## wpiea2020005-print-pdf — Introduction & Empirical Results on Well‑Being Effects of Fiscal Consolidations

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### Context, research question, and data
- Research question:
  - How do discretionary fiscal consolidations (spending cuts and tax increases) affect individual life satisfaction?
  - Identification exploits action-based, narrative-identified fiscal consolidations to isolate (close to) causal discretionary shocks.
- Sample and datasets:
  - Over a half million individuals across 13 European countries.
  - Time period: 1980-2007.
  - Action-based fiscal consolidations database: 17 OECD countries, 173 episodes over 1978-2009; analysis focuses on 13 European countries in 1980-2007.
  - Eurobarometer life satisfaction recode: very satisfied [4], fairly satisfied [3], not very satisfied [2], not at all satisfied [1]; repeated cross-sections (~1000 interviews per country per year).
- Main macro controls:
  - Real GDP per capita; Real GDP per capita growth; Inflation (CPI); National unemployment rate; Gini coefficient (post-tax, post-transfer disposable income).
- Main micro controls:
  - Age; Gender; Marital status; Employment status (retired, unemployed).

### Estimation strategy and identification
- Baseline micro specification:
  - Y_ict = α1 Fiscal consol_ct + α2 X_ict + α3 X′_ct + δ_c + trend_c + ε_ict
  - Y_ict: individual life satisfaction; Fiscal consol_ct: size of fiscal consolidations; X_ict: individual covariates; X′_ct: macro controls; δ_c: country fixed effect; trend_c: country-specific linear time trend.
- Identification rationale:
  - Narrative, action-based fiscal consolidation episodes treated as exogenous discretionary shocks.
  - Country fixed effects and country-specific trends control for time-invariant heterogeneity and serial correlation.
- Hypothesis tested:
  - α1 < 0 (consolidations reduce well-being), acknowledging ambiguity from literature (possible expansionary consolidations versus contractionary effects via unemployment/inequality).

### Baseline results (weighted OLS; robustness reported)
- Aggregate effects (Table 1 reported coefficients across baseline specifications):
  - Fiscal consolidation size coefficients: around -0.013***, -0.012***, -0.012***, -0.014***, -0.011***.
  - Spending cut size coefficients: around -0.032***, -0.037***, -0.023***, -0.029***, -0.028***.
  - Tax hike size: mixed coefficients reported 0.005, 0.013***, -0.002, 0.001, 0.006 (not consistently significant).
- Key baseline interpretation:
  - Fiscal consolidations generate a short-run drop in individual well-being.
  - Well-being costs are mainly driven by spending cuts.
  - An increase of 1 percentage point of GDP in spending cuts leads to a reduction in individual well-being roughly three times larger than the aggregate effect in column (1) (as summarized in the text).
- Robustness (Table 2, Ordered Probit, predicted life satisfaction):
  - Fiscal consolidation size estimates under additional controls: -0.012***, -0.010***, -0.021***, -0.016***, -0.016***.
  - Ordered Probit / predicted life satisfaction robustness: effects reported as -0.007***, -0.006***, -0.006***, -0.008***, -0.006*** (A3) and -0.015***, -0.014***, -0.014***, -0.016***, -0.015*** (A4).
  - Micro control example: being unemployed associated with a 0.45 unit drop in life satisfaction (column (1) of Table 2: -0.45).

### Heterogeneities and mitigating policies (interaction framework)
- Interaction specification:
  - Y_ict = α1 Fiscal consol_ct + β1 Fiscal consol_ct × X + α2 X_ict + α3 X′_ct + δ_c + trend_c + ε_ict
  - Interpretation: α1 < 0 and β1 > 0 ⇒ policy X mitigates well-being cost; for unemployed, β1 < 0 ⇒ amplification.
- Mitigating factors tested and measures:
  - Exchange rate (LCU per USD from OECD Statistics).
  - Capital account openness (Chinn and Ito index).
  - EMU membership (dummy = 1 starting 1999).
  - ALMP expenditures (percent of GDP).
  - Party orientation dummy (conservative/right-wing = 1).
- Main interaction findings (Table 3; Appendix A6 parallels):
  - Fiscal consolidation size × Exchange rate (LCU-USD) = 0.004*** (Table 3); Exchange rate main effect = -0.071***.
  - Fiscal consolidation size × Capital account openness = 0.023*** (Table 3); Capital account openness main effect = 0.100***.
  - Fiscal consolidation size × EMU = 0.013** (Table 3); EMU main effect = -0.025***.
  - ALMP main effect = 0.034***; interaction estimates for ALMP vary (Table 3 interaction = 0.002; Appendix A6 interaction = -0.001).
  - Group-specific interactions:
    - Fiscal consolidation size × Retired = 0.022*** (retired individuals do not suffer from consolidations).
    - Fiscal consolidation size × Unemployed = -0.055*** (unemployed particularly vulnerable).
- Quantitative illustrations:
  - For exchange rate ratios of at least 6 units of local currency per USD, fiscal consolidations do not have statistically significant effects on well-being (text summary referencing Figure 4).
  - A fiscal consolidation of 1 percentage point of GDP accompanied by a fully opened capital account has a well-being cost of roughly 0.01 unit versus 0.03 unit when capital account is not opened (text summary referencing Figure 5).
- Policy implications from heterogeneities:
  - Accompanying monetary policies (credible disinflation/EMU membership), exchange rate depreciation, and capital account liberalization help dampen well-being costs.
  - Target policies to protect unemployed individuals; ALMPs show positive association with well-being but do not robustly mitigate consolidation cost.

### Event-study dynamics (country-average life satisfaction)
- Event specification:
  - Y_ct = γ E_ct + α2 X′_ct + δ_c + trend_c + ε_ct, where E_ct are dummies for 2-year windows before/after largest within-country consolidation.
- Event study evidence (Figure 6; Table A7):
  - Largest consolidation year −3−4: coefficient −0.053 (SE 0.039).
  - Consolidation year +0−1: coefficient −0.081** (SE 0.033).
  - Largest consolidation year +2−3: coefficient −0.029 (SE 0.018).
  - Largest consolidation year +4−5: coefficient −0.021 (SE 0.014).
  - Conclusion: negative effects are concentrated in the two years around implementation; no evidence of pre-existing negative trends.

### Granular disaggregation of fiscal instruments (Alesina et al. 2017 extension)
- Public spending subcomponents:
  - Government consumption (current expenditures; goods and services; public sector salaries).
  - Public investments (gross fixed capital formation).
  - Transfers (social assistance, unemployment benefits, pensions).
- Tax subcomponents:
  - Direct taxes (property, income, capital gains).
  - Indirect taxes (VAT, sales taxes).
- Main granular findings (Table 4 and extensions):
  - Taxes:
    - Direct tax hikes have a detrimental effect on subjective well-being (e.g., Direct tax hike coefficients: -0.010***, -0.010***, -0.011***, -0.006*, -0.007* across specifications).
    - Indirect tax hikes show no robust negative effect in higher-level disaggregation; some mixed positive estimates (e.g., 0.017** in one specification).
    - Property tax hikes show positive estimates (e.g., 0.062***, 0.084***, 0.064***, 0.083***, 0.102***), consistent with potential inequality‑reducing effects.
    - Negative effects on well-being driven by personal income tax and corporate income tax hikes (personal income tax: -0.027***, -0.034***, -0.024**, -0.029***, -0.032***; corporate income tax: -0.048**, -0.048**, -0.049**, -0.036, -0.038*).
  - Spending:
    - Public investment cuts: large negative effect (e.g., -0.099***, -0.101***, -0.098***, -0.089***, -0.095***).
    - Transfer cuts: robust negative impact (e.g., -0.024***, -0.026***, -0.014***, -0.025***, -0.019***).
    - Public consumption cuts: no consistent statistically significant negative effect in most estimations (mixed signs).
    - Salaries cuts: very large detrimental effect (e.g., -0.132***, -0.143***, -0.114***, -0.123***, -0.124***); marginal effect described as ten times larger than baseline.
- Announced vs unexpected consolidations:
  - Announced consolidations have larger negative effects on well-being than unexpected ones.
  - Tax hikes have a large negative effect when announced; unexpected spending cuts have large negative effects.

### Country case studies: Denmark (1983–1985) and Ireland (1987–1988)
- Episode descriptions (database sizes):
  - Denmark spending-cut consolidations: 1983 (1.85% of GDP), 1984 (1.71% of GDP), 1985 (0.77% of GDP).
  - Ireland spending-cut consolidations: 1987 (1.12% of GDP), 1988 (1.95% of GDP).
  - Denmark average tax revenues 1980-2007: 45% of GDP; Ireland: 31.7% of GDP; OECD average: 32.6% of GDP (OECD Stat; Data accessed on 23rd November 2018).
- Estimation specification:
  - Y_it = γ1 Fiscal consol_t + γ2 Fiscal consol_t × Exp consol + γ3 Exp consol + γ4 X_it + γ5 X′_t + ε_it.
  - Exp consol dummy = 1 for expansionary consolidation years (Denmark 1983–1985; Ireland 1987–1988).
- Key results:
  - Ireland:
    - Fiscal consolidations reduce individual well-being in baseline; interaction with expansionary consolidation period shows a sizable positive effect on life satisfaction (fiscal consolidation × Exp consol Ireland = 0.345***, SE 0.115).
    - Interpretation: spending cuts perceived as “good news” via expectations/wealth effects (permanent lower taxes → higher lifetime income).
  - Denmark:
    - Baseline fiscal consolidation coefficient: -0.020*** (SE 0.004); interaction with expansionary consolidation in Denmark: -0.087*** (SE 0.028).
    - Interaction indicates expansionary consolidations in Denmark had a negative effect on individual well-being.
    - Interpretation: large loss in valued public goods and country-specific social norms implied spending cuts were not read as “good news”.

### Magnitudes, sample statistics, and controls (selected)
- Coefficient magnitudes (selected reported):
  - Baseline fiscal consolidation size: ~ -0.013*** (Table 1 variants).
  - Spending cut size: ~ -0.032*** to -0.037*** in several specifications.
  - Public investment cut: ~ -0.099***.
  - Salaries cut: ~ -0.132*** (largest marginal effect; described as ten times baseline).
  - Transfers cut: ~ -0.024***.
- Sample summary statistics (Appendix Table A1):
  - Fiscal consolidation size: Obs 1950, Mean 0.305, Std. Dev. 0.677, Min -0.75, Max 3.5.
  - Life satisfaction: Obs 565454, Mean 3.065, Std. Dev. 0.731, Min 1, Max 4.
  - Exchange rate (LCU-USD): Obs 1951, Mean 1.815, Std. Dev. 2.647, Min 0.374, Max 9.378.
  - Capital account openness: Obs 1950, Mean 0.814, Std. Dev. 0.264, Min 0.165, Max 1.
  - Gini coefficient: Obs 1950, Mean 28.886, Std. Dev. 4.029, Min 20.415, Max 36.824.
- Micro control estimates (examples with consistent signs):
  - Unemployed: around -0.452*** (Table 2) and -0.449*** (Table 3).
  - Male: around -0.040*** to -0.037***.
  - Married: around 0.129–0.132***.
  - Retired: around -0.080*** to -0.079***.
- Macroeconomic control signs:
  - Real GDP per capita growth: positive (e.g., 0.004***).
  - Real GDP per capita (log): positive large coefficients (e.g., 0.425***).
  - Inflation (CPI): negative effects (e.g., -0.005** to -0.008***); CPI squared small positive coefficients (0.001***).

### Policy implications and recommendations (empirical guidance)
- Minimize well-being costs when designing consolidations:
  - Prefer tax instruments less costly for well-being in granular evidence: property tax and indirect taxes.
  - Avoid cuts to transfers and public-sector salaries where possible (strong negative well-being effects).
  - Avoid large cuts to public investment given sizable negative impacts on life satisfaction.
- Use accompanying macro policies to dampen costs:
  - Credible disinflation/EMU membership, exchange rate depreciation, and capital account liberalization help dampen the well-being cost of consolidations.
- Target vulnerable groups:
  - Protect unemployed individuals; labor-market channel is key as unemployed are particularly vulnerable to consolidation shocks.
  - ALMPs correlate positively with well-being but do not show robust mitigating interaction effects.
- Account for country-specific context:
  - Cultural valuation of public goods and expectations shape whether spending cuts are perceived as “good news” (Ireland vs Denmark lessons).
  - Policymakers face trade-offs between output dynamics and political/well-being costs; minimizing well-being loss can reduce political costs and social unrest risk.

### Summary conclusions
- Fiscal consolidations produce short-run well-being costs concentrated in the two-year window around implementation.
- Costs are mainly driven by spending cuts; salaries cuts and public investment cuts have particularly large negative effects.
- Direct income and corporate tax hikes reduce subjective well-being; property taxes and some indirect taxes may be less costly or inequality‑reducing.
- Expansionary consolidations can increase or decrease well-being depending on country context and expectations; announced vs unexpected nature matters.
- Combining micro subjective well-being data (565,000+ observations across 13 European countries) with action-based fiscal consolidation episodes over 1980-2007 yields robust evidence on composition, timing, and conditional policy factors shaping well-being impacts.

*Source: wpiea2020005-print-pdf.*

### Introduction4

### Introduction4

### Context and research question
- The paper investigates the subjective well-being costs of fiscal consolidations in Europe following the European sovereign debt crisis and contentious austerity debates (e.g., November 14, 2012 European Day of Action and Solidarity).
- Core question: How do discretionary fiscal consolidations (spending cuts and tax increases) affect individual life satisfaction?
- Novelty: combines microeconomic subjective well-being data with exogenous, action-based measures of fiscal consolidations to assess both direct and indirect well-being effects.

### Key datasets and sample scope
- Micro + macro combined sample:
  - Over a half million individuals across 13 European countries.
  - Time period: 1980-2007.
- Fiscal consolidations data:
  - Uses the “action-based” fiscal consolidations database (Devries et al., 2011; Guajardo et al., 2014).
  - The full dataset covers 17 OECD countries and records 173 fiscal consolidation episodes over 1978-2009; analysis focuses on the 13 European countries in 1980-2007.
  - Size of fiscal consolidations defined as budgetary impact in share of GDP.
  - Distinguishes consolidations based on spending cuts versus tax hikes.
- Eurobarometer subjective well-being data:
  - Repeated cross-section design, approximately 1000 face-to-face interviews per country per year.
  - Life satisfaction question recoded as: very satisfied [4], fairly satisfied [3], not very satisfied [2], not at all satisfied [1].
  - Country coverage: countries included since year of EU accession (note: Finland, Sweden and Austria data available since 1995; Spain and Portugal no observations until 1985).

### Macroeconomic variables and controls
- Main macro variable: size and composition of fiscal consolidations (positive budgetary impact focus in descriptive figures).
- Other macroeconomic controls:
  - Real GDP per capita.
  - Real GDP per capita growth.
  - Inflation rate (CPI from OECD Statistics).
  - National unemployment rate (total unemployment as percentage of total labor force from WDI).
  - Gini coefficient (household disposable post-tax and post-transfer income) from SWIID.
- Rationale: control for channels through which consolidations may affect well-being (income, economic cycle, unemployment, inequality).

### Microeconomic variables and individual controls
- Main micro variable: individual life satisfaction (subjective well-being) from Eurobarometer.
- Individual covariates included:
  - Age (nonlinear U-shaped effect expected).
  - Gender (men less happy than women in literature).
  - Marital status (marriage expected positive effect).
  - Employment status (controls for being retired and unemployed; unemployment expected large negative effect).

### Empirical identification and strategy (overview)
- Identification uses exogeneity of action-based fiscal consolidations (narrative approach à la Romer and Romer, 2010) to isolate discretionary consolidation shocks motivated by intention to reduce the budget deficit and confirmed as implemented.
- The dataset inclusion rules reduce correlation with prospective economic conditions and separate “exogenous” consolidations from endogenous cyclical policy changes.
- Empirical strategy exploits cross-country panel variation and individual-level life satisfaction responses to estimate short-run well-being effects and heterogeneous impacts.

### Main findings (as stated in the Introduction)
- Overall effect:
  - Fiscal consolidations have a negative effect on individual well-being in the short run, especially when they are based on spending cuts.
- Composition matters:
  - Spending-cut-based consolidations are associated with larger short-run well-being losses compared with tax-based consolidations.
  - Granular evidence suggests tax-based consolidations relying on property tax and indirect taxes may be the least costly for individual well-being.
- Macroeconomic and policy mitigators:
  - Accompanying monetary policies (disinflation), exchange rate policies (devaluations or depreciations), and liberalization of capital flows help dampen the well-being cost of fiscal consolidations.
- Heterogeneity:
  - Unemployed individuals are particularly vulnerable to fiscal consolidation shocks.
- Case studies (Denmark and Ireland):
  - Expansionary fiscal consolidations can still generate well-being costs.
  - Example: an expansionary fiscal consolidation in Denmark generated a 3.6% growth in real GDP but led to a reduction in individual well-being.
  - Ireland’s case corroborates expectation-based (anti-Keynesian) explanations for expansionary consolidations; Denmark’s case shows spending cuts are not necessarily perceived as “good news”.
  - Well-being consequences may depend on country-specific culture and norms.

### Contribution to literature
- Places the study within macroeconomics of happiness and fiscal policy on subjective well-being literature (e.g., Di Tella et al., 2003; Bjørnskov et al., 2007; Ram, 2009; Oishi et al., 2011).
- Distinctions from prior work:
  - Focus on fiscal consolidations (not broad cross-sectional associations).
  - Uses panel microdata to account for cultural differences and individual characteristics.
  - Links action-based, narrative-identified discretionary fiscal consolidations to individual life satisfaction.

### Organization of the paper (as described)
- Section 1: Data (macroeconomic and microeconomic variables).
- Section 2: Empirical strategy and baseline results on well-being costs of fiscal consolidations.
- Section 3: Exploration of heterogeneities and the role for mitigating policies.
- Section 4: Event study approach and granular data on consolidation composition.
- Section 5: Country-specific analysis of expansionary consolidations in Denmark and Ireland.
- Conclusion and Appendix follow.

*Source: wpiea2020005-print-pdf - Introduction4.*

### 2.1    Estimation strategy

### wpiea2020005-print-pdf - 2.1    Estimation strategy

### 2.1 Estimation strategy
- Model specification:
  - Y_ict = α1 Fiscal consol_ct + α2 X_ict + α3 X′_ct + δ_c + trend_c + ε_ict
  - Y_ict: reported life satisfaction of individual i, in country c and year t.
  - Fiscal consol_ct: size of fiscal consolidations.
  - X_ict: set of individual characteristics.
  - X′_ct: set of macroeconomic controls.
  - δ_c: country fixed effect.
  - trend_c: country-specific linear time trend.
  - ε_ict: error term.
- Identification and interpretation:
  - Country fixed effects remove time-invariant country heterogeneities; country-specific trends control time-varying unobservables and serial correlation.
  - α1 is the coefficient of interest capturing the effect of fiscal policy shocks on individual well-being and can be considered (close to) causal because:
    - Fiscal policy shocks are identified via the narrative approach and are exogenous (Romer and Romer, 2010; Cloyne, 2013).
    - Individual agents are unlikely to influence macroeconomic policy implementation.
- Ambiguity of expected sign for α1:
  - Literature shows mixed predictions:
    - Expansionary fiscal consolidations / “anti-keynesian effects” (Giavazzi and Pagano, 1990; Alesina and Ardagna, 2010).
    - Always contractionary consolidations (Guajardo et al., 2014; Jordá et al., 2016).
  - Consolidations raise unemployment and inequality (Ball et al., 2013; Agnello and Sousa, 2014; Agnello et al., 2014), which negatively affect well-being (Clark and Oswaldd, 1994; Frey and Stutzer, 2000; Alesina et al., 2004; Burkhauser et al., 2016).
  - Direct channels: tax hikes reduce net income; spending cuts reduce public goods and transfers.
  - Hypothesis tested: α1 < 0.

### 2.2 Baseline results
- Estimation method:
  - Weighted OLS.
  - European weights used to adjust national samples proportionally to EU population; includes post-stratification sample weighting factors.
  - Standard errors not clustered due to only 13 countries; country-specific trends used to account for serial correlation.
  - Results robust to wild cluster bootstrap and alternative estimators in Appendix, though wild cluster bootstrap does not allow weighted OLS.
- Key findings (Table 1 summary):
  - Fiscal consolidations lead to a drop in well-being; point estimate robust across specifications with different macro controls (columns (1) to (5)).
  - When distinguishing composition (columns (6) to (10)):
    - An increase of 1 percentage point of GDP in spending cuts leads to a reduction in individual well-being three times larger than the aggregate effect reported in column (1).
    - Tax hikes do not have a statistically significant effect in column (6).
  - Main interpretation:
    - Well-being costs of fiscal consolidations are mainly driven by spending cuts.
    - Spending cuts remain negative and statistically significant after controlling for growth and income.
    - Column (7) shows tax hikes with a positive and statistically significant effect on well-being, plausibly due to redistributive opportunities reducing inequality.
    - Consistent with studies showing spending-cut consolidations have more detrimental effects on inequality than tax-based consolidations (Mula-Granados, 2005; Ball et al., 2013; Ciminelli et al., 2018).

### 2.3 Robustness checks
- Approaches and controls:
  - Include additional individual characteristics.
  - Control for inequality (Gini coefficient) and unemployment rate.
  - Include year fixed effects to control common shocks.
  - Use weighted Ordered Probit estimator and predicted life satisfaction from a weighted Ordered Probit to account for categorical nature of life satisfaction.
- Results (Table 2 summary):
  - Columns (1)–(4): similar results to baseline; fiscal consolidations generate well-being costs, especially via spending cuts.
    - Example: in column (1), being unemployed is associated with a 0.45 unit drop in life satisfaction.
  - Columns (5)–(8): inequality and unemployment have negative and statistically significant effects on individual well-being.
    - Column (7): controlling for Gini (post-tax, post-transfer disposable income inequality), fiscal consolidations based on tax hikes have a negative and statistically significant effect—consistent with tax increases potentially used for redistribution.
  - Columns (9)–(10): with all controls, tax hikes do not have any statistically significant effect.
  - Overall: negative effect of fiscal consolidations on individual well-being is mainly driven by spending cuts.
- Appendix robustness:
  - TableA2, TableA3, TableA4: show robustness to inclusion of common shocks, weighted Ordered Probit, and predicted life satisfaction; overall findings hold.

### 3 Exploring heterogeneities and the role for mitigating policies
- Motivation:
  - If fiscal consolidations affect well-being via macroeconomic channels, accompanying macroeconomic policies may mitigate consequences.
  - Test role of devaluation/depreciation, capital account liberalization, monetary credibility (EMU membership), party orientation, and Active Labor Market Policies (ALMP).
- Measures used:
  - Devaluations/depreciations: local currency units per unit of USD from OECD Statistics.
  - Capital account openness: index from Chinn and Ito (2006).
  - Party orientation dummy: value 1 if party in power is conservative/Christian democratic/right-wing from Database on Political Institutions (Keefer, 2010).
  - EMU membership dummy: value 1 starting in 1999 from Comparative Political Data Set (CPDS).
  - ALMP expenditures: percent of GDP from CPDS.
- Rationale on labor market:
  - Unemployment has a large negative effect on well-being; fiscal consolidations raise unemployment (Ball et al., 2013; Agnello et al., 2014).
  - Test whether ALMPs dampen effects and whether unemployed individuals are more affected than retired individuals.

### 3.1 Estimation strategy for mitigating policies
- Interaction specification:
  - Y_ict = α1 Fiscal consol_ct + β1 Fiscal consol_ct × X + α2 X_ict + α3 X′_ct + δ_c + trend_c + ε_ict
  - X: conditioning factor (macroeconomic policy X′_ct or individual employment status X_ict).
- Interpretation:
  - Mitigation: α1 < 0 and β1 > 0 implies policy X helps mitigate well-being costs of fiscal consolidations.
  - Vulnerability amplification: for unemployed individuals, β1 < 0 indicates amplification of negative effects.

### 3.2 Results on mitigating policies (Table 3)
- Main findings:
  - Column (1): depreciations dampen the well-being cost of fiscal consolidations.
    - Dampening effect varies with level of depreciation.
    - Figure 4: for ratios of at least 6 units of local currency per USD, fiscal consolidations do not have any statistically significant effect on well-being.
  - Column (2): capital account openness dampens the well-being cost.
    - Figure 5: a fiscal consolidation of 1 percent point of GDP accompanied by a fully opened capital account has a well-being cost of roughly 0.01 unit versus 0.03 unit when the capital account is not opened.
    - Openness cannot fully absorb all well-being costs, unlike high depreciation levels or credible disinflation.
  - Column (3): EMU membership / credible disinflation tends to overcome and neutralize the well-being cost of fiscal consolidations.
  - Columns (4) and (5): ALMP and party orientation do not show statistically significant mitigating effects, though ALMPs appear to have a positive effect on individual well-being.
  - Column (6): retired individuals do not suffer from fiscal consolidations.
  - Unemployed individuals are particularly vulnerable to fiscal consolidation shocks.
- Policy implications:
  - Accompanying monetary policies (disinflation), exchange rate policies (depreciation), and capital account liberalization help dampen well-being costs of fiscal consolidations (consistent with Giavazzi and Pagano, 1990).
  - Targeting unemployed individuals is important because they are particularly vulnerable; labor market is an important channel.
  - No robust support found that ALMPs mitigate the well-being cost.

### 4 Further investigations: event study and granular data on fiscal consolidations
- Additional empirical strategies:
  - Event study approach defining event as implementation of the fiscal consolidation with the largest size within a country.
  - Use of recently developed granular data on composition of fiscal consolidations (analysis referenced but not detailed here).
- Event study specification:
  - Y_ct = γ E_ct + α2 X′_ct + δ_c + trend_c + ε_ct
  - E_ct: vector of dummy variables equal to 1 within 2-year period before or after the fiscal consolidation event.
  - Y_ct: average life satisfaction in country c at time t.
- Event study results:
  - Figure 6: negative effect of fiscal consolidations is confined within the two years of implementation; outside this time frame, no statistically significant effect.
  - No evidence of a pre-existing negative trend in life satisfaction prior to consolidation events.
  - Conclusion: effects on subjective well-being are short-lived and concentrated in the immediate 2-year window around the largest consolidation event.

*Source: wpiea2020005-print-pdf - 2.1    Estimation strategy*

### 4.2    Using a new granular data on fiscal consolidations

### 4.2    Using a new granular data on fiscal consolidations

### Data and methodology
- Use of a new database developed by Alesina et al (2017), an extension of the IMF action-based database (Devries et al, 2011), providing granular data on composition of spending cuts, tax hikes and public transfers, and identifying “exogenous” fiscal shocks based on the narrative approach.
- Public spending disaggregation:
  - Government consumption: current expenditures (goods and services), public sector salaries, managing cost of public services such as healthcare and education.
  - Public investments: government gross fixed capital formation expenditures (e.g., construction of roads and railways).
  - Transfers: disbursements in favor of private entities (e.g., social assistance benefits, unemployment benefit, pensions).
- Tax disaggregation:
  - Direct taxes: imposed on a property or a person and do not involve any transaction (e.g., property, income and capital gains taxes).
  - Indirect taxes: imposed relative to a transaction involving purchase of goods or services (e.g., VAT or sales taxes).
- Empirical approach similar to Smith (2015) and extensions reported in Table 4 and subsequent country-specific estimations (Equation (4) for Denmark and Ireland).

### Main findings from granular disaggregation
- Taxes:
  - Direct tax hikes have a detrimental effect on individual subjective well-being.
  - No robust evidence for negative effects of indirect tax hikes in higher-level disaggregation.
- Spending:
  - Public investment cuts have a sizable negative effect on subjective well-being.
  - Cuts in total public consumption show no statistically significant effect in most estimations.
  - Transfer cuts have a robust negative impact on subjective well-being (transfers include unemployment benefit and pensions).
- Salaries cuts:
  - Salaries cuts have a quite large detrimental effect on subjective well-being, with a marginal effect ten times larger than the baseline effect.

### Sub-component and heterogeneity results
- Finer tax sub-components (columns (6)-(10)):
  - Negative and statistically significant effects on subjective well-being are driven by personal income and corporate income taxes.
  - Property tax hikes and tax hikes on goods and service show an opposite (non-negative) effect; consistent with evidence these taxes may reduce income inequality.
  - Interpretation: direct income taxation reduces individuals' net income and may hurt well-being via reduced consumption.
- Announced versus unexpected fiscal consolidations (using Alesina et al (2017) dataset):
  - Announced fiscal consolidations have a larger negative effect on individual subjective well-being than unexpected ones.
  - Composition heterogeneity:
    - Tax hikes have a large negative effect on subjective well-being when they were announced.
    - Unexpected spending cuts are those with a large negative effect.
  - Interpretation: announced tax hikes may trigger (income) loss aversion; unexpected spending cuts may reflect unexpected loss in valued public services.

### Case studies: Denmark (1983–1985) and Ireland (1987–1988)
- Context:
  - Giavazzi and Pagano (1990) documented expansionary fiscal consolidations in Denmark and Ireland; both episodes were based on spending cuts rather than tax hikes.
  - Reported average growth in Denmark over 1983-1985: 3.6% in real GDP.
  - Database information: Ireland fiscal consolidations of 1987 and 1988 are based on spending cuts of sizes 1.12% and 1.95% of GDP respectively. Denmark fiscal consolidations of 1983, 1984 and 1985 are based on spending cuts of sizes 1.85%, 1.71% and 0.77% of GDP respectively. Other consolidations recorded in the database are based on tax hikes.
- Estimation strategy:
  - Country-specific estimation of Equation (4): Y_it = γ1 Fiscal consol_t + γ2 Fiscal consol_t × Exp consol + γ3 Exp consol + γ4 X_it + γ5 X′_t + ε_it.
  - Exp consol dummy = 1 for years of expansionary consolidations: Denmark 1983–1985; Ireland 1987–1988.
  - Coefficients of interest: γ1 and γ2. γ2 > 0 would be consistent with expansionary consolidations increasing well-being via expectations/wealth effects.
- Results:
  - Ireland:
    - Column (3): fiscal consolidations reduce individual well-being; marginal effect roughly four times the baseline finding.
    - Column (4): interaction with expansionary consolidation period (1987–1988) shows a sizable positive effect on life satisfaction; expansionary consolidations increased individual well-being in Ireland.
    - Other fiscal consolidations based on tax hikes had a negative effect on individual well-being.
    - Consistent mechanism: spending cuts read as “good news” (permanent reduction in government consumption leads to expectation of permanently lower taxes and higher lifetime income), creating a wealth effect on consumption that outweighed Keynesian recessionary effects.
  - Denmark:
    - Column (1): a one percentage point increase in the size of fiscal consolidations leads to a drop in individual well-being roughly twice the baseline effect.
    - Column (2): interaction term for expansionary period (1983–1985) shows expansionary fiscal consolidations had a negative effect on individual well-being (contrary to Ireland).
    - Figure evidence: fall in well-being especially at beginning of the period; average well-being recovered as the size of fiscal consolidation decreases in Denmark.
    - Interpretation: in Denmark, spending cuts reduced provision of public goods (health care, education, transportation) valued by households; citizens accustomed to large public spending may not read spending cuts as “good news”.
    - Supporting facts: over 1980-2007 average tax revenues were 45% of GDP in Denmark and 31.7% of GDP in Ireland; OECD average 32.6% of GDP (OECD Stat; Data accessed on 23rd November 2018).
    - Additional interpretation: low elasticities to taxable income in Denmark imply tax increases may have limited well-being cost; positive effect of fiscal consolidations based on tax hikes aligns with this.
- Two key lessons from the case studies:
  - Spending cuts are not necessarily read as good news compared to tax hikes, especially if they reduce public goods valued by households.
  - Even an expansionary fiscal consolidation can entail well-being costs; country-specific culture and social norms matter for how fiscal consolidations affect subjective well-being.

### Policy implications and recommendations
- Design of fiscal consolidations to minimize well-being cost:
  - In tax-based consolidations, governments could rely on property tax and indirect taxes (these are not costly for individual well-being in granular results).
  - Avoid cuts to transfers and salaries where possible: transfer cuts and salaries cuts have strong negative effects on subjective well-being.
  - Complement fiscal consolidations with macroeconomic and policy measures that dampen well-being costs:
    - Accompanying monetary policies (disinflation).
    - Exchange rate policies (depreciation).
    - Liberalization of capital flows.
  - Protect unemployed individuals who are particularly vulnerable to fiscal consolidation shocks.
  - Consider country-specific valuation of public goods, social norms and expectations when choosing the composition of consolidation measures.
- Trade-offs highlighted:
  - Policymakers may face a trade-off between output loss and political/well-being costs of fiscal consolidations; designing consolidations to minimize well-being loss could reduce political costs and chances of protests.

### Summary of overall conclusions
- Fiscal consolidations have a short-run well-being cost, especially when based on spending cuts.
- Salaries cuts have the worst effect on subjective well-being (marginal effect ten times larger than baseline).
- Granular evidence suggests tax-based consolidations relying on property tax and indirect taxes are less costly for well-being; direct income and corporate tax hikes are detrimental to subjective well-being.
- Expansionary fiscal consolidations can increase or decrease well-being depending on country context and how spending cuts are perceived; Ireland and Denmark provide contrasting historical examples.
- The effect of fiscal consolidations on subjective well-being is complex and depends on composition, announcement timing, and country-specific culture and valuation of public goods.
- This analysis combines micro data on subjective well-being covering more than half a million individuals across 13 European countries with macro data on fiscal consolidations over 1980-2007.

*Source: IMF working paper content (sections 4.2, 5, 5.1, 5.2, Conclusion from the supplied PDF content).*

### 15.  Deaton, A. (2012). “The financial crisis and the well-being of Americans 2011 OEP Hicks Lecture”.

### 15.  Deaton, A. (2012). “The financial crisis and the well-being of Americans 2011 OEP Hicks Lecture”.

### Major themes covered in the referenced bibliography
- Subjective well-being measurement and economics
  - Kahneman, D., & Krueger, A. B. (2006). “Developments in the measurement of subjective well-being”. The Journal of Economic Perspectives, 20(1), 3-24.
  - Di Tella, R., & MacCulloch, R. (2006) “Some uses of happiness data in economics”. The Journal of Economic Perspectives, 20(1), 25-46.
  - Di Tella, R., MacCulloch, R. J., & Oswald, A. J. (2003). “The macroeconomics of happiness”. Review of Economics and Statistics, 85(4), 809-827.
  - Lucas, R. E. & Gohm, C. L. (2000). “Age and sex differences in subjective well-being across cultures”. Culture and subjective well-being, 3(2), 91-317.
  - Kahneman & Krueger (2006) (see above) and Oswald, A. J., & Wu, S. (2010). “Objective confirmation of subjective measures of human well-being: Evidence from the USA”. Science, 327(5965), 576-579.
  - Stevenson, B., & Wolfers, J. (2008). “Economic Growth and Subjective Well-Being: Reassessing the Easterlin Paradox”. Brookings Papers on Economic Activity, 1-87.
  - Oishi, S., Schimmack, U., & Diener, E. (2012). “Progressive taxation and the subjective well-being of nations”. Psychological science, 23(1), 86-92.
  - Layard, R. (2006). “Happiness and public policy: A challenge to the profession”. The Economic Journal, 116(510), C24-C33.

- Financial crises, economic growth, and well-being
  - Deaton, A. (2012). “The financial crisis and the well-being of Americans 2011 OEP Hicks Lecture”. Oxford Economic Papers, 64(1), 1-26.
  - De Neve, J. E., Ward, G., De Keulenaer, F., Van Landeghem, B., Kavetsos, G., & Norton, M. I. (2018). "The asymmetric experience of positive and negative economic growth: Global evidence using subjective well-being data". Review of Economics and Statistics, 100(2), 362-375.
  - Ponticelli, J., & Voth, H. J. (2017). “Austerity and anarchy: Budget cuts and social unrest in Europe, 1919-2008”.

- Fiscal policy, austerity, and macroeconomic effects
  - Giavazzi, F., & Pagano, M. (1990). “Can severe fiscal contractions be expansionary? Tales of two small European countries”. NBER Macroeconomics Annual, 5, 75-111.
  - Guajardo, J., Leigh, D., & Pescatori, A. (2014). “Expansionary austerity? International evidence”. Journal of the European Economic Association, 12(4), 949-968.
  - Jordà, Ò., & Taylor, A. M. (2016). “The time for austerity: estimating the average treatment effect of fiscal policy”. The Economic Journal, 126(590), 219-255.
  - Devries, P., Guajardo, J., Leigh, D., & Pescatori, A. (2011). “A new action-based dataset of fiscal consolidation”. International Monetary Fund Working Paper, (WP/11/128).
  - Romer, C. D., & Romer, D. H. (2010). “The macroeconomic effects of tax changes: estimates based on a new measure of fiscal shocks”. The American Economic Review, 100(3), 763-801.
  - Mulas-Granados, C. (2005). “Fiscal adjustments and the short-term trade-off between economic growth and equality”. Hacienda Pública Española/Revista de Economia Pública, 172(1), 61-92.
  - Ponticelli & Voth (2017) (see above).

- Taxation, redistribution, and behavioral responses
  - Kleven, H. J. (2014). “How can Scandinavians tax so much?”. The Journal of Economic Perspectives, 28(4), 77-98.
  - Kleven, H. J., & Schultz, E. A. (2014). “Estimating taxable income responses using Danish tax reforms”. American Economic Journal: Economic Policy, 6(4), 271-301.
  - Oishi, S., Schimmack, U., & Diener, E. (2012) (see above).
  - Ram, R. (2009). “Government spending and happiness of the population: additional evidence from large cross-country samples”. Public Choice, 138(3-4), 483-490.

- Methods, data resources, and robustness
  - Kezdi, G. (2003). “Robust standard error estimation in fixed-effects panel models”. Available at SSRN 596988.
  - Nichols, A., & Schaffer, M. (2007). “Clustered errors in Stata.” In United Kingdom Stata Users’ Group Meeting.
  - Keefer, P. (2010). “Database on Political Institutions (DPI2010)”. Development Research Group, (Washington: The World Bank).
  - Smith, B. (2015). “The resource curse exorcised: Evidence from a panel of countries”. Journal of Development Economics, 116, 57-73.
  - Stiglitz, J., A. Sen & J. Fitoussi (2009), “Report by the Commission on the Measurement of Economic Performance and Social Progress, Commission on the Measurement of Economic Performance and Social Progress”, http://ec.europa.eu/eurostat/documents/118025/118123/Fitoussi+Commission+report (accessed on 02 February 2019).

### Key bibliographic entries (items 15–42)
- 15. Deaton, A. (2012). “The financial crisis and the well-being of Americans 2011 OEP Hicks Lecture”. Oxford Economic Papers, 64(1), 1-26.
- 16. De Neve, J. E., Ward, G., De Keulenaer, F., Van Landeghem, B., Kavetsos, G., & Norton, M. I. (2018). "The asymmetric experience of positive and negative economic growth: Global evidence using subjective well-being data". Review of Economics and Statistics, 100(2), 362-375.
- 17. Devries, P., Guajardo, J., Leigh, D., & Pescatori, A. (2011). “A new action-based dataset of fiscal consolidation”. International Monetary Fund Working Paper, (WP/11/128).
- 18. Di Tella, R., & MacCulloch, R. (2006) “Some uses of happiness data in economics”. The Journal of Economic Perspectives, 20(1), 25-46.
- 19. Di Tella, R., MacCulloch, R. J., & Oswald, A. J. (2003). “The macroeconomics of happiness”. Review of Economics and Statistics, 85(4), 809-827.
- 20. Ferrer-i-Carbonell, A. (2005). “Income and well-being: an empirical analysis of the comparison income effect”. Journal of Public Economics, 89(5), 997-1019.
- 21. Frey, B. S., & Stutzer, A. (2000). “Happiness, economy and institutions”. The Economic Journal, 110(466), 918-938.
- 22. Giavazzi, F., & Pagano, M. (1990). “Can severe fiscal contractions be expansionary? Tales of two small European countries”. NBER Macroeconomics Annual, 5, 75-111.
- 23. Guajardo, J., Leigh, D., & Pescatori, A. (2014). “Expansionary austerity? International evidence”. Journal of the European Economic Association, 12(4), 949-968.
- 24. Jordà, Ò., & Taylor, A. M. (2016). “The time for austerity: estimating the average treatment effect of fiscal policy”. The Economic Journal, 126(590), 219-255.
- 25. Kahneman, D., & Krueger, A. B. (2006). “Developments in the measurement of subjective well-being”. The Journal of Economic Perspectives, 20(1), 3-24.
- 26. Kezdi, G. (2003). “Robust standard error estimation in fixed-effects panel models”. Available at SSRN 596988.
- 27. Keefer, P. (2010). “Database on Political Institutions (DPI2010)”. Development Research Group, (Washington: The World Bank).
- 28. Kleven, H. J. (2014). “How can Scandinavians tax so much?”. The Journal of Economic Perspectives, 28(4), 77-98.
- 29. Kleven, H. J., & Schultz, E. A. (2014). “Estimating taxable income responses using Danish tax reforms”. American Economic Journal: Economic Policy, 6(4), 271-301.
- 30. Layard, R. (2006). “Happiness and public policy: A challenge to the profession”. The Economic Journal, 116(510), C24-C33.
- 31. Lucas, R. E. & Gohm, C. L. (2000). “Age and sex differences in subjective well-being across cultures”. Culture and subjective well-being, 3(2), 91-317.
- 32. Mulas-Granados, C. (2005). “Fiscal adjustments and the short-term trade-off between economic growth and equality”. Hacienda Pública Española/Revista de Economia Pública, 172(1), 61-92.
- 33. Nichols, A., & Schaffer, M. (2007). “Clustered errors in Stata.” In United Kingdom Stata Users’ Group Meeting.
- 34. Oishi, S., Schimmack, U., & Diener, E. (2012). “Progressive taxation and the subjective well-being of nations”. Psychological science, 23(1), 86-92.
- 35. Oswald, A. J. (1997). “Happiness and economic performance”. The Economic Journal, 107(445), 1815-1831.
- 36. Oswald, A. J., & Wu, S. (2010). “Objective confirmation of subjective measures of human well-being: Evidence from the USA”. Science, 327(5965), 576-579.
- 37. Ponticelli, J., & Voth, H. J. (2017). “Austerity and anarchy: Budget cuts and social unrest in Europe, 1919-2008”.
- 38. Ram, R. (2009). “Government spending and happiness of the population: additional evidence from large cross-country samples”. Public Choice, 138(3-4), 483-490.
- 39. Romer, C. D., & Romer, D. H. (2010). “The macroeconomic effects of tax changes: estimates based on a new measure of fiscal shocks”. The American Economic Review, 100(3), 763-801.
- 40. Smith, B. (2015). “The resource curse exorcised: Evidence from a panel of countries”. Journal of Development Economics, 116, 57-73.
- 41. Stevenson, B., & Wolfers, J. (2008). “Economic Growth and Subjective Well-Being: Reassessing the Easterlin Paradox”. Brookings Papers on Economic Activity, 1-87.
- 42. Stiglitz, J., A. Sen & J. Fitoussi (2009), “Report by the Commission on the Measurement of Economic Performance and Social Progress, Commission on the Measurement of Economic Performance and Social Progress”, http://ec.europa.eu/eurostat/documents/118025/118123/Fitoussi+Commission+report (accessed on 02 February 2019).

*Source: wpiea2020005-print-pdf - 15.  Deaton, A. (2012). “The financial crisis and the well-being of Americans 2011 OEP Hicks Lecture”.*

### 43.  Wolfers, J. (2003). “Is Business Cycle Volatility Costly? Evidence from Surveys of Subjective Well-

### wpiea2020005-print-pdf - 43.  Wolfers, J. (2003). “Is Business Cycle Volatility Costly? Evidence from Surveys of Subjective Well-

### Major findings: fiscal consolidations reduce individual life satisfaction
- Fiscal consolidation size: coefficient estimates reported around -0.013***, -0.012***, -0.012***, -0.014***, -0.011*** across baseline specifications (Table 1).
- Spending cut size: estimated coefficients around -0.032***, -0.037***, -0.023***, -0.029***, -0.028*** (Table 1).
- Tax hike size: mixed results with coefficients 0.005, 0.013***, -0.002, 0.001, 0.006 (Table 1).
- Robustness (Table 2): fiscal consolidation size estimates include -0.012***, -0.010***, -0.021***, -0.016***, -0.016*** under additional controls.
- Ordered probit and predicted-life-satisfaction robustness (Appendix Tables A3–A4): fiscal consolidation size effects reported as -0.007***, -0.006***, -0.006***, -0.008***, -0.006*** (A3) and -0.015***, -0.014***, -0.014***, -0.016***, -0.015*** (A4).

### Heterogeneity and interaction effects
- Exchange rate interaction (Table 3 / Appendix A6): Fiscal consolidation size × Exchange rate (LCU-USD) = 0.004*** (Table 3) and 0.002*** (Appendix A6). Exchange rate (LCU-USD) main effect = -0.071*** (Table 3) and -0.049*** (Appendix A6).
- Capital account openness (Table 3 / Appendix A6): Fiscal consolidation size × Capital account openness = 0.023*** (Table 3) and 0.015*** (Appendix A6). Capital account openness main effect = 0.100*** (Table 3) and 0.054*** (Appendix A6).
- EMU membership (Table 3 / Appendix A6): Fiscal consolidation size × EMU = 0.013** (Table 3) and 0.010*** (Appendix A6). EMU main effect = -0.025*** (Table 3) and -0.015*** (Appendix A6).
- Active Labor Market Policy (ALMP) (Table 3 / Appendix A6): ALMP main effect = 0.034*** (Table 3) and 0.017*** (Appendix A6); interaction estimates vary (Table 3: fiscal consolidation size×ALMP = 0.002; Appendix A6: fiscal consolidation size×ALMP = -0.001).
- Group-specific effects (Table 3): Fiscal consolidation size × Retired = 0.022***; Fiscal consolidation size × Unemployed = -0.055***. Appendix ordered-probit analogs: fiscal consolidation size×Retired = 0.012***; fiscal consolidation size×Unemployed = -0.020***.

### Disaggregating fiscal components: which instruments matter most
- Taxes and transfers (Table 4):
  - Direct tax hike: -0.010***, -0.010***, -0.011***, -0.006*, -0.007* across specifications.
  - Indirect tax hike: mixed (0.007, 0.017**, -0.005, -0.003, 0.002).
  - Property tax hike: positive estimates 0.062***, 0.084***, 0.064***, 0.083***, 0.102***.
  - Personal income tax hike: -0.027***, -0.034***, -0.024**, -0.029***, -0.032***.
  - Corporate income tax hike: -0.048**, -0.048**, -0.049**, -0.036, -0.038*.
- Spending categories (Table 4):
  - Public consumption cut: 0.013, 0.009, 0.026*, 0.011, 0.017 (mixed signs).
  - Public investment cut: -0.099***, -0.101***, -0.098***, -0.089***, -0.095***.
  - Transfers cut: -0.024***, -0.026***, -0.014***, -0.025***, -0.019***.
  - Salaries cut: -0.132***, -0.143***, -0.114***, -0.123***, -0.124***.

### Event study / dynamics
- Event study (Figure 6; Table A7): dynamic effects around the largest within-country fiscal consolidation:
  - Largest consolidation year −3−4: coefficient −0.053 (SE 0.039).
  - Consolidation year +0−1: coefficient −0.081** (SE 0.033).
  - Largest consolidation year +2−3: coefficient −0.029 (SE 0.018).
  - Largest consolidation year +4−5: coefficient −0.021 (SE 0.014).
- Notes: identification omits the 1–2 years before the event; dependent variable is country-level average of individual life satisfaction. Observations = 133 (Table A7).

### Country case studies: expansionary consolidations in Ireland and Denmark
- Table 5 (Denmark / Ireland):
  - Denmark baseline fiscal consolidation size coefficient: -0.020*** (SE 0.004); interaction with expansionary consolidation in Denmark: -0.087*** (SE 0.028); period of expansionary consolidation Denmark: -0.024 (SE 0.044).
  - Ireland baseline fiscal consolidation size coefficient: 0.072*** (SE 0.021) in one specification and -0.044*** (SE 0.005) / -0.025*** (SE 0.005) in others; fiscal consolidation size × Exp consol Ireland = 0.345*** (SE 0.115); Period of Exp consol Ireland = -0.763*** (SE 0.201).
  - Observations: Denmark models: 519, 455; Ireland models: 1945, 51501, 51501 (as reported).

### Controls, robustness and data
- Micro controls with consistent signs across tables: Unemployed around -0.452*** (Table 2) and -0.449*** (Table 3); Male around -0.040*** to -0.037***; Married ~0.129–0.132***; Retired ~-0.080*** to -0.079***.
- Macroeconomic controls with reported coefficients:
  - Real GDP per capita growth: positive (e.g., 0.004*** in Table 1; Appendix variants show 0.001–0.006*** depending on specification).
  - Real GDP per capita (Log): positive large effects (e.g., 0.425*** Table 1; Appendix variations reported).
  - Inflation rate (CPI): negative effects (e.g., -0.005**, -0.006***, -0.007***, -0.008*** in Table 1); CPI squared positive small coefficients (0.001***).
- Sample sizes and summary statistics (Appendix Table A1):
  - Fiscal consolidation size: Obs 1950, Mean 0.305, Std. Dev. 0.677, Min -0.75, Max 3.5.
  - Life satisfaction: Obs 565454, Mean 3.065, Std. Dev. 0.731, Min 1, Max 4.
  - Exchange rate (LCU-USD): Obs 1951, Mean 1.815, Std. Dev. 2.647, Min 0.374, Max 9.378.
  - Capital account openness: Obs 1950, Mean 0.814, Std. Dev. 0.264, Min 0.165, Max 1.
  - Gini coefficient: Obs 1950, Mean 28.886, Std. Dev. 4.029, Min 20.415, Max 36.824.
  - Observations vary by specification; many micro-level regressions report Observations = 565499 or 565454 depending on controls.

### Policy-relevant implications (empirical)
- Large and statistically significant negative associations between the size of fiscal consolidations and individual life satisfaction, driven primarily by spending cuts and certain tax increases.
- Cuts to public investment and transfers, and public-sector salaries, are strongly associated with lower life satisfaction (public investment cut ~ -0.099***; salaries cut ~ -0.132***; transfers cut ~ -0.024*** in Table 4).
- Heterogeneous effects suggest exchange rate movements, capital account openness, EMU membership, ALMP spending, and labor-market status (especially unemployment and retirement) condition the well-being impacts of consolidations.
- Event-study evidence indicates the largest negative average country-level life-satisfaction effect occurs in the consolidation year and immediate aftermath (Consolidation year +0−1 = -0.081**).

*Italic: Source — wpiea2020005-print-pdf (content unit provided).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020005-print-pdf.pdf_