Which bills are lobbied? Predicting and interpreting lobbying activity in the US

Ivan Slobozhan, Peter Ormosi and Rajesh Sharma
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Ivan Slobozhan: Institute of Computer Science, University of Tartu
Peter Ormosi: Centre for Competition Policy and Norwich Business School, University of East Anglia
Rajesh Sharma: Institute of Computer Science, University of Tartu

No 2020-03, Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) from Centre for Competition Policy, University of East Anglia, Norwich, UK.

Abstract: Using lobbying data from OpenSecrets.org, we offer several experiments applying machine learning techniques to predict if a piece of legislation (US bill) has been subjected to lobbying activities or not. We also investigate the influence of the intensity of the lobbying activity on how discernible a lobbied bill is from one that was not subject to lobbying. We compare the performance of a number of different models (logistic regression, random forest, CNN and LSTM) and text embedding representations (BOW, TF-IDF, GloVe, Law2Vec). We report results of above 0.85% ROC AUC scores, and 78% accuracy. Model performance significantly improves (95% ROC AUC, and 88% accuracy) when bills with higher lobbying intensity are looked at. We also propose a method that could be used for unlabelled data. Through this we show that there is a considerably large number of previously unlabelled US bills where our predictions suggest that some lobbying activity took place. We believe our method could potentially contribute to the enforcement of the US Lobbying Disclosure Act (LDA) by indicating the bills that were likely to have been affected by lobbying but were not led as such.

Keywords: lobbying; rent seeking; text classification; US bills (search for similar items in EconPapers)
Date: 2020-01-01
New Economics Papers: this item is included in nep-big, nep-cmp and nep-exp
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Persistent link: https://EconPapers.repec.org/RePEc:uea:ueaccp:2020_03

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Juliette Hardman, Center for Competition Policy, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK

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