Asset Pricing with Garbage

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How researchers see this paper

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The Cross-Section of Expected Stock Returns: What Have We Learnt from the Past Twenty-Five Years of Research? (2010, unknown): “In a paper with a humorous title ('Asset Pricing With Garbage'), Savov (2009) indicates that garbage production in the USA provides a better measure of consumption variation than traditional measures of consumption obtained from National Income and Product Accounts (NIPA) and he shows that garbage…”
Empirical cross-sectional asset pricing: a survey (2011, background): “Savov (2011) shows that growth in garbage is a better proxy for actual consumption growth than the usual measures.”
What Ties Return Volatilities to Price Valuations and Fundamentals? (2013, methodology): “The skepticism stems from numerous sources: First, NIPA quarterly data have been shown to be “managed” and smoothed using numerous filters, which substantially dampens their volatility and increases their autocorrelation ðsee Savov 2011Þ.”
Robust Inference for Consumption‐Based Asset Pricing (2019, unknown): “To facilitate comparison, we use the same data as in Savov (2011) and Kroencke (2017).”
The Pollution Premium (2023, methodology): “Moreover, Savov (2011) uses garbage release data to capture volatile consumption, and Da, Yang, and Yun (2015) use electricity data to proxy for missing homemade goods.”