Download σ I /σ Y

MACROECONOMETRICS
LAB 6 – CALIBRATION
ROADMAP

What is the reality of business cycles?

What are the business cycles?

How can we try to model them

Are we happy with ourselves?

Nothing about STATA 
Business cycles – US data
Y:Q of peak
No. of Q to recovery
GDP change (to average)
1948:4
4
-1.1%
1953:2
4
-3.1%
1957:3
2
-2.2%
1960:1
4
-0.8%
1969:3
3
-0.9%
1973:4
5
-4.1%
1980:1
1
-1%
1981:3
4
-2.8%
1990:2
3
-1.6%
Business cycles – US data
Component of GDP
Average share
in GDP (%)
Share of GDP during
recession (%)
Consumption
(nondurables)
24.8
14,3
Consumption
(durables)
6.9
6,7
Investment
(in equipment)
10
21
Investment
(residential structures)
5.1
14.7
Inventories
0.6
30,7
!!!
Business cycles – US data
Variable
Average change in
recession (%)
Real GDP
-4.7
Employment
-2.2
Average no. of hours
(per week)
-0.9
Productivity
(output per worker)
-1.4
Wages
-0.5
Unemployment
2,1
Business cycles – conclusions

No regularity
–

Uneven distribution
–

From 1 do 5 quarters, longest aren’t hardest
Nothing deterministic
–

On average 5, but sometimes 9 and sometimes 1
Kondratiev and others – no applicability
Shocks
–
–
Seem to be random
Have to have a mechanism to propagate over the economy
Business cycles - conclusions

ANY (!) model has to reproduce
–
–

Anti-cyclical unemployment
Pro-cyclical employment, productivity AND slightly
pro-cyclical wages (!)
REMARK:
–
–
–
Neoclassical model has NO business cycles!
Keynesian model WILL NOT WORK
In Lucas we could, but assumptions not realistic
Kydland and Prescott (Minnesota)

Cycles driven by technological shocks
–
How do we get recessions? Sudden amnesia?
PROPAGATION-ACCELERATION MECHANISM

Technological improvement in any sector
–
How does it spread into whole economy?
GENERAL EQUILIBRIUM MODEL
Nature of the modelling

Consumer equation
–
–

Producer equation
–

IntERtemporal
IntRAtemporal
Solow function works well, if A stochastic
Market clearing condition
–
–
–
Labour market
Good’s market
Financial markets
New techniques and methods

Separation variables
–
–

Method:
–
–
–

State: A, G, K optimal
Decision: L, C, I (=> w, r)
Detrend
Substract the deterministic trend
Obtain a zero deterministic steady-state PROCESS (!)
Analyse laws of motion
How well do we do?

Method:
–
–
–
–
estimate moments on real economy
simulate your model
estimate moments on the modelled economy
compare
How well do we do?
US real data
Simulated models
σY
1.92
1.3
σG/σY
0.45
0.31
σI/σY
2.75
3.15
cov(L, Y/L)
-0.14
0.93
σL/σY
0.96
0.49
How well do we do?
US real data
Simulated models
σY
1.92
1.3
σG/σY
0.45
0.31
σI/σY
2.75
3.15
cov(L, Y/L)
-0.14
0.93
σL/σY
0.96
0.49
How well do we do?
US real data
Simulated models
σY
1.92
1.3
σG/σY
0.45
0.31
σI/σY
2.75
3.15
cov(L, Y/L)
-0.14
0.93
σL/σY
0.96
0.49
How well do we do?
US real data
Simulated models
σY
1.92
1.3
σG/σY
0.45
0.31
σI/σY
2.75
3.15
cov(L, Y/L)
-0.14
0.93
σL/σY
0.96
0.49
How well do we do?
US real data
Simulated models
σY
1.92
1.3
σG/σY
0.45
0.31
σI/σY
2.75
3.15
cov(L, Y/L)
-0.14
0.93
σL/σY
0.96
0.49
How well do we do?
US real data
Simulated models
σY
1.92
1.3
σG/σY
0.45
0.31
σI/σY
2.75
3.15
cov(L, Y/L)
-0.14
0.93
σL/σY
0.96
0.49
!!!