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Wagner’s law vs. Keynes’ hypothesis in very different countries (Armenia and Spain)

Wagner’s law vs. Keynes’ hypothesis in very different countries (Armenia and Spain). Gohar S. Sedrakyan International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University Laura Varela- Candamio

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Wagner’s law vs. Keynes’ hypothesis in very different countries (Armenia and Spain)

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  1. Wagner’s law vs. Keynes’ hypothesis in very different countries (Armenia and Spain) Gohar S. Sedrakyan International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University Laura Varela-Candamio Faculty of Economics and Business, Department of Economics, University of A Coruna Armenian Economic Association Meetings Yerevan, Republic of Armenia June 28, 2019

  2. INTRODUCTION • The discussion on the role of public expenditures in economic growth has a long history and is still an extensive topic for discussion among public economists and policymakers. • The aim of this paper is to determine similarities and possibly divergences in the causal effect of public expenditures on the economic growth, and conversely, in studies of two very different countries: Armenia and Spain.

  3. Wagner’s Law vs. Keynes’ Hypothesis • Wagner’s law suggests that government activity by means of government spending increases as a result of economic growth with a long-term trend. • Keynes’ hypothesis suggests an active role of fiscal policy, where increased government spending, through multiplier and accelerator effects, has positive effects on demand and subsequently on income or economic activity of a country.

  4. Armenia Spain High-income, developed economy in the OECD region and 5th largest economy in the EU. Lower-middle-income, transition economy in the ECA region and member of the EUEU. Figure 1. Share of expenses by functions in total government expenditures Figure 2. Share of expenses by functions in total government expenditures

  5. Armenia Spain Only those public expenditures that exceed 5% of total government spending are included in the further analysis. • General Public Services • Defense • Maintaining Public Order • Healthcare • Education • Social Protection • General Public Services • Economic Affairs • Healthcare • Education • Social Protection

  6. Table1. Descriptive statistics.

  7. Methodology: • Vector Autoregressive Function (background test) • Augmented Dickey-Fuller Test (data stationarity) • Granger Causality Test (Short-term) • Impulse-Response Function (Long-term) • Forecast Error Variance Decomposition (Long-term)

  8. Methodology: Vector autoregressive function The VAR model is a multi-equation system where all variables are treated as endogenous. For two series 𝑋𝑡 and 𝑌𝑡 a vector autoregressive method combines the following equations: 𝑋𝑡=𝛿0+𝛼1𝑋𝑡−1+𝑏1𝑌𝑡−1+𝛼2𝑋𝑡−2+𝑏2𝑌𝑡−2+⋯ 𝑌𝑡=𝜂0+𝑐1𝑋𝑡−1+𝑑1𝑌𝑡−1+𝑐2𝑋𝑡−2+𝑑2𝑌𝑡−2+⋯ Each equation contains an error that has zero expected value given past information on 𝑋 and 𝑌. The equations are estimated by OLS. Before conducting VAR, the Augmented Dickey-Fuller (ADF) unit-root test is performed to identify the stationary nature of the variables, since the causality tests are very sensitive to the stationarity of time series.

  9. Table 2. Augmented Dickey-Fuller Test Results.

  10. Methodology: Granger causality Wald test The VAR model itself does not allow us to make statements about causal relationships. Therefore, the effect between public expenditures and economic growth is obtained by performing a Granger causality test. The main idea of Granger causality is as follows: a variable 𝑋 Granger-causes 𝑌 if 𝑌 can be better predicted using the past values of both 𝑋 and 𝑌 than it can be using the history of 𝑌 alone. 𝑌𝑡=Σ𝑐𝑗𝑋𝑡−𝑗+ Σ𝑑𝑗𝑌𝑡−𝑗+ 𝜇𝑡 𝑋𝑡=Σ𝑎𝑗𝑋𝑡−𝑗+ Σ𝑏𝑗𝑌𝑡−𝑗+ 𝜀𝑡 The null hypothesis of the Granger causality test is that all the lagged variables of 𝑋𝑡−𝑗 do not cause 𝑌𝑡 . If the 𝜌 𝑣𝑎𝑙𝑢𝑒<5 𝑝𝑒𝑟𝑐𝑒𝑛𝑡, we can reject the null hypothesis, which would mean there is a short-run causality from 𝑋 to 𝑌.

  11. Table 3. Granger Causality Wald Test Results.

  12. Results: Granger causality wald test applied to Armenia • Real GDP has a causal effect on all public expenditures: General Public Services, Defense, Maintenance of Public Order, Healthcare, Education and Social Protection. • Public expenditures, such as Defense, Healthcare and Education have a significant impact on economic growth. • Bidirectional causality hypothesis is observed in the cases of Defense, Healthcare and Education.

  13. Results: Granger causality wald test applied to Spain • Real GDP has a causal effect on General Public Services, Healthcare and Social Protection. • Public expenditures, such asHealthcare and to some degree Economic Affairs have a significant impact on the economic growth. • Bidirectional causality hypothesis is observed in the case of Healthcare.

  14. Methodology: fevd and IRF • The forecast error variance decomposition (FEVD) and impulse-response function (IRF) methods are essential tools in interpreting the studied VAR modelin the long-term perspective and 12 year time-frame is used for these tests. • The FEVD method estimates how much of the forecast error variance of each of the variables can be explained by exogenous shocks to other variables in the VAR system. • The IRF identifies the responsiveness of the endogenous variables in the system when a unit shock or impulse is applied to the error terms 𝜀1and 𝜀2. 𝑋𝑡=𝛼1+𝛼2𝑋𝑡−𝑖+𝛼3𝑌𝑡−𝑖+𝜀1 𝑌𝑡=𝛽1+𝛽2𝑋𝑡−𝑖+𝛽3𝑌𝑡−𝑖+𝜀2

  15. Figure 2. FEVD and IRF Test Results for Armenia.

  16. Figure 3. FEVD and IRF Test Results for Spain.

  17. Policy implications: • Public policy varies due to the time-frame of expected results. • Public policy design should consider whether public expenditures have direct or invers implications on GDP. • Strong evidence of Wagner’s law signals that implementation of public policies supporting national income growth is essential for both countries and subsequently leads to higher public spending. • During the periods of economic downturn or instances of high public debt accumulation, allocation of public expenditures fitting Keynesian rule is recommended (MPO in Armenia, education in Spain, healthcare both countries). • Some public expenditures have comparatively long-term reverse impact on GDP (education in Armenia, general public services in Spain and social protection in both countries).

  18. Policy implications: education • In despite to a widely accepted assumption of public spending on education to be productive and contributive in the long-termnational income growth (e.g. Duval & de la Maisonneuve, 2010), ourstudy definesthat whileinsignificant positive causality of education and GDP is true for Spain; however, in the case ofArmenia this long-term relation is negative. • More studies are needed to evaluate themigration phenomenon, and specifically of well-educated labor, on the national incomethrough causes of international labor migration versus remmitances received from them in Armenia.

  19. Policy implications: defense • In general, the defense sector is viewed as a trade-off between defense spending and social welfare expendituressuch as healthcare and education (both having productive nature in Spain) (Barro, 1990; Heo&Bohte, 2012; Russett, 1982). • The case of Armenia suggeststhe functioninginfrastructure built around the defense sector has a significant effect on GDP both short and long-termand over time this effect magnifies; however, there is no clear evidence of positive impact ofthis sector on the national income (the positive causality is better defined in the case of MPO forfive-year period).

  20. Policy implications: defense • More recent developments in the European Union and associationwith the NATO suggest that the policies with low defense spending will probably be revisited and more resources of theEU member countries, including Spain, may be directed to finance this sector (NATO, 2017). Abalanced public policy modeling approach may develop a positive scenario for the gradual increase of these investments in the nationaldefense oriented infrastructure and further implications on the national income as well as ensure that the expenditures of social welfare natuare are met on the local levels.

  21. Policy implications: General Public Services • The composition of GPS as a public expenditure is verycomplex; it covers a large spectrum of government programs from research and development toforeign economic aid and coverage of public debt. • For the case of Armenia, there is no clear evidence of positive or negative impact of GPS on GDP. • Forthe case of Spain, the nexus between GPS and GDP is negative for five periods. • Policy modeling which would allow directinghigher share of these funds to more productive programs (e.g. Research and development) and possibly reduction of funds direced to cover expenditures of less productive nature (e.g. repayment of public debt) would positively impact the nexus between GPS and GDP.

  22. Q&A For more information on this study, please, contact Gohar Sedrakyan at goharsedrakyan@gsu.edu

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