Although typically modeled as a centralized firm decision, pricing often involves multiple organizational teams that have decision rights over specific pricing inputs. We study team input decisions using comprehensive data from a large U.S. airline. We document that pricing at a sophisticated...

Airfares fluctuate over time due to both demand shocks and intertemporal variation in willingness to pay. I develop and estimate a model of dynamic airline pricing accounting for both forces with new flight-level data. With the model estimates, I disentangle key interactions between the arrival...

Airfares are determined by both intertemporal price discrimination and dynamic adjustment to stochastic demand. I estimate a model of dynamic airline pricing accounting for both forces with new flight-level data. With model estimates, I disentangle key interactions between the arrival pattern of...

This paper examines the question whether information is contained in forecasts from DSGE models beyond that contained in lagged values, which are extensively used in the models. Four sets of forecasts are examined. The results are encouraging for DSGE forecasts of real GDP. The results suggest...

Inversion of the yield curve has come to be viewed as a leading recession indicator. Unsurprisingly, some recent instances of inversion have attracted attention from economic commentators and policymakers about possible impending recessions. Using a variety of time series models and recent...

Nielsen (2009) shows that vector autoregression is inconsistent when there are common explosive roots with geometric multiplicity greater than unity. This paper discusses that result, provides a co-explosive system extension and an illustrative example that helps to explain the finding, gives a...

This paper computes the semiparametric efficiency bound for finite dimensional parameters identified by models of sequential moment restrictions containing unknown functions. Our results extend those of Chamberlain (1992b) and Ai and Chen (2003) for semiparametric conditional moment restriction...

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models offers some salient advantages over classical global parametric approaches. Consistency and...

A limit theory is established for autoregressive time series that smooths the transition between local and moderate deviations from unity and provides a transitional form that links conventional unit root distributions and the standard normal. Edgeworth expansions of the limit theory are given....

Some convenient limit properties of usual information criteria are given for cointegrating rank selection. Allowing for a nonparametric short memory component and using a reduced rank regression with only a single lag, standard information criteria are shown to be weakly consistent in the choice...