Is the U.S. in Recession? CBS Experts Weigh in on the Economic Outlook
New data has sparked a debate about the state of the economy. Here’s what some of our faculty members had to say.
New data has sparked a debate about the state of the economy. Here’s what some of our faculty members had to say.
There is perhaps no topic that is more important for the functioning of a market economy than competition policy. The theorems and analyses stating that market economies deliver benefits in the form of higher living standards and lower prices are all based on the assumption that there is effective competition in the market. At the same time when Adam Smith emphasised that competitive markets deliver enormous benefits, he also emphasised the tendency of firms to suppress competition.
The veteran economist and CBS professor joined Professor Brett House to explore how erratic policymaking, rising tariffs, and politicized institutions are shaking global confidence in the U.S. economy.
During a recent Distinguished Speakers Series event, the Senior Partner and Chair of North America at McKinsey shared leadership insights on AI business strategy, climate innovation, and the future of work.
Insights from Columbia Business School faculty explain how the president’s “Liberation Day” tariffs are fueling market volatility, undermining global economic stability, and impacting the Fed's ability to lower interest rates.
A Columbia Business School study shows that experiencing a recession in young adulthood leads to lasting support for wealth redistribution—but mostly for one’s own group.
Two experiments investigated the hypothesis that strategic behavioral mimicry can facilitate negotiation outcomes. Study 1 used an employment negotiation with multiple issues, and demonstrated that strategic behavioral mimicry facilitated outcomes at both the individual and dyadic levels: Negotiators who mimicked the mannerisms of their opponents both secured better individual outcomes, and their dyads as a whole also performed better when mimicking occurred compared to when it did not.
We consider the problem of nonparametric estimation of signal singularities from indirect and noisy observations. Here by singularity, we mean a discontinuity (change-point) of the signal or of its derivative. The model of indirect observations we consider is that of a linear transform of the signal, observed in white noise. The estimation problem is analyzed in a minimax framework. We provide lower bounds for minimax risks and propose rate-optimal estimation procedures.
We focus on the problem of adaptive estimation of signal singularities from indirect and noisy observations. A typical example of such a singularity is a discontinuity (change-point) of the signal or of its derivative. We develop a change-point estimator which adapts to the unknown smoothness of a nuisance deterministic component and to an unknown jump amplitude. We show that the proposed estimator attains optimal adaptive rates of convergence. A simulation study demonstrates reasonable practical behavior of the proposed adaptive estimates.
We consider a revenue management, network capacity control problem in a setting where heterogeneous customers choose among the various products offered by a firm (e.g., different flight times, fare classes, and/or routings). Customers may therefore substitute if their preferred products are not offered. These individual customer choice decisions are modeled as a very general stochastic sequence of customers, each of whom has an ordered list of preferences. Minimal assumptions are made about the statistical properties of this demand sequence.