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Output Composition of the Monetary PolicyTransmission Mechanism: Is Australia Different?
Tuan PhanAustralian National University
November 2013
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Outline
I Motivation
I Literature
I Methodology
I DataI Results
I Output compositionI Housing and non-housing investmentI Durable and non-durable consumption
I Conclusion
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Motivation
I Concensus: i ↑−→ Y ↓ (output, aggregate demand)
I Two main channels:- Investment channel: i ↑−→ I ↓−→ Y ↓- Consumption channel: i ↑−→ C ↓−→ Y ↓
I Deeper look: Which channel is more important(dominant)?
I Consumption smoothing and Investment volatility: investmentchannel might be more sensitive to interest rate changes.
I Answers can be informative for the theory on the channels ofthe monetary policy transmission mechanism, and alsopotentially help central bankers/policy makers in monitoringthe economy.
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Literature
I Angeloni, I, Kashyap, A, Mojon, B and Terlizzese, D 2003,‘The Output Composition Puzzle: A Difference in theMonetary Transmission Mechanism in the Euro Area andU.S.’, Journal of Money, Credit and Banking, 35(6):- European countries (1970 - 2000): I>C- US (1965 - 2001): C>I “Output Composition Puzzle”
I Fujiwara, I 2004, ‘Output composition of the monetary policytransmission mechanism in Japan’, The B.E. Journal ofMacroeconomics, 0(1): I>C (1980 - 2003)
I Reasons: most possible: structure of housing markets (iaffects C and I in housing markets)
I If so, we can guess: for Australia: C>I, or at least closer toUS rather than Japan or Euro area.
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The VAR models
I Christiano, Eichenbaum and Evans (2001): 10 variables(consumption, investment, other GDP components, CPI, realwages, labour productivity, policy rate, the profit-to-GDPratio, money and share price index)
I Erceg and Levin (2002): 6 variables (consumption,investment, other GDP components, CPI, commodity prices,and policy rate)
I Generalized Erceg and Levin (2002): add 2 variables (bondyields and money)
I Peersman and Smets (2003): 7 endogenous variables(consumption, investment, other GDP components,commodity prices, money, policy rate, and the real effectiveexchange rate), 3 exogenous variables (the US federal fundsrate, the US GDP, and the US price index) for Australia andthe Euro area; oil prices for the US
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Data
I Australia, the Euro area, the US
I Quarterly data for the period 1982Q3–2007Q4
I Log form
I 1 or 2 lag structure
I Exogenous variables for all VARs for Australia
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Output composition (Consumption and Investmentchannels)
Results are based on 2 indicators:
I Impulse Responses: Proportional effect
I Contribution: Size effect
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Impulse Responses for AustraliaConsumption Investment Other GDP CPI Policy rate
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Impulse Responses for Euro areaConsumption Investment Other GDP CPI Policy rate
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Impulse Responses for the USConsumption Investment Other GDP CPI Policy rate
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Proportional effect
I Investment reacts stronger at peak, but comes back faster
I Consumption stays significant for longer period
I Investment responds relatively strongest in Australia, then US,then Euro area
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Calculation of Size contribution
1. Step 1
IC × weightC
C × weightC + I × weightI +G× weightG= C1
II × weightI
C × weightC + I × weightI +G× weightG= I1
2. Step 2
IC1
C1 + I1= C2
II1
C1 + I1= I2
So C2 + I2 = 1. Normally C2, I2 ∈ (0, 1).If C2 > 0.5⇒ C > I.If C2 < 0.5⇒ I > C.
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Shares of GDP components
Country/Region Consumption Investment Other GDP components
Australia 0.54 0.17 0.29Euro area 0.57 0.21 0.22
US 0.65 0.16 0.19
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Consumption contributionAustralia Euro area US
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Size contribution results
I Consumption channel is much weaker in Australia (Investmentchannel is much stronger).
I In the Euro area and the US: not clear whether investment orconsumption channel is dominant.
So what are the main reasons of the differences between Australiaand the two comparators?
I Might be the housing investment (themore-interest-rate-sensitive component of investment)?
I To check: decompose investment into housing andnon-housing investment
I Use the same VARs, the same techniques (proportional andsize effect)
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Housing and non-housing investment: impulse responsesAustralia Euro area US
Housing Non-housing Housing Non-housing Housing Non-housing
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Shares of housing and non-housing investment
Country Housing Non-housing
/Region In GDP (In investment) In GDP (In investment)
Australia 0.06 (35%) 0.11 (65%)
Euro area 0.075 (36%) 0.135 (64%)
US 0.05 (31%) 0.11 (69%)
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Housing contributionAustralia Euro area US
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Housing contribution results
I Housing contribution is higher in Australia and the US.
I Housing contribution is much lower in the Euro area.
I Therefore, the difference in housing investment responsesrelatively to non-housing investment is likely the key reasonbehind the difference between Australia and the Euro area.
I Remain: between Australia and the US?
I Next: decompose consumption into durable consumption(more sensitive to interest rate changes) and non-durableconsumption (for Australia and the US).
I Use the same VARs, the same techniques (proportional andsize effect).
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Durable and non-durable consumption: impulse responsesAustralia US
Durable Non-durable Durable Non-durable
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Shares of durable and non-durable consumption
Country Durable consumption Non-durable consumption
/Region In GDP (In consumption) In GDP (In consumption)
Australia 0.04 (7.5%) 0.54 (92.5%)
US 0.055 (8.5%) 0.595 (91.5%)
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Durable consumption contributionAustralia US
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Durable and non-durable contribution results
I Durable contribution is around 0.3–0.4 in both Australia andthe US (though the band is much narrower in the US).
I Therefore, the difference in the shares of consumption andinvestment in total GDP is the main reason behind the outputcompostion difference between Australia and the US.
Country/Region Consumption Investment Other GDP components
Australia 0.54 0.17 0.29US 0.65 0.16 0.19
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Conclusion
I Investment channel is stronger compared to consumptionchannel in Australia.
I In the Euro area and the US, the two channels are basicallynot different when shares are taken into account.
The reasons behind:
I Between Australia and the Euro area: the housing investmentresponses.
I Between Australia and the US: the shares in the total GDP.
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Thank you!