Estimating the effects of fiscal consolidations: A synthetic control approach
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| Main Author: | |
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| Publication Date: | 2021 |
| Format: | Master thesis |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/10071/23842 |
Summary: | This thesis applies the synthetic control method to estimate the effects of fiscal consolidations on GDP. The framework developed requires the identification of suitable multi-year treatment episodes as well as periods that can serve as controls (where fiscal policy was relatively neutral). The identification of treatment and control episodes is done through the two most used measures of fiscal policy in the recent literature. Since the two measures are very different and have little overlap in terms of countries and period covered, the estimation is done in two different datasets and only the main results are compared. The rationale behind the implementation of the synthetic control method was to explore the possibility that it could provide robust estimations for the effects of individual fiscal consolidations. However, through the evaluation of the estimation method on placebos, it seems that this methodology generates too much variance, making individual estimations unreliable. Nevertheless, the average estimated effects are unbiased and can provide some useful insights: fiscal consolidations tend to generate significant losses in GDP, consolidations based on expenditure reduction are less contractionary than those based on tax increases and consolidations implemented following a recession generate higher costs. These conclusions are robust to both identification methods (when it could be tested with both) and are also in line with recent studies that use more common estimation methods. |