The timing of elections is flexible in many countries. We study this optimization by first creating a Bayesian learning model of a mean-reverting political support process. We then explore optimal electoral timing, modelling it as a renewable American option with interacting waiting and stopping values. Inter alia, we show that the expected longevity is a convex, then concave, function of the support. Finally, we calibrate our model to the post-1945 Labour-Tory U.K. rivalry. Our story quite well explains when the elections were called. We also show that election options approximately double the expected time in power in the current streak.

We document significant persistence in the market timing performance of active individual investors, suggesting that some investors are skilled at timing. Using data on all trades by active Finnish individual investors over almost 15 years, we also show that the net purchases of skilled versus unskilled investors predict monthly market returns. Our results lend credibility to the view that market returns are predictable, without having to specify which variables active investors use to successfully time the market.

Search frictions and misallocation are common in decentralized transportation markets. Using novel trip-level data of taxis in Singapore, this paper examines the impactof real-time demand information at airport terminals on search frictions. The in-formation reduces taxi supply misallocation, increasing deadheading speed by 16.3%and decreasing deadheading time by 10.77%, benefiting both passengers and drivers.It raises daily earnings by $3.70 USD and adds 6.2 minutes of operational time perairport-trip taxi. Spatial spillovers are primarily observed among drivers in adjacentdistricts. Taxis from the Budget Terminal and drivers with fewer prior airport pickups benefit more from this information.