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Discussion of: Coordinated fiscal policies in the euro area: revisiting the size of spillovers by Mario Alloza, Pablo Burriel and Javier Perez Beatrice.

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Presentation on theme: "Discussion of: Coordinated fiscal policies in the euro area: revisiting the size of spillovers by Mario Alloza, Pablo Burriel and Javier Perez Beatrice."— Presentation transcript:

1 Discussion of: Coordinated fiscal policies in the euro area: revisiting the size of spillovers by Mario Alloza, Pablo Burriel and Javier Perez Beatrice Pierluigi Fiscal Policies Division Directorate General Economics European Central Bank First Annual Workshop of ESCB Research Cluster 2: International Macro, Fiscal Policy, Labour Economics, Competitiveness and EMU Governance Banco De España 16-17 November 2017 The views expressed in this discussion do not necessarily reflect those of the ECB

2 Main innovations Dataset: construction of new disaggregated quarterly fiscal data (back to 1980) for the largest EA countries and EA aggregate; Combination of SVAR (BP, 02) to identify G and NT shocks and LPM (Jorda 05) to derive multipliers and spillovers; Computation of pairwise spillovers aggregated to derive spillovers by destination and by origin. 2 2

3 1. Hybrid approach (Structural VAR & LPM) 2. Spending multipliers
Focus of my discussion 1. Hybrid approach (Structural VAR & LPM) 2. Spending multipliers 3. Spillovers 3 3

4 1. Hybrid approach Hybrid approach: SVAR used to identify shocks and LPM used to estimate the size of multipliers and spillovers. Benefit: LPM allows for a non-linear world (i.e. distinguishing between boom and recession, low and high fiscal stress) in a much straightforward manner than VAR models. Questions: The series of shocks have been identified in a linear world and then used in a non linear setting. Is there a contradiction? It would be good if the paper could show how the series of identified shocks look like. Adding non linearities in LPM leads to a large deterioration of the significance of the estimated coefficients. Prima facie not much gains from introducing non linearities in LPM. 4 4

5 In this paper: 2. Spending multipliers
Estimates of multipliers vary significantly across countries, sample periods and methodologies (EC, 2012), and depend on different fiscal reaction functions (Caldara & Kamps, 2017). In this paper: Estimates on spending multipliers generally more precise than on tax multipliers. Significant variations of spending multipliers across EA countries in the short tem, but reduced over time. Spending (G) and tax (NT) multipliers for the EA Spending multipliers: EA and big 4 Note: not statistically significant estimates shown in lighter/patterned colours 5 5

6 Government Consumption (GC) Government Investment (GI)
2. Spending multipliers: consumption and investment Results broadly in line with other studies: G multiplier higher than NT multipliers and multipliers on GI higher than multipliers on GC New: Germany stands out as the country with highest GC and GI multipliers, in particular from year 1 onwards. How to reconcile a multiplier for G lower than that on its components GC and GI, both in the short and the long run? Government Consumption (GC) Government Investment (GI) Note: not statistically significant estimates shown in lighter/patterned colours 6 6

7 But little value added when introducing non linearities:
2. Spending multipliers: recessions & high fiscal stress But little value added when introducing non linearities: Spending multipliers in most cases not significant for recessions and high fiscal stress periods. Suggestion: Test for other definitions of increased slack (e.g. U) or fiscal stress (e.g. spreads). Recessions High fiscal stress Note: not statistically significant estimates shown in lighter/patterned colours 7 7

8 Average spillovers in year 3: Destination and Origin
Aggregation of pairwise spillovers: Benefits: Aggregation of pairwise spillovers allows to compute the effects on output of a simultaneous increase in G, while generally other papers (e.g. AG13) measure the effect of an average increase in G. Thus, this approach more than others helps in understanding benefits from policy coordination in the EA. Questions: Why different weights have been used for aggregating spillovers by Destination and Origin? The average spillovers effects of a simultaneous increase in G are found to be systematically higher for Origin than for Destination. Why this occurs? Shouldn’t they be broadly similar? Average spillovers in year 3: Destination and Origin 8 8

9 But some results are not intuitive and need some explanations, e.g.:
3. Spillovers Interesting results: Fiscal policy coordination matters, in particular in the case of Government Investment But some results are not intuitive and need some explanations, e.g.: Germany is the strongest recipient of spillovers and Spain the strongest source. Limited impact on EA from G expansion in DE and larger impact found for IT, ES (and FR): What can explain these results? Spending multiplier (G) and spillovers in year 3 by Destination and Origin Note: not statistically significant estimates shown in lighter/patterned colours 9 9

10 Thank you for your attention!

11 Annex: Spending multipliers in booms and low fiscal stress
Note: not statistically significant estimates shown in lighter/patterned colours


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