister C and JD Hamilton (2022), ‘Advances in Using Vector Autoregressions to Estimate Structural Magnitudes’, Unpublished manuscript, June. Available at <https://drive.google.com/file/d/1gbR6HllbhqkE2msfuApKNe80SPgJe6FY/view>.

Beaudry P, D Nam and J Wang (2011), ‘Do Mood Swings Drive Business Cycles and Is It Rational?’, NBER Working Paper No 17651.

Border KC (2020), ‘Alternative Linear Inequalities’, Unpublished manuscript, California Institute of Technology, v 2020.10.15::09.50. Available at <https://healy.econ.ohio-state.edu/kcb/Notes/Alternative.pdf>.

Del Negro M and F Schorfheide (2011), ‘Bayesian Macroeconometrics’, in J Geweke , G Koop and H van Dijk (eds), The Oxford Handbook of Bayesian Econometrics, Oxford Handbooks, Oxford University Press, Oxford, pp 293–389.

Fry R and A Pagan (2011), ‘Sign Restrictions in Structural Vector Autoregressions: A Critical Review’, Journal of Economic Literature, 49(4), pp 938–960.

Gafarov B, M Meier and JL Montiel Olea (2018), ‘Delta-Method Inference for a Class of Set-Identified SVARs’, Journal of Econometrics, 203(2), pp 316–237.

Galí J (2008), Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework, Princeton University Press, Princeton.

Giacomini R and T Kitagawa (2021), ‘Robust Bayesian Inference for Set-Identified Models’, Econometrica, 89(4), pp 1519–1556.

Giacomini R, T Kitagawa and M Read (2021a), ‘Identification and Inference under Narrative Restrictions’, Unpublished manuscript, University College London, 15 February. Available at <https://doi.org/10.48550/arXiv.2102.06456>.

Giacomini R, T Kitagawa and M Read (2021b), ‘Robust Bayesian Analysis for Econometrics’, Centre for Economic Policy Research Discussion Paper DP16488.

Giacomini R, T Kitagawa and M Read (2022a), ‘Narrative Restrictions and Proxies: Rejoinder’, Journal of Business & Economic Statistics, 40(4), pp 1438–1441.

Giacomini R, T Kitagawa and M Read (2022b), ‘Robust Bayesian Inference in Proxy SVARs’, Journal of Econometrics, 228(1), pp 107–126.

Granziera E, HR Moon and F Schorfheide (2018), ‘Inference for VARs Identified with Sign Restrictions’, Quantitative Economics, 9(3), pp 1087–1121.

Hamilton JD (1994), Time Series Analysis, Princeton University Press, Princeton.

Inoue A and L Kilian (2022), ‘The Role of the Prior in Estimating VAR Models with Sign Restrictions’, Unpublished Manuscript, 4 January. Available at <https://drive.google.com/file/d/1HDXiP_b3DTznVhH4bxi8hbo9n1Cs3O2f/view>.

Kilian L (2022), ‘Comment on Giacomini, Kitagawa, and Read's “Narrative Restrictions and Proxies’”, Journal of Business & Economic Statistics, 40(4), pp 1429–1433.

Kilian L and H Lütkepohl (2017), Structural Vector Autoregressive Analysis, Themes in Modern Econometrics, Cambridge University Press, Cambridge.

Kilian L and DP Murphy (2012), ‘Why Agnostic Sign Restrictions Are Not Enough: Understanding the Dynamics of Oil Market VAR Models’, Journal of the European Economic Association, 10(5), pp 1166–1188.

Mangasarian OL (1994), Nonlinear Programming, Classics in Applied Mathematics, 10, corrected republication, Society for Industrial and Applied Mathematics, Philadelphia.

Plagborg-Møller M and CK Wolf (2021), ‘Local Projections and VARs Estimate the Same Impulse Responses’, Econometrica, 89(2), pp 955–980.

Poirier DJ (1998), ‘Revising Beliefs in Nonidentified Models’, Econometric Theory, 14(4), pp 483–509.

Ramey VA (2016), ‘Macroeconomic Shocks and Their Propagation’, in JB Taylor and H Uhlig (eds), Handbook of Macroeconomics: Volume 2A, Handbooks in Economics, Elsevier, Amsterdam, pp 71–162.

Read M (2022), ‘Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions’, The Econometrics Journal, 25(3), pp 699–718.

Romer CD and DH Romer (1989), ‘Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz’, in OJ Blanchard and S Fischer (eds), NBER Macroeconomics Annual 1989, 4, The MIT Press, Cambridge, pp 121–184.

Rothenberg TJ (1971), ‘Identification in Parametric Models’, Econometrica, 39(3), pp 577–591.

Rubio-Ramírez JF, DF Waggoner and T Zha (2010), ‘Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference’, The Review of Economic Studies, 77(2), pp 665–696.

Stock JH and MW Watson (2016), ‘Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics’, in JB Taylor and H Uhlig (eds), Handbook of Macroeconomics: Volume 2A, Handbooks in Economics, Elsevier, Amsterdam, pp 415–525.

Stock JH and MW Watson (2018), ‘Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments’, The Economic Journal, 128(610), pp 917–948.

Uhlig H (2005), ‘What Are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure’, Journal of Monetary Economics, 52(2), pp 381–419.

Volpicella A (2022), ‘SVARs Identification through Bounds on the Forecast Error Variance’, Journal of Business & Economic Statistics, 40(3), pp 1291–1301.