Alexi Savov, Asset Pricing with Garbage, 2011, Journal of Finance 66, 177 – 201. Topic: Consumption Capital Asset Pricing (CCAPM) requires that consumption growth have the same order of magnitude of variation as asset returns. But consumption growth using the official data is much smoother (less volatile) than asset returns. Under these conditions, CCAPM implies that consumers must have unreasonably high risk aversion. This is also referred to as the risk premium puzzle (risk premium is too high) or , by implication, the risk free rate puzzle (risk free rate is too low). Contribution: The paper uses garbage growth as a better proxy for true consumption growth. He finds that using garbage produces a more volatile consumption series that is more highly correlated with stock returns, and that implies a more reasonable level of consumer risk aversion than using the official consumption series. He shows using EU country data that the results hold for 19 other countries.

Advantages of garbage as a consumption measure. The timing of garbage it tightly linked to consumption because there is no benefit to keeping goods past their usefulness. If luxury (costly) goods’ garbage is less than normal goods, then garbage growth understates true consumption volatility – making his results understated. (must assume that luxuries drop relatively more in recession than normal goods) Garbage catches consumption of goods hidden from the official consumption measure such as black market or home produced goods that still generate waste. Official consumption is autocorrelated due to imputations and smoothing methods used for computation. Garbage is not autocorrelated as predicted by Hall (1978) PIH. 2. Weaknesses of garbage Misses much of services because they do not produce much garbage, which are a large part of consumption. Garbage data available annually, which partly defeats the purpose of trying to find a measure that fits true consumption tighter, varies with returns, and is more volatile than official consumption.

3. Garbage gives a coefficient of risk aversion of 17 and a risk free rate of 17%, which is much lower than earlier studies but still high. Consider the Euler equation of Lucas and Breeden. So Here, β is the subjective discount factor for time value, C is consumption, consumption growth is c = Ct+1/Ct, γ is relative risk aversion, and R is excess return. What folks have observed is that the excess return is large but because traditional measured consumption has low variance and low correlation with R (so Cov[ ] is small), then the only way to explain the large R is that γ is large making E[βc-γ] small in the denominator. In other words, when the observed quantity of risk is (too) low (consumption too smooth) then the unobserved price of risk must be (too) high to offset it to match the data. The garbage measure of consumption increases the size of Cov[ ] so that γ is not as large.