Working Papers

Are you a Zombie Firm? An Early Warning System Based on Machine Learning Methods – Latest Version – Video CEBRA Conference MIT (41:15)
(with Thomas Heil and Franziska Peter)

Abstract: In this paper, we propose an empirical approach that finds the features that matter to categorize zombie firms, separate them from the non-zombies and the recovered, and ultimately predict tomorrow’s zombies and recovered zombie firms. We apply our approach to listed US and European firms. Using machine learning models for feature selection and logistic regressions, we show that an ensemble of firm-level variables on the firm capital, financial, and industry structure lead to the prediction of zombies and recovered zombie firms. The final model, our early warning system, produces variables that could be of use in monitoring firms’ zombie status versus recovered.

Presentations: IFM Brown Bag 2020 (University of Bern), EFMA 2021 (University of Leeds), Swiss Society of Economics & Statistics Annual Congress 2021 (University of Zurich), EEA Women in Economics 2021, Bern Data Science Day 2021 (University of Bern), Big Data and Machine Learning in Finance Conference 2021 (Polytechnic of Milan), CEBRA Annual Meeting 2021 (MIT Golub Center for Finance and Policy), 28^th Finance Forum (Nova SBE), IFABS 2021 Oxford Conference (University of Oxford), Tepper Finance Brown Bag (Tepper School of Business, Carnegie Mellon University), Young Scholars Conference on Machine Learning in Economics & Finance of the Philadelphia Fed, AEA/ASSA Annual Meeting 2022 (AEA Poster Session), 8^th Emerging Scholars in Banking and Finance (Bayes Business School).

Media: ifo Institute, Frankfurter Allgemeine Zeitung

How Does Competition Affect Zombie Firms? (with Marc Brunner and Philip Valta) – Paper

Abstract: This paper analyzes the effects of product market competition on zombie firms in the US using a large sample of publicly traded firms. First, we show that the asset-weighted share of zombie firms at the industry level decreases significantly with more competition. This decrease is mostly pronounced in industries characterized by a low concentration and low margins. Second, neither the exit or default probability, nor the recovery likelihood are significantly affected by changes in competition. Third, at the firm level, zombie firms grow more slowly, reduce their assets and cash holdings, issue less equity, and obtain smaller loans. These findings suggest that zombie firms adapt to higher competition by scaling down the size of the firm.

Presentations: Gerzensee Alumni Conference (Gerzensee, Switzerland), Bank of England, Wadham College (University of Oxford) and Waseda University Workshop on “Financial Frictions, Zombie Firms and the Macroeconomy”, Swiss National Bank/SIAW-University of St.Gallen Conference on “Corporate Distress as Financial Conditions Tighten”.

When Companies Don’t Die: Analyzing Zombie and Distressed Firms in a Low Interest Rate Environment (with Franziska Peter) – Paper

Abstract: We analyze the phenomenon of zombification in Europe and show that monetary policy alone is not its only driver. Concurring phenomena explain zombie and distressed firms’ prevalence. Using Compustat data on public firms, we find that a rise in short-term interest rates is associated with a decrease in zombie status, suggesting that low rates constitute a favorable environment for zombie firms; there is no evidence of credit misallocation within the ECB’s Corporate Sector Purchase Program; and that a decrease in inflation and a lower state of the business cycle is associated with a rise in zombie prevalence.

Media: The FinReg Blog, Duke Financial Economics Center

The Effects of Organized Crime on Distressed Firms – Paper

Abstract: This study captures the presence of organized crime groups in the Italian territories and examines their relationship to firms that are in a condition of financial distress. At the end of the nineteenth century the first criminal groups emerged in the South of Italy as a response to the demand for private protection by local landlords. Using firm-level data and detailed information on organized crime activities, this paper tests the hypothesis that organized crime groups support financially distressed companies by supplying them with private protection in the form of access to credit. The results show a higher concentration of distressed firms in regions with a high presence of organized crime groups.

Presentations: Economics of Crime Seminar 2020 (Jennifer Doleac Seminar Series), EEA Women in Economics 2020, European Public Choice Society Meeting 2018 (University of the Sacred Heart), 6^th Lindau Nobel Laureate Meeting (Germany), German Economic Association Meeting 2017 (University of Vienna), Italian Doctoral Workshop (Collegio Carlo Alberto).

Discussions

Daniel Giamouridis, Chara Prassa, Debt Renegotiation, Default Risk and Risk-Shifting Incentives, European Financial Management Annual Meeting, University of Leeds, 2021.

Federico Huneeus, Joseph P. Kaboski, Mauricio Larrain, Sergio L. Schmuckler, Mario Vera, The Distribution of Crisis Credit and Firm Indebtedness, CEBRA Annual Meeting, MIT Golub Center for Finance and Policy, 2021.

Roberto Daluiso, Emanuele Nastasi, Andrea Pallavicini, Stefano Polo, Reinforcement Learning for Options on Target Volatility Funds, Big Data and Machine Learning in Finance Conference, Polytechnic of Milan, 2021.

Andreas Dibiasi, Klaus Abberger, Michael Siegenthaler, Jan-Egbert Sturm, The Effects of Policy Uncertainty on Investment: Evidence from the Unexpected Acceptance of a Far-Reaching Referendum in Switzerland, European Public Choice Society Meeting, University of Budapest, 2017.