Imputing consumption from income and wealth information
By Martin Browning, Søren Leth-Petersen. 2003
138 citations recorded by the source corpus.
Subfields: Accounting, Economics and Econometrics, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/bb000b60a86b0e8d45ff32fc3f245922b6724779
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Oscar Stolper
- A. Walter
- Mette Gørtz
- Martin Browning
- Søren Leth-Petersen
- Michael McMahon
- Francesco Giavazzi
- Tullio Jappelli
In Economics and Econometrics
- Oscar Stolper
- A. Walter
- Mette Gørtz
- Martin Browning
- Søren Leth-Petersen
- Michael McMahon
- Francesco Giavazzi
- Tullio Jappelli
In Management Science and Operations Research
Citations in the corpus
- Disability Benefits, Consumption Insurance, and Household Labor Supply (2019, unknown): “Browning & Leth-Petersen (2003) shows how one can construct such measures of consumption from longitudinal data on income and assets.”
- Financial literacy, financial advice, and financial behavior (2017, methodology): “To overcome this data limitation, the author resorts to the imputation method proposed by Browning and Leth-Petersen (2003) and designed to link datasets featuring the above-mentioned properties.”
- Policy Uncertainty and Household Savings (2012, background): “14 In an appendix to Giavazzi and McMahon (2008), we follow Browning and Leth-Petersen (2003), among others, and impute saving rates for those for whom no saving is reported.”
- Housing Wealth and Consumption: A Micro Panel Study (2013, methodology): “8 Browning and Leth-Petersen (2003) examine the quality of the imputation using data drawn from the Danish Family Expenditure Survey (DES) for the years 1994-1996.”
- Consumer responses to the Covid‐19 crisis: evidence from bank account transaction data (2020, unknown): “To learn more about the causal mechanisms underlying the spending dynamics, we construct subsamples of individuals who had different ex ante exposure to the various negative consequences of the pandemic.(7) First, we use industry information about the firms making salary payments to define a subsamp”