Since 2009, stock markets have resided in a long bull market regime. Passive investment strategies have succeeded during this low-volatility growth period. From 2018 on, however, there was a transition into a more volatile market environment interspersed by corrections increasing in amplitude...

We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which we apply to the housing markets of China's major cities. Building on the Log-Periodic Power Law Singular (LPPLS) model of self-reinforcing feedback loops, we use the quantile...

We examine forecast accuracy and efficiency of the Social Security Administration’s projections for cost rate, trust fund balance, trust fund ratio made during 1980-2020 with horizons up to 95 years. We find that the reported deterioration in the accuracy of the forecasts during 2010’s has...

This paper presents a global model linking individual country vector error-correcting models in which the domestic variables are related to the country-specific variables as an approximate solution to a global common factor model. This global VAR is estimated for 26 countries, the euro area...

This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic variables, xit, to their foreign counterparts,...

This paper focuses on testing long run macroeconomic relations for interest rates, equity, prices and exchange rates within a model of the global economy. It considers a number of plausible long run relationships suggested by arbitrage in financial and goods markets, and uses the global vector...

New Keynesian Phillips Curves (NKPC) have been extensively used in the analysis of monetary policy, but yet there are a number of issues of concern about how they are estimated and then related to the underlying macroeconomic theory. The first is whether such equations are identified. To check...

We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...