The previous chapter explained the difference between open-loop and Markov Perfect equilibria. The Markov Perfect equilibrium assumes that firms are rational, insofar as they expect their rivals to respond to changes in the state variable; the equilibrium is subgame perfect. In contrast, the open-loop equilibrium is (in most cases) not subgame perfect. For this reason, the Markov Perfect equilibrium is more consistent with the standard assumption of firms' rationality. However, the open-loop equilibrium is easier to estimate. We start by showing how to estimate open-loop equilibria using two examples of discrete-time, dynamic games with different types of data and objectives. We then briefly discuss an estimation approach when firms use Markov Perfect strategies.

OVERVIEW OF TWO EXAMPLES

The first of our two discrete-time examples, the sticky price model, shows how to estimate an index of market power in a dynamic setting when the econometrician has only industry-level (rather than firm) data. The market power (“conjectural variation”) parameter nests a family of equilibria, including the leading cases of competition, cartel, and symmetric Cournot.

The second example, which is based on Roberts and Samuelson (1988) – the RS model, includes the open-loop equilibrium as a special case. In this example, the econometrician has firm-level data. Because the econometrician assumes that firms behave noncooperatively, rather than estimate an index of market structure, the econometrician is interested in estimating a particular feature of the noncooperative behavior and the implication of that behavior.