RDP 7903: Monetary Rules: A Preliminary Analysis Appendix B: The Impulses and Policy Regimes

This attachment briefly outlines each of the nine counterfactual shocks and the three monetary policy regimes.

1. The Counterfactual Shocks

• shocks to components of real aggregate demand
  
  

  – a sustained increase in real government current expenditure is generated by increasing the variable g₁ by 10% over the whole simulation period;

  – a sustained increase in real world exports is generated by increasing the variable x_w by 7.5% over the simulation period;

  – an increase in the household saving ratio is achieved by adjusting the constant term (d_O) in the long run household expenditure equation, log . The increase is equivalent to a sustained decrease of 1.5% in the desired level of consumption;

  – a sustained cut of 1% in the level of investment in business fixed capital is achieved by a once and for all shock to the long term desired rate of investment .

• supply side shocks
  
  

  – a sustained rise in award wages is generated by increasing the variable w_A by 5% over the full simulation period;

  – a sustained fall in the level of capacity of 2% is generated by altering the constant (y_o) in the capacity equation, .

  – a sustained increase in the world price level is generated by increasing the variables P_w, P_w1 and P_i by 5% over the simulation period.

• financial shocks
  
  

  – a cut in the demand for money of 3% is achieved by altering the constant (m_O) in the money demand equation, log .

  – a sustained increase of 10% in net Australian capital owned by overseas residents is generated by adjusting the constant term (f_O) in the long run equation, log .

In each case the impulse is ramped in to allow for the effects of the discretisation of the continuous model and the associated data transformations.

The size of the first four shocks was designed to produce similar initial effects on aggregate demand.

2. The Policy Regimes

The first regime, that of a rigid bond rate is simulated in the model by setting the bond rate to its control solution values. The second regime uses the estimated bond rate equation (equation 17), in which the bond rate responds to monetary expansion. This response is greatly strengthened in the third regime by adding the proportional gap between the simulated and control solution values for the money stock to the bond equation.

In all cases, the model variables were transformed after simulation to remove the discretisation and data transformation. Thus the graphs show the paths in terms of seasonally adjusted raw data.