Modeling Income in the Near Term 5

Smith, Karen E.; Favreault, Melissa M.; Ratcliffe, Caroline; Butrica, Barbara A.; Toder, Eric; Bakija, Jon

doi:10.2139/ssrn.2206397

Cited by 32 publications

(33 citation statements)

References 9 publications

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“…Our work can be extended by introducing more structural and behavioural elements using a life-cycle framework along several dimensions: consumption-saving choice under uncertainty, portfolio choice, borrowing for housing and durable consumption goods, saving for retirement, and more detailed modeling of income and social benefits (see e.g., Rehder Harris et al (2005) and Smith et al (2010)). A u s t r i a B e l g i u m C y p r u s F i n l a n d F r a n c e G e r m a n y G r e e c e I t a l y L u x e m b o u r g M a l t a N e t h e r l a n d s P o r t u g a l S l o v a k i a S l o v e n i a S p a i n…”

Section: Discussionmentioning

confidence: 99%

Household heterogeneity in the euro area since the onset of the Great Recession

Ampudia

Pavlickova

Slacalek

et al. 2016

Journal of Policy Modeling

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The HFCN collects household-level data on households' fi nances and consumption in the euro area through a harmonised survey. The HFCN aims at studying in depth the micro-level structural information on euro area households' assets and liabilities. The objectives of the network are: Terms of use: Documents in1) understanding economic behaviour of individual households, developments in aggregate variables and the interactions between the two;2) evaluating the impact of shocks, policies and institutional changes on household portfolios and other variables;3) understanding the implications of heterogeneity for aggregate variables; 4) estimating choices of different households and their reaction to economic shocks; 5) building and calibrating realistic economic models incorporating heterogeneous agents; 6) gaining insights into issues such as monetary policy transmission and fi nancial stability.The refereeing process of this paper has been co-ordinated by a team composed of Gabriel Fagan (ECB), Pirmin Fessler (Oesterreichische Nationalbank), Michalis Haliassos (Goethe University Frankfurt), Tullio Jappelli (University of Naples Federico II), Sébastien PérezDuarte (ECB), Jiri Slacalek (ECB), Federica Teppa (De Nederlandsche Bank), Peter Tufano (Oxford University) and Philip Vermeulen (ECB).The paper is released in order to make the results of HFCN research generally available, in preliminary form, to encourage comments and suggestions prior to fi nal publication. The views expressed in the paper are the author's own and do not necessarily refl ect those of the ESCB. AcknowledgementsThis paper uses data from the Eurosystem Household Finance and Consumption Survey. We thank John Sabelhaus and seminar participants at the ECB and the Eurosystem Household Finance and Consumption Network for useful comments. The views presented in this paper are those of the authors, and do not necessarily refl ect those of the European Central Bank. Miguel AmpudiaEuropean Central Bank; e-mail: miguel.ampudia@ecb.europa.eu Akmaral PavlickovaEuropean Central Bank; e-mail: akmaral.pavlickova@ecb.europa.eu Jiri SlacalekEuropean Central Bank; e-mail: jiri.slacalek@ecb.europa.eu Edgar VogelEuropean Central Bank; e-mail: edgar.vogel@ecb.europa.eu AbstractWe extend household-level data from the Household Finance and Consumption Survey using aggregate series and micro-simulations to investigate heterogeneity in the euro area. We quantify shocks to wealth, income and financial pressure face...

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Section: Discussionmentioning

confidence: 99%

Household heterogeneity in the euro area since the onset of the Great Recession

Ampudia

Pavlickova

Slacalek

et al. 2016

Journal of Policy Modeling

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“…We estimate transition probabilities between these states as a function of age, marital status, and gender using reported coefficient estimates from the Urban Institute's Model of Income in the Near To model transitions across all demographic states, we need information on the probabilities of divorce, marriage, and mortality. The MINT5 report (Smith et al, 2007) presents estimates of continuous-time hazard models for separate divorce and marriage equations for men and women. The MINT5 report also calibrates the original MINT's mortality hazard estimates to match the Social Security Office of the Actuary projections.…”

Section: Mortality Marriage and Divorcementioning

confidence: 99%

The Effect of Marital Status and Children on Savings and Portfolio Choice

Love

2008

SSRN Journal

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This paper investigates the impact of demographic shocks on optimal decisions about saving, life insurance, and, most centrally, asset allocation. We analyze these choices within the framework of a life-cycle model that features exogenous changes in family composition, heterogeneity in lifetime income, and uninsurable fluctuations in earnings and medical costs. Our analysis indicates that marital-status transitions and children can have important effects on optimal household decisions. Widowhood induces sharp reductions in the portfolio shares in stock, and the impact is largest for women and individuals with children. Divorce causes men and women to reallocate their portfolios in different directions; men choose much riskier allocations, while women opt for safer ones. Children play a fundamental role in the optimal portfolio decisions. Men with children, for example, increase their shares in response to divorce by less than half as much as men without children. Comparing our simulation results with panel-data evidence on stockholding from the PSID and the HRS, we conclude that changes in marital status and children matter empirically as well, but not always in the ways that the model predicts.JEL classification: G11; G22; D91; E21; I10; J12 Keywords: Portfolio choice; mortality risk; marital status; precautionary saving; bequests; risk and uncertainty. * Dept. of Economics, Williams College, Williamstown, MA 01267, david.love@williams.edu. I am grateful to Chris Carroll, Michael Palumbo, Maria Perozek, Lucie Schmidt, and two anonymous referees.

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“…6 For descriptions of versions 5 and 6 of MINT, see Smith et al (2007Smith et al ( , 2010. 7 To ensure that our cohort estimates are representative, and to minimize survival bias, we use two versions of the MINT model -MINT 5 and MINT 6.…”

Section: Replacement Rate Calculationsmentioning

confidence: 99%

“…Part of the reason is that MINT's OASI-claiming model does not explicitly build in the rising FRA or cohort effects as covariates in estimation and then projection. See page IV-10, table 4-4 in Smith et al (2010) for detailed description of model specification and list of independent variables. However, MINT 6 partially accounts for the higher FRA, by estimating and simulating two separate models depending on whether the individual is subject to the Retirement Earnings Test (RET), which in 2000 was suspended after reaching FRA.…”

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confidence: 99%

How Do the Changing Labor Supply Behavior and Marriage Patterns of Women Affect Social Security Replacement Rates?

Karamcheva

Munnell

et al. 2013

SSRN Journal

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for their thoughtful comments and suggestions.© 2013, April Yanyuan Wu, Nadia S. Karamcheva, Alicia H. Munnell, and Patrick Purcell. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. About the Center for Retirement ResearchThe Center for Retirement Research at Boston College, part of a consortium that includes parallel centers at the University of Michigan and the National Bureau of Economic Research, was established in 1998 through a grant from the Social Security Administration. The Center's mission is to produce first-class research and forge a strong link between the academic community and decision-makers in the public and private sectors around an issue of critical importance to the nation's future. To achieve this mission, the Center sponsors a wide variety of research projects, transmits new findings to a broad audience, trains new scholars, and broadens access to valuable data sources. the Near Term, show that Social Security replacement rates have dropped sharply at both the household-and individual-level, and the decline will continue for future retirees. Our second finding is that this aggregate change masks a complex relationship between replacement rates and the marital status and income levels of individuals. The decline in replacement rates over time is largest for married couples with husbands whose earnings are in the top tercile.Decomposing the reasons for the overall decline shows that increases in the labor supply and earnings of women explain more than one-third of the change. In contrast, the impact of changing marital patterns is relatively small. Much of the remaining explanation rests with the increased Full Retirement Age and changing claiming behaviors.

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Modeling Income in the Near Term 5

Cited by 32 publications

References 9 publications

Household heterogeneity in the euro area since the onset of the Great Recession

Household heterogeneity in the euro area since the onset of the Great Recession

The Effect of Marital Status and Children on Savings and Portfolio Choice

How Do the Changing Labor Supply Behavior and Marriage Patterns of Women Affect Social Security Replacement Rates?

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