I develop a quantitative model of multi-plant oligopolists where each firm decides where to locate the set of plants and how to serve each market, taking into account cannibalization across its own plants as well as competition with others. In contrast to canonical trade models with multinational firms where neither spatial interdependency of decisions nor oligopoly is considered, I advance the existing research by allowing for interdependent entry, oligopolistic rivalry and variable markups. Despite having a high-dimensional discrete choice problem, I provide an estimation toolkit for the model in a three-step procedure, leveraging the gravity-type regressions, the analytical expression for market price given the spatial distribution of plants, and the solution algorithm for a combinatorial problem when the location game is submodular. I present simulation-based evidence to show that neglecting interdependencies among plant locations within a multi-plant firm introduces quantitatively relevant differences in estimation.
Recent decades have witnessed the growing importance of trade in intermediate goods and pursuit of free trade agreements (FTAs). They distort firms’ sourcing decisions internationally through preferential tariffs and rules of origin (RoOs), a set of criteria that define the origin of a product to qualify for preferential access. The paper distinguishes trade diversion through RoOs from tariff reduction on intermediate goods, focusing on the automotive industry. Car assemblers' decisions of how much to acquire from which supplier are modeled for every auto part. With the derived gravity trade equation, the estimation identifies significant diversion in intermediate sourcing and the effect is nonlinear with respect to the restrictiveness of RoOs. The shift from foreign to regional inputs increases before a sharp decline when the required minimum FTA content reaches 65%. Impacts of RoOs are further decomposed to three channels: export destinations of final goods, magnitude of preferential treatments and value of intermediate goods. Results show that the RoO effects are stronger when car exports are mainly intra-FTA, but indifferent to preferential margins of cars or values of parts.
We study whether consumer taste is biased towards beer brands originated from countries where the ancestors of consumers came. The empirical analysis takes advantage of a single Chicago-area grocery store chain, Dominick’s, having stores located at census tracts with different ethnic background composition. Combining the sales data at store-UPC level controlling for prices and brand offerings with 173 beer brands’ origin information scraped from one of the most visited beer online platform, we find significant home bias in consumption. The result sheds light on why this grocery chain has its market share plummeted after it was taken over by Safeway and replaced with house branded products.
One of the central questions revolving multinational firm theory is whether firms choose to internalize or engage in arm’s length licensing when entering a foreign market. Decisions on firm boundaries become more complicated when firms carry more than one brand and multiple stages of operation before reaching consumers. This paper compares two approaches in the literature concerning a multinational firm’s organization of foreign operation, namely the transaction-cost theory and property-rights theory. The two differ in whether efficiency losses from incomplete contracts are endogenous and whether they are of the same nature even for integrated relationships. Two models yield opposite predictions which open the door for empirical investigation that I test using a unique brand-market level data in the beer industry. I empirically characterize the optimal allocation of ownership rights by brand quality, contractual environment, market size, competition structure, and the existed band portfolio of the licensor and licensee. Results support the property-right theory for beer companies. I also overcome the data limitation on licensing agreements and develop an innovative way to infer contractual relationship by combining brands’ ownership information at the national and global level.