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The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks

Rosen Chowdhury Orcid Logo, Bill Russell

Scottish Journal of Political Economy, Volume: 65, Issue: 3, Pages: 271 - 292

Swansea University Author: Rosen Chowdhury Orcid Logo

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DOI (Published version): 10.1111/sjpe.12142

Abstract

The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show th...

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Published in: Scottish Journal of Political Economy
ISSN: 00369292
Published: 2018
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URI: https://cronfa.swan.ac.uk/Record/cronfa35145
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first_indexed 2017-09-06T18:57:32Z
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spelling 2020-06-22T13:11:47.1424792 v2 35145 2017-09-06 The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks 6f0a211cd0023a2a351371189c33ae4b 0000-0003-1796-9603 Rosen Chowdhury Rosen Chowdhury true false 2017-09-06 ECON The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range auto-regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data. Journal Article Scottish Journal of Political Economy 65 3 271 292 00369292 Dynamic panel estimators, mean shifts/structural breaks, bank lending channel 31 7 2018 2018-07-31 10.1111/sjpe.12142 COLLEGE NANME Economics COLLEGE CODE ECON Swansea University 2020-06-22T13:11:47.1424792 2017-09-06T16:17:46.4348495 Faculty of Humanities and Social Sciences School of Management - Economics Rosen Chowdhury 0000-0003-1796-9603 1 Bill Russell 2 0035145-06092017162009.pdf Paper3.pdf 2017-09-06T16:20:09.3630000 Output 1021358 application/pdf Accepted Manuscript true 2019-10-10T00:00:00.0000000 true eng
title The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
spellingShingle The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
Rosen Chowdhury
title_short The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
title_full The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
title_fullStr The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
title_full_unstemmed The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
title_sort The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks
author_id_str_mv 6f0a211cd0023a2a351371189c33ae4b
author_id_fullname_str_mv 6f0a211cd0023a2a351371189c33ae4b_***_Rosen Chowdhury
author Rosen Chowdhury
author2 Rosen Chowdhury
Bill Russell
format Journal article
container_title Scottish Journal of Political Economy
container_volume 65
container_issue 3
container_start_page 271
publishDate 2018
institution Swansea University
issn 00369292
doi_str_mv 10.1111/sjpe.12142
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Economics{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Economics
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description The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range auto-regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data.
published_date 2018-07-31T03:43:38Z
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score 11.035349