Near unit roots,cointegration, and the term structure of interest rates

The term structure of interest rates is often modelled as a cointegrated system with the yield spreads forming the cointegrating vectors. Testing whether the yield spreads span the cointegration space is problematic because conventional tests on the cointegration vectors tend to overreject when the largest autoregressive roots deviate from unity, as is likely to be the case with interest rates. A new test that is robust w.r.t. deviations from the exact unit root assumption is developed and applied to monthly US interest rate data from 1952:1–1991:2. Taking into account the regime shift in 1979, the hypothesis of the yield spreads being the cointegrating vectors cannot be rejected using the robust test. Copyright © 2000 John Wiley & Sons, Ltd.     

Data‐Driven Identification Constraints for DSGE Models

We propose imposing data‐driven identification constraints to alleviate the multimodality problem arising in the estimation of poorly identified dynamic stochastic general equilibrium models under non‐informative prior distributions. We also devise an iterative procedure based on the posterior density of the parameters for finding these constraints. An empirical application to the Smets and Wouters ( 2007 ) model demonstrates the properties of the estimation method, and shows how the problem of multimodal posterior distributions caused by parameter redundancy is eliminated by identification constraints. Out‐of‐sample forecast comparisons as well as Bayes factors lend support to the constrained model.     

Temporal Dynamics in Acquisition Behavior: The Effects of Activity Load on Strategic Momentum

Momentum theory suggests that acquisition experience leads to acquisition momentum in the form of a higher likelihood of subsequent acquisitions of the same type. However, this argument has been challenged theoretically and empirically. We reconcile conflicting predictions and findings of prior research and extend momentum theory by incorporating activity load as a novel causal mechanism to both replicate the base finding and explain deviations from it. We find that a high activity load due to increased acquisition activity acts as a counterforce to momentum, decreasing the likelihood of subsequent acquisitions of the same type. Moreover, we also find that the interplay of routines, cognitive frames, and activity load causes companies to alternate between different types of acquisitions – from small to large and from large to small – as management engages in attention modulation to preserve momentum. Taken together, our arguments and findings contribute to an improved understanding of temporal patterns of acquisition behaviour.