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On the implications of unobserved technology and preference shifts for aggregate labor demand and supply [Elektronische Ressource] / vorgelegt von Almut Balleer

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163 pages
On the Implications of Unobserved Technology andPreference Shifts for Aggregate Labor Demand and SupplyInaugural-Dissertationzur Erlangung des Grades eines Doktorsder Wirtschafts- und Gesellschaftswissenschaftendurch dieRechts- und Staatswissenschaftliche Fakult˜atder Rheinischen Friedrich-Wilhelms-Universit˜atBonnvorgelegt vonAlmut Balleeraus G˜ottingenBonn 2009Dekan: Prof. Dr. Christian HillgruberErstreferent: Prof. Monika Merz, PhDZweitreferent: Prof. Dr. J˜org BreitungTag der mundlic˜ hen Prufung:˜ 28.07.2009Diese Dissertation ist auf dem Hochschulschriftenserver der ULB Bonn(http://hss.ulb.uni-bonn.de/diss online) elektronisch publiziert.to my parents4AcknowledgmentsI owe much gratitude to my supervisor Monika Merz for her guidance throughout thedissertation, her fruitful advice during many discussions and her extensive and valuablesupport on the job market. I would also like to thank Thijs van Rens for many usefulcomments and our pleasant and instructive cooperation. His continuous support duringthe dissertation and the job market cannot be taken for granted.I have greatly benefltted from productive comments in- and outside the seminars at theUniversityofBonnandtheUniversitatPompeuFabrainBarcelona. Inparticular,Iwouldlike to thank J˜org Breitung in Bonn as well as Jordi Gal¶‡ and Fabio Canova in Barcelonafor helpful suggestions and constructive comments.
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On the Implications of Unobserved Technology and
Preference Shifts for Aggregate Labor Demand and Supply
Inaugural-Dissertation
zur Erlangung des Grades eines Doktors
der Wirtschafts- und Gesellschaftswissenschaften
durch die
Rechts- und Staatswissenschaftliche Fakult˜at
der Rheinischen Friedrich-Wilhelms-Universit˜at
Bonn
vorgelegt von
Almut Balleer
aus G˜ottingen
Bonn 2009Dekan: Prof. Dr. Christian Hillgruber
Erstreferent: Prof. Monika Merz, PhD
Zweitreferent: Prof. Dr. J˜org Breitung
Tag der mundlic˜ hen Prufung:˜ 28.07.2009
Diese Dissertation ist auf dem Hochschulschriftenserver der ULB Bonn
(http://hss.ulb.uni-bonn.de/diss online) elektronisch publiziert.to my parents4Acknowledgments
I owe much gratitude to my supervisor Monika Merz for her guidance throughout the
dissertation, her fruitful advice during many discussions and her extensive and valuable
support on the job market. I would also like to thank Thijs van Rens for many useful
comments and our pleasant and instructive cooperation. His continuous support during
the dissertation and the job market cannot be taken for granted.
I have greatly benefltted from productive comments in- and outside the seminars at the
UniversityofBonnandtheUniversitatPompeuFabrainBarcelona. Inparticular,Iwould
like to thank J˜org Breitung in Bonn as well as Jordi Gal¶‡ and Fabio Canova in Barcelona
for helpful suggestions and constructive comments. Many thanks also to Jarkko Turunen
for the support during my time at the European Central Bank and our joint project. I
greatly enjoyed both the academic and recreational interaction with my fellow graduate
students. In particular, I would like to thank Michael Evers for interesting and fruitful
discussions, his continuous help and a lot of fun. Special thanks also go to Zeno Enders,
Andrea Felfe, Katharina Greulich, Stefan Niemann and Markus Poschke.
Financial support from the Bonn Graduate School of Economics, J˜org Breitung and the
MarieCurieFellowshipattheUniversitatPompeuFabraisgratefullyacknowledged. Many
thanks go also to Urs Schweizer and Jurgen˜ von Hagen for managing the Bonn Graduate
School of Economics.
Last but not least, I am deeply indebted to Malte, my friends and my family for their pa-
tience,theirunconditionalemotionalsupportandencouragementaswellastheirenduring
belief in me.Contents
Introduction 1
1 On the Implications of Technology and Non-Technology Shocks for Ag-
gregate Labor Demand 9
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2 A standard labor market model . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.2.1 The model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.2.2 Empirical performance based on neutral shocks . . . . . . . . . . . . 15
1.3 Moments conditional on technology shocks . . . . . . . . . . . . . . . . . . . 17
1.3.1 Identiflcation and estimation . . . . . . . . . . . . . . . . . . . . . . 17
1.3.2 The Shimer puzzle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.3.3 The \job flnding puzzle" . . . . . . . . . . . . . . . . . . . . . . . . . 22
1.3.4 Are the estimated shocks really technology shocks? . . . . . . . . . . 26
1.4 Difierent shocks: Fisher identiflcation . . . . . . . . . . . . . . . . . . . . . 27
1.4.1 Identiflcation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
1.4.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
1.4.3 Robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
1.5 Alternative variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
1.5.1 Alternative worker ows . . . . . . . . . . . . . . . . . . . . . . . . . 33
1.5.2 Job ows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
i1.6 Alternative identiflcation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
1.6.1 Motivation and identiflcation . . . . . . . . . . . . . . . . . . . . . . 37
1.6.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
1.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Appendix to Chapter 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2 On the Implications of Skill-Biased Technological Progress for the Busi-
ness Cycle 53
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
2.2 Empirical approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
2.2.1 Shocks to the production technology . . . . . . . . . . . . . . . . . . 57
2.2.2 Identiflcation and estimation . . . . . . . . . . . . . . . . . . . . . . 59
2.2.3 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
2.3 Skill-biased technology shocks . . . . . . . . . . . . . . . . . . . . . . . . . . 65
2.3.1 Skill bias in ‘neutral’ technology shocks . . . . . . . . . . . . . . . . 65
2.3.2 Shocks to the supply of skill . . . . . . . . . . . . . . . . . . . . . . . 67
2.3.3 Identifled skill-biased technology shocks . . . . . . . . . . . . . . . . 69
2.3.4 Robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
2.4 Investment-speciflc shocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
2.4.1 Skill bias in investment-speciflc shocks . . . . . . . . . . . . . . . . . 75
2.4.2 Contribution to business cycle uctuations . . . . . . . . . . . . . . 78
2.4.3 Capital-skill complementarity . . . . . . . . . . . . . . . . . . . . . . 80
2.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
Appendix to Chapter 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
3 On the Implications of Unobserved Age and Cohort Efiects for Aggre-
gate Labor Supply 93
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
ii3.2 Data and methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
3.3 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
3.3.1 Basic model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
3.3.2 Model with observed determinants . . . . . . . . . . . . . . . . . . . 107
3.3.3 Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Appendix to Chapter 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Conclusion 131
Appendix 135
A Identiflcation and estimation in Chapters 1 and 2 137
A.1 Standard long-run identiflcation . . . . . . . . . . . . . . . . . . . . . . . . . 137
A.2 Estimation of the BVAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
A.3 Restricted Fisher identiflcation . . . . . . . . . . . . . . . . . . . . . . . . . 139
A.4 Alternative identiflcation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
A.5 VAR identiflcation with short- and long-run restrictions . . . . . . . . . . . 141
iiiivList of Figures
1.1 Impulse-responses to Gal¶‡ technology shocks . . . . . . . . . . . . . . . . . . 24
1.2onses to BFK technology shocks . . . . . . . . . . . . . . . . . 26
1.3 Impulse-responses to Fisher technology shocks. . . . . . . . . . . . . . . . . 30
1.4 Shimer versus Fujita-Ramey . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
1.5 Productivity shocks from sign restrictions . . . . . . . . . . . . . . . . . . . 41
1.6 Restricted and unrestricted Fisher identiflcation. . . . . . . . . . . . . . . . 49
1.7 Job ow responses to Fisher technology shocks . . . . . . . . . . . . . . . . 50
1.8 Gal¶‡ identiflcation - price and productivity . . . . . . . . . . . . . . . . . . . 50
1.9 Unrestricted Fisher technology shocks . . . . . . . . . . . . . . . . . . . . . 51
1.10 Sign identiflcation - price and productivity . . . . . . . . . . . . . . . . . . . 51
1.11 Fisher technology shocks - no trend . . . . . . . . . . . . . . . . . . . . . . . 52
2.1 Skill premium and Mincer return to schooling in the US . . . . . . . . . . . 62
2.2 Relative employment and relative supply of skill in the US . . . . . . . . . . 62
2.3 Gal¶‡ identiflcation with skill premium . . . . . . . . . . . . . . . . . . . . . 65
2.4 SBT identiflcation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
2.5 Impulse-responses to Solow residual . . . . . . . . . . . . . . . . . . . . . . 73
2.6 Fisher identiflcation with skill supply shocks . . . . . . . . . . . . . . . . . . 76
2.7 Capital-skill substitutability . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
2.8 Gal¶‡ identiflcation - additional variables . . . . . . . . . . . . . . . . . . . . 87
v