Government, National Government, and State Enterprises.<sup>2</sup> Bussolo, Commander, and Poupakis (2018) provide a detailed discussion on the PEP data set.

Second, we source firm-level data from the Orbis data set by Bureau van Dijk. Orbis reports corporate ownership and shareholder information, along with balance sheet and financial data for listed and unlisted firms. While Orbis provides an extensive resource for firm-level empirical studies, there are several challenges related to using this data set. We address these challenges by using the three steps approach first proposed by Kalemli-Ozcan,<sup> ̈</sup> Sorensen, Villegas-Sanchez, Volosovych, and Yesiltas (2015) and Kalemli-Ozcan,<sup> ̈</sup> Laeven, and Moreno (2018). First, we drop firms with inconsistent information on generic variables such as date of establishment, type of company, and suspect of inconsistent units.<sup>3</sup> Second, we drop firms for which total assets, fixed assets, sales, number of employees, wages, or cost of goods sold is negative in any year. We also drop firms that report having more than 2 million employees. Third, we drop observations for firm-years with zero or missing values for total assets.

Our main firm-level variables are Investment, Return on Assets (ROA), Leverage, Capitalization, Cash Flow, Sales Growth, and Marginal Product of Capital. Investment is defined as change in fixed assets scaled by total assets. ROA is the percentage share of financial and operational profits (before taxes) to total assets. Leverage is the ratio of total debt to total assets. Capitalization is the ratio of total assets to total funds from shareholders. Cash Flow is taken from balance sheet data directly and is scaled by total assets. Sales Growth is calculated as the annual change in sales over total assets. We follow Hsieh and Song (2015) and use average return to capital (measured as value added over fixed assets) as a proxy for the marginal product of capital. We also use information on firm size, firm age, and on whether a firm is state-owned or not.

We identify politically connected firms by merging Orbis with the PEP data set. As a first step we focus on firm names. Specifically, we identify politically exposed persons and their connections from the PEP data set and merge the PEP data set with Orbis by matching the firm names reported

> 2The original PEP data set has eight categories of politically exposed persons. These comprise individuals in International and Regional Organizations, National, Sub-national and Local Government, State-Owned Enterprises and State-Invested Enterprises, as well as Non-Governmental Organizations (Bussolo, Commander, and Poupakis (2018)). However, for the countries in our sample, after merging with Orbis data we find four afore-mentioned categories to be relevant. Please note that for our analysis we collapse State-Owned Enterprises and State-Invested Enterprises to a single category titled State Enterprises.

> 3The criteria for consistency check are based on a ”reasonable” move in total assets. We drop firms if we observe a sudden sharp spike in growth rate of total assets, with a lower threshold of -99% and an upper threshold 19900%.

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