We propose a dynamic oligopoly pricing model, in which consumers’ choices exhibit inertia and firms face costly price adjustments. The primitives of the model are estimated using scanner data from the UK butter and margarine industry. We evaluate the effects of frictions on price dynamics, profits and consumer welfare. We find that price adjustment costs are substantial and represent between 24-34% of net margins. Our model predicts that absence of these costs reduces persistence in prices, increases firms’ profits but has little effect on consumer surplus. The effects of consumer inertia on prices are much more pronounced than when firms cannot adjust prices freely.
We propose a model of nonsequential consumer search where consumers and firms differ in search and production costs respectively. We characterize the equilibrium of the game. The search cost distribution is first identified by market shares and prices. The production cost distribution is subsequently identified using a similar strategy to Guerre, Perrigne and Vuong (2000) as the firms’ decisions resemble bidders’ decisions in a procurement auction. We show the firms’ cost density can be estimated at the same convergence rate as the optimal rate in Guerre et al. uniformly over any fixed subset on the interior of the support; it can be made close to that rate when the subset increases to the full support asymptotically. The difference in rates is due to a pole in the price pdf that we show to be a feature of the equilibrium. We give two extensions of our model with analogous results. One allows for vertically differentiated products. The other has an intermediary. Our simulation study confirms theoretical features of the model. We apply our model to study loan search using UK mortgage data.
Many controversies that beset the digital economy turn on the role of advertising and its use of personal data. We document several new stylised facts about the global digital advertising marketplace and examine the trade-off between privacy and ad targeting accuracy from the advertisers’ perspective. We exploit a novel dataset with billions of observations of online ads spanning multiple countries, advertisers, and websites. Our focus is to estimate the impact of Apple’s gradual restriction and ultimate abolition of ad tracking in its Safari browser called Intelligent Tracking Prevention (ITP). We analyse how much advertisers are willing to pay for third-party cookies and how tightening privacy policies affects market outcomes. Our empirical strategy treats Apple’s policy changes as exogenous shocks to the supply of tracking opportunities and uses a series of event study models to estimate their causal impact. We find that the estimated treatment effects around the ITP introduction dates are small in magnitude on average but differ markedly across countries, advertising campaigns, and type of marketplace. These finding are consistent with a theoretical literature showing that changes in ad targeting have ambiguous general equilibrium effects. Moreover, our results suggest that markets failed to adjust immediately to new, more privacy-sensitive equilibria.
We formulate a structural model of search with lender and borrower heterogeneity to estimate the value of information provided to UK households by mortgage brokers. Using administrative data on loans originating in 2016 and 2017, we document the existence of a substantial degree of unexplained price dispersion, and observe that while mortgages obtained from brokers are cheaper, borrowers who use intermediaries pay more once commissions are factored in. Assuming that it is borrowers with high search costs who use brokers, we nonparametrically estimate the distributions of search and banks’ costs of providing the loan. Our results show that search costs vary by demographic groups, and that broker presence exerts negative pressure on lenders’ market power. Compared to a world where broker advice is not available, we estimate that their presence reduces average monthly mortgage costs by 21% and welfare losses arising from search frictions by 70% – although the results differ by borrower and loan characteristics. We also find that regulation in support of market centralization halves lenders’ markups and lowers monthly costs of an average mortgage by 4.4%.
We combine multiple data sources to construct an extensive dataset on London property prices, rents, residential amenities, travel times and wages. These data are then used to estimate a structural location choice model with heterogeneous workers and firms to explain residential sorting patterns and the impact of planning decisions and infrastructure investments on house prices, rents, and location choices. To control for endogenous amenities we leverage techniques developed in the IO literature on demand estimation, such as BLP instruments.
… and several more projects with tentative titles
The National Infrastructure Commission (NIC) commissioned a team of academics and researchers at the IFS and UCL to create a software tool that estimates how land values respond to changes in land purpose or infrastructure improvements.
|© 2018-2020 Mateusz Mysliwski. Template by Bootswatch.