Revenue maximizing inflation

The Revenue Maximizing Auction

Mining Revenue-Maximizing Bundling Configuration

With greater prevalence of social media, there is an increasing amount of user-generated data revealing consumer preferences for various products and services. Businesses seek to harness this wealth of data to improve their marketing strategies. Bundling, or selling two or more items for one price is a highly-practiced marketing strategy. In this paper, we address the bundle configuration probl...

Maximizing Revenue in Sequential Auctions

We study sequential auctions for private value objects and unit-demand bidders using second-price sealed-bid rules. We analyze this scenario from the seller’s perspective and consider several approaches to increasing the total revenue.We derive the equilibrium bidding strategies for each individual auction.We then study the problem of selecting an optimal agenda, i.e., a revenue-maximizing orde...

Seigniorage-maximizing inflation

What is the seigniorage-maximizing level of inflation? Four models formulae for the seigniorage maximizing inflation rate (SMIR) are compared. Two sticky-price models arrive at very different quantitative recommendations although both predict somewhat lower SMIRs than Cagan’s formula and a variant of a .ex-price model due to Kimbrough (2006). The models differ markedly in how inflation distorts...

Approximating Revenue-Maximizing Combinatorial Auctions

Designing revenue-maximizing combinatorial auctions (CAs) is a recognized open problem in mechanism design. It is unsolved even for two bidders and two items for sale. Rather than attempting to characterize the optimal auction, we focus on designing approximations (suboptimal auction mechanisms which yield high revenue). Our approximations belong to the family of virtual valuations combinatoria...