The stabilizing effects of economic policies in Spain in times of COVID-19

1. Introduction

Only two weeks after the start of the COVID-19 lockdown in Spain, we carried out simulations based on a dynamic stochastic general equilibrium (DSGE) model, offering the first quantifications of the potential macroeconomic impact of the COVID-19 pandemic on the Spanish economy and the effects of the stabilizing economic policies announced at that time (Boscá et al., 2020a, 2020b). These simulations were updated in May (Boscá et al., 2020c), when the lockdown de-escalation process began, producing economic scenarios for 2020 similar to those projected by the Bank of Spain (2020). Subsequently (Boscá et al., 2020d), we estimated a historical decomposition of the gross domestic product (GDP) growth rate into structural shocks of different nature, using the available information at that time and forecast for the remaining quarters of 2020.

All these simulations and historical decomposition exercises have been computed using the latest version of the dynamic and stochastic general equilibrium model the estimated rational expectation model for Spain (EREMS) (Boscá et al., 2020e). This model is similar to those used by different international institutions such as, for example, the European Commission (EC; see Kollmann et al., 2016, or Albonico et al., 2017), and is based on an earlier version (Boscá et al., 2011), which was extended introducing a banking sector and a wide set of structural shocks. Using the theoretical constraints of the model, it is possible to estimate the structural shocks and their contributions to the behaviour of the main macroeconomic aggregates over time. Specifically, in this article we extended the model to include three stochastic implicit tax rates on consumption, and labour and capital incomes, and use 21 observed variables to identify the 21 shocks consistent with these theoretical restrictions [1]. To simplify the analysis and presentation, the 21 estimated factors have been grouped into supply shocks (for example, total factor productivity [TFP] or efficiency in the use of residential capital), demand shocks (such as changes in preferences of private consumption or changes in public consumption) and credit (disturbances that alter the credit stock of firms and households).

These characteristics make this model a useful complement to the modelling and analysis tools already available, while improving our understanding of the Spanish economy from a macroeconomic perspective. Additionally, its use during the COVID-19 pandemic is analogous to other recent research (for example, Eichenbaum et al., 2020, Faria-e-Castro, 2020, or Guerrieri et al., 2020) that have evaluated the effects of this crisis with similar models, although ours is richer and more detailed in terms of economic agents, sectors, variables and empirical observables.

Conditional on the information available until the third quarter of 2020, in this paper we estimate the historical decomposition of the main economic variables, in terms of the contributions of structural shocks, and we extend this decomposition until the end of 2021, using the latest available economic forecasts from BBVA Research (2020). These forecasts are exogenous to the model. Additionally, we update the simulations of the effects of the economic policies implemented in 2020 and offer a preliminary assessment of the effects of Next Generation EU (NGEU) for 2021 (see, European Commission, 2020b), conditional on the scarce information available so far.

According to our findings, negative TFP and demand shocks explain most of the fall of GDP in the second quarter of 2020. Nevertheless, their negative contribution, unparalleled in history, has been partially offset by public consumption, transfers to the private sector and the credit impulse, especially for firms. Looking forward, NGEU can accelerate the recovery of the Spanish economy in 2021 and the following years. Our results show the usefulness of EREMS as a complementary tool for the analysis of the economic cycle and to understand its causes, and as a preliminary step for the design and evaluation of economic policies, such as those deployed during the crisis.

The structure of this article is as follows. Section 2 provides a brief description of the theoretical model, its calibration and estimation. Section 3 presents the results of the historical decomposition of GDP growth in terms of the structural shocks estimated. In Section 4, we update the simulated effects of the economic policies implemented so far. Section 5 simulates the potential effects of NGEU on the Spanish economy from 2021 to 2024. Section 6 offers the main conclusions of this article.

2. Model

3. Historical decomposition in times of COVID-19

Figure 2 represents GDP per working-age population (WAP) in real terms and the estimated linear trend from the first quarter of 1990 to the fourth of 2020. The COVID-19 crisis truncated the recovery after the 2007–2009 Great Recession and the 2011–2012 sovereign debt crisis. At the end of 2019, GDP per WAP was 3.2% above the maximum reached in the previous expansionary cycle. Assuming that the linear trend would adequately approximate the long-term equilibrium path, during 2019 the Spanish economy would have been slightly above (1.2 pp) its trend growth path and, therefore, with an almost neutral cyclical position. The fall in GDP per WAP in the first half of 2020 is unparalleled in history. Between the last quarter of 2019 and the second of 2020, its contraction was 25.3%, reaching levels not seen since the second half of 1997. Despite the recovery in the second half of the year, GDP per WAP will still be 8.7% below that of the end of 2019, a level equivalent to that of 2015.

Figure 3 represents the deviation since 2008 of the interannual growth rate of GDP per WAP with respect to its sample mean. This is the transformation used as observable in the estimation of the model. According to this evidence, the Spanish economy has been slowing down since 2016 and at the end of 2019 GDP per WAP growth was already on its temporary average. The falls in the first half of 2020 were unprecedented: four times those observed in the previous international financial crisis, showing the exceptional nature of the COVID-19 crisis.

Behind the evolution over time of this GDP per WAP growth rate are supply and demand shocks, whose contribution can be estimated with the model described in the previous section. Figure 4 presents the contribution since 2008 of aggregate supply, aggregate demand and credit shocks to the growth rate of GDP per WAP, obtained from the estimation of the model with observations up to the third quarter of 2020 and extending the sample period with exogenous forecasts to the model until the fourth quarter of 2020 (BBVA Research, 2020). The bars above the horizontal axis indicate positive contributions to the cycle, while those below correspond to negative contributions. By construction, the sum of all contributions is equal to the deviation from their long-term average of the annual growth rate of GDP per WAP, which is represented by a solid line.

As seen in Figure 4, the contribution of supply, demand and credit factors during the COVID-19 crisis is very different from that of the previous crisis. Except for the increase in wage mark-ups in the first quarters (in line with the results of Doménech et al., 2018), the Great Recession was mainly a crisis caused by unsustainable growth in demand. In fact, during the sovereign debt crisis and a good part of the recovery, supply factors have had a crucial positive contribution and led to a sharp improvement in productivity. The estimates show that supply factors, which supported the economic recovery, gradually lost weight after their maximum contribution reached in 2016. In the last quarter of 2018 supply shocks started to have a negative contribution in GDP per WAP growth.

During the COVID-19 crisis, supply and demand factors have been very relevant. During the recession caused by the lockdown, supply shocks represented 58% of the fall of GDP per WAP and demand and credit represented the remaining 42%. With the recovery started in the third quarter of 2020, demand is recovering and most of the year-on-year decline at the end of the year is explained by supply factors.

However, this does not mean that some demand shocks do not continue to contribute negatively to the decline in GDP per WAP, but that other demand or credit factors offset the negative contribution of some demand shocks with their positive contribution. This is precisely what Figure 5 shows, in which some demand factors, such as the credit impulse and aggregate demand by the public sector (public consumption and investment and indirect taxes), have partially offset the negative contribution of consumption and private investment demand, as well as foreign demand. It should be noted that public sector transfers to households and firms are not used as an observable and are not explicitly identified in the model. Therefore, unemployment benefits, tax deferrals, job furlough or retention schemes and self-employed aids for temporary cessation of activity implicitly reduce the fall of aggregate demand from the private sector. As we will see in the next section, these discretionary measures of the public sector have been very relevant to avoid a greater contraction in activity.

It is important to highlight the significant contribution of the credit impulse, which reaches almost three points of year-on-year growth of GDP per WAP in the third quarter of 2020, partly as a consequence of the public guarantee programs that, together with a more capitalized and active banking sector, made it possible to face the enormous increase in liquidity demand and the financing needs of firms during the crisis. Regarding the public components of aggregate demand, their contribution has been positive and slightly above one percentage point of GDP at the end of 2020. Lower implicit indirect taxes contribute almost 6 tenths to growth, public consumption almost 3 tenths and public investment 2 tenths throughout 2020.

As with demand factors, not all supply shocks have contributed equally during the COVID-19 crisis. Figure 6 shows that, within supply shocks, the factor that has contributed the most to the fall in GDP per WAP has been TFP, as might be expected, due to the lockdown and closure of economic activities. In the second quarter its contribution is approximately half of all the observed decrease in the level of activity. Conditional on the forecasts used for the last part of 2020, TFP gradually recovers, although its negative contribution does not disappear, while mark-ups also contribute negatively, with a fall of almost 5 percentage point (pp) to year-on-year growth at the end of 2020. This result indicates that, again, prices and wages flexibility should be key to accelerate the recovery of the Spanish economy after COVID-19.

Figure 6 also draws attention to the procyclicality of the implicit tax rates on labour and capital incomes, which in the second and third quarters of 2020 have subtracted one percentage point of year-on-year GDP per WAP growth. This means that the tax exemptions and deferrals adopted during the COVID-19 crisis, mainly through decreases in social contributions, have probably been insufficient, given the characteristics and magnitude of the crisis, since have only partially compensated the fall of the tax bases and have not prevented the increase in the tax burden on labour and, to a lesser extent, on capital incomes.

In Figure 7 we represent the year-on-year growth of government budget balance. The results confirm that public consumption and investment and implicit tax rates shocks have not been the main determinant of the deterioration of the general government primary budget balance during the crisis. In fact, in the second quarter of 2020 the contribution of these shocks was even positive. The main determinants of the increase in the fiscal deficit (equal to 16.5 pp of GDP in 2Q2020 with respect to the same quarter of 2019) have been other (non-fiscal) shocks estimated by the model, and more importantly, fiscal variables, such as transfers. These transfers fall in the category of residuals, because they are not used as observables in the model and for which we do not estimate shocks.

4. Stabilizing effects of economic policies

The objective of this section is to evaluate the effect of the countercyclical economic policies adopted in order to stabilize the economy and partially cushion the effects of lockdown, activity restrictions, uncertainty and other consequences of the COVID-19 crisis. More specifically, to counteract the sharp drop in activity, the Spanish Government approved an important package of economic measures that, with the information available in the 2021 Budget Plan, is estimated to have been mobilizing public resources in 2020 for about €164.1 billion, distributed between discretionary spending measures (€55,588 million), discretionary income measures (€922 million) and public guarantees and guarantees for loans (€107.6 billion). These measures include increases in health spending, subsidies to protect income for workers, self-employed and firms, as well as public guarantees for loans, or exemptions and extensions in the payment of taxes.

As Table 1 details, all these measures are introduced in EREMS altering some exogenous variables in the model, mainly in the second and third quarters of 2020, with the objective of simulating a counterfactual scenario of the economy without all these implemented temporary measures. It should be noted, however, that our simulations do not assess discretionary policies implemented by regional governments or municipalities.

In addition to the previous discretionary policies, we also take into account the temporary activation of the general escape clause of the Stability and Growth Pact, adopted on March 23 by ECOFIN. In the model, this implies that the fiscal rule is temporarily halted until mid-2022. We do not simulate the effects of measures approved by the Eurogroup through the additional resources available at the ESM, the European Investment Bank or the European unemployment fund SURE.

The extraordinary measures adopted by the ECB, such as the Pandemic Emergency Purchase Program (PEPP) of €1,350 billion, the expansion of the Asset Purchase Program (APP), new liquidity instruments as TLTRO III and PELTRO or the forward guidance (Borgioli et al., 2020), have the objective of providing all the necessary liquidity and avoiding any type of tensions in financial markets such as, for example, an increase in risk premia of countries with smaller fiscal margins and high levels of public debt.

Figure 8 presents the GDP baseline and the simulated counterfactual scenario in absence of the COVID-19 economic policy measures detailed in Table 1, under the assumption that they are reverted in 2021. The results show that the set of policies implemented has a significant impact on mitigating the decline in economic activity. According to our results, the annual fall in GDP moderates by 5 pp. The difference in the second quarter is even greater: economic policies limited the accumulated fall since 4Q19 in 7.6 pp.

It is important to note that in this simulation the public credit guarantees only limit the increase in non-performing loans, incentivizing banks to meet the demand of liquidity, mainly of firms, during the pandemic. The simulation does not consider a gloomier scenario in which a credit restriction by the full amount of the public credit guarantee (9.7% of GDP in 2020) could have implied an additional fall of GDP or, even worse, hysteresis effects with the disappearance of many firms. Alternative simulation strategies that reduce the flow of credit to firms by the amount of these public credit guarantees increase the fall of GDP in line with an elasticity close to one. However, casual information indicates that not all credit has been used by firms to avoid a greater fall in GDP, but to store liquidity in the event that it is needed throughout a crisis with uncertain duration. In any case, according to these results, it cannot be ruled out that the economic policy measures have prevented an additional contraction in GDP of close to 10 pp in the worst phase of the COVID-19 crisis.

5. Potential effects of Next Generation EU

In addition to the measures adopted by the ECB, the ESM, the EIB and SURE, the European Union has launched a European recovery plan, better known as NGEU. This plan will be a very important and timely step in supporting the recovery in Europe. With a fiscal stimulus of 5.4% of the GDP for the EU, according to the simulations of the EC, it could raise the GDP of some countries by more than 4% in 2024. This recovery plan is strongly redistributive since countries with a higher level of per capita income, and that have suffered the least during the COVID-19 crisis, contribute around 2% of their annual GDP. This temporary fund will be financed by a long-term European bond, a decision that can be interpreted as a step towards a future fiscal union. All these elements of NGEU reinforce the European project and make its response to the crisis an opportunity to advance the process of integration, transformation and modernization of the EU.

According to current estimates, Spain can receive around €140bn between grants and loans for four years, which is equivalent to 12.0% of GDP and just over €3,000 per capita. Grants can reach €72bn (6.4 pp of GDP forecasted for 2020) in the period 2021–2023. The Recovery and Resilience Facility would allow Spain to obtain more than €59bn in grants and Recovery Assistance for Cohesion and the Territories of Europe, €12bn.

The European Commission (2020a, 2020b) has carried out some simulations with the QUEST III model (Ratto et al., 2009) of the effects of NGEU on European economies that, like Spain, have a per capita income below the average and a public debt to GDP ratio above average. To carry out these simulations, the EC assumes that 93.5% of NGEU is used for public investment (with a higher fiscal multiplier, as found by Gechert, 2015) and the rest for public consumption, that 25% is disbursed each year between 2021 and 2024, and that between 50% and 100% of the grants, and 50% of the loans would be used.

Under the preceding assumptions and in countries with GDP per capita below EU average and high levels of public debt, the EC estimates that the NGEU effects on GDP level range from 4.2% in 2024 to 1.5% in 2030 for fiscal impulses ranging between 1.5% and 2.3% of GDP in four years. In the short term the estimated fiscal multiplier is equal to 1.37 and the cumulative fiscal multiplier until 2024 is equal to 1.71, decreasing significantly after that year.

In a similar vein, in Figure 9 we have simulated the effects of NGEU with EREMS for the low (50% grants and 50% loans) and high scenarios (100% grants and 50% loans). We make the same assumptions as the EC for comparability with their results. The only difference is that we use a DSGE model that has been calibrated and estimated for the Spanish economy. In particular, we obtain slightly minor effects than the EC and the Spanish Government (Ministerio de Hacienda, 2020). In the high scenario, GDP increases by 3 pp in 2024 (4 pp in the simulation of the EC), with a peak fiscal multiplier equal to 1.33 (1.83 for the EC). The cumulative fiscal multiplier from 2021 to 2024 is 1.08 (1.65 for the EC).

It is important to take these simulation results with some caution. The effects of NGEU on the Spanish economy will depend on so many factors that can hardly be fully taken into account in a quantitative analysis like ours. The first factor is the absorption and execution capacities of these European funds by the Spanish public administration. With NGEU Spain will have available an aid that more than doubles the structural funds of the last multiannual financial framework of the EU, to execute it in approximately half the time. Second, many characteristics of the current economic conditions favour high fiscal multipliers (Blanchard and Leigh, 2013, and Andrés and Doménech, 2013), such as, the low-capacity utilization of many inputs, the expansionary monetary policy in a low or even negative interest rate environment (Christiano et al., 2011), the ability of the ECB to dampen any sovereign risk (Corsetti et al., 2013), or a higher share of financial restricted economic agents. Nevertheless, high uncertainty may increase precautionary saving and reduce the effects of government spending as in Alloza (2017). Third, the focus of NGEU funds on transformation projects that increase potential growth also increase the likelihood of higher fiscal multipliers. Fourth, as a large part of funds are grants, Ricardian equivalence is less likely. For example, we have checked that if Spain receives 2.25% of GDP in EU grants, the cumulative fiscal multiplier from 2021 to 2024 is 30% higher than in the case the same amount is financed only by EU loans.

At the end of the day, the main factors will be the effectiveness and the speed of the projects financed by these European funds (with positive ex ante public policy evaluations), its design, selection, governance, execution and ability to increase potential growth. The last point is extremely important. To the extent that NGEU may increase potential growth, this should reinforce confidence, reduce precautionary saving and increase certainty about the ability of the government to sustain or even reduce the public debt to GDP ratio, avoiding a trade-off between fiscal expansion and the risk of unsustainable debt dynamics, as pointed out by Blanchard (2019). Structural reforms, in line with the EC’s Specific Recommendations to Spain, would also significantly increase the effects of NGEU in the long term, facilitating digitization and transition to an emissions-neutral economy, increasing potential growth and productivity, and reducing structural unemployment (European Commission, 2019).

6. Conclusions

In this article we have analysed the stabilizing role of economic policies during the COVID-19 crisis in Spain. First, we have estimated the contribution of the structural shocks that explain the behaviour of the main macroeconomic aggregates, using a DSGE model. Our results highlight the importance of supply and demand shocks in explaining the COVID-19 crisis. During the recession caused by the lockdown, supply shocks represented 58% of the fall of GDP per WAP and demand and credit represented the remaining 42%. With the recovery started in the third quarter of 2020, demand has been recovering and most of the annual decline at the end of the year is explained by supply factors. Within them, the factor that has contributed the most to the fall in GDP per WAP has been TFP, due to the lockdown and closure of economic activities. In the second quarter its contribution is approximately half of all the observed decrease in the level of activity. Conditional on the forecasts used for the last part of 2020, TFP gradually recovers, although its negative contribution does not disappear, while mark-ups also contribute negatively, with a fall of almost 5 pp to year-on-year growth at the end of 2020. Regarding the public components of aggregate demand, their contribution has been positive and slightly above one percentage point of GDP at the end of 2020. On the contrary, implicit tax rates on labor and capital incomes have been procyclical and in the second and third quarters of 2020 have subtracted one percentage point of year-on-year GDP per WAP growth. Therefore, tax exemptions and deferrals have only partially compensated the fall of the tax bases and have not prevented the increase in the tax burden on labour and, to a lesser extent, on capital incomes. The results confirm that unemployment benefits, job furlough schemes and self-employed aids for temporary cessation of activity have been the main fiscal instruments to avoid a larger fall of aggregate demand and the main determinants of the deterioration of the general government primary budget balance during the crisis.

In a second exercise, we have simulated a counterfactual scenario for GDP in absence of the COVID-19 economic policy measures. We show that the set of policies implemented had a significant impact on mitigating the decline in economic activity. In particular, according to our results, the annual fall in GDP moderates at least by 5 percentage points thanks to these stabilizing policies, with a larger effect in the second quarter when discretionary fiscal policies limited the fall of GDP by 7.6 pp.

Finally, we have estimated the potential effects of NGEU in the Spanish economy. Assuming that Spain may receive between 1.5 and 2.25 percentage points of GDP between EU grants and loans from 2021 to 2024, to finance mainly public investment, GDP could increase between 2 and 3 pp in 2024, with a peak fiscal multiplier equal to 1.33 and a cumulative fiscal multiplier of 1.08 in these four years. These effects would be larger if Spain implements structural reforms in line with the Country Specific Recommendations made by the European Commission.

All these results show the usefulness of a DSGE model, like EREMS, as a practical tool for the applied economic analysis and understanding of the Spanish economy, complementing other helpful empirical methodologies already available.