How Useful Are Estimated DSGE Model Forecasts for Central Bankers?

bank, banker, DSGE, forecast, macroeconomic

A Scalable Near-Memory Architecture for Training Deep Neural Networks on Large In-Memory Datasets

Most investigations into near-memory hardware accelerators for deep neural networks have primarily focused on inference, while the potential of accelerating training has received relatively little attention so far. Based on an in-depth analysis of the key computational patterns in state-of-the-art gradient-based training methods, we propose an efficient near-memory acceleration engine called NTX that can be used to train state-of-the-art deep convolutional neural networks at scale. Our main contributions are: (i) a loose coupling of RISC-V cores and NTX co-processors reducing offloading overhead by 7 x over previously published results; (ii) an optimized IEEE 754 compliant data path for fast high-precision convolutions and gradient propagation; (iii) evaluation of near-memory computing with NTX embedded into residual area on the Logic Base die of a Hybrid Memory Cube; and (iv) a scaling analysis to meshes of HMCs in a data center scenario. We demonstrate a 2.7 x energy efficiency improvement of NTX over contemporary GPUs at 4.4 x less silicon area, and a compute performance of 1.2 Tflop/s for training large state-of-the-art networks with full floating-point precision. At the data center scale, a mesh of NTX achieves above 95 percent parallel and energy efficiency, while providing 2.1 x energy savings or 3.1 x performance improvement over a GPU-based system

Modeling the dynamics of inflation compensation

This paper investigates the relationship between short-term and long-term inflation expectations using daily data on inflation compensation. We use a flexible econometric model which allows us to uncover this relationship in a data-based manner. We relate our …ndings to the issue of whether inflation expectations are anchored, unmoored or contained. Our empirical results indicate no support for either unmoored or …rmly anchored inflation expectations. Most evidence indicates that inflation expectations are contained

Is time-variant information stickiness state-dependent?

This paper estimates information stickiness with regard to inflation expectations in the United States and the Eurozone for the 1981/06–2015/12 and 1998/Q4–2015/Q2 periods, respectively, and further investigates whether such information stickiness is state- dependent. Based on a bootstrap sub-sample rolling-window estimation, we find that information stickiness varies over time, which contradicts the strict time dependency implied under sticky-information theory. We provide evidence that information stickiness depends on inflation volatility, which indicates that information stickiness is state-dependent and that it has a time trend. Using a threshold model, we estimate structural changes in the state- dependence and time-trend of information stickiness. The results show that information stickiness has been more dependent on inflation volatility and has had a higher time-trend in both regions following the 2008 financial crisis.info:eu-repo/semantics/publishedVersio