By Wenqing Li and James Nieberding (August 3, 2017, 4:12 PM EDT) -- Antitrust agencies in the U.S. and other countries have investigated numerous high-profile global price-fixing cases in recent years. These schemes have included products and services such as thin film transistor-liquid crystal display (LCD) panels, cathode ray tubes, DRAMS, vitamins, chemicals, automobile parts, air transportation, ready-mix concrete, and optical disk drives, to name just a few.[1] An important economic task in these types of cases is to estimate the increase in price of the affected items that can be attributed to the collusive behavior. Expert economists often use a reduced-form regression model with a dummy variable indicating the collusion period to estimate overcharges resulting from the price-fixing, where price (often expressed as its logarithm) is the dependent variable.[2] Supply and demand factors that affect prices, along with a dummy variable which is equal to 1 during the collusion period and zero otherwise, are the explanatory variables. In this brief article, we explain how to avoid making a methodological mistake when applying such a reduced-form price regression to estimate an overcharge....