Earnings Risk and Heterogeneous Expected Earnings Profiles

2020 ◽  
Author(s):  
Scott D. Drewianka ◽  
Phillip Oberg
Keyword(s):  
Expected Earnings ◽  
Earnings Risk

Estimating Heterogeneity in Lifetime Earnings Risk

2019 ◽  
Author(s):  
Scott D. Drewianka ◽  
Phillip Oberg
Keyword(s):  
Lifetime Earnings ◽  
Earnings Risk

Dissecting Idiosyncratic Earnings Risk

2020 ◽  
Author(s):  
Elin Halvorsen ◽  
Hans Aasnes Holter ◽  
Serdar Ozkan ◽  
Kjetil Storesletten
Keyword(s):  
Earnings Risk

Expected earnings growth and portfolio performance

2006 ◽  
Vol 26 (4) ◽  
pp. 431-437 ◽  
Author(s):  
Ronald W. Best ◽  
Charles W. Hodges ◽  
James A. Yoder
Keyword(s):  
Portfolio Performance ◽  
Earnings Growth ◽  
Expected Earnings

Choice, Order Statistics and the Distribution of Earnings

1997 ◽  
Author(s):  
Michael Sattinger
Keyword(s):  
Order Statistics ◽  
Order Statistic ◽  
Occupational Choice ◽  
Earnings Inequality ◽  
Limiting Distribution ◽  
Asymptotic Results ◽  
Expected Earnings

This paper analyzes the distribution of earnings as being generated by workers choosing among occupations on the basis of earnings maximization. A worker’s earnings then have characteristics of an order statistic. The extension to multiple occupations leads to the revision results from A.D. Roy’s two-occupation case. An additional occupation raises expected earnings while in general reducing earnings inequality. Asymptotic results from order statistics suggest that the process of occupational choice determines a limiting distribution of earnings independently of underlying distributions of occupational abilities.

scholarly journals Methodological Choices In Detecting Divergent Earnings

2011 ◽  
Vol 16 (3) ◽  
Author(s):  
David T. Doran
Keyword(s):  
Market Price ◽  
Test Statistics ◽  
Font Size ◽  
Methodological Choices ◽  
Random Samples ◽  
Nonparametric Statistical Methods ◽  
Expected Earnings ◽  
The Difference ◽  
Reported Earnings ◽  
Nonparametric Statistical

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="letter-spacing: -0.15pt;"><span style="font-size: x-small;"><span style="font-family: Batang;">This paper empirically tests for methodological superiority in detecting divergent earnings (the difference between actual and expected earnings).<span style="mso-spacerun: yes;">&nbsp; </span>Divergent earnings are generated using Value Line forecasted and reported earnings data.<span style="mso-spacerun: yes;">&nbsp; </span>Two hundred random samples of 100 cases each are drawn.<span style="mso-spacerun: yes;">&nbsp;&nbsp;&nbsp; </span>One hundred independent two sample tests are performed with 0%, 1%, 3%, 5%, 7%, and 10 % positive earnings introduced.<span style="mso-spacerun: yes;">&nbsp; </span>The two sample tests are performed using both parametric (t test), and nonparametric (Mann Whitney test) statistics.<span style="mso-spacerun: yes;">&nbsp; </span>They are performed on the &ldquo;divergent earnings&rdquo; data deflated by: 1) forecasted earnings , and 2) the market price of the stock.<span style="mso-spacerun: yes;">&nbsp; </span>The results indicate that the superior alternative is nonparametric statistical methods based upon ranks, and the deflator choice under these nonparametric methods is of little consequence.</span></span></span></p>

Daily Labor Supply and Adaptive Reference Points

2021 ◽  
Vol 111 (8) ◽  
pp. 2417-2443
Author(s):  
Neil Thakral ◽  
Linh T. Tô
Keyword(s):  
Labor Supply ◽  
Reference Point ◽  
Structural Model ◽  
Reference Points ◽  
Degree Of Freedom ◽  
Reference Dependence ◽  
Field Evidence ◽  
Dynamic View ◽  
Expected Earnings ◽  
Dependence Models

This paper provides field evidence on how reference points adjust, a degree of freedom in reference-dependence models. Examining this in the context of cabdrivers’ daily labor-supply behavior, we ask how the within-day timing of earnings affects decisions. Drivers work less in response to higher accumulated income, with a strong effect for recent earnings that gradually diminishes for earlier earnings. We estimate a structural model in which drivers work toward a reference point that adjusts to deviations from expected earnings with a lag. This dynamic view of reference dependence reconciles conflicting “neoclassical” and “behavioral” interpretations of evidence on daily labor-supply decisions. (JEL J22, J31, L94)

scholarly journals Modeling life-cycle earnings risk with positive and negative shocks

2020 ◽  
Vol 37 ◽  
pp. 103-126 ◽  
Author(s):  
Manuel Sanchez ◽  
Felix Wellschmied
Keyword(s):  
Life Cycle ◽  
Earnings Risk

Earnings, Expected Earnings, and Unemployment Amongst School Leavers

1987 ◽  
pp. 145-184 ◽  
Author(s):  
Brian G. M. Main
Keyword(s):  
Expected Earnings

scholarly journals What Do Data on Millions of U.S. Workers Reveal About Life-Cycle Earnings Risk?

2015 ◽  
Author(s):  
Fatih Guvenen ◽  
Fatih Karahan ◽  
Serdar Ozkan ◽  
Jae Song
Keyword(s):  
Life Cycle ◽  
Earnings Risk
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