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.
According to human capital theory, technological change will influence the retirement decisions of older workers in two ways. First, workers in industries with high rates of technological change will retire later if there is a net positive correlation between technological change and on-the-job training. Second, an unexpected change in the rate of technological change will induce older workers to retire sooner because the required amount of retraining will be an unattractive investment.
We develop a simple O(n log n) solution method for the standard lot-sizing model with backlogging and a study horizon of n periods. Production costs are fixed plus linear and holding and backlogging costs are linear with general time-dependent parameters. The algorithm has linear [O(n)] time complexity for several important subclasses of the general model. We show how a slight adaptation of the algorithm can be used for the detection of a minimal forecast horizon and associated planning horizon.
We consider distribution systems with a single depot and many retailers each of which faces external demands for a single item that occurs at a specific deterministic demand rate. All stock enters the systems through the depot where it can be stored and then picked up and distributed to the retailers by a fleet of vehicles, combining deliveries into efficient routes. We extend earlier methods for obtaining low complexity lower bounds and heuristics for systems without central stock.