We document the numerical challenges we experienced estimating random-coefficient demand models as in Berry, Levinsohn, and Pakes (1995) using two well-known data sets and a thorough optimization design. The optimization algorithms often converge at points where the first- and second-order...

Empirical exercises in economics frequently involve estimation of highly nonlinear models. The criterion function may not be globally concave or convex and exhibit many local extrema. Choosing among these local extrema is non-trivial for a variety of reasons. In this paper, we analyze the...

In this paper, we share our experience with merger simulations using a Random Coefficient Logit model on the demand side and assuming a static Bertrand game on the supply side. Drawing largely from our work in Knittel and Metaxoglou (2008), we show that different demand estimates obtained from...

Using the daily trade of futures from the prediction markets site Intrade, we pin down the effect of printed newspapers endorsements (announcement of an explicit support for a political candidate) on the candidates' likelihood of winning. It is established that unexpected endorsements have a...

We show that monitoring by individuals with preferences regarding the outcome of the supervised task interferes with the task's process: the monitors bias the results in favor of their own preferences. In particular, using an original dataset from the 2011 national elections in Argentina, we...

We use information released during the investigation of the California electricity crisis of 2000 and 2001 by the Federal Energy Regulatory Commission to diagnose allocative inefficiencies in the state’s wholesale reserve markets. Material that has been largely neglected allows us to...

We introduce a state-space representation for vector autoregressive moving-average models that enables maximum likelihood estimation using the EM algorithm. We obtain closed-form expressions for both the E- and M-steps; the former requires the Kalman filter and a fixed-interval smoother, and the...

We test the efficiency of the California electricity reserves market by examining systematic differences between its day- and hour-ahead prices. We uncover significant day-ahead premia, which we attribute to market design characteristics. On the demand side, the market design established a...

Incompatibility in markets with indirect network effects can reduce consumers’ willingness to pay if they value “mix and match” combinations of complementary network components. For integrated firms selling complementary components, incompatibility should also strengthen the demand-side...

Estimating market power is often complicated by the lack of reliable measures of marginal cost. Instead, policy-makers often rely on other summary statistics of the market, thought to be correlated with price cost margins---such as concentration ratios or the HHI. In many industries, these...