Monetary policy surprises and fiscal sustainability: the case of the Euro Area

Ionta, Serena; Afonso, António; Alves, José Article — Published Version Monetary policy surprises and fiscal sustainability: the case of the Euro Area Economic Change and Restructuring Provided in Cooperation with: Springer Nature Suggested Citation: Ionta, Serena; Afonso, António; Alves, José (2025) : Monetary policy surprises and fiscal sustainability: the case of the Euro Area, Economic Change and Restructuring, ISSN 1574-0277, Springer US, New York, NY, Vol. 58, Iss. 3, https://doi.org/10.1007/s10644-025-09881-4 This Version is available at: https://hdl.handle.net/10419/323354 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) Economic Change and Restructuring (2025) 58:42 https://doi.org/10.1007/s10644-025-09881-4 Monetary policy surprises andfiscal sustainability: thecase oftheEuro Area SerenaIonta1· AntónioAfonso2,3· JoséAlves2,3 Received: 10 October 2024 / Accepted: 8 April 2025 / Published online: 13 May 2025 © The Author(s) 2025 Abstract We study the interaction between monetary and fiscal policies in the Euro Area, in particular the effect of monetary surprise shocks on real output and the price level under different fiscal sustainability regimes. We first estimate a time-varying Bohn (Q J Econ 113:949–963, 1998) rule using the Schlicht (2003) method. Then, we use a nonlinear local projection model for the Euro Area (aggregate data), Germany, Italy, and Portugal conditional on the fiscal regimes obtained in the first step. We find that the effect of monetary shocks depends on the degree of fiscal sustainability of each country. In the case of a more Ricardian regime, output and prices respond to monetary tightening by contracting. Instead, in the less Ricardian regime, the response is insignificant or even positive. Our results show that fiscal solvency is important for the effectiveness of monetary policy. The results are robust to different specifications and models. Keywords Monetary surprises· Fiscal sustainability· Local projection models· Fiscal-monetary policy mix· Euro Area· Germany· Italy· Portugal JEL C32· E58· E62· E63 * Serena Ionta [email protected] António Afonso aaf[email protected] José Alves jal[email protected] 1 Department ofFinance, Bocconi University, Milan, Italy 2 UECE – Research Unit onComplexity andEconomics, REM – Research inEconomics andMathematics, ISEG – Lisbon School ofEconomics andManagement, Universidade de Lisboa, Lisbon, Portugal 3 Center forEconomic Studies andIfo Institute, Munich, Germany Economic Change and Restructuring (2025) 58:42 42 Page 2 of 20 1 Introduction There has been a recurring ongoing debate about the importance of the interaction between fiscal and monetary policy since notably the Global and Financial Crisis (GFC) of 2008–2009. This debate has intensified with the pandemic crisis and the consequent fiscal and monetary policy responses. In addition, the geopolitical crisis of the past two years has triggered an inflationary dynamic that is still in place. Some studies attribute its persistence not to the energy crisis but to demand and fiscal factors (Bianchi and Melosi 2022; Cochrane 2022a, 2022b). In particular, they see today’s inflation as a consequence of the large pandemic fiscal packages, central banks’ accommodative monetary policies, and agents’ expectations about the future conduct of government policy. While this argument may hold in the USA, where fiscal stimuli have likely fueled inflationary pressures, the Euro Area presents a more complex case. In some instances, fiscal expansion has appeared to mitigate inflationary pressures, while in others, its effects have been less clear. This highlights the importance of studying the interaction between fiscal policies and the European Central Bank’s monetary policy, especially within the Euro Area’s unique institutional framework, characterized by a single monetary authority and multiple fiscal policymakers. In this asymmetric setting, fiscal rules and treaties aim to maintain a clear separation between monetary and fiscal policies, based on the belief that macroeconomic stability relies on an independent central bank ensuring price stability and fiscal authorities maintaining sustainable debt levels. However, recent developments, such as the Pandemic Emergency Purchase Program (PEPP) and the activation of the general escape clause of the Stability and Growth Pact in March 2020, have challenged this framework, necessitating stronger policy coordination. The changing evolution of economic policy coordination is a topic that has been studied extensively in the theoretical literature, but less so in the empirical one. For example, the Fiscal Theory of the Price Level (FTPL) shows the existence of different policy coordination schemes. The monetary-dominant regime, in which monetary policy is active and fiscal policy is passive (Ricardian fiscal regime), alternates with the fiscal-dominant regime, in which the government chooses the primary budget balance independently of the public debt-to-GDP ratio and prices adjust endogenously to satisfy the government budget constraint. Hence, it would be then up to the government budget constraint to play a key role in the determination of the price level. Several studies have dealt with such topic, notably Sargent and Wallace (1981), Leeper (1991), Sims (1994), Woodford (1995) and Cochrane (2001). In this framework, one policy’s effectiveness on macroeconomic outcomes depends on the other policy in place. The main objective of this paper is to investigate the effectiveness of Jaronciski and Karadi (2020)’s monetary surprises in the Euro Area, conditional on different degrees of fiscal sustainability. First, to distinguish between high and low fiscal sustainability regimes, we implement the time-varying fiscal reaction function (Bohn 1998) using Schlicht (2003)’s method. Second, we use the local projection Economic Change and Restructuring (2025) 58:42 Page 3 of 20 42 method (Jordà 2005) and compare the results of the linear, threshold and smooth transition models. We use quarterly data for Euro Area (aggregated), Germany, Italy, and Portugal. We choose these countries in order to cover countries with different fiscal characteristics. The literature that has empirically estimated the FTPL has mostly looked only at fiscal rules or examined the conduct of monetary policy separately from fiscal policy. Our main contribution is to look directly at the effectiveness of monetary policy under different fiscal sustainability regimes. To the best of our knowledge, this is the first attempt in the literature that uses a time-varying fiscal reaction function (Bohn 1998) to distinguish between more and less Ricardian periods. Moreover, we run this test for the Euro Area, in order to examine the dependence of a European central bank’s policy on the fiscal stance of each member country. This is something unexplored in the literature and provides a comprehensive view of the Fiscal Theory within an incomplete monetary union such as the European one. As regards our results, we show that the effect of monetary shocks indeed depends on each country’s fiscal sustainability degree. The findings are robust with different specifications and models. This paper is organized as follows. Section2 reviews the literature. Section3 explains the empirical strategy. Section 4 provides estimation results and related discussion. Section5 concludes. 2 Related literature This paper refers to three strands of literature. The first is related to the Fiscal Theory of Price Level (FTPL) literature. The seminal work on the relationship between fiscal policy and inflation is by Sargent and Wallace (1981). The authors show how, under certain assumptions (notably when population growth is lower than the interest rate), the monetary authority loses control over price stability and is bound by the government’s intertemporal budget. In particular, when fiscal policy “dominates” monetary policy, deficits are not financed solely by new bond sales, and the monetary authority is forced to create money and tolerate additional inflation (even if initially tries to control the growth rate on money). As defined by Leeper (1991), this scenario is also referred to as an active fiscal policy and a passive monetary policy regime,1 where “passive” stands for the policy that does not freely and independently control its policy variable and fiscal activism does not prevent an explosive path of government debt. The latter policy is constrained by the actions of the active authority, which specifies the policy and uniquely determines the equilibrium price function. A stable and unique equilibrium solution requires a combination of active and passive policies, corresponding to the “fiscal dominance” or “monetary dominance” regimes. Other related contributions 1 Woodford (1995) also calls this regime a “Non-Ricardian” regime. Economic Change and Restructuring (2025) 58:42 42 Page 4 of 20 can be attributed to Sims (1994, 2011), Woodford (1994), and Cochrane (1998, 2001, 2023).2 Bianchi and Ilut (2017), studying the FTPL equilibrium in a Markov-switching DSGE model, show how the effect of a monetary policy shock depends on the regime in place: tighter monetary policy causes inflation to rise under fiscal dominance and fall under monetary dominance. The second strand of the literature concerns empirical studies on fiscal sustainability and the consequent determination of fiscal regimes. The literature divides empirical tests into a backward-looking approach (Bohn 1998) and a forward-looking approach (Canzoneri etal. 2001). According to the first approach, fiscal policy is sustainable (or even Ricardian/passive) if it adjusts the primary surplus to the increase in lagged debt. According to the forward-looking approach, policy is Ricardian if the shocks to the primary surplus lead to a reduction in debt. Moreover, another way to assess the degree of fiscal sustainability is based on unit root tests and the cointegration study of the relationships between the two sides of the government budget (Hakkio and Rush 1991; Quintos 1995; Afonso 2005). There is no consensus in the literature regarding the sustainability outcomes of the Euro Area. On the one hand, some studies do not find empirical evidence for Ricardian regimes; for example, Semmler and Zhang (2004) find nonRicardian regimes in both France and Germany. Afonso (2005) finds a lack of fiscal sustainability within the EU-15 sample and calls it “unpleasant” from a policymaker’s point of view.3 Afonso and Jalles (2017), who study 11 European countries, show that fiscal policy has been sustainable only in the cases of Belgium, France, Germany, and the Netherlands. On the other hand, a number of works show the existence of fiscal Ricardian regimes in Europe (Favero 2002; Creel and Bihan 2006; Afonso 2008; Afonso and Jalles 2017).4 Panjer etal. (2020) study the existence of Ricardian regimes in the Eurozone using the Area Wide Model fiscal database (Paredes etal. 2014), taking into account the structural breaks and show how fiscal sustainability is time-varying. The authors find no evidence in favor of either regime for the period before the Euro Convergence Criteria, and a Ricardian regime after the ECC until the Global Financial Crisis, when fiscal policy became active. This latter idea of nonlinearity is also related to the broader emerging literature on MS methodology (e.g., Davig etal. 2006, and Bianchi and Melosi 2017, for the US, and Afonso and Toffano 2013, for the EU). Hence, in this paper, we do not examine the presence or absence of fiscal sustainability, but rather the effect of monetary policy conditional on this varying degree of sustainability. 2 It is important to mention other works which have studied the equilibrium within MS-DSGE models, focusing on the underlying theoretical relationships such as Davig etal. (2006), Leeper and Leith (2016), Bianchi and Melosi (2017). 3 The author does cointegration tests for the annual sample period 1970–2003. 4 There is also a strand of literature that has dealt with the impact that European treaties have had on the degree of sustainability: Buti and Giudice (2002) and Galì and Perotti (2003) among others. Economic Change and Restructuring (2025) 58:42 Page 5 of 20 42 Finally, the third strand of the literature relates to empirical studies of the interactions between monetary and fiscal policies. For the EMU countries, Melitz (2000) finds evidence of policy substitutability, namely coordinated macroeconomic policy: an easier fiscal policy leads to tighter monetary policy and an easier monetary policy to tighter fiscal policy. Muscatelli etal. (2004) estimate a VAR for G7 countries with both fiscal and monetary policy instruments and show that policy interdependence is asymmetric and differs across countries; however, complementarity seems to dominate substitutability. Kliem etal. (2016a) estimate the low-frequency time-varying relationship between fiscal deficits and inflation for the USA, and Kliem etal. (2016b) extend the same analysis to Germany and Italy. According to the authors, the low-frequency relationship between the fiscal stance and inflation is around zero for periods to which narrative accounts assign an independent central bank and a responsible fiscal authority (e.g., when Paul Volcker became chairman of the Federal Reserve, and Italy joined the EMU).5 Instead, the low-frequency relationship is high whenever the narrative accounts point to a fiscal authority which did not stabilize its outstanding government debt together with a central bank that accommodated this behavior. De Luigi and Huber (2018), through a Threshold SVAR analysis, discover that the effect of monetary policy is less pronounced in ‘high’ debt regimes than the ‘low’ ones, pointing to the different spending and investment behavior of private sector agents. Afonso and Gonçalves (2020) use a SVAR approach to investigate on the effects of fiscal and monetary policies, as well as their interactions with the USA and the Euro Area; they find in both cases that the policies act as complements. Hülsewig and Rottmann (2022) discover that the fiscal balance improves in response to monetary policy surprises that bring down yields on sovereign bonds. Kloosterman etal. (2022) estimate the effects of monetary policy shocks across different fiscal regimes through a panel smooth transition local projection model for ten Euro Area countries, where the fiscal regimes are characterized by the change in the cyclically adjusted primary balance. They show that expansionary (contractionary) monetary policy shocks lead to significant increases (decreases) in inflation and output, but only when fiscal policy is also expansionary (contractionary). Reichlin etal. (2023) study the fiscal-monetary policy mix in Euro Area, their findings suggest that conventional monetary easing is accompanied by an expansionary fiscal policy, but unconventional monetary easing is not. What differentiates us from the above literature is the distinction we make between fiscal regimes. Our fiscal stance indicates neither an expansionary/ restrictive fiscal policy (Kloosterman etal. 2022) nor a low/high level of public debt (De Luigi and Huber 2018). We are interested in the sustainability behavior of the fiscal authority, and we estimate it through a time-varying fiscal rule a la Bohn (1998). We believe that dividing the sample into periods of more or less fiscal solvency is an appropriate method to best test the FTPL empirically. 5 This low-frequency relationship between the fiscal stance and inflation is the procedure described in Sargent and Surico (2011), based on Lucas (1980)’s regression. Economic Change and Restructuring (2025) 58:42 42 Page 6 of 20 3 Methodology, data, andmonetary policy surprises We assess the impact of monetary policy shocks on the level of real output and prices. To do so, we use the Local Projection methodology (Jordà 2005). The LPs method offers several advantages over the traditional SVAR approach. First, it is a better estimator than the VAR when the latter is misspecified; second, it is much easier to implement because it is an OLS regression; and third, it is suitable for nonlinear estimation, which is the ultimate goal of this paper.6 We use quarterly data ranging from 2003Q4 to 2021Q4 for the aggregated Euro Area, and from 2001Q4 to 2021Q4 for Germany, Italy, and Portugal, and we estimate three models: (1) an unconditional linear model, (2) a nonlinear threshold model conditional on the fiscal stance (Jordà 2005), and (3) a conditional smooth transition model (Auerbach and Gorodnichenko 2012). We have chosen these countries for specific reasons. We study the Euro Area as an aggregate (i) because monetary surprises are common to all countries, and (ii) because we want to have an overall and summarized view of the aggregate economic and political structure of the Euro Area; furthermore, we analyze the other three countries because of their different characteristics, especially from a fiscal point of view. We believe that Germany represents a “core” country, especially from a fiscal and financial markets point of view; Italy is an example of a country in the “middle,” characterized by both high domestic product and some fiscal imbalances; and Portugal is to be considered as a “periphery” country. To discriminate between different fiscal regimes and to perform time-varying fiscal regression, we follow Afonso and Jalles (2017) and Afonso etal. (2025), and we estimate Bohn (1998)’s rule through Schlicht (2003)’s method. The approach proposed by Schlicht (2003) has several advantages compared to other methods to compute time-varying coefficients (TVC), such as rolling windows. It uses all observations in the sample to estimate the magnitude of spillover in each period, which by construction is not possible in the rolling windows approach. In addition, changes in the size of estimated TVC in a given year come from innovations in the same year, rather than from shocks occurring in neighboring years; it reflects the fact that changes in policy are slow and depend on the immediate past. Lastly, it reduces reverse causality problems when the estimated TVC is used as an explanatory variable since it depends on the past (Afonso and Coelho, 2022). Hence, we follow a two-step approach. First, we estimate the following timevarying equation: where st is the primary budget balance, bt−4 is the lagged public debt, the outputgapt−4 is the output gap computed by the Hodrick-Prescott filter.7 We take the lagged value “-4” because the variables are quarterly but at the same time (1) st=𝛼+𝛿bt−4+𝜓outputgapt−4+𝜀t 6 For a discussion of the local projection method see Ramey (2016) or Kilian and Kim (2011). 7 We compute it choosing 1600 as the lamda for the HP filter. We divide the cyclical component on its trend, and we multiply by 100. Economic Change and Restructuring (2025) 58:42 Page 7 of 20 42 annualized. Fiscal variables are as ratio of GDP. We discriminate the periods based on the average of the 𝛿 coefficients, which indicate the magnitude of fiscal solvency. When the coefficient is greater than the average, we are in a more (high) Ricardian regime; when it is less, we are in a less (low) Ricardian regime. Second, we construct the impulse response functions (IRF), estimating our LP model. As for the monetary shocks, we follow Ramey and Zubairy (2018), and we insert an exogenous shock already identified: the surprises of Jaronciski and Karadi (2020). The authors derive a monetary policy shock by focusing on the changes in the Euro Stoxx 50 index and the price difference between the EONIA interest swaps in the windows around press statements and conferences. The surprises are identified by imposing sign restrictions. An expansionary shock is assumed to raise the stock price. The surprises are aggregated by summing the shocks within the same quarter, and then divided by the standard deviation. The first model is an estimation of the following equation: where yt+h is our variable of interest, real output and inflation, 𝛼h denotes the constant, xt is the vector of control variables that includes two lags of the LHS variable and one lag of the monetary policy shock, and shockt is our monetary surprises shock.8 The coefficient 𝛽h corresponds to the response of yt+h to the shock at time t. The impulse responses are the sequence of all estimated 𝛽h . The second model (Eq.3) is a nonlinear extension of the first one and it separates data into the two fiscal regimes, using a binary (dummy) variable I , which is one period lagged to the shock.9 Hence, It is 0 when the sustainability coefficient is lower than the average and 1 when it is higher: The third model (Eq. 4) is a smooth transition model, which computes state probabilities with a logistic function, preserving the magnitude of the fiscal stance: where F (zt)=e −𝛾(z t ) (1+e −𝛾(zt) ) is our logistic function, zt is the standardized state variable, 𝛾 is the parameter which measures how abruptly the economy transitions between the two fiscal state regimes; we set it to 1.5.10 When fiscal sustainability (2) yt+h =𝛼 h +𝛽 h shock t +𝜙x t +u h t+h ,h=0, 1, …,H− 1 (3) yt+h = ( 1−I t−1 )[𝛼 ah +𝛽 ah shock t +𝜙 a x t] +(I t−1 ) [ 𝛼 bh +𝛽 bh shock t +𝜙 b x t] +u h t+h. (4) yt+h =F ( z t−1) [𝛼 ah +𝛽 ah shock t +𝜙 a x t ]+(1−F ( z t−1) ) [ 𝛼 bh +𝛽 bh shock t +𝜙 b x t] +u h t+h 8 A further test was done by entering 4 lags instead of 2 as regards the control variables, and taking only positive monetary policy shocks (corresponding to monetary tightening); the results do not change. 9 We follow the literature (Ramey and Zubairy, 2018), and we insert the dummy in a lagged manner because of a possible interference between the state and the shock at time t. 10 Robustness tests have been done changing 𝛾 , and it does not change the findings of the estimates. This results are available upon request. Economic Change and Restructuring (2025) 58:42 42 Page 8 of 20 improves, our state variable zt increases and causes F( z t) to go to 0. On the other case, F( z t) tends toward 1 when the fiscal sustainability gets worse. Regarding the fiscal variables, primary balances and government debt are taken from the EUROSTAT dataset and then annualized. The endogenous variables of the LP models are the logarithmic levels of real output and the price index taken from the FRED dataset. The shocks are common to all the countries and are taken from Jarociński’s site (Fig.1). More information about the dataset is in Appendix. Figure 2 illustrates the TVC-estimated magnitude of fiscal sustainability for the countries studied. The figure highlights several key points: (i) a common trend Fig. 1 ECB monetary surprises shocks. Notes Monetary surprises are taken from Jarociński and Karadi (2020), quarterly aggregated, and divided by the standard deviation Fig. 2 Time-varying sustainability (Bohn’s rule). Note Schlicht (2003)’s time-varying coefficients of regression of primary balance on the lagged debt-to-GDP ratio (Bohn 1998) Economic Change and Restructuring (2025) 58:42 Page 15 of 20 42 Finally, further robustness analyses were performed: first, we checked for 4 lags instead of 2; second, we included only the positive shocks (those of the monetary contraction); third, we made the same estimates using output and prices in growth rates. The results are in Appendix. 5 Conclusions andpolicy implications In recent decades, the study of the interactions between monetary policy and fiscal policy has become increasingly important. The literature shows the existence of a dependence between the two policies for their relative effectiveness. Accordingly, we investigate the effect of Jarociński and Karadi (2020) monetary policy surprises on output and price levels under different degrees of fiscal sustainability for the Euro Area (aggregate data), Germany, Italy, and Portugal. We use quarterly data from 2003Q4 to 2021Q4 for the Euro Area and from 2001Q4 to 2021Q4 for the other countries. Our study consists of two parts. First, we estimate a time-varying fiscal reaction function (Bohn 1998), namely the responses of the primary fiscal balance to lagged debt. We do this using the method of Schlicht (2003). Next, we estimate three models: (1) a linear model, (2) a threshold model conditional on our fiscal stance (Jordà 2005), and (3) a smooth transition model (Auerbach and Gorodnichenko 2012). Our fiscal stance represents periods of “low” and “high” sustainability, based on the average of time-varying coefficients indicating the magnitude of fiscal solvency. According to our knowledge, this relationship between surprises and time-varying sustainability has never been investigated before. Our findings can be summarized as follows: (i) the unconditional effect of monetary surprise shocks has a recessionary effect on the macroeconomic outcomes, compressing output, and price level; (ii) when we insert the fiscal stance, the monetary effect depends on the regime in place; specifically, in the “higher” sustainable regime output and prices tend to respond more strongly to monetary tightening, in contrast to the “lower” sustainable regime; (iii) in the most Ricardian regime the output contraction is very pronounced compared to the unconditioned linear model; (iv) for all the countries in the irresponsible regime, we find an increase in the price level, in line with the so-called “Stepping on a rake” effect (Sims 2011); (v) when we discriminate the fiscal stance through the contemporaneous relationship between government revenues and expenditures (Afonso 2005), the main results do not change and are robust, even if they do not manage to capture the fiscal inflation; (vi) the dependence of the effectiveness of monetary policy on fiscal solvency is valid for Euro Area and all the study countries, therefore it does not depend on whether a country is “core” or “periphery,” but only by the policy conduct over time. Moreover, according to our estimation, the smooth transition model manages to fit better in terms of results and significance. This is due to the logistic function, which does not lose any observations and preserves the magnitude of the fiscal stance. Our results have important policy implications. The most important one is related to the European Central Bank’s ability to control inflation. According to Economic Change and Restructuring (2025) 58:42 42 Page 16 of 20 our idea, the ECB’s effectiveness depends strongly on the type of fiscal policy pursued by each member state, in particular, whether the single fiscal authority is pursuing a path of fiscal sustainability or not. The latter suggestion is in line with the FTPL, and with Cochrane (2022a, 2022b), who states “… Monetary policy is important, as a simplistic reading of “fiscal theory” might not recognize, but fiscal policy also creates inflation that monetary policy cannot fully control, as a simplistic reading of the dictum “inflation is always and everywhere a monetary phenomenon” might deny…”. Appendix Data source Countries: Euro Area 20; Germany; Italy; Portugal • Primary Balance on GDP. Constructed Variable. Total General Government Expenditure—Total General Government Revenue + Interest on Debt. Quarterly data. Annualized and expressed as a percentage of GDP. Data Source: EUROSTAT. • Public Debt on GDP. Constructed Variable. Quarterly Data. The ratio of cumulative Debt Quarter over Nominal GDP Year. Data Source: EUROSTAT. • Total General Government Revenue on GDP. Constructed Variable. Quarterly Data. The Ratio of Total General Government Revenue (Annualized) over Nominal GDP Year. Data Source: EUROSTAT. • Total General Government Expenditure on GDP. Constructed Variable. Quarterly Data. The Ratio of Total General Government Expenditure (Annualized) over Nominal GDP Year. Data Source: EUROSTAT. • Monetary Surprises. Jaronciski and Karadi (2020). Shock aggregated quarterly, through the sum of the monthly shocks. Divided by their Standard Deviation. • Price Index. Harmonized Index of Consumer Prices: All Items. Index 2015 = 100, Quarterly. Seasonally Adjusted by Census-X13 (R Software). Variable taken in natural logarithm. Data Source: FRED. • Real Gross Domestic Product. Millions of Chained 2010 Euros, Quarterly, Seasonally Adjusted. Variable taken in natural logarithm. Data Source: FRED. • HCPI Growth. All Items. Index 2015 = 100, Quarterly. Seasonally Adjusted by Census-X13 (R Software). Data Source: FRED. • Real Output Growth. Millions of Chained 2010 Euros, Quarterly, Seasonally Adjusted. Data Source: FRED. Only positive surprises shock (monetary tightening) The next figures show the results of the model in which the monetary surprises are positive, indicating an even sharper monetary tightening than in the baseline Economic Change and Restructuring (2025) 58:42 Page 17 of 20 42 model. Overall, the results not only confirm those of the previous model (with all shocks), but also accentuate even more the recessionary effect on the economy in the less Ricardian regime. Moreover, in this specification, we are able to capture the dynamics of the wealth effect through the pattern of output which increases in the less sustainable regime for Italy and Germany (smooth transition model). See Figs. 12, 13, 14 and 15 Fig. 12 Euro Area results (2003Q4–2021Q4), Bohn’s rule. Only positive surprises. Note The IRFs indicate the responses of real output and the price level to monetary policy surprises, for the 12-quarter forecast horizon. The gray bands indicate the 90 percent confidence interval. The linear model is not conditional on the new fiscal stance, while the second and third models represent the dummy/threshold approach and the smooth transition model, respectively Fig. 13 Germany results (2001Q4–2021Q4), Bohn’s rule. Only positive surprises. Note The IRFs indicate the responses of real output and the price level to monetary policy surprises, for the 12-quarter forecast horizon. The gray bands indicate the 90 percent confidence interval. The linear model is not conditional on the new fiscal stance, while the second and third models represent the dummy/threshold approach and the smooth transition model, respectively Fig. 14 Italy results (2001Q4–2021Q4), Bohn’s rule. Only positive surprises. Note The IRFs indicate the responses of real output and the price level to monetary policy surprises, for the 12-quarter forecast horizon. The gray bands indicate the 90 percent confidence interval. The linear model is not conditional on the new fiscal stance, while the second and third models represent the dummy/threshold approach and the smooth transition model, respectively Economic Change and Restructuring (2025) 58:42 42 Page 18 of 20 Acknowlegdement We thank the editor and two anonynous referees for very useful suggestions. The authors acknowledge financial support from FCT – Fundação para a Ciência e Tecnologia (Portugal), national funding through research grant UIDB/05069/2020. The opinions expressed herein are those of the authors and do not necessarily reflect those of the authors’ employers. The authors declare that they have no conflicts of interest, financial or otherwise, that could have influenced the research and findings presented in this paper. Any remaining errors or omissions are solely the responsibility of the authors. Funding Open access funding provided by Università Commerciale Luigi Bocconi within the CRUICARE Agreement. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. References Aastveit KA, Natvik GJ, Sola S (2017) Economic uncertainty and the influence of monetary policy. 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