Forecasting inflation with thick models and neural networks

This paper applies linear and neural network-based “thick” models for forecasting inflation based on Phillips–curve formulations in the USA, Japan and the euro area. Thick models represent “trimmed mean” forecasts from several neural network models. They outperform the best performing linear models for “real-time” and “bootstrap” forecasts for service indices for the euro area, and do well, sometimes better, for the more general consumer and producer price indices across a variety of countries. JEL Classification: C12, E31bootstrap, Neural Networks, Phillips Curves, real-time forecasting, Thick Models

Inflation Targeting and Q Volatility in Small Open Economies

This paper examines the welfare implications of managing Q with inflation targeting by monetary authorities who have to "learn" the laws of motion for both inflation and the rate of growth of Q. Our results show that the Central Bank can achieve great success in reducing the volatility of GDP growth with basically the same inflation volatility, if it incorporates this additional target into its policy regime. However, the welfare effects are generally lower, in terms of consumption, when the monetary authorithy reacts to Q growth as well as inflationTobin's Q, monetary policy, learning

Financial liberation and adjustment in Chile and New Zealand

The authors analyze macrodynamic adjustment during financial liberalization in Chile and New Zealand. During the adjustment to more open capital accounts in the late 1970s or mid-1980s, both countries experienced appreciation of the real exchange rate and a collapse of net exports, while domestic interest rates slowly converged to international levels. The authors develop and estimate a two-sector dynamic model using both current and time-varying parameters. They find the domestic interest rate to be more responsive to shocks under imperfect capital mobility, the real exchange rate more responsive under perfect capital mobility. In short, liberalization of the capital account does not eliminate volatility but rather shifts it from the domestic interest rate to the real exchange rate.Economic Theory&Research,Macroeconomic Management,Economic Stabilization,Environmental Economics&Policies,Banks&Banking Reform

The Response of Australian Stock, Foreign Exchange and Bond Markets to Foreign Asset Returns and Volatilities

This paper is a data-analytic study of the relationships among international asset price volatilities and the time-varying correlations of asset returns in a small open economy (Australia) with international asset returns. Making use of recent developments in time-series approaches to volatility estimation, impulse response functions, variance decomposition, and Kalman filtering, I show that the Australian stock market volatility is most closely linked with volatility in the UK stock market, and the correlation of Australian stock returns with UK returns are high when there is increasing turbulence in financial markets. Volatility in the Australian dollar/US dollar exchange rate is most closely linked with volatility measures of the US dollar/Canadian dollar rate, and volatility in Australian long-term bond yields is most closely linked to volatility measures of long term German bond returns. The results indicate that asset markets in a small open economy can adapt in different ways during periods of high or increasing volatility. The ways in which domestic volatility measures react to foreign turbulence, and the ways in which domestic returns correlate with international returns, depend on the particular circumstances (such as transactions costs and degree of risk aversion) which prevail in each financial market.

Output Gap Estimation for Inflation Forecasting: The Case of the Philippines

This paper examines alternative estimation models for obtaining output gap measures for the Philippines. These measures are combined with the rates of growth of broad money, nominal wages and oil prices for forecasting inflation. We find that models which combine these leading indicators in a nonlinear way out-perform other linear combinations of these variables for out-of-sample forecasting performance

Structural Dynamic Analysis of a Spacecraft Multi-DOF Shaker Table

Finite element enforced response analysis was performed on a three axis expander head shaker table to aid in the design of the table structure and vibration control system. The payload for this shaker system is a generic spacecraft with a multitude of flexible modes across a broad frequency band. A Craig-Bampton representation of the spacecraft was used to expedite analysis of multiple shaker table designs. The analysis examines the required forces in the actuators for a constant amplitude base acceleration sine sweep test, the resulting forces in the spacecraft and table attachment restraints, and the resulting accelerations on the spacecraft structure. The results show the spacecraft response is very high at the spacecraft center of gravity (CG) due to the high CG offset and cantilever effect of the low frequency spacecraft bending modes. The high response can be addressed by "notching" the input vibration levels to avoid over-testing the spacecraft. At frequencies above 25 Hz, the spacecraft modal effective masses are very small, and the response of the shaker table dominates the response. Anti-resonances of the shaker table in the frequency range of interest reduce the acceleration output and require much higher actuator forces to achieve the acceleration specification. These effects may require stiffening the shaker structure to move the modes out of the test frequency range or increasing the shaker table damping

Intelligent (Autonomous) Power Controller Development for Human Deep Space Exploration

As NASAs Evolvable Mars Campaign and other exploration initiatives continue to mature they have identified the need for more autonomous operations of the power system. For current human space operations such as the International Space Station, the paradigm is to perform the planning, operation and fault diagnosis from the ground. However, the dual problems of communication lag as well as limited communication bandwidth beyond GEO synchronous orbit, underscore the need to change the operation methodology for human operation in deep space. To address this need, for the past several years the Glenn Research Center has had an effort to develop an autonomous power controller for human deep space vehicles. This presentation discusses the present roadmap for deep space exploration along with a description of conceptual power system architecture for exploration modules. It then contrasts the present ground centric control and management architecture with limited autonomy on-board the spacecraft with an advanced autonomous power control system that features ground based monitoring with a spacecraft mission manager with autonomous control of all core systems, including power. It then presents a functional breakdown of the autonomous power control system and examines its operation in both normal and fault modes. Finally, it discusses progress made in the development of a real-time power system model and how it is being used to evaluate the performance of the controller and well as using it for verification of the overall operation