Patrick Altmeyer, Eduard Gimenez, Simon Neumeyer and Jakob Poerschmann ’21 competed against 57 teams from 14 countries.
The Novartis Datathon is a Data Science competition taking place annually, usually in Barcelona. In 2020, the Barcelona GSE team “Non-Juvenile Asymptotics” consisting of Eduard Gimenez, Patrick Altmeyer, Simon Neumeyer and Jakob Poerschmann won third place after a fierce competition against 57 teams from 14 countries all over the globe. While the competition is usually hosted in Barcelona, the Covid-friendly version was fully remote. Nevertheless, the increased diversity of teams clearly made up for the missed out atmosphere.
This year’s challenge: predict the impact of generic drug market entry
The challenge of interest concerned predicting the impact of generic drug market entry. The risk of losing ground against cheaper drug replicates once the patent protection runs out is evident for pharmaceutical companies. The solutions developed helped solving exactly this problem, making drug development much easier to plan and calculate.
While the problem could have been tackled in various different ways, the Barcelona GSE team focused on initially developing a solid modeling framework. This represented a risky extra effort in the beginning. In fact more than half of the competition period passed without any forecast submission by the Barcelona GSE team. However, the initial effort clearly paid off: as soon as the obstacle was overcome, the “Non-Juvenile Asymptotics” were able to benchmark multiple models at rocket speed.
Fierce competition until the very last minute
The competition was a head-to-head race until the last minute. Still in first place until minutes before the final deadline, the predictions of two teams from Hungary and Spain ended up taking the lead by razor sharp margins.
Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2014. The project is a required component of every master program.
Multimarket Contact and Collusion in the Ecuadorian Pharmaceutical Sector
Jerónimo Callejas and Igne Grazyte
Competition and Market Regulation
The paper analyses the effects of multimarket contact on prices in the Ecuadorian pharmaceutical sector and its capacity to serve as a tool to facilitate collusion. We estimate the effect that the multimarket contact has on firms’ price setting behaviour by applying multimarket contact models and simple econometric techniques. Our findings show that multimarket contact has a positive effect on multivitamin prices in Ecuador and could indeed be helping to sustain collusion between firms.
We have tried to estimate the possible effect that multimarket contacts might have on prices and collusion in the Ecuadorian pharmaceutical industry. For the purposes of this paper we have chosen to limit our analysis and only focus on the market for multivitamins defined at the 4th ATC level. To test our predictions we tried to replicate simple techniques used by Ciliberto and Williams (2013), Evans and Kessides (1994) and Coronado (2010). We have constructed a multimarket contact index and estimated its effect on prices by using IV and then Panel Data with fixed effects estimations and also correcting for endogeneity.
As seen in section 5, our model gives robust results and provides a reasonable confirmation of our expectations: the coefficients predicted by the two models (IV and panel data with fixed effects) have the correct sings and are highly significant. Our results show that the IV estimation alone is insufficient to successfully solve all endogeneity issues, however we find that using panel data with fixed effects and also instrumenting endogenous variables (MMC) we can successfully remove the endogeneity problem from the proposed regression and obtain unbiased estimates. Our analysis shows that average multimarket contact index has a significant positive effect on price, thus confirming our predictions that the contacts between firms in different product markets can lead to higher prices for pharmaceutical products. Although we believe that this result could be indicative of possible collusive practices in the sector, the actual existence of collusion could only be confirmed by direct evidence, such as direct contacts between firms with the aim of setting prices or sharing markets.
Due to time constraints we were only able to conduct our analysis in one market and using only simple estimations and models of multimarket contact index. Therefore possible future extensions to this paper could include estimating the effect of the multimarket contact index in other markets, possibly taking into account both private and public markets; or to estimate the effect of multimarket contact by using more complex models, such as nested logit model used in Ciliberto and Williams (2013).
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