Merger simulation is a commonly used technique when analyzing potential welfare costs and benefits of mergers between firms. Merger simulation models differ with respect to assumed form of competition that best describes the market (e.g. differentiated Bertrand competition, Cournot competition, auction models, etc.) as well as the structure of the chosen demand system (e.g. linear or log-linear demand, logit, almost ideal demand system (AIDS), etc.) [1]
Farrell and Shapiro (1990) [2] highlighted issues of the Department of Justice's Merger Guidelines (1984), with its use of Herfindahl-Hirschman indices. The main issues they raised were the base assumptions that:
They sought to instead to model mergers by Cournot oligopoly theory, establishing a series of propositions in both mergers effect on price and welfare. To establish their propositions a series of assumptions and conditions were made:
These conditions favour accuracy of the modelling in markets with limited demand and products that do not have economies of scale. Based on the assumptions, they established 7 propositions relating to price and welfare outcomes of mergers.
The steps in the merger simulation process can be divided into two categories: "front-end" and "back-end" analysis. [3]
1. Estimation of demand before the merger.
2. Specification of parameters in the demand function.
3. Model of the supply side before the merger.
4. Model of the new equilibrium after the merger using the demand and supply models pre-merger. This is done by using the previous functions to calculate the firms' equilibrium price after the merger has happened, and calculating the consequent welfare effects. [4]
The following elements are used to simulate the effects of a merger. [5]
Modelling the estimated demand requires selecting the demand model that best suits consumer behaviour in the industry, and either functional form models (AIDS, PCAIDS) or discrete-form models (Logit, Nested Logit) can be used. Additionally, the demand elasticity of the product(s) and how consumers in the industry select which products they wish to consume will also need to be estimated.
The firm's marginal costs are taken into account, as well as factors that may influence it, such as diseconomies of scale.
The strategic variable(s) the firm would focus on and modify in order to compete with its rivals.
Depending on the state of their competition, firms' objectives may align. For example, firms may have a mutual understanding to not produce too much output as it may decrease their prices.
When carrying out merger simulation, there are three key assumptions to be held: [6]
When assessing the welfare effects of a vertical merger, both the upstream and downstream game effects must be considered. Therefore, it is an extension of the horizontal merger model consisting of five elements. [7]
1. Downstream demand
2. Assumption with respect to the upstream game
3. Assumption with respect to the downstream game
4. Assumption of the timing of moves
5. Marginal Costs
The simulations can then be either econometric or Monte Carlo. Backward induction will be used to find the subgame perfect equilibrium of the simulation because the game will be modelled vertically. [8]
Merger simulation is a commonly used technique when analyzing potential welfare costs and benefits of mergers between firms. Merger simulation models differ with respect to assumed form of competition that best describes the market (e.g. differentiated Bertrand competition, Cournot competition, auction models, etc.) as well as the structure of the chosen demand system (e.g. linear or log-linear demand, logit, almost ideal demand system (AIDS), etc.) [1]
Farrell and Shapiro (1990) [2] highlighted issues of the Department of Justice's Merger Guidelines (1984), with its use of Herfindahl-Hirschman indices. The main issues they raised were the base assumptions that:
They sought to instead to model mergers by Cournot oligopoly theory, establishing a series of propositions in both mergers effect on price and welfare. To establish their propositions a series of assumptions and conditions were made:
These conditions favour accuracy of the modelling in markets with limited demand and products that do not have economies of scale. Based on the assumptions, they established 7 propositions relating to price and welfare outcomes of mergers.
The steps in the merger simulation process can be divided into two categories: "front-end" and "back-end" analysis. [3]
1. Estimation of demand before the merger.
2. Specification of parameters in the demand function.
3. Model of the supply side before the merger.
4. Model of the new equilibrium after the merger using the demand and supply models pre-merger. This is done by using the previous functions to calculate the firms' equilibrium price after the merger has happened, and calculating the consequent welfare effects. [4]
The following elements are used to simulate the effects of a merger. [5]
Modelling the estimated demand requires selecting the demand model that best suits consumer behaviour in the industry, and either functional form models (AIDS, PCAIDS) or discrete-form models (Logit, Nested Logit) can be used. Additionally, the demand elasticity of the product(s) and how consumers in the industry select which products they wish to consume will also need to be estimated.
The firm's marginal costs are taken into account, as well as factors that may influence it, such as diseconomies of scale.
The strategic variable(s) the firm would focus on and modify in order to compete with its rivals.
Depending on the state of their competition, firms' objectives may align. For example, firms may have a mutual understanding to not produce too much output as it may decrease their prices.
When carrying out merger simulation, there are three key assumptions to be held: [6]
When assessing the welfare effects of a vertical merger, both the upstream and downstream game effects must be considered. Therefore, it is an extension of the horizontal merger model consisting of five elements. [7]
1. Downstream demand
2. Assumption with respect to the upstream game
3. Assumption with respect to the downstream game
4. Assumption of the timing of moves
5. Marginal Costs
The simulations can then be either econometric or Monte Carlo. Backward induction will be used to find the subgame perfect equilibrium of the simulation because the game will be modelled vertically. [8]