A number of existing studies have identified product market competition as an important industry characteristic influencing firms’ disclosure practices, earnings volatility, and the uncertainty of future performance. The authors examine how this characteristic affects the extent of analyst coverage and the accuracy of analyst forecasts as well as whether the effect of competition on forecasting activity is influenced by the country-level institutions that regulate product market competition. They find that firms in more concentrated industries and with added pricing power attract more analysts who generate more accurate and less diffuse earnings forecasts. Moreover, the authors discover that countries with less competitive practices strengthen the market power of firms, which affects the accuracy of analysts’ forecasting.

The empirical results confirm that the intensity of the competition in product markets has important implications for informational efficiency in financial markets. Firms in more concentrated industries and with greater firm-specific pricing power receive significantly more analyst coverage and have more accurate and less dispersed earnings forecasts than firms in less concentrated industries.

This result can be explained by the notion that a less competitive industry environment and a dominant position in an industry increase firms’ earnings predictability while reducing information complexity and its uncertainty. Strong market power acts as a natural hedge to smooth cash flow fluctuations, which improves the efficiency and accuracy of analyst forecasting and reduces the divergence in analyst expectations for a firm’s future performance. Conversely, in more competitive industries, forecasting effectiveness based on historical earnings is reduced.

The effect of competition on forecasting activity varies across countries as well. The authors’ results indicate that the effect of product market power on analyst following is greater in countries with less effective competition laws and high entry costs. In particular, forecast accuracy is significantly higher in countries following common law and those with effective law enforcement. This finding implies that institutional regulations that promote competition can effectively curb firms’ market power, which limits the effect of market power on the production of analysts’ information.

Additionally, the authors reveal that the deregulation of the European utilities industries led to a decrease in analyst following and less accurate and more dispersed earnings forecasts in the post-deregulation period. This result suggests that the intense competition resulting from deregulation increases the cost of generating precise analyst forecasts by reducing the earnings predictability and increasing the information uncertainty.

The authors use an empirical method approach and develop a multivariate regression model to explore the relationship between product market competition and analyst forecasting activity. The sample consists of 53,226 firm-year observations in 37 countries for the period from 1990 to 2008. The selected countries must have at least 100 firm-year observations and at least one of the country-level institutional variables—the effectiveness of competition law or the level of entry cost—that can be measured. The stock price and financial data are retrieved from the Worldscope database and analyst data from the historical I/B/E/S international database. Regulated industries, including financial institutions, utility firms, and government-owned firms, are excluded from the observations.

The authors measure product market competition at the industry level and the firm level. Industry-level competition is measured by using the Herfindahl–Hirschman Index, which is defined as the sum of the squared market shares of the firms competing in each industry for each country. Firm-level competition is measured by using the price–cost margin, which is determined from net sales divided by operating costs.

Analyst forecasting activities are measured by (1) number of analysts forecasting, (2) forecast accuracy, and (3) forecast dispersion among analysts. Control variables include industry size, firm size, cross-listing status, leverage ratio, earnings surprise, standard deviation of return on equity, and the correlation between stock returns and earnings. The results are robust to using alternative competition measures, industry-level analyses, different sample selection procedures, and alternative-estimation methods.

I agree with the authors that the intensity of the competition in product markets has important implications for the information efficiency in financial markets. In particular, financial analysts should pay extra attention to the reverse effect of deregulation on forecasting accuracy. Because deregulation is a trend in many developing countries, it will be more challenging for analysts to forecast in these countries.