Download Table 1 - Riccardo Fiorito

Riccardo Fiorito
University of Siena
Fiscal Policy and Recessions
May 2012
1. Goals and motivations
 Recessions are different from negative cycles
 Negative (and positive) cycles involve 50% of cases.
 Recessions are much less frequent
 This has important implications for fiscal policy
Here, Oecd annual data are used to show:
 the frequency and the depth of postwar recessions
 Number of countries involved in major recession episodes
Government Spending:
 Really countercyclical?
 Always useful?
 Discretionary spending: measure, timing and possible effects.
Graph 1: Textbook business cycle phases
F
trend
Actual output
B
(P
)A
E
output gap
(positive)
C
output gap
(negative)
D
A
 Output gaps ( yt - y*t ) refer to the areas ABC and CDE
 DGAP = dt - d* is the growth gap, i.e. the difference between actual (dt ) and potential growth (d*t)
 Recessions dt < d*t occur in phases BC and CD.
Phase1 = AB: dt > d*t and yt > y*t  ρ(DGAP, YGAP) >0
Phase2 = BC: dt < d*t and yt > y*t  ρ(DGAP, YGAP) <0
Phase3 = CD: dt < d*t and yt < y*t  ρ(DGAP, YGAP) >0
Phase4 = DE: dt > d*t and yt < y*t  ρ(DGAP, YGAP) <0
2
2. What the data say instead?
Table 1: Business cycle phases and recessions in a number of Oecd countries
Country
Austria
1961-2010
Belgium
1981-2010
Denmark
1972-2010
Finland
1971-2010
France
1979-2010
Iceland
1981-2010
Ireland
1991-2010
Italy
1964-2010
Japan
1967-2010
Netherlands
1970-2010
Norway
1963-2010
Spain
1966-2010
Sweden
1964-2010
UK
1971-2010
US
1961-2010
Number of
observations
50
30
39
40
32
30
20
47
44
41
48
45
47
40
50
Phase1
AB (44%)
21
(.42)
14
(.47)
18
(.46)
18
(.45)
15
(.47)
14
(.47)
7
(.35)
21
(.45)
21
(.48)
21
(.51)
21
(.44)
18
(.40)
19
(.40)
13
(.32)
23
(.46)
Phase2
BC (3%)
0
1
(.03)
2
(.05)
0
1
(.03)
2
(.07)
1
(.05)
1
(.02)
1
(.02)
1
(.02)
0
0
2
(.04)
3
(.07)
2
(.04)
Phase3
CD (9%)
4
(.08)
2
(.07)
6
(.13)
4
(.10)
2
(.06)
4
(.13)
2
(.10)
4
(.08)
4
(.09)
3
(.07)
2
(.04)
4
(.09)
5
(.11)
4
(.10)
5
(.10)
Phase4
DE (44%)
25
(.50)
13
(.43)
13
(.33)
18
(.45)
14
(.44)
10
(.33)
10
(.50)
21
(.45)
18
(.41)
16
(.39)
25
(.52)
23
(.51)
21
(.45)
20
(.50)
20
(.40)
Recessions
(12%)
.08
.10
.20
.10
.09
.20
.15
.11
.11
.10
.04
.09
.15
.17
.14
Legend : Oecd, Economic Outlook database. Numbers in parenthesis denote the percentage frequency of each phase.
3
A few stylized facts summarize what Table 1 and other analyses (Fiorito, 2012) say instead:
 Expansion phases (AB+DE) dominate (88%). AB and DE have the same frequency (.44)
 Recession phases (BC+CD) are much less frequent (12%)
 Within recessions, the BC portion (3%) occurs much less than the CD phase does (9%)
 Overall, in the full Oecd sample (Table 2), annual recessions involve about the 10% of cases
 Strong recessions - i.e. GDP contractions of at least 2% (Table 2) - are about the 4% of cases.
 Excluding last crisis, recessions and strong recessions are 8.2% and 2.5% of cases, respectively
 Recovery cases (DE) (dt > d*t ) still belong to negative output gap cases when fiscal expansion is recommended..
Major recession episodes  Number of countries involved (Table 3)
1. 1974-75  first oil shocks  12 countries over 26
2. Early 80s: a mixture between the 2nd oil shock and a (regional) Northern countries crisis: 8 (1981), 6 (1982) cases
3. Early 90s crisis: EMS fall  Lira, Peseta and UK Pound devaluation  12 countries
4. Last crisis peak in 2009: 27 Oecd countries over 30 have been involved!
Length of recessions (quarterly data)
 Most recessions last about 1-2 years. Using quarterly data (Table 4), recessions are more frequent but are still
less frequent than negative output cycles (50%). A distinction between contractions and recessions (at least two
consecutive quarters, is also made (Shiskin, 1974).
4
Table 2 – Recessions in the Oecd (1961-2011)
Country
Recessions
Australia
61, 83, 91
Austria
Belgium
Canada
Czech Republic
93-11
Denmark
66-11
Finland
France
63-11
Germany
Greece
Hungary
91-11
Iceland
Ireland
Italy
Japan
Strong recessions
Country
Recessions
Strong recessions
80, 98
98
77, 81, 09
75, 93, 09
82, 91, 09
09
09
82, 91, 09
Korea
70-11
Luxembourg
Mexico
Netherlands
75, 81, 09
82, 83, 86, 95, 09
75, 81, 82, 03, 09
75, 09
83, 86, 95, 09
09
09
09
81, 09
67, 68, 77, 78, 91, 08,
09
88, 09
67, 68, 78,
75, 80, 81, 93, 08, 09
New Zealand
62-11
Norway
76, 90, 91, 92, 93, 09
91, 92, 09
91
91
75, 93, 09
09
Poland
90-11
Portugal
75, 93, 09
67, 75, 82, 93, 03, 09
09
74, 81, 82, 83, 87, 93,
09, 10, 11
92, 93, 09
74, 87, 09, 10, 11
Slovenia
93-11
Spain
75, 83, 84,93, 03, 09,
11
09
81, 93, 09, 10
09
92, 09
Sweden
77, 81, 92, 93. 08, 09
93, 09
61, 83, 92, 02, 09, 10
92, 02, 09, 10
08, 09
75, 09
09
75, 76, 82, 91, 93, 03,
09
79, 80, 94, 99, 01, 09
74,75, 80, 81, 91, 09
74, 75, 80, 82, 91, 09
75
86, 08, 09, 10
75, 93, 08, 09
74, 98, 99, 02, 08, 09,
11
Switzerland
65-11
Turkey
United Kingdom
United States
09
09
80, 99, 01, 09
80, 09
09
* Legend: Oecd, Economic Outlook Database. Data for 2001 stem from # 90 Economic Outlook (December 2011). Strong recessions indicate at least 2% real
GDP contractions with respect to previous year.
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Table 3 – Number of countries involved in recession episodes
Year
Recession
1974
1975
1981
1982
1983
1991
2011
4/26
12/26
8/26
6/26
5/26
7/28
3/34
Strong
recessions
1/26
4/26
1/26
1/26
3/28
1/34
Year
Recession
1992
1993
2003
2008
2009
2010
2012 *
4/28
12/30
4/30
6/30
27/30
4/34
4/34
Strong
recessions
3/28
2/30
1/30
23/30
2/34
2/34
Source: See Table 1. 1997-98 crisis in Asia for non-Oecd countries is not calculated; * The 2012 forecast refers to the # 90 Oecd Economic Outlook (December 2011).
Table 4: G-7 recessions frequency and length for quarterly data *
Country
Sample
Number of
observations
Number of
contractions
Number of
recessions
Canada
1980.12011.4
1980.12011.4
1980.12011.4
1980.12011.4
1991.12011.4
1980.12011.4
1981.12011.4
127
23 (.18)
17 (.14)
127
15 (.12)
10 (.08)
127
35 (.28)
15 (.12)
127
20 (.16)
15 (.12)
83
22 (.26)
13 (.16)
127
16 (.13)
10 (.08)
123
32 (.26)
22 (.18)
United
States
Japan
United
Kingdom
Germany
France
Italy
Longest
recession
phase
1990.11990.4
2008.22009.1
2008.22009.2
2008.22009.3
2008.22009.1
2008.22009.1
1992.21993.3
*Source: Oecd, Economic Outlook database (s.a. real GDP data, March 2012).
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3. A Possible Reconciliation between Growth and Cyclical Views
Let both actual (y) and potential output (y*) be a unit root process:
(1)
yt =
dt + yt-1,
(2)
dt =
d + a(L)et ,
(3)
y*t = d*t + y*t-1
(4)
d*t = d + a*(L)e*t ,
et ~ iid(0, σ2 ), a0 = 1
et ~ iid(0, σ2* ), a*0 = 1, σ2*< σ2< ∞.
Variables are in logs and then cycles (Coricelli-Fiorito, 2009) can be expressed as the sum of the growth
gap (dt – d*t) and of the previous cycle, it being ct-1 = yt-1– y*t-1 :
(5) ct = (dt – d*t) + ( yt-1 – y*t-1), d*t > 0,
where d* can be obtained by the HP filter.
Implications:
 Recessions (dt<0) are more volatile than normal changes since the growth gap (dt – d*t) variance
must be necessarily bigger once potential growth (d*t ) is positive..
 Δ ct = (dt – dt*)  business cycle changes = growth gap.
7
Fig. 1 – Canada: Business cycles (CCAN), actual (DCAN) and potential (DCANHP) rates of growth
.08
.06
.04
.02
.00
-.02
-.04
-.06
1970 1975 1980 1985 1990 1995 2000 2005 2010
CCAN
DCAN
DCANHP
Fig. 2 – United States: Business Cycles (CUS), actual (DUS) and potential (DUSHP) rates of growth
.08
.06
.04
.02
.00
-.02
-.04
-.06
1970 1975 1980 1985 1990 1995 2000 2005 2010
CUS
DUS
DUSHP
8
Fig. 3 – Japan: Business Cycles (CJAP), actual (DJAP) and potential (DJAPHP) rates of growth
.10
.08
.06
.04
.02
.00
-.02
-.04
-.06
1970 1975 1980 1985 1990 1995 2000 2005 2010
CJAP
DJAP
DJAPHP
Fig. 4 – United Kingdom: Business Cycles (CUK), actual (DUK) and potential (DUKHP) rates of growth
.08
.06
.04
.02
.00
-.02
-.04
-.06
1970 1975 1980 1985 1990 1995 2000 2005 2010
CUK
DUK
DUKHP
9
Fig. 5 – Germany: Business Cycles (CGER), actual (DGER) and potential (DGERHP) rates of growth
.04
.02
.00
-.02
-.04
-.06
90
92
94
96
CGER
98
00
02
DGER
04
06
08
10
DGERHP
Fig. 6 – France: Business cycles (CFR), actual (DFR) and potential (DFRHP) rates of growth
.08
.06
.04
.02
.00
-.02
-.04
1970 1975 1980 1985 1990 1995 2000 2005 2010
CFR
DFR
DFRHP
10
Fig. 7 – Italy: Business cycles (CIT), actual (DIT) and potential (DITHP) rates of growth
.08
.06
.04
.02
.00
-.02
-.04
-.06
1970 1975 1980 1985 1990 1995 2000 2005 2010
CIT
DIT
DITHP
4. Fiscal Implications
Automatic Stabilizers
Advantages:
 Data release takes time and the present must be predicted too!
 Automatic stabilizers avoid the need of forecasting and – even more important - of
 Obtaining political consensus.
Limits:
 Apply in nominal terms and refer to actual data rather than to estimated output gaps.
 If they apply too much to government spending, spending becomes heavy, procyclical and difficult to cut.
 Why is it so? Again, because expansions are much more frequent than contractions!
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Government spending: really countercyclical?
 Traditional views: government spending is countercyclical in developed countries, being procyclical in
developing ones because of inefficiency and corruption (Talvi - Vegh, 2000; Alesina, Campante, Tabellini, 2008).
 Careful analysis of disaggregated spending (Fiorito, 1997; Lane, 2003) shows instead that government spending
is not countercyclical in the Oecd area too, though there are differences by variable and country.
 The simple fact that government debt is high shows that government spending is not countercyclical but often
acyclical or inertial. Why? Positive and negative cycles should offset each other as in Graph 1!
Wrong remedies: cyclically adjusted (primary) balances (CAPB)
Basically, CAPB corrects actual balances for the output gap:
(5)
f*(t) = f(t) - α*[output gap].
 This is done to make fiscal policy more countercyclical (stabilizing) and
 to measure discretion (Blanchard, 1990), implicitely meant as a business cycle responsive tool.
The widely accepted value α ≈ ½ for the output gap correction (Girouard-André, 2005) implicitly assumes a zero
government spending elasticity to the business cycle and a unit tax elasticity.
12
5. Discretionary spending is measured in 3 ways:
 Cyclically adjusted deficits
 Regression residuals from fiscal variable estimates (Fatás and Mihov, 2003)
 Event Studies (Romer and Romer, 2010; Ramey, 2011).
5.1 Cyclically adjusted deficits
 Despite actual data in Tables 1-2, government balance corrections adjust for the cyclical component only
 However, recently the IMF (WEO, 2010) criticizes the CAPB as stabilization tool.
5.2 Regression residuals: Fatás and Mihov (2003) use in a panel of countries a 2-stage procedure
 1st stage: DCG  DY + controls + u(t), where the u(t) residuals should measure discretionary spending.
 2nd stage: The volatility of each country residual (σ2i) growth in the 2nd stage cross section.
 Government spending is confined to consumption and discretion is measured by DCG residuals
3. Event studies:
 informations taken by laws, presidential speeches and then made quantitavive: Romer and Romer (2010) postwar reconstruction on tax legislation in the US. In a similar study V. Ramey (2011), obtains smaller VAR
multipliers than Blanchard-Perotti (2002) and shows that government purchases help recovery.
 IMF study (2010) shows that fiscal contraction does not help growth as claimed by Alesina and Ardagna (2010).
13
6. A simple alternative
Confining discretion to government spending only, definition naturally applies to spending decided to face crises or
transitory emergency situations. Thus, discretion should apply more to recessions than to negative cycles to be
accomodated by automatic stabilizers.
This definition has been used for the Oecd countries by Coricelli and Fiorito (2009) on the basis of few criteria:
i)
Methods should be easily applied to several countries
ii)
Different spending items should be evaluated and then aggregated
iii)
Criteria should not be too subjective or ad hoc.
THREE DISCRETION REQUIREMENTS:
6.1 DISCRETION SHOULD AVOID INERTIA: Discretionary policy does not have to be so inertial as many government
spending components are (Fiorito, 1997). An implicit requirement is also that spending components must be evaluated
separately and cannot be confined to government consumption only.
2. DISCRETION REQUIRES NO OBLIGATION: Discretionary spending should not reflect any type of obligation,
regardless if legal, contractual or even moral: typical obligations are not only the payment of debt interests but also payment of
employees (usually, about 2/3 of government consumption) and pensions (often the highest transfer).
3. DISCRETIONARY SPENDING SHOULD NOT BE PERMANENT
The third requirement is that discretionary spending must be temporary and revocable: as when a specific spending aims at
obtaining an immediate goal and does not need to keep on after the goal is achieved.
14
These requirements:
 do not imply that discretionary spending must be a white noise process: they only imply that discretionary
spending should be volatile but also less persistent than real GDP. This can also imply a conflict since volatility
is increased by persistence as several data show.
 In particular, discretionary spending
should be less persistent than automatic stabilizers are, though some
persistence can be induced by the fact investment spending projects take neceassirily time.
To measure discretionary spending, Coricelli and Fiorito (2009) sum (and also deflate) the following variables:
1. Government purchases (CGNW), i.e. about 1/3 of government consumption in the Oecd countries.
Purchases buy on the market the intermediate inputs, necessary for providing government services.
2. Capital expenditure (IGAA+TKPG): potentially, is a growth enhancing factor (e.g. infrastructures). Thus,
single projects must be activated only when necessary and then stopped once the project is accomplished.
3. Welfare and unemployment insurances (SSPG – PENSIONS): empirically, this (heterogeneous) variable can
be calculated as the difference between household transfers and pensions. These transfers (in Italy, e.g.
CIG) must be temporary and conditional to make more flexible labor market adjustment.
4. Finally, firm subsidies (SUBSIDIES) are also added, though usually their share is small or negligible.
MAIN RESULT: This measure of discretionary spending (GD) roughly corresponds to 1/3 of total spending so that
most of government spending seems to be automatic (GN), i.e. resulting more from habits than from decisions.
15
Table 5: Discretionary (GD) and non discretionary (GN) % spending given gov.t spending/GDP (GY) share*
Country
Austria
1970-2010
Belgium
1980-2010
Denmark
1971-1979
Finland
1970-2010
France
1978-2010
Iceland
1980-2010
Ireland
1990-2010
Italy
1980-2010
Japan
1980-2010
.Netherlands
1980-2010
Norway
1980-2010
Spain
1980-2010
Sweden
1980-2010
United
Kingdom
1980-2010
United States
1970-2010
1970-79
GD GN GY
.38
.62
.40
1980-89
GD GN GY
.36 .64. .45
1990-99
GD GN GY
.34
.66
.46
2000-10
GD GN GY
.36
.64
.45
--
--
--
.36
.64
.47
.37
.67
.42
.36
.64
.43
.34
.66
.43
.28
.72
.48
.27
.73
.49
.29
.71
.48
.38
.62
.34
.33
.67
.40
.29
.71
.50
.30
.70
.43
--
--
--
.35
.65
.45
.34
.66
.47
.34
.66
.47
--
--
--
.52
.48
.34
.46
.53
.37
.45
.55
.39
--
--
--
--
--
--
.35
.65
.33
.41
.59
.35
.36
.64
.34
.36
.64
.40
.32
.68
.41
.33
.67
.42
.55
.45
.25
.53
.47
.29
.55
.45
.32
.50
.50
.36
.35
.64
.45
.38
.62
.51
.42
.58
.44
.50
.50
.41
.40
.60
.39
.38
.62
.41
.34
.66
.45
.33
.65
.40
.41
.59
.25
.40
.60
.36
.37
.63
.39
.38
.62
.37
.33
.67
.44
.33
.67
.53
.33
.67
.55
.33
.67
.48
--
--
--
.42
.58
.39
.35
.65
.39
.32
.68
.33
.34
.66
.30
.34
.66
.31
.30
.70
.31
.31
.69
.32
Source: Average data based on nominal ratios and on national samples (first subperiod); GY = total government spending/GDP ratio.
16
What Table 5 basically shows?
 In most cases, discretionary spending (GD) is about 1/3 of total spending
 In some cases (AT, BE, FR, SW) the discretionary share is about constant over time
 In other cases GD (DE FI, I, UK, US) share tends to fall over time, strongly in Japan.
 Overall, the tendency to increase the government spending/GDP ratio (GY) is due to an increase of the
automatic (GN) component, probably because of social security.
 In the last decade, Japan has the smallest G/Y ratio but also the highest GD share (.50%) while Northenrn
countries such as Denmark and Sweden have the highest G/Y share but a small (D) or a normal (SW) GD share.
Other set of results can be drawn from the following Table 6 and 7 where more details are available:
 As expected, discretionary spending is always more volatile than automatic spending but is less persistent just in
about half of cases. There is in other words, an apparent difficulty in revoking ‘decided’ expenditures.
 In some cases, the goal of reducing deficit/debt ratios contributed to increase the non-discretionary share.
 Looking at the components for a smaller number of countries (Tables 7.1-7.6) there are interesting differences,
though capital spending generally conforms to our criteria.
 It must also noticed that differences in the composition of social spending (SSPG) can affect the aggregate results
since pension share is always little volatile.
17
Table 6: Discretionary (GD) and Non-Discretionary Spending (GN) Cyclical patterns
Country
Austria
1990-2011
Belgium
1980-2011
Denmark
1980-2011
Finland
1980-2011
Discretionary spending (GD)
Volatility
Persistence
Correlation with
(LB)
GDP
2.60
5.7
-.33
ρ(g(0), y(0))
2.94
15.7
-.38
ρ[g(0), y(0)]
1.39
18.1
-.40
ρ[g(0), y(0)]
1.20
11.3
-.72
ρ[g(0), y(0)]
Non-Discretionary Spending (GND)
Volatility
Persistence
Correlation
with GDP
1.01
12.3
.31
ρ[g(0), y(0)]
.96
7.5
-.27
ρ[g(0), y(0)]
.78
17.6
-.23
ρ[g(0), y(0)]
.80
23.9
.40
ρ[g(+1), y(0)]
GD/GN
contemporaneous
correlation
-.21
GDP
persistence
(LB)
11.9
.20
11.6
.53
16.4
-.45
20.6
France
1.19
5.9
-.46
.73
10.6
-.12
.07
25.0
1980-2011
ρ[g(0), y(0)]
ρ[g(0), y(0)]
Iceland
3.95
4.6
-.39
.92
12.2
.59
.09
21.6
1990-2011
ρ[g(-1), y(0)]
ρ[g(0), y(0)]
Ireland
5.63
2.8
-.40
.97
25.4
.48
.01
18.8
1990-2011
ρ[g(+1), y(0)]
ρ[g(0), y(0)]
Italy
2.84
11.0
-.35
1.82
9.7
.29
-.58
17.9
1980-2011
ρ[g(0), y(0)]
ρ[g(+1), y(0)]
Japan
3.64
14.8
-.27
.58
11.8
.11
.01
12.4
1980-2008
ρ[g(0), y(0)]
ρ[g(0), y(0)]
Netherlands
2.47
12.1
-.26
1.05
7.1
-.45
.28
23.1
1980-2011
ρ[g(-1), y(0)]
ρ[g(-1), y(0)]
Norway
2.25
20.5
-.72
1.13
7.1
-.35
-.20
18.7
1988-2011
ρ[g(0), y(0)]
ρ[g(-1),y(0)]
Spain
2.86
15.4
-.28
1.27
16.2
.74
.27
31.0
1980-2011
ρ[g(0), y(0)]
ρ[g(+1),(0)]]
Sweden
1.86
12.5
-.50
1.03
5.3
.46
-.30
13.1
1980-2011
ρ(g(0), y(0))
ρ(g(+1), y(0))
UK
2.52
10.1
-.46
.86
30.4
-.20
-.01
14.6
1980-2011
ρ[g(-1), y(0)]
ρ[g(0), y(0)]
United States
1.46
18.6
-.38
.96
10.5
-.70
.49
13.7
198-2011
ρ(g(0), y(0))
ρ[g(0), y(0)]
Legend: Data are from the Oecd (November, 2011) database. All statistics refer to deflated cyclical deviations from the HP trend (6.25 is the smoothing parameter); Volatility
is relative to GDP; Cross-correlations with GDP refer to the highest value in the interval [(g(-1),y(0); g(0), y(0); g(+1), y(0)] where g and y denote the spending and the GDP
variable, respectively. LB is the - asymptotically ~ χ2(p) - Ljung-Box portmanteau statistics where T is the number of observations and p = T/4 is the number of sample
autocorrelations.
18
Government Spending Components in A Few Countries1
Table 7.1: France (1980-2011)
Variables
Volatility
CGNW
1.18
IGAA
2.78
TKPGQ
8.94
TSUB
4.05
WELFARE
3.02
PENSIONS
0.91
CGW
0.76
SSPG (Social security) % Shares
Ρ(G(t),Y(t))
-.13
.40
-.00
-.57
-.52
.15
-.40
PENSIONS (.65)
Persistence (LB)
21.1
6.5
14.4
21.5
10.1
8.9
12.2
WELFARE (.35)
Table 7.2: ITALY (1980-2011)
Variables
Volatility
CGNW
2.20
IGAA
6.35
TKPGQ
30.8
TSUB
4.59
WELFARE
8.07
PENSIONS
2.63
CGW
2.07
SSPG (Social security) % Shares
Ρ(G(t),Y(t))
-.11
-.13
-.07
-.10
-.44
.08
.02
PENSIONS (.76)
Persistence (LB)
10.1
6.8
8.1
12.9
12.0
8.7
7.9
WELFARE (.24)
Table 7.3: SPAIN (1980-2011)
Variables
Volatility
CGNW
2.37
IGAA
6.72
TKPGQ
10.6
TSUB
6.84
WELFARE
5.19
PENSIONS
1.12
CGW
1.97
SSPG (Social security) % Shares
1
ρ(G(t),Y(t))
.10
.08
-.35
.02
-.53
.26
.08
PENSIONS (.64)
Persistence (LB)
15.8
15.5
8.8
15.9
15.7
12.2
14.5
WELFARE (.36)
Symbols are those of the Oecd database and are explained at page 15. CGW is the compensation of employees providing government consumption (CG).
19
Table 7.3: SWEDEN (1980-2011)
Variables
Volatility
CGNW
2.18
IGAA
3.52
TKPGQ
TSUB
3.37
WELFARE
3.03
PENSIONS
1.82
CGW
1.78
SSPG (Social security) % Shares
ρ(G(t),Y(t))
-.55
-.01
Persistence (LB)
7.9
7.9
-.20
-.46
.40
.40
PENSIONS (.44)
38.3
19.9
9.5
12.7
WELFARE (.56)
Table 7.4: UK (1980-2011
Variables
Volatility
ρ(G(t),Y(t))
CGNW
1.49
-.02
IGAA
18.1
.09
TKPGQ
TSUB
7.40
-.19
WELFARE
4.02
-.79
PENSIONS
1.53
-.10
CGW
1.28
-.21
SSPG (Social security) % Shares
PENSIONS (.40)
Table 7.5: US (1980-2011
Variables
Volatility
ρ(G(t),Y(t))
CGNW
1.29
-.27
IGAA
2.64
.23
TKPGQ
TSUB
8.34
-.12
WELFARE
3.57
-.75
PENSIONS
1.14
-.54
CGW
0.80
-.18
SSPG (Social security) % Shares
PENSIONS (.55)
Persistence (LB)
14.2
4.4
9.0
19.0
9.5
22.8
WELFARE (.60)
Persistence (LB)
6.3
27.8
17.9
17.7
6.5
20.0
WELFARE (.45)
20
7. Conclusions
 The main conclusion is that discretionary government spending should be used in recessions only to be stopped
afterwards. This implies that this type of spending is revocable and has also some efficacy.
 This study does not produce evidence on the efficacy: this is still under scrutiny in a related research.
 My previous evidence (Fiorito, 1997) on government spending in the G-7 excludes that most government
spending items anticipate procyclically real GDP changess: the only variable obtaining this result for all countries
is the government purchases and this is also what has been recently obtained by Ramey (2011) for the US.
 The Italian paradox is that it is impossible help the economy when it could be necessary because most of the
excess spending was done when it was not necessary, at least for economic reasons.
 This is basically the main reason why Italy’s government debt is so big and so hindering fiscal discretion.
 If the policy goal is reducing excess government spending, the focus should be more on cutting the automatic
component, especially in recession times.
 In other words, reforms deal more with affecting the transmission mechanism of automatic stabilizrs than with
cutting temporary spending, provided discretionary spending is really temporary and also really useful.
21
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23