Asking Households About Expenditures: What Have We Learned?

Crossley, Thomas F.; Winter, Joachim

doi:10.3386/w19543

Cited by 20 publications

(14 citation statements)

References 68 publications

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“…Specifically, when a variable with errors is used as the dependent variable in a regression model, the errors will cause an estimation bias, when the errors are correlated with independent variables or involve a mean-reverting pattern (Gibson andKim, 2007, 2010). This study adds evidence to the literature on consumption recall errors that has started to gain more attention (Battistin, Miniaci and Weber (2003), Ahmed, Brzozowski and Crossley (2006), Attanasio, Battistin, and Ichimura (2007), Attanasio and Pistaferri (2016), and Crossley and Winter (2015) for data from developed countries). In the context of developing countries, notable studies include Chesher and Schluter (2002), Gibson (2002), Gibson andKim (2007, 2010), Brozozowski, Crossley, and Winter (2017), and Conforti, Grünberger and Troubat (2017).…”

supporting

confidence: 67%

Short and Long Recall Errors in Retrospective Household Surveys: Evidence from a Developing Country

Sawada

Nakata

Tanaka

2018

The Journal of Development Studies

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While recall errors in retrospective data from household surveys may generate estimation biases, the nature and the relative magnitude of the errors are still largely unknown, especially in the context of developing countries. To bridge this gap in the existing studies, we conduct a resurvey of respondents of the Vietnam Household Living Standards Survey (VHLSS) 2006. The combined data set allows us to investigate a variety of short-term and long-term errors associated with recall surveys. First, our empirical results suggest that when we ask total expenditure rather than categorized expenditures, long recall errors are no worse than short recall errors. Second, we found mean-reversion only for long recall errors in the sum of categorized expenditures but not necessarily for total expenditure. Finally, the inclusion of household size, asset, income, and geographical dummy variables in regression analyses may mitigate the biases arising from measurement errors.

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confidence: 67%

Short and Long Recall Errors in Retrospective Household Surveys: Evidence from a Developing Country

Sawada

Nakata

Tanaka

2018

The Journal of Development Studies

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“…However, obtaining reliable estimates of saving or consumption using survey methods is generally difficult (e.g., Crossley and Winter, 2012), and measurement problems are even more severe in the context of this study where survey time is very limited.…”

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confidence: 99%

Teaching teenagers in finance: Does it work?

Lührmann

Serra-García

Winter³

2015

Journal of Banking & Finance

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127

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Many initiatives worldwide aim at improving financial literacy through targeted education programs, yet there is little evidence regarding their effectiveness. We examine the impact of a short financial education program on teenagers in German high schools.Our findings reveal that the training program significantly increases teenagers' interest in financial matters and their financial knowledge, especially their ability to properly assess the riskiness of assets. Behaviorally, we observe a decrease in the prevalence of self-reported impulse purchases, but at the same time find no evidence of a significant increase in savings. Our data reveals strong gender differences already before adulthood: Girls show less interest in, and self-assessed knowledge of, financial matters, and are less likely to save.

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“…The International Comparison Program (ICP) is an international effort to address this issue (World Bank, 2015). See also Crossley and Winter (2015) and the 2015 special issue of the Journal of Development Studies for further discussion on survey comparability issues.…”

Section: Introductionmentioning

confidence: 99%

Data Gaps, Data Incomparability, and Data Imputation: A Review of Poverty Measurement Methods for Data-Scarce Environments

Dang¹,

Jolliffe²,

Carletto³

2017

Policy Research Working Papers

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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. Terms of use: Documents in EconStor may AbstractWe offer a review of methods that have been employed to provide poverty estimates of poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross sectional household surveys, to missing panel household data. We focus on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. We present the various existing methods under a common framework, with pedagogical discussion on the intuition. Empirical illustrations are provided using several rounds of household survey data from Vietnam. Furthermore, we also offer a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.

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Asking Households About Expenditures: What Have We Learned?

Cited by 20 publications

References 68 publications

Short and Long Recall Errors in Retrospective Household Surveys: Evidence from a Developing Country

Short and Long Recall Errors in Retrospective Household Surveys: Evidence from a Developing Country

Teaching teenagers in finance: Does it work?

Data Gaps, Data Incomparability, and Data Imputation: A Review of Poverty Measurement Methods for Data-Scarce Environments

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