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Class 1
Macroeconomics 2
Prof. Michael HaliassosCristian Badarinza
Goethe University, Frankfurt am Main
Wintersemester 2010/2011
October 19, 2010
Introduction
• Contact: [email protected]
• Office hours: Monday, 16:00-18:00, HoF Room 363
• Our plan for the semester:– Class:
• Summary of the Lecture: clarification questions
• Problems and further applications
– Mentorium:• Solutions to Exercises
• Online material: check updates on the course website
October 19, 2010 2Class 1
DataConsumer
Firms
ECB
Modern macroeconomics
Why did macroeconomists fail to
forecast the crisis?
October 19, 2010 Class 1 3
A question you may have asked yourselves
Ignorance
True fundamental uncertainty
Uncertainty
Is macroeconomics really a science?
Yes
Empiricalanalysis
Theoreticalmodeling
Implications forgovernment and monetary policy
grossly underestimated byfinancial institutions
but: we learn from historyECB systemic risk board
can be reduced bybetter understandingthe incentives of agents
Modern macroeconomics
October 19, 2010 Class 1 4
Ignorance
True fundamental uncertainty
Uncertainty
subject of this course
• Three elements– data analysis
– macro modeling
– policy implications
• Characteristics– formal mathematical treatment
– focus on general methods and principles
Summary of the Lecture
• trend and cyclical components
• stabilization policies
• business cycles– aggregate economic activity
– organization in business enterprises
– expansions and contractions
– duration of more than one year
– recurrent but not periodic
• dating and measurement
• volatility, correlation and persistence
October 19, 2010 Class 1 5
Questions about the Lecture?
Problem 1
• GDP (real, trend, cycle)
• Private consumption
• Public (government) consumption
• Public (government) investment
• Exports, imports and the current account balance
• Employment
• Wages and household savings
• Inflation
• Short-term interest rates, long-term interest rates
• etc.
October 19, 2010 Class 1 6
Statistical aggregated measures characterizing the business cycle
Problem 1
October 19, 2010 Class 1 13
Volatility and persistence: the rate of inflation
-3
-2
-1
0
1
2
3
4
5
6
91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
United States inflation rate Euro area inflation rate
low volatility and high persistencevery low volatility in Euro area
high volatility and low persistence
-16
-12
-8
-4
0
4
8
12
91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
United States industrial production growthEuro area industrial production growth
Problem 1
October 19, 2010 Class 1 14
Volatility and persistence: the rate of industrial production growth
high volatility and high persistencevery low volatility
very high volatility
0.0
0.4
0.8
1.2
1.6
2.0
91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
DAX Index DJ Euro Stoxx Index
Problem 1
October 19, 2010 Class 1 15
Volatility and persistence: stock market indices
low volatility
high volatility
high persistence
Problem 1
October 19, 2010 Class 1 16
-.04
.00
.04
.08
.12
.16
2
4
6
8
10
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
log GDP growth Unemployment rate
Co-movement in macroeconomic aggregates
Problem 1
October 19, 2010 Class 1 17
-.05
.00
.05
.10
.15
2
4
6
8
10
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
log wages growth Unemployment rate
Co-movement in macroeconomic aggregates
Problem 1
October 19, 2010 Class 1 18
-4
0
4
8
12
16
0
4
8
12
16
20
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Inflation Short term interest rate
Co-movement in macroeconomic aggregates
Problem 1
October 19, 2010 Class 1 19
-1.50E+12
-1.00E+12
-5.00E+11
0.00E+00
5.00E+11
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Household net savings Government net savings
Co-movement in macroeconomic aggregates
Problem 2
• decomposition of log GDP:
• the HP Filter:
• limiting cases
October 19, 2010 Class 1 20
[ ]∑ ∑= =
−+ −−−+−←T
t
T
ttttttt
HPt gggggyg
1 1
211 )()()(min λ
ttt cgy +=
Hodrick-Prescott filter
Problem 2
October 19, 2010 Class 1 21
Hodrick-Prescott filter
-1.0
-0.5
0.0
0.5
1.0
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=0
Problem 2
October 19, 2010 Class 1 22
Hodrick-Prescott filter
-.4
-.2
.0
.2
.4
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=1
Problem 2
October 19, 2010 Class 1 23
Hodrick-Prescott filter
-.6
-.4
-.2
.0
.2
.4
.6
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=10
Problem 2
October 19, 2010 Class 1 24
Hodrick-Prescott filter
-1.2
-0.8
-0.4
0.0
0.4
0.8
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=500
Problem 2
October 19, 2010 Class 1 25
Hodrick-Prescott filter
-1.5
-1.0
-0.5
0.0
0.5
1.0
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=2000
Problem 2
October 19, 2010 Class 1 26
Hodrick-Prescott filter
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=50000
Problem 2
October 19, 2010 Class 1 27
Hodrick-Prescott filter
-3
-2
-1
0
1
2
3
4
6
8
10
12
14
16
93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Variable Trend Cycle
lambda=10000000
Problem 2
October 19, 2010 Class 1 31
Hodrick-Prescott filter
• Drawbacks:– imprecise estimates at the end points of the time series
– arbitrary choice of lambda
– cannot capture structural breaks
• Further questions:– what is the trend component really?
• something like a permanent, long-run component, a potential value
– can we get a better understanding of it?
Problem 3
• why is it important to have proper identification of potential output?
– central bank• if output is below potential, decrease interest rates
• if output is above potential, increase interest rates, to avoid overheating
• very intense discussion around year 2000: did potential output increase?
– government• important to know whether output movements are due to cyclical or trend components
• cyclical movements short-run tax or industry policy
• trend movements long-run investment policy
October 19, 2010 Class 1 32
Estimating potential output: the production function method
Problem 3
October 19, 2010 Class 1 33
Estimating potential output: the production function method
Assume an aggregate production function for the economy:
B = total factor productivityK = aggregate capital stockL = aggregate number of hours worked
Problem 3
October 19, 2010 Class 1 34
Estimating potential output: the production function method
Working hours are given by:
u = unemployment rateN = total labor forceH = average number of working hours per person employed
Problem 3
A short note:– don‘t let yourself get confused by equations like the ones on the two
previous slides
– both equations are assumed to look like they do, they are not derivedand there is no true justification (at least not yet) for choosing themlike we did
– this means you are not supposed to justify why and when and who, just take them as given and work out the results which they imply
– very important: don‘t confuse assumptions with derived results
(more on this also later during the course)
October 19, 2010 Class 1 35
Estimating potential output: the production function method
Problem 3
October 19, 2010 Class 1 36
Estimating potential output: the production function method
Replace the equation for labor in the production function:
Take logs on both sides:
Problem 3
October 19, 2010 Class 1 37
Estimating potential output: the production function method
Now let bars denote long-run trend levels:
Again take logs on both sides:
potential output long-run unemployment rate
potential factor productivity
Problem 3
October 19, 2010 Class 1 38
Estimating potential output: the production function method
Subtracting the two equations in logs, we obtain:
Now, data needed on:• total factor productivity• working hours• unemployment• labor force
But: is there any data on productivity ? Not really.
Problem 3
October 19, 2010 Class 1 39
Estimating potential output: the production function method
Solution: estimate productivity from the production function directly:
Cookbook recipe:
1. collect data for GDP, capital and labor variables
2. estimate productivity
3. estimate cyclical components of all variables by HP filter
4. calculate output gap
October 19, 2010 Class 1 40
Problem 3Estimating potential output: the production function method
The contribution of the unemployment rate
October 19, 2010 Class 1 41
Problem 3Estimating potential output: the production function method
The contribution of aggregate hours worked