We consider all nonfinancial Worldscope, Compustat Global, and Compustat North America firms from 1990 to 2012. This table reports OLS regressions. Columns 1 and 2 report the results where the dependent variable is annual asset growth, winsorized at 1%; Columns 3 and 4 report the results where the dependent variable is net issue of debt plus net issue of equity, winsorized at 1%; Columns 5 and 6 report the results, where the dependent variable is change in common stock over lagged assets, winsorized at 1%; Columns 7 and 8 report the results where the dependent variable is change in financial debt over lagged assets, winsorized at 1%; Columns 9 and 10 report the results where the dependent variable is book debt to book equity ratio, limited to between 0 and 9. All regressions include firm fixed effects and time fixed effects, and controls such as log assets, ROA, log GDP, unemployment rate, country imports as the percentage of GDP, and exchange rate change. Standard errors are clustered at the country-SIC3 industry level.

In panel A, our main variable of interest is the interaction between the passage of the leniency laws and the likelihood that the market is cartelized. We use a prediction model based on time-varying firm characteristics (asset size, leverage and ROA), country characteristics (GDP and unemployment), as well country fixed effects and SIC3 fixed effects. We fit the prediction model only by using pre-leniency observations and predict the probability that the firm will be convicted in the cartel case in the year after the passage of the leniency law. In Columns 1, 3 5, 7, and 9, our main variable of interest is the interaction term between the passage of the leniency law and the predicted conviction probability. In Columns 2, 4 6, 8, and 10, our main variable of interest is the interaction term between a continuous variable of country-SIC3 export-weighted laws passed in other countries and the predicted conviction probability.

In panel B, our main variable of interest is the interaction between the passage of the leniency laws and Herfindahl-Hirschman index of the firm’s industry in a specific year. In Columns 1, 3 5, 7, and 9, our main variable of interest is the interaction term between the passage of the leniency law and the Herfindahl-Hirschman index. In Columns 2, 4 6, 8, and 10, our main variable of interest is the interaction term between a continuous variable of country-SIC3 export-weighted laws passed in other countries and the Herfindahl-Hirschman index.

In panel C, our main variable of interest is the interaction between the passage of the leniency laws and the number of patents filed with the USPTO by the firms in the firm’s industry in a specific year. In Columns 1, 3 5, 7, and 9, our main variable of interest is the interaction term between the passage of the leniency law and the number of patents. In Columns 2, 4 6, 8, and 10, our main variable of interest is the interaction term between a continuous variable of country-SIC3 export-weighted laws passed in other countries and the number of patents.

In panel D, our main variable of interest is the interaction between the passage of the leniency laws and the median lagged 2-year sales growth in the firm’s industry. In Columns 1, 3 5, 7, and 9, our main variable of interest is the interaction term between the passage of the leniency law and the industry growth. In Columns 2, 4 6, 8, and 10, our main variable of interest is the interaction term between a continuous variable of country-SIC3 export-weighted laws passed in other countries and the industry growth.

*, **, and *** denote significance at the 10%, 5%, and 1%, respectively.