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Executive Job Matching: Estimates fr...

Huang, Ruoyan.

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Executive Job Matching: Estimates from a Dynamic Model.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Executive Job Matching: Estimates from a Dynamic Model./
Author:	Huang, Ruoyan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
Description:	93 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-03(E), Section: A.
Contained By:	Dissertation Abstracts International78-03A(E).
Subject:	Finance. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10157788
ISBN:	9781369128055

Executive Job Matching: Estimates from a Dynamic Model.
Huang, Ruoyan.

Executive Job Matching: Estimates from a Dynamic Model. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 93 p.

Source: Dissertation Abstracts International, Volume: 78-03(E), Section: A.

Thesis (Ph.D.)--University of Rochester, 2016.

I evaluate how firms' and CEOs' learning about their fit with one another affects CEO turnover and compensation decisions. Building and estimating a dynamic model of the executive labor market, I find that learning and selection eliminate low-quality matches and provide explanatory power for the excess skewness of CEO compensation in the data after controlling for firm and CEO characteristics. I further establish that learning generates a hump-shaped hazard rate curve of CEO turnover conditional on CEO tenure. Using a hand-collected dataset of CEO turnover, I discover that the speed and precision of learning determine the level and length of the "discovery phase" of the conditional hazard rate curve. I also find that CEO compensation demonstrates a firm's evaluation of the match quality and is predictive of the expected future tenure of its CEO. In short, I show the importance of learning and selection in explaining the relations between CEO compensation, CEO turnover, and firm performance.

ISBN: 9781369128055Subjects--Topical Terms:

542899
Finance.

Executive Job Matching: Estimates from a Dynamic Model.
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245 1 0 $a Executive Job Matching: Estimates from a Dynamic Model.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 93 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-03(E), Section: A.
500 $a Advisers: Ron Kaniel; Toni M. Whited.
502 $a Thesis (Ph.D.)--University of Rochester, 2016.
520 $a I evaluate how firms' and CEOs' learning about their fit with one another affects CEO turnover and compensation decisions. Building and estimating a dynamic model of the executive labor market, I find that learning and selection eliminate low-quality matches and provide explanatory power for the excess skewness of CEO compensation in the data after controlling for firm and CEO characteristics. I further establish that learning generates a hump-shaped hazard rate curve of CEO turnover conditional on CEO tenure. Using a hand-collected dataset of CEO turnover, I discover that the speed and precision of learning determine the level and length of the "discovery phase" of the conditional hazard rate curve. I also find that CEO compensation demonstrates a firm's evaluation of the match quality and is predictive of the expected future tenure of its CEO. In short, I show the importance of learning and selection in explaining the relations between CEO compensation, CEO turnover, and firm performance.
590 $a School code: 0188.
650 4 $a Finance. $3 542899
650 4 $a Labor economics. $3 642730
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690 $a 0510
710 2 $a University of Rochester. $b Business Administration. $3 2099800
773 0 $t Dissertation Abstracts International $g 78-03A(E).
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10157788