7 citations · 7 across the 4 of their papers we have counts for
10 papers
Deep learning for detecting bid rigging: Flagging cartel participants based on convolutional neural networks
Martin Huber, David Imhof
Adding to the literature on the data-driven detection of bid-rigging cartels, we propose a novel approach based on deep learning (a subfield of artificial intelligence) that flags…
The fiscal response to revenue shocks
Simon Berset, Martin Huber, Mark Schelker
We study the impact of fiscal revenue shocks on local fiscal policy. We focus on the very volatile revenues from the immovable property gains tax in the canton of Zurich, Switzerla…
Assessing the effects of seasonal tariff-rate quotas on vegetable prices in Switzerland
Daria Loginova, Marco Portmann, Martin Huber
Causal estimation of the short-term effects of tariff-rate quotas (TRQs) on vegetable producer prices is hampered by the large variety and different growing seasons of vegetables a…
The Impact of Response Measures on COVID-19-Related Hospitalization and Death Rates in Germany and Switzerland
Martin Huber, Henrika Langen
We assess the impact of COVID-19 response measures implemented in Germany and Switzerland on cumulative COVID-19-related hospitalization and death rates. Our analysis exploits the…
On the plausibility of the latent ignorability assumption
Martin Huber
The estimation of the causal effect of an endogenous treatment based on an instrumental variable (IV) is often complicated by attrition, sample selection, or non-response in the ou…
A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels
Hannes Wallimann, David Imhof, Martin Huber
We propose a new method for flagging bid rigging, which is particularly useful for detecting incomplete bid-rigging cartels. Our approach combines screens, i.e. statistics derived…