Abstract
This paper studies front-page choices made by editors of major US newspapers. I document that newspaper front pages are biased to certain combinations of news after controlling for the newspaper bias and the overall market coverage of such news. I also provide a reader-maximization model for front-page decisions that I use to interpret the empirical biases as preferences of the newspaper population of target readers. Through the lens of my model, my estimates recover maps of complementarities among pairs of topics for each newspaper and I find that these contribute to the probability that news on a topic appears on the front page.
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