Measuring the Effects of a Shock to Monetary Policy - Humboldt ...

More documents

Recommendations

Info

Abstract In this thesis I try to measure the dynamic effects of a shock to monetary policy in a Bayesian FAVAR framework. The innovation is to combine the Bayesian FAVAR with the agnostic identification introduced by Uhlig [2005] which has not been done yet. This identification scheme provides reasonable results and furthermore the possibility to im- pose a broader set of sign restriction on variables, proposed by Uhlig that are consistent with the conventional wisdom. Due to the greater information set it is possible to set the sign restrictions on several prices, monetary aggregates and short term interest rates considered in the dataset. In this vein one can narrow down the space of reasonable impulse responses in order to disentangle precisely the quantitative effects induced by contractionary monetary policy. Although the agnostic identification is a ”weaker” one with respect to the structure and restrictions imposed, this identification scheme com- bined with Markov chain Monte Carlo simulation methods delivers results that appear to be reasonable for a broad set of variables and with a higher accuracy than the alternative results provided by Bernanke, Boivin and Eliasz [2005]. Combining the two methodologies hold the enticing promise to measure the effects of a shock to monetary policy very pre- cisly when applying it to large panels of data. From the results one can conclude that the identification scheme is crucial for a succesful identification especially when the dataset considered is large. However with increasingly restrictions the results are delivered increasingly infrequent. Additionally I provide a Matlab code for the estimation procedure. Acknowledgements I would like to thank Harald Uhlig for excellent guidance and also Albrecht Ritschl and Bartosz Maćkowiak for supportive discussions. The material provided by Piotr Eliasz is thankfully acknowledged. I cordially thank Samad Sarferaz for proofreading this thesis and for helpful discussions. But of most I am indebted to Alborz Radmanesch to who I am sincerely greatful for invaluable support.
2 Bayesian FAVARs with Agnostic Identification Contents 1 Introduction 4 2 Literature 7 3 Dynamic Factor Models 11 4 The Econometric Framework 16 4.1 FAVARs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4.2 FAVAR Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.3 Estimation Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.3.1 Generalized Dynamic Factor Model . . . . . . . . . . . . . . . . . . 21 4.3.2 Two-Step Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3.3 Likelihood-Based Estimation . . . . . . . . . . . . . . . . . . . . . . 23 4.3.4 Markov Chain Monte Carlo . . . . . . . . . . . . . . . . . . . . . . 23 4.3.5 The Gibbs Sampler . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 5 The Econometric Model 25 5.1 The Bayesian Approach versus the Frequentists Approach . . . . . . . . . 25 5.2 State-Space Representation . . . . . . . . . . . . . . . . . . . . . . . . . . 26 5.3 Inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6 Structural FAVARs 33 6.1 Identification of Shocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.2 Identification Schemes in SVARs . . . . . . . . . . . . . . . . . . . . . . . . 34 6.3 Identification in DFMs and FAVARs . . . . . . . . . . . . . . . . . . . . . 34 7 Empirical Results 38 8 Discussion 49 9 Summary and Concluding Remarks 51
Page 1: Measuring the Effects of a Shock to
Page 5 and 6: 4 Bayesian FAVARs with Agnostic Ide
Page 11 and 12: 10 Bayesian FAVARs with Agnostic Id
Page 53 and 54:
52 Bayesian FAVARs with Agnostic Id
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
100 Bayesian FAVARs with Agnostic I
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
show all

Measuring the Effects of a Shock to Monetary Policy - Humboldt ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?