Imputation of the 2002 Wave of the Spanish Survey of Household Finances (EFF)

Barceló, Cristina

doi:10.2139/ssrn.901584

Cited by 63 publications

(25 citation statements)

References 21 publications

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“…5 This class of assets commonly imposes restrictions on the investment horizon or the availability of funds to make payments. Moreover, this class encompasses a wide variety of investment products with varying characteristics.…”

Section: Modelmentioning

confidence: 99%

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Portfolio choice with indivisible and illiquid housing assets: the case of Spain

Mayordomo¹,

Rodríguez‐Moreno²,

Peña³

2013

Quantitative Finance

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This paper presents a procedure for computing the theoretically optimal portfolio under the assumption that housing is an indivisible, illiquid asset that restricts the portfolio choice decision. The analysis also includes the financial constraints households may face when they apply for external funding. The set of financial assets that constitute the household's portfolios are bank time deposits, stocks, mortgage, and housing. We compare the theoretically optimal portfolio against Spanish households' actual choices using a unique data set, the Spanish Survey of Household Finance. In comparison with the optimal portfolio, households significantly underinvest in stocks and deposits. In the case of mortgages, the optimal and actual portfolios weights are not unequal. At a more disaggregated level, some additional differences emerge that are explained by demographic, educational, and income characteristics. This paper presents a procedure for computing the theoretically optimal portfolio under the assumption that housing is an indivisible, illiquid asset that restricts the portfolio choice decision. The analysis also includes the …nancial constraints households may face when they apply for external funding. The set of …nancial assets that constitute the household's portfolios are bank time deposits, stocks, mortgage, and housing. We compare the theoretically optimal portfolio against Spanish households' actual choices using a unique data set, the Spanish Survey of Household Finance. In comparison with the optimal portfolio, households signi…-cantly underinvest in stocks and deposits. In the case of mortgages, the optimal and actual portfolios weights are not unequal. At a more disaggregated level, some additional di¤erences emerge that are explained by demographic, educational, and income characteristics. Sergio MayordomoJEL classi…cation: C61, D14, G11

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Section: Modelmentioning

confidence: 99%

“…5 to include housing-related …nancial liabilities (i.e., mortgages) in their models of households' portfolio decisions. One way to take housing investments into account is di¤erentiating liquid from illiquid assets, as do Koren and Szeidl (2002), Schwartz and Tebaldi (2006) and Anglin and Gao (2011).…”

Section: Introductionmentioning

confidence: 99%

Portfolio choice with indivisible and illiquid housing assets: the case of Spain

Mayordomo¹,

Rodríguez‐Moreno²,

Peña³

2013

Quantitative Finance

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“…been implemented in the Spanish Survey of Household Finances (EFF) (Barceló, 2006;Bover, 2004) and the German SAVE survey (Schunk, 2007(Schunk, , 2008. …”

Section: Why Multiple Imputation?mentioning

confidence: 99%

“…In the case of saving, the first questions ask whether a household saves at all, has a saving goal or not, or whether the household saves for precautionary reasons and so on. 12 The same procedure was implemented in the EFF (Barceló, 2006) and the SCF (Kennickell, 1998). 13 It is very important that the imputation model does not impose restrictions on parameters (e.g.…”

Section: Initial Implementation Of Ownership and Amount Imputationsmentioning

confidence: 99%

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Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey

Ziegelmeyer

2012

AStA Adv Stat Anal

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Questions about monetary variables (such as income, wealth or savings) Key words: Imputation methods, Monte-Carlo simulation, imputation evaluation, itemnonresponse, missing data, imputation, retransformation, sample surveys, SAVE JEL classification: C01, C81, C49 1 I would like to thank Michela Coppola (MEA) for very helpful support, as well as Axel Börsch-Supan (MEA), Daniel Schunk (Johannes Gutenberg University Mainz), Armin Rick (University of Chicago), Mathias Sommer, Hendrik Jürges (Universität Wuppertal), Uli Schlieper (MEA), Cornelius Schmidt (Université de Lausanne) for their helpful comments. Alexander Aldinger, Helen Grupp, Dörte Heger, Corinna Kartzke, Julius Nick, Michael Schardt, Stefanie Schulz, and Marius Wolter provided excellent research assistance. I am grateful to the seminar participants at MEA for many useful comments. MEA is a research institute which is funded by two thirds through public third-party means for which I am very grateful. Furthermore, I would like to thank the state of Baden-Württemberg and the German Insurance Association for financing the basic funding of MEA. I am particularly grateful to the German Research Foundation (Deutsche Forschungsgemeinschaft) for financing the SAVE survey.

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