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Consumption network effects

Author: Giacomo De Giorgi; Anders Frederiksen; Luigi Pistaferri; National Bureau of Economic Research,
Publisher: Cambridge, Mass. : National Bureau of Economic Research, 2016.
Series: Working paper series (National Bureau of Economic Research), no. 22357.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
In this paper we study consumption network effects. Does the consumption of our peers affect our own consumption? How large is such effect? What are the economic mechanisms behind it? We use long panel data on the entire Danish population to construct a measure of consumption based on administrative tax records on income and assets. We combine tax record data with matched employer-employee data so that we can  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Giacomo De Giorgi; Anders Frederiksen; Luigi Pistaferri; National Bureau of Economic Research,
OCLC Number: 951907709
Notes: "June 2016"
Description: 1 online resource (56 pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 22357.
Responsibility: Giacomo De Giorgi, Anders Frederiksen, Luigi Pistaferri.

Abstract:

In this paper we study consumption network effects. Does the consumption of our peers affect our own consumption? How large is such effect? What are the economic mechanisms behind it? We use long panel data on the entire Danish population to construct a measure of consumption based on administrative tax records on income and assets. We combine tax record data with matched employer-employee data so that we can construct peer groups based on workplace, which gives us a much tighter, precise, and credible definition of networks than used in previous literature. We use the available data to construct peer groups that do not perfectly overlap, and as such provide valid instruments derived from the network structure of one's peers group. The longitudinal nature of our data also allow us to estimate fixed effects models, which help us tackle reflection, self-selection, and common-shocks issues all at once. We estimate non-negligible and statistically significant endogenous and exogenous peer effects. Estimated effects are quite relevant for policies as they generate non-negligible multiplier effect. We also investigate what mechanisms generate such effects, distinguishing between "keeping up with the Joneses", a status model, and a more traditional risk sharing view.

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