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020 ▼a 9780438153547
035 ▼a (MiAaPQ)AAI10752454
035 ▼a (MiAaPQ)uiowa:15709
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 330
1001 ▼a Cundy, Lance Deloyce.
24510 ▼a Essays on the Elasticity of Intertemporal Substitution.
260 ▼a [S.l.] : ▼b The University of Iowa., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 83 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: A.
500 ▼a Adviser: Antonio Galvao.
5021 ▼a Thesis (Ph.D.)--The University of Iowa, 2018.
520 ▼a This dissertation estimates the elasticity of intertemporal substitution (EIS) of consumption using the Nielsen Consumer Panel. The Nielsen Consumer Panel is built from transactional data that follows households in the United States and their grocery purchases from 2004 to 2014. Because of the transactional nature of the dataset, there is a low source of measurement error in consumption, and aggregation bias can be minimized. Due to changes in the economy during this timeframe, the data is examined for structural breaks. The data suggests evidence for two structural changes in the U.S. economy leading to three regimes. The first regime, 2004 to 2006, was a period of economic expansion, while the second regime, 2007 and 2008, was a period of recession. Lastly, during the third regime, 2009 to 2014, the economy exhibited quantitative easing.
520 ▼a Chapter 1 introduces the EIS and provides an overview of the literature. In Chapter 2, the EIS is estimated for each regime using expected utility with linearized Epstein-Zin preferences and by the use of fixed effects and instrumental variables. In order to estimate the EIS, consumption is aggregated weekly, and consumption growth is measured over a four-week time period in order to match four-week Treasury bills. This study adds to the literature by examining individual EIS during different periods of economic activity. With a more complete dataset that has less measurement error and aggregation bias than the existing literature, this study gives evidence of a small and negative EIS during a period of expansion, a small and positive EIS during a period of recession, and a large and positive EIS during quantitative easing.
520 ▼a Lastly, Chapter 3 extends Chapter 2 by assuming quantile utility preferences instead of the expected utility framework. The quantile EIS is estimated by the use of a smooth instrumental variables method of moments estimator. Estimates give evidence of heterogeneity of the EIS in the periods of expansion and quantitative easing. These quantile results can be used to inform the theory behind the EIS and quantile models of rational behavior.
590 ▼a School code: 0096.
650 4 ▼a Economics.
690 ▼a 0501
71020 ▼a The University of Iowa. ▼b Economics.
7730 ▼t Dissertation Abstracts International ▼g 79-12A(E).
773 ▼t Dissertation Abstract International
790 ▼a 0096
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15013666 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자