The Consumption-Wealth Ratio Under Asymmetric Adjustment

This paper argues that nonlinear adjustment may provide a better explanation of fluctuations in the consumption-wealth ratio. The nonlinearity is captured by a Markov-switching vector error-correction model that allows the dynamics of the relationship to differ across regimes. Estimation of the system suggests that these states are related to the behaviour of financial markets. In fact, estimation of the system suggests that short-term deviations in the consumption-wealth ratio will forecast either asset returns or consumption growth: the first when changes in wealth are transitory; the second when changes in wealth are permanent. Our approach uncovers a richer and more complex dynamics in the consumption-wealth ratio than previous results in the literature, whilst being in accordance with theoretical predictions of a simple model of consumption under uncertainty.Consumption, Financial markets, Uncertainty, Forecast, Markov switching

On the Stability of the Wealth Effect

Evidence of instability of the wealth effect in the USA is presented through the estimation of a Markov switching model of the long-run aggregate consumption function. The dating of the regimes appears to bear relation to movements in asset prices. A model-based explanation of the findings is suggested, highlighting the importance of the short-run relation between consumption, income and wealth in explaining the estimated long-run coefficients.Parameter instability, Markov switching, Consumption, Wealth effect.

Taylor-type rules versus optimal policy in a Markov-switching economy¤

We analyse the e®ect of uncertainty concerning the state and the nature of asset price movements on the optimal monetary policy response. Uncertainty is modelled by adding Markov-switching shocks to a DSGE model with capital accumulation. In our analysis we consider both Taylor-type rules and optimal policy. Taylor rules have been shown to provide a good description of US monetary policy. Deviations from its implied interest rates have been associated with risks of ¯nancial disruptions. Whereas interest rates in Taylor-type rules respond to a small subset of information, optimal policy considers all state variables and shocks. Our results suggest that, when a bubble bursts, the Taylor rule fails to achieve a soft landing, contrary to the optimal policy.Asset Prices, Monetary Policy, Markov Switching.

Taylor-type rules versus optimal policy in a Markov-switching economy

We analyse the effect of uncertainty concerning the state and the nature of asset price movements on the optimal monetary policy response. Uncertainty is modeled by adding Markov-switching shocks to a DSGE model with capital accumulation. In our analysis we consider both Taylor-type rules and optimal policy. Taylor rules have been shown to provide a good description of US monetary policy. Deviations from its implied interest rates have been associated with risks of financial disruptions. Whereas interest rates in Taylor-type rules respond to a small subset of information, optimal policy considers all state variables and shocks. Our results suggest that, when a bubble bursts, the Taylor rule fails to achieve a soft landing, contrary to the optimal policy.Asset Prices, Monetary Policy, Markov Switching

On the Stability of the Wealth Effect

Evidence of instability of the wealth effect in the USA is presented through the estimation of a Markov switching model of the long-run aggregate consumption function. The dating of the regimes appears to bear relation to movements in asset prices. A model-based explanation of the findings is suggested, highlighting the importance of the short-run relation between consumption, income and wealth in explaining the estimated long-run coefficients.Parameter instability; Markov switching; Consumption; Wealth effect

Taylor-type rules versus optimal policy in a Markov-switching economy

We analyse the effect of uncertainty concerning the state and the nature of asset price movements on the optimal monetary policy response. Uncertainty is modelled by adding Markov-switching shocks to a DSGE model with capital accumulation. In our analysis we consider both Taylor-type rules and optimal policy. Taylor rules have been shown to provide a good description of US monetary policy. Deviations from its implied interest rates have been associated with risks of financial disruptions. Whereas interest rates in Taylor-type rules respond to a small subset of information, optimal policy considers all state variables and shocks. Our results suggest that, when a bubble bursts, the Taylor rule fails to achieve a soft landing, contrary to the optimal policy.Asset Prices, Monetary Policy, Markov Switching.

On the Stablity of the Wealth Effect

Evidence of instability of the wealth effect in the USA is presented through the estimation of a Markov switching model of the long-run aggregate consumption function. The dating of the regimes appears to bear relation to movements in asset prices. A model-based explanation of the findings is suggested, highlighting the importance of the short-run relation between consumption, income and wealth in explaining the estimated long-run coefficients.Parameter instability; Markov switching; consumption; wealth effect.

The Consumption-Wealth Ratio Under Asymmetric Adjustment

This paper argues that nonlinear adjustment may provide a better explanation of °uctuations in the consumption-wealth ratio. The nonlinearity is captured by a Markov-switching vector error-correction model that allows the dynamics of the relationship to di®er across regimes. Estimation of the system suggests that these states are related to the behaviour of ¯nancial markets. In fact, estimation of the system suggests that short-term deviations in the consumption-wealth ratio will forecast either asset returns or consumption growth: the ¯rst when changes in wealth are transitory; the second when changes in wealth are permanent. Our approach uncovers a richer and more complex dynamics in the consumption-wealth ratio than previous results in the literature, whilst being in accordance with theoretical predictions of a simple model of consumption under uncertainty.Consumption; Financial markets; Uncertainty; Forecast; Markov switching

Load balancing for constraint solving with GPUs

Solving a complex Constraint Satisfaction Problem (CSP) is a computationally hard task which may require a considerable amount of time. Parallelism has been applied successfully to the job and there are already many applications capable of harnessing the parallel power of modern CPUs to speed up the solving process. Current Graphics Processing Units (GPUs), containing from a few hundred to a few thousand cores, possess a level of parallelism that surpasses that of CPUs and there are much less applications capable of solving CSPs on GPUs, leaving space for further improvement. This paper describes work in progress in the solving of CSPs on GPUs, CPUs and other devices, such as Intel Many Integrated Cores (MICs), in parallel. It presents the gains obtained when applying more devices to solve some problems and the main challenges that must be faced when using devices with as different architectures as CPUs and GPUs, with a greater focus on how to effectively achieve good load balancing between such heterogeneous devices