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FISCAL MULTIPLIERS

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

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FISCAL MULTIPLIERS

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  1. FISCAL MULTIPLIERS Arbresh MAMUDI, State University of Tetovo, Geoff PUGH, Staffordshire University Business School

  2. 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

  3. 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: • The indebtedness of the economy, (central government debt/ GDP) • Monetary policy reaction,(short term money market rates) • The degree of openness, (imports of goods and services/GDP) • 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: • Employment protection legislation indicator, EPL-(index scaled 0-5) • Trade union density, TUD-(ratio) • Benefit replacement rates, BRR-(ratio) • Coordination of wage bargaining, COOR-(index scaled 1 to 5)

  4. 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

  5. MRA methodology ki= k0 +mZim+ β1)i+ ei • kiis the multiplier value of observation i; • k0 is the “underlying” or “reference” multiplier valueto be estimated; • Zimare m characteristics (“moderator variables”) of observation i; • αm are m parameters to be estimated ( effects of Zimon 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

  6. Publication bias: Funnel plot & FAT-PET • ‘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

  7. 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

  8. 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

  9. Alonger 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

  10. 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

  11. 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

  12. ‘True’ multiplier

  13. 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

  14. Thank you!

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