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FISCAL MULTIPLIERS. Arbresh MAMUDI, State University of Tetovo, Geoff PUGH, Staffordshire University Business School. Theoretical approaches. F ar from consensus The range of reported multipliers varies from negative to higher than one - PowerPoint PPT Presentation
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FISCAL MULTIPLIERS
Arbresh MAMUDI, State University of Tetovo,Geoff PUGH, Staffordshire University Business School
Theoretical approaches• Far from consensus• The range of reported multipliers varies from negative to higher than one• Empirical evidence on the size of the multiplier cannot distinguish
between the competing theories
Range RBC NK-DSGE
0 < k < 1• fully competitive labor and goods
markets• ‘Ricardian consumers’
Inflation targeting monetary authority
k >1 • complementarity of public and private consumption
• Monopolistic competition• Sticky prices and wagesPost crisis studies:• ‘non- Ricardian consumers’• zero lower bound interest rate
k <0• distortional effects of taxation • ‘wage pressure’ effect of public
employmentPost crisis studies:• risk premium on interest rates for high
government debt
The dataset• 65 empirical studies, 914 observations estimated by
– single equation approaches (SEE) or – Vector autoregression (VAR) models;
• Primary data for structural characteristics of the countries:o The indebtedness of the economy, (central government debt/ GDP)o Monetary policy reaction, (short term money market rates)o The degree of openness, (imports of goods and services/GDP)o Financial development, (domestic credit to private sector/ GDP)
• NOVELTY- augment MRA with primary data on labour market variables • Why? Labour market characteristics important in both leading theories:
o Employment protection legislation indicator, EPL-(index scaled 0-5)
o Trade union density, TUD-(ratio)
o Benefit replacement rates, BRR-(ratio)
o Coordination of wage bargaining, COOR-(index scaled 1 to 5)
Moderator variables: coding the literature
• Type of model class• Type of fiscal impulse• Direction of the impulse• The way fiscal shocks are financed• The duration of the shock• Type of the country• Type of data• Horizon of estimation• Type of fiscal multiplier• Controlling for country specific characteristics• Controlling for the quality of the study
MRA methodology
ki= k0 +mZim + β1)i+ ei
– ki is the multiplier value of observation i;
– k0 is the “underlying” or “reference” multiplier value to be estimated;
– Zim are m characteristics (“moderator variables”) of observation i;
– αm are m parameters to be estimated ( effects of Zim on ki);
– ej is the meta-regression disturbance term;
– ) is a proxy for publication bias (N =sample size for observation i)
• Standardization is not necessary; multiplier is dimensionless• Multiple estimates per study used;
– each estimate is weighted by the inverse of number of estimates in a given study• standard errors adjusted for data clustering,
– using each study in our dataset as a distinct cluster
Publication bias: Funnel plot & FAT-PET0
10
20
30
40
sqrsamsiz
-5 0 5 10 15k
• ‘Funnel plot’ –ambiguous:• slightly skewed to the right, but weight to the left• around a mean that is positive,
• Cf. ‘FAT’: Ho:β1=0 ; no systematic variation of effect size with sample size• Ho rejected, β1=-2.37, (p-value=0.01) , negative coefficient indicates
positive relationship between size of multiplier and sample size• No ‘classical’ reason for publication search• Competing theories with different predicted multipliers
Multivariate MRA: 2 models
• Baseline model:– All MVs– 2 dummies for Japan studies
• All Japan studies• Japan studies after 1990
• Preferred model:– Exclude DV controlling for the financial crisis
• A few observations controlling for financial crisis during the sample period
– Cures substantial multicollinearity effects • e.g. with Japan dummies
– Cures diagnostic failure with respect to linearity
Table 4: Total sample results- different specification (WLS and cluster-robust SEs)
Group Variables Description Baseline model (1)a
Preferred model(2)b
k0Constant 1.198**
(0.434)1.010**(0.395)
Model class var VAR models 0.887***(0.232)
0.873**(0.233)
see SEE models Fiscal impulse cons Public consumption 0.609***
(0.145)0.639***(0.145)
invest Public Investments 0.562***(0.200)
0.584***(0.197)
milita Militaryexpenditure
-0.276(0.405)
-0.280(0.406)
tax Tax shocks -0.474***(0.141)
-0.487***(0.142)
pubemp Public employment expenditure
-0.017(0.421)
-0.008(0.417)
notspec General government expenditure
• Diagnostic test: • Preferred model is well specified with respect to linear functional form ( 1% level) and normality• But may suffer from heteroscedasticity; so model is estimated with cluster robust standard errors
• Multivariate results :• Multipliers from the VAR model are significantly higher than estimates from SEE• Public investment and public consumption produce higher multiplier values • Tax shocks have lower impact compared to unspecific/general public spending
Table 4: Total sample results- different specification (WLS and cluster-robust SEs)
Group Variables Description Baseline model (1)a
Preferred model(2)b
Direction of impulse
incr Positive fiscal shock -0.247(0.194)
-0.266(0.194)
Duration of impulse
tempor Temporary shock -0.925***(0.331)
-0.902***(0.330)
Type of economy transit Transition countries 0.661**(0.268)
0.673**(0.263)
Data characteristics
quart Quarterly data -0.575**(0.239)
-0.535**(0.241)
horiz Horizon after shock 0.018*(0.010)
0.018*(0.009)
• A longer horizon of measurement yields significantly higher multipliers• Studies using quarterly data report significantly lower multipliers compared to
studies using annual data• Multipliers from a temporary shock are lower than multipliers from a permanent
shock• Fiscal policy in transition countries appears to be more effective than in advanced
economies although the results are not stable across different specifications
Table 4: Total sample results- different specification (WLS and cluster-robust SEs)
Group Variables Description Baseline model(1)a
Preferred model(2)b
MV for augmented
models
indebt Indebtedness of the country
-0.159(0.102)
-0.171(0.104)
open Openness -0.470***(0.162)
-0.499***(0.163)
er Exchange rate 0.251*(0.153)
0.279*(0.133)
employ Employment 0.063(0.116)
0.049(0.116)
lmi Labour market institutions
0.595***(0.125)
0.579***(0.126)
recc Multipliers estimated assuming reccesion
-0.198(0.332)
-0.273(0.293)
exp Multipliers estimated assuming expansion
-0.406**(0.209)
-0.484**(0.212)
fincrisis Multipliers estimated assuming financial crisis
0.362(0.331)
• Primary studies controlling for the degree of openness, type of exchange rate and labour market characteristics, yield significantly different estimates compared to conventional studies
• The multipliers estimated for expansion periods are smaller
Table 4: Total sample results- different specification (WLS and cluster-robust SEs)
Group Variables Description Baseline model (1)a
Preferred model(2)b
Primary data
epl Employment protection rate
0.029(0.067)
0.043(0.066)
tud Trade union density -0.001(0.004)
-0.000(0.004)
brr Benefit replacement rate 0.566(0.481)
0.788*(0.440)
coor Wage coordination 0.058(0.072)
0.059(0.077)
ir Interest rate -0.002(0.024)
-0.002(0.023)
impgdp Import/GDP -0.013**(0.005)
-0.013**(0.005)
credgdp Domestic credit/GDP 0.000(0.002)
0.001(0.002)
debtgdp Debt/GDP 0.002(0.002)
0.003(0.002)
• Primary (contextual) variables:• All models:
• Openness channel is an important determinant of the multiplier • A difference between economies of 30pp implies a difference in multiplier of 0.39
• Preferred model:• The replacement ratio also affects the value of the multiplier• A difference between economies of 0.10 implies a difference in multiplier of 0.08
‘True’ multiplierStudy characteristics (other factors held constant) Combined
effectt-stat p-value CI
Study estimated by SEE(incr=0; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
1.549 3.67 0.001 0.70;2.39
Study estimated by VAR(incr=0; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
2.423 4.75 0.000 1.4;3.44
Fiscal impulse is CONSUMPTION(incr=1; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
3.041 6.09 0.000 2.03;4.04
Fiscal impulse is INVESTMENT(incr=0; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
2.995 5.83 0.000 1.96;4.02
Fiscal impulse is MILITARY SPENDING(incr=0; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
2.294 3.81 0.000 1.08;3.5
Fiscal impulse is TAX SHOCK(incr=0; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
1.934 4.17 0.000 1;2.86
Fiscal impulse is PUBLIC EMPLOYMENT(incr=0; tempor=0; transit=0; quart=0; horiz=mean; primary data=mean)
2.508 3.98 0.000 1.24;3.76
Study estimated by SEE, fiscal impulse is NOTSPE,(incr=1; tempor=1; exp=1; quart=1; japan=1)
-1.504 -2.64 0.011 -2.64;-0.36
Study estimated by SEE, fiscal impulse is TAX,(incr=1; tempor=1; exp=1; quart=1; japan=1)
-1.957 -3.38 0.001 -3.11;-0.79
Study estimated by SEE, fiscal impulse is TAX,(incr=1; tempor=1; transit=0; quart=1; horiz=mean; primary data=mean)
-0.627 -2.41 0.02 -1.15;-0.10
Study estimated by VAR, fiscal impulse is TAX,(incr=1; tempor=1; transit=0; quart=1; horiz=mean; primary data=mean)
0.25 2.01 0.049 0.001;0.49
Study estimated by VAR, fiscal impulse is TAX,(incr=0; tempor=1; exp=1; quart=1; horiz=mean; primary data=mean)
-0.003 -0.02 0.459 -0.34;0.76
Main findings
• The heterogeneity of the reported multipliers arises from many study characteristics
• Structural characteristics:– Openness channel - very large– Replacement ratio - smaller but still
substantial• There is no true multiplier – the multiplier is time and state dependent
Thank you!
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