Predictability over Volatility: When simple strategies help households save on fuel
Abstract
What reasonable strategies can households use to save on gasoline or diesel purchases under different pricing functions? We assess basic strategies households might employ under a simplified model of a 10-gallon tank, fixed fuel consumption between refill opportunities, and price changes at each opportunity to refill. Purchases always fill the tank, and if the tank is empty, it must be refilled regardless of price. We explore three strategy types: price-independent (filling once the tank is below a specific level), price-dependent (filling when the price is below the last $n$ days or their average), and mixed (filling only below a set level, and then only when the price is below the last $n$ days or their average). We construct price functions from the nearest-in-time US weekly averages of regular gasoline and diesel, filling in higher-frequency values with a smoothing spline, linear interpolation, and random draws from normal and uniform distributions based on national averages. Additional simulations are built using Brownian motion. Together, these pricing models span a wide range of volatilities. We find that price-independent strategies are effective for the spline and linear functions, which have low volatility, while price-dependent strategies are effective for the normal and uniform distributions, which are highly volatile. Brownian motion, despite its mid-range volatility, admits no effective strategy. Our findings suggest that the predictability of price movements, whether prices trend or revert toward a stable level, matters more for household strategies than overall volatility: the random walk is volatile in the middle of our range yet offers households no usable signal. Policymakers can therefore assist households by addressing how prices move from day to day, not only the retail prices they face.