The Relationship between Growth and Volatility under Alternative Shocks

This paper presents a simple stochastic endogenous growth model with multiple shocks � a preference shock and a learning shock. The model is used to predict alternative relationships between growth and volatility on the basis of the underlying impulse source of fluctuations.

Monetary Stabilisation Policy and Long-run Growth

This paper presents a stochastic monetary growth model with nominal rigidities and active monetary policy in which technological change contains both deliberate (internal) and serendipitous (external) learning mechanisms. The model is used to describe how the implications of monetary stabilization policy for the long-run economic performance could change due to the ambiguity on the relationship between secular growth and cyclical volatilitygrowth, cyclies, money, stabilisation policy

Uncertainty, learning and growth

The paper extends Blackburn and Galindev (2003)' s stochastic growth model in which productivity growth entails both external and internal learning behaviour with a Constant Relative Risk Aversion utility function and productivity shocks. Consequently, the relationship between long-term growth and short-term volatility depends not only on the relative importance of each learning mechanism but also on a parameter measuring individuals' attitude towards risk.Growth; Uncertainty, Learning

On the Effect of Monetary Stabilisation Policy on Long-run Growth

This paper presents a stochastic monetary growth model with nominal rigidities and active monetary policy in which technological change contains both deliberate (internal) and serendipitous (external) learning mechanisms. The model is used to describe how the implications of monetary stabilization policy for the long-run economic performance could change due to the ambiguity on the relationship between secular growth and cyclical volatility

The Relationship between Growth and Volatility under Alternative Shocks

This paper presents a simple stochastic endogenous growth model with multiple shocks a preference shock and a learning shock. The model is used to predict alternative relationships between growth and volatility on the basis of the underlying impulse source of fluctuations

On the Effect of Monetary Stabilisation Policy on Long-run Growth (Revised September 2005)

This paper presents a stochastic monetary growth model with nominal rigidities and active monetary policy in which technological change contains both deliberate (internal) and serendipitous (external) learning mechanisms. The model is used to describe how the implications of monetary stabilization policy for the long-run economic performance could change due to the ambiguity on the relationship between secular growth and cyclical volatility.

Discretization of highly persistent correlated AR(1) shocks

The finite state Markov-Chain approximation method developed by Tauchen (1986) and Tauchen and Hussey (1991) is widely used in economics, finance and econometrics in solving for functional equations where state variables follow an autoregressive process. For highly persistent processes, the method requires a large number of discrete values for the state variables to produce close approximations which leads to an undesirable reduction in computational speed, especially in a multidimensional case. This paper proposes an alternative method of discretizing vector autoregressions. This method can be treated as an extension of Rouwenhorst's (1995) method which, according to our experiments, outperforms the existing methods in the scalar case for highly persistent processes. The new method works well as an approximation that is much more robust to the number of discrete values for a wide range of the parameter space.Finite State Markov-Chain Approximation; Discretization of Multivariate Autoregressive Processes; Transition Matrix; Numerical Methods; Value Function Iteration; the Rouwenhorst method; VAR

Discretization of highly persistent correlated AR(1) shocks

The finite state Markov-Chain approximation method developed by Tauchen (1986) and Tauchen and Hussey (1991) is widely used in economics, finance and econometrics in solving for functional equations where state variables follow an autoregressive process. For highly persistent processes, the method requires a large number of discrete values for the state variables to produce close approximations which leads to an undesirable reduction in computational speed, especially in a multidimensional case. This paper proposes an alternative method of discretizing vector autoregressions. This method can be treated as an extension of Rouwenhorst's (1995) method which, according to our experiments, outperforms the existing methods in the scalar case for highly persistent processes. The new method works well as an approximation that is much more robust to the number of discrete values for a wide range of the parameter space

Leisure goods, education attainment and fertility choice

Fertility, Leisure goods, Technological progress, Growth, J13, O11, O33, O40,