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In this paper, we construct a Dynamic Stochastic General Equilibrium (DSGE) model to examine the implications of dual rates for green lending. We demonstrate that implementing a distinct interest rate for banks engaged in green lending can effectively mitigate transition risks while channeling more capital towards green production sectors and firms for an immediate cut of emissions and net zero emission economy targets.
We use a structural VAR model to study the German natural gas market and investigate the impact of the 2022 Russian supply stop on the German economy. Combining conventional and narrative sign restrictions, we find that gas supply and demand shocks have large and persistent price effects, while output effects tend to be moderate. The 2022 natural gas price spike was driven by adverse supply
shocks and positive storage demand shocks, as Germany filled its inventories before the winter. Counterfactual simulations of an embargo on natural gas imports from Russia indicate similar positive price and negative output effects compared to what we observe in the data.
This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward non-linear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE) model, a Bayesian vector autoregression (BVAR) using optimized priors as well as Greenbook and SPF forecasts. Model estimation and forecasting is based on an expanding window scheme using quarterly U.S. real-time data (1964Q2:2020Q3) for 8 macroeconomic time series (GDP, inflation, federal funds rate, spread, consumption, investment, wage, hours worked), allowing for up to 8 quarter ahead forecasts. The results show that the BVAR improves forecasts compared to the DSGE model, however there is evidence for an overall improvement of predictions when relying on ANN, or including them in a weighted average. Especially, ANN-based inflation forecasts improve other predictions by up to 50%. These results indicate that nonlinear data-driven ANNs are a useful method when it comes to macroeconomic forecasting.
Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. The author introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables between 1990 and 2015, the economy is estimated by artificial neural networks. Historical counterfactual analyses show that real effects are less pronounced than yield effects.
Disentangling the effects of the individual asset purchase programs, impulse response functions provide evidence for QE being less effective the more the crisis is overcome. The peak effects of all QE interventions during the Financial Crisis only amounts to 1.3 pp for GDP growth and 0.6 pp for inflation respectively. Hence, the time as well as the volume of the interventions should be deliberated.
We create an alternative version of the present utility value formula to explicitly show that every store-of-value in the economy bears utility-interest (non-pecuniary income) for ist holder regardless of possible interest earnings from financial markets. In addition, we generalize the well-known welfare measures of consumer and producer surplus as present value concepts and apply them not only for the production and usage of consumer goods and durables but also for money and other financial assets. This helps us, inter alia, to formalize the circumstances under which even a producer of legal tender might become insolvent. We also develop a new measure of seigniorage and demonstrate why the well-established concept of monetary seigniorage is flawed. Our framework also allows us to formulate the conditions for liability-issued money such as inside money and financial instruments such as debt certificates to become – somewhat paradoxically – net wealth of the society.
The Federal Reserve has been publishing federal funds rate prescriptions from Taylor rules in its Monetary Policy Report since 2017. The signals from the rules aligned with Fed action on many occasions, but in some cases the Fed opted for a different route. This paper reviews the implications of the rules during the coronavirus pandemic and the subsequent inflation surge and derives projections for the future.
In 2020, the Fed took the negative prescribed rates, which were far below the effective lower bound on the nominal interest rate, as support for extensive and long-lasting quantitative easing. Yet, the calculations overstate the extent of the constraint, because they neglect the supply side effects of the pandemic.
The paper proposes a simple model-based adjustment to the resource gap used by the rules for 2020. In 2021, the rules clearly signaled the need for tightening because of the rise of inflation, yet the Fed waited until spring 2022 to raise the federal funds rate. With the decline of inflation over the course of 2023, the rules’ prescriptions have also come down. They fall below the actual federal funds rate target range in 2024. Several caveats concerning the projections of the interest rate prescriptions are discussed.
Despite a number of helpful changes, including the adoption of an inflation target, the Fed’s monetary policy strategy proved insufficiently resilient in recent years. While the Fed eased policy appropriately during the pandemic, it fell behind the curve during the post-pandemic recovery. During 2021, the Fed kept easing policy while the inflation outlook was deteriorating and the economy was growing considerably faster than the economy’s natural growth rate—the sum of the Fed’s 2% inflation goal and the growth rate of potential output.
The resilience of the Fed’s monetary policy strategy could be enhanced, and such errors be avoided with guidance from a simple natural growth targeting rule that prescribes that the federal funds rate during each quarter be raised (cut) when projected nominal income growth exceeds (falls short) of the economy’s natural growth rate. An illustration with real-time data and forecasts since the early 1990s shows that Fed policy has not persistently deviated from this simple rule with the notable exception of the period coinciding with the Fed’s post-pandemic policy error.
Highlights
• Six Newton methods for solving matrix quadratic equations in linear DSGE models.
• Compared to QZ using 99 different DSGE models including Smets and Wouters (2007).
• Newton methods more accurate than QZ with comparable computation burden.
• Apt for refining solutions from alternative methods or nearby parameterizations.
Abstract
This paper presents and compares Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. We find that Newton-based methods compare favorably in solving DSGE models, providing higher accuracy as measured by the forward error of the solution at a comparable computation burden. The methods, however, suffer from their inability to guarantee convergence to a particular, e.g. unique stable, solution, but their iterative procedures lend themselves to refining solutions either from different methods or parameterizations.
The Eurosystem and the Deutsche Bundesbank will incur substantial losses in 2023 that are likely to persist for several years. Due to the massive purchases of securities in the last 10 years, especially of government bonds, the banks' excess reserves have risen sharply. The resulting high interest payments to the banks since the turnaround in monetary policy, with little income for the large-scale securities holdings, led to massive criticism. The banks were said to be making "unfair" profits as a result, while the fiscal authorities had to forego the previously customary transfers of central bank profits. Populist demands to limit bank profits by, for example, drastically increasing the minimum reserve ratios in the Eurosystem to reduce excess reserves are creating new severe problems and are neither justified nor helpful. Ultimately, the EU member states have benefited for a very long time from historically low interest rates because of the Eurosystem's extraordinary loose monetary policy and must now bear the flip side consequences of the massive expansion of central bank balance sheets during the necessary period of monetary policy normalisation.
Central banks sowing the seeds for a green financial sector? NGFS membership and market reactions
(2024)
In December 2017, during the One Planet Summit in Paris, a group of eight central banks and supervisory authorities launched the “Network for Greening the Financial Sector” (NGFS) to address challenges and risks posed by climate change to the global financial system. Until 06/2023 an additional 69 central banks from all around the world have joined the network. We find that the propensity to join the network can be described as a function in the country’s economic development (e.g., GDP per capita), national institutions (e.g., central bank independence), and performance of the central bank on its mandates (e.g., price stability and output gap). Using an event study design to examine consequences of network expansions in capital markets, we document that a difference portfolio that is long in clean energy stocks and short in fossil fuel stocks benefits from an enlargement of the NGFS. Overall, our results suggest that an increasing number of central banks and supervisory authorities are concerned about climate change and willing to go beyond their traditional objectives, and that the capital market believes they will do so.
The complexities of geopolitical events, financial and fiscal crises, and the ebb and flow of personal life circumstances can weigh heavily on individuals’ minds as they make critical economic decisions. To investigate the impact of cognitive load on such decisions, the authors conducted an incentivized online experiment involving a representative sample of 2,000 French households. The results revealed that exposure to a taxing and persistent cognitive load significantly reduced consumption, particularly for individuals under the threat of furlough, while simultaneously increasing their account balances, particularly for those not facing such employment uncertainty. These effects were not driven by supply constraints or a worsening of credit constraints. Instead, cognitive load primarily affected the optimality of the chosen policy rules and impaired the ability of the standard economic model to accurately predict consumption patterns, although this effect was less pronounced among college-educated subjects
We investigate how unconventional monetary policy, via central banks’ purchases of corporate bonds, unfolds in credit-saturated markets. While this policy results in a loosening of credit market conditions as intended by policymakers, we report two unintended side effects. First, the policy impacts the allocation of credit among industries. Affected banks reallocate loans from investment-grade firms active on bond markets almost entirely to real estate asset managers. Other industries do not obtain more loans, particularly real estate developers and construction firms. We document an increase in real estate prices due to this policy, which fuels real estate overvaluation. Second, more loan write-offs arise from lending to these firms, and banks are not compensated for this risk by higher interest rates. We document a drop in bank profitability and, at the same time, a higher reliance on real estate collateral. Our findings suggest that central banks’ quantitative easing has substantial adverse effects in credit-saturated economies.
This paper applies structure preserving doubling methods to solve the matrix quadratic underlying the recursive solution of linear DSGE models. We present and compare two Structure-Preserving Doubling Algorithms ( SDAs) to other competing methods – the QZ method, a Newton algorithm, and an iterative Bernoulli approach – as well as the related cyclic and logarithmic reduction algorithms. Our comparison is completed using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium scale New Keynesian model of Smets and Wouters (2007) iteratively. We find that both SDAs perform very favorably relative to QZ, with generally more accurate solutions computed in less time. While we collect theoretical convergence results that promise quadratic convergence rates to a unique stable solution, the algorithms may fail to converge when there is a breakdown due to singularity of the coefficient matrices in the recursion. One of the proposed algorithms can overcome this problem by an appropriate (re)initialization. This SDA also performs particular well in refining solutions of different methods or from nearby parameterizations.
Whatever it takes to understand a central banker : embedding their words using neural networks
(2023)
Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. In this paper, the author propose a novel language model that is able to capture subtleties of messages such as one of the most famous sentences in central bank communications when ECB President Mario Draghi stated that "within [its] mandate, the ECB is ready to do whatever it takes to preserve the euro".
The authors utilize a text corpus that is unparalleled in size and diversity in the central bank communication literature, as well as introduce a novel approach to text quantication from computational linguistics. This allows them to provide high-quality central bank-specific textual representations and demonstrate their applicability by developing an index that tracks deviations in the Fed's communication towards inflation targeting. Their findings indicate that these deviations in communication significantly impact monetary policy actions, substantially reducing the reaction towards inflation deviation in the US.
This paper develops and implements a backward and forward error analysis of and condition numbers for the numerical stability of the solutions of linear dynamic stochastic general equilibrium (DSGE) models. Comparing seven different solution methods from the literature, I demonstrate an economically significant loss of accuracy specifically in standard, generalized Schur (or QZ) decomposition based solutions methods resulting from large backward errors in solving the associated matrix quadratic problem. This is illustrated in the monetary macro model of Smets and Wouters (2007) and two production-based asset pricing models, a simple model of external habits with a readily available symbolic solution and the model of Jermann (1998) that lacks such a symbolic solution - QZ-based numerical solutions miss the equity premium by up to several annualized percentage points for parameterizations that either match the chosen calibration targets or are nearby to the parameterization in the literature. While the numerical solution methods from the literature failed to give any indication of these potential errors, easily implementable backward-error metrics and condition numbers are shown to successfully warn of such potential inaccuracies. The analysis is then performed for a database of roughly 100 DSGE models from the literature and a large set of draws from the model of Smets and Wouters (2007). While economically relevant errors do not appear pervasive from these latter applications, accuracies that differ by several orders of magnitude persist.
In his speech at the conference „The SNB and its Watchers“, Otmar Issing, member of the ECB Governing Council from its start in 1998 until 2006, takes a look back at more than twenty years of the conference series „The ECB and Its Watchers“. In June 1999, Issing established this format together with Axel Weber, then Director of the Center for Financial Studies, to discuss the monetary policy strategy of the newly founded central bank with a broad circle of participants, that is academics, bank economists and members of the media on a „neutral ground“. At the annual conference, the ECB and its representatives would play an active role and engage in a lively exchange of view with the other participants. Over the years, Volker Wieland took over as organizer of the conference series, which also was adopted by other central banks. In his contribution at the second conference „The SNB and its Watchers“, Issing summarizes the experience gained from over twenty years of the ECB Watchers Conference.
This paper studies the macro-financial implications of using carbon prices to achieve ambitious greenhouse gas (GHG) emission reduction targets. My empirical evidence shows a 0.6% output loss and a rise of 0.3% in inflation in response to a 1% shock on carbon policy. Furthermore, I also observe financial instability and allocation effects between the clean and highly polluted energy sectors. To have a better prediction of medium and long-term impact, using a medium-large macro-financial DSGE model with environmental aspects, I show the recessionary effect of an ambitious carbon price implementation to achieve climate targets, a 40% reduction in GHG emission causes a 0.7% output loss while reaching a zero-emission economy in 30 years causes a 2.6% output loss. I document an amplified effect of the banking sector during the transition path. The paper also uncovers the beneficial role of pre-announcements of carbon policies in mitigating inflation volatility by 0.2% at its peak, and our results suggest well-communicated carbon policies from authorities and investing to expand the green sector. My findings also stress the use of optimal green monetary and financial policies in mitigating the effects of transition risk and assisting the transition to a zero-emission world. Utilizing a heterogeneous approach with macroprudential tools, I find that optimal macroprudential tools can mitigate the output loss by 0.1% and investment loss by 1%. Importantly, my work highlights the use of capital flow management in the green transition when a global cooperative solution is challenging.
The debate on monetary and fiscal policy is heavily influenced by estimates of the equilibrium real interest rate. In particular, this concerns estimates derived from a simple aggregate demand and Phillips curve model with time-varying components as proposed by Laubach and Williams (2003). For example, Summers (2014a) refers to these estimates as important evidence for a secular stagnation and the need for fiscal stimulus. Yellen (2015, 2017) has made use of such estimates in order to explain and justify why the Federal Reserve has held interest rates so low for so long. First, we re-estimate the United States equilibrium rate with the methodology of Laubach and Williams (2003). Then, we build on their approach and an alternative specification to provide new estimates for the United States, Germany, the euro area and Japan. Third, we subject these estimates to a battery of sensitivity tests. Due to the great uncertainty and sensitivity that accompany these equilibrium rate estimates, the observed decline in the estimates is not a reliable indicator of a need for expansionary monetary and fiscal policy. Yet, if these estimates are employed to determine the appropriate monetary policy stance, such estimates are better used together with the consistent estimate of the level of potential output.
The forward guidance trap
(2023)
This paper examines the policy experience of the Fed, ECB and BOJ during and after the Covid-19 pandemic and draws lessons for monetary policy strategy and ist communication. All three central banks provided appropriate accommodation during the pandemic but two failed to unwind this accommodation in a timely manner. The Fed and ECB guided real interest rates to inappropriately negative levels as the economy recovered from the pandemic, fueling high inflation. The policy error can be traced to decisions regarding forward guidance on policy rates that delayed lift-off while the two central banks continued to expand their balance sheets. The Fed and the ECB fell into the forward guidance trap. This could have been avoided if policy were guided by a forward- looking rule that properly adjusted the nominal interest rate with the evolution of the inflation outlook.
We present determinacy bounds on monetary policy in the sticky information model. We find that these bounds are more conservative here when the long run Phillips curve is vertical than in the standard Calvo sticky price New Keynesian model. Specifically, the Taylor principle is now necessary directly - no amount of output targeting can substitute for the monetary authority’s concern for inflation. These determinacy bounds are obtained by appealing to frequency domain techniques that themselves provide novel interpretations of the Phillips curve.
In the euro area, monetary policy is conducted by a single central bank for 20 member countries. However, countries are heterogeneous in their economic development, including their inflation rates. This paper combines a New Keynesian model and a neural network to assess whether the European Central Bank (ECB) conducted monetary policy between 2002 and 2022 according to the weighted average of the inflation rates within the European Monetary Union (EMU) or reacted more strongly to the inflation rate developments of certain EMU countries.
The New Keynesian model first generates data which is used to train and evaluate several machine learning algorithms. They authors find that a neural network performs best out-of-sample. They use this algorithm to generally classify historical EMU data, and to determine the exact weight on the inflation rate of EMU members in each quarter of the past two decades. Their findings suggest disproportional emphasis of the ECB on the inflation rates of EMU members that exhibited high inflation rate volatility for the vast majority of the time frame considered (80%), with a median inflation weight of 67% on these countries. They show that these results stem from a tendency of the ECB to react more strongly to countries whose inflation rates exhibit greater deviations from their long-term trend.
Climate change has become one of the most prominent concerns globally. In this paper, the authors study the transition risk of greenhouse gas emission reduction in structural environmental-macroeconomic DSGE models. First, they analyze the uncertainty in model prediction on the effect of unanticipated and pre-announced carbon price increases. Second, they conduct optimal model-robust policy in different settings. They find that reducing emissions by 40% causes 0.7% to 4% output loss with 2% on average. Pre-announcement of carbon prices affects the inflation dynamics significantly. The central bank should react slightly less to inflation and output growth during the transition risk. With optimal carbon price designs, it should react even less to inflation, and more to output growth.
We analyze the repercussions of different kinds of uncertainty on cash demand, including uncertainty of the digital infrastructures, confidence crises of the financial system, natural disasters, political uncertainties, and inflationary crises. Based on a comprehensive literature survey, theoretical considerations and complemented by case studies, we derive a classification scheme how cash holdings typically evolve in each of these types of uncertainty by separating between demand for domestic and international cash as well as between transaction and store of value balances. Hereby, we focus on the stabilizing macroeconomic properties of cash and recommend guidelines for cash supply by central banks and the banking system. Finally, we exemplify our analysis with five case studies from the developing world, namely Venezuela, Zimbabwe, Afghanistan, Iraq, and Libya.
Trotz der von der EZB eingeleiteten Zinswende in der zweiten Jahreshälfte 2022 als späte Reaktion auf die deutlich unterschätzte Persistenz hoher Inflationsraten im Euroraum sind die Realzinsen sowohl in der Ex-post-Betrachtung als auch in der Ex-ante-Betrachtung keineswegs als restriktiv einzuschätzen. Die Banken haben allerdings recht rasch strengere Vergaberichtlinien beschlossen, und die Nachfrage im Wohnungsbau und bei den Hypothekarkrediten ist stark eingebrochen.
Die Autoren thematisieren die Bedeutung von Zahlungsstromeffekten bei Annuitätenkrediten und analysiert hier vor allem den sogenannten Front-Loading-Effekt. Danach führen höhere Nominalzinsen selbst bei vollständig antizipierten Inflationsraten und unveränderten Realzinsen zu starken finanziellen Zusatzbelastungen in den ersten Phasen der typischerweise langen Kreditlaufzeit. Derartige Liquiditätseffekte können die Zahlungsfähigkeit bzw. die Zahlungsbereitschaft der privaten Investoren empfindlich verringern. Dies gilt vor allem bei Darlehen in Form der Prozentannuität, da hier zusätzlich ein Laufzeitenverkürzungseffekt auftritt. Solche Darlehen sind in Deutschland recht populär.
Mit Blick auf die Zukunft sehen die Autoren auch eine reale Gefahr für den Bestand an Wohnungsbaukrediten, wenn es zu einer Refinanzierung des großen Bestands an billigen Wohnungsbaukrediten kommt, ein Risiko, das auch Auswirkungen auf die makroökonomische und finanzielle Stabilität hat.
We assemble a data set of more than eight million German Twitter posts related to the war in Ukraine. Based on state-of-the-art methods of text analysis, we construct a daily index of uncertainty about the war as perceived by German Twitter. The approach also allows us to separate this index into uncertainty about sanctions against Russia, energy policy and other dimensions. We then estimate a VAR model with daily financial and macroeconomic data and identify an exogenous uncertainty shock. The increase in uncertainty has strong effects on financial markets and causes a significant decline in economic activity as well as an increase in expected inflation. We find the effects of uncertainty to be particularly strong in the first months of the war.
I have assessed changes in the monetary policy stance in the euro area since its inception by applying a Bayesian time-varying parameter framework in conjunction with the Hamiltonian Monte Carlo algorithm. I find that the estimated policy response has varied considerably over time. Most of the results suggest that the response weakened after the onset of the financial crisis and while quantitative measures were still in place, although there are also indications that the weakening of the response to the expected inflation gap may have been less pronounced. I also find that the policy response has become more forceful over the course of the recent sharp rise in inflation. Furthermore, it is essential to model the stochastic volatility relating to deviations from the policy rule as it materially influences the results.
This paper presents and compares Bernoulli iterative approaches for solving linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. I find that Bernoulli methods compare favorably in solving DSGE models to the QZ, providing similar accuracy as measured by the forward error of the solution at a comparable computation burden. The method can guarantee convergence to a particular, e.g., unique stable, solution and can be combined with other iterative methods, such as the Newton method, lending themselves especially to refining solutions.
Fabo, Janˇcokov ́a, Kempf, and P ́astor (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions are replaced by regressions that downweight outliers. We examine those outliers and find no reason to downweight them. Most of them represent estimates from influential central bank papers published in respectable academic journals. For example, among the five papers finding the largest peak effect of QE on output, all five are published in high-quality journals (Journal of Monetary Economics, Journal of Money, Credit and Banking, and Applied Economics Letters), and their average number of citations is well over 200. Moreover, we show that these papers have supported policy communication by the world’s leading central banks and shaped the public perception of the effectiveness of QE. New evidence based on quantile regressions further supports the results in Fabo et al. (2021).
Optimal monetary policy studies typically rely on a single structural model and identification of model-specific rules that minimize the unconditional volatilities of inflation and real activity. In their proposed approach, the authors take a large set of structural models and look for the model-robust rules that minimize the volatilities at those frequencies that policymakers are most interested in stabilizing. Compared to the status quo approach, their results suggest that policymakers should be more restrained in their inflation responses when their aim is to stabilize inflation and output growth at specific frequencies. Additional caution is called for due to model uncertainty.
Output gap revisions can be large even after many years. Real-time reliability tests might therefore be sensitive to the choice of the final output gap vintage that the real-time estimates are compared to. This is the case for the Federal Reserve’s output gap. When accounting for revisions in response to the global financial crisis in the final output gap, the improvement in real-time reliability since the mid-1990s is much smaller than found by Edge and Rudd (Review of Economics and Statistics, 2016, 98(4), 785-791). The negative bias of real-time estimates from the 1980s has disappeared, but the size of revisions continues to be as large as the output gap itself.
The authors systematically analyse how the realtime reliability assessment is affected through varying the final output gap vintage. They find that the largest changes are caused by output gap revisions after recessions. Economists revise their models in response to such events, leading to economically important revisions not only for the most recent years, but reaching back up to two decades. This might improve the understanding of past business cycle dynamics, but decreases the reliability of real-time output gaps ex post.
Highly interconnected global supply chains make countries vulnerable to supply chain disruptions. The authors estimate the macroeconomic effects of global supply chain shocks for the euro area. Their empirical model combines business cycle variables with data from international container trade.
Using a novel identification scheme, they augment conventional sign restrictions on the impulse responses by narrative information about three episodes: the Tohoku earthquake in 2011, the Suez Canal obstruction in 2021, and the Shanghai backlog in 2022. They show that a global supply chain shock causes a drop in euro area real economic activity and a strong increase in consumer prices. Over a horizon of one year, the global supply chain shock explains about 30% of inflation dynamics. They also use regional data on supply chain pressure to isolate shocks originating in China.
Their results show that supply chain disruptions originating in China are an important driver for unexpected movements in industrial production, while disruptions originating outside China are an especially important driver for the dynamics of consumer prices.
The author proposes a Differential-Independence Mixture Ensemble (DIME) sampler for the Bayesian estimation of macroeconomic models.It allows sampling from particularly challenging, high-dimensional black-box posterior distributions which may also be computationally expensive to evaluate. DIME is a “Swiss Army knife”, combining the advantages of a broad class of gradient-free global multi-start optimizers with the properties of a Monte Carlo Markov chain (MCMC). This includes fast burn-in and convergence absent any prior numerical optimization or initial guesses, good performance for multimodal distributions, a large number of chains (the “ensemble”) running in parallel, an endogenous proposal density generated from the state of the full ensemble, which respects the bounds of the prior distribution. The author shows that the number of parallel chains scales well with the number of necessary ensemble iterations.
DIME is used to estimate the medium-scale heterogeneous agent New Keynesian (“HANK”) model with liquid and illiquid assets, thereby for the first time allowing to also include the households’ preference parameters. The results mildly point towards a less accentuated role of household heterogeneity for the empirical macroeconomic dynamics.
The authors estimate perceptions about the Fed's monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions is time-varying and cyclical: high during tightening episodes but low during easings. Forecasters update their perceptions about the policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that forecasters have imperfect information about the rule. The perceived rule impacts asset prices crucial for monetary policy transmission, driving how interest rates respond to macroeconomic news and explaining term premia in long-term interest rates.
The authors propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting. The second method transforms a quarterly state space into a monthly frequency. Their algorithm combines the advantages of these two existing approaches.They compare the new method with the existing methods using simulated data and real-world data. With simulated data, the new method outperforms all other methods, including forecasts from the standard quarterly model. With real world data, incorporating auxiliary variables as in their method substantially decreases forecasting errors for recessions, but casting the model in a monthly frequency delivers better forecasts in normal times.
The authors present and compare Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. They find that Newton-based methods compare favorably in solving DSGE models, providing higher accuracy as measured by the forward error of the solution at a comparable computation burden. The methods, however, suffer from their inability to guarantee convergence to a particular, e.g. unique stable, solution, but their iterative procedures lend themselves to refining solutions either from different methods or parameterizations.
Gegen den Landeshaushalt 2022 des Freistaats Thüringen bestehen nach Einschätzung von Helmut Siekmann erhebliche verfassungsrechtliche Bedenken. In einem Gutachten kommt Siekmann zu dem Schluss, dass sich die festgestellten globalen Minderausgaben im Vergleich zum gesamten Haushaltsvolumen nicht rechtfertigen lassen. Der verfassungsrechtlich gebotene Haushaltsausgleich sei nur dadurch erzielt worden, dass die eigentlich gebotenen Einzelkürzungen nicht vom Parlament entschieden, sondern der Exekutive überlassen worden seien. Durch Globale Minderausgaben soll der Ausgleich von Einnahmen und Ausgaben erreicht werden, ohne dafür erforderliche und politisch oft schwer durchsetzbare Kürzungen bei Einzeltiteln vornehmen zu müssen.
In Thüringen fehlen der Minderheitskoalition aus Linke, SPD und Grünen im Parlament vier Stimmen für eine eigene Mehrheit. Sie muss damit bei allen Entscheidungen eine Unterstützung der oppositionellen CDU aushandeln. Siekmann weist in seinem Gutachten darauf hin, dass die Veranschlagung von globalen Minderausgaben gleich welcher Art in keinem Fall die Exekutive ermächtigt, bestehende Verpflichtungen nicht zu erfüllen.
In the communication of the European Central Bank (ECB), the statement that „we act within our mandate“ is often referred to. Also among practitioners of the Eurosystem the term „mandate“ has become popular. In his Working Paper, Helmut Siekmann analyzes the legal foundation of the tasks and objectives of the Eurosysstem and price stability as a legal term. He finds that the primary law of the EU only very sparsely employs the term „mandate“. It is never used in the context of monetary policy and its institutions. Moreover, he comes to the conclusion that inflation targeting as a task, competence, or objective of the Eurosystem is legally highly questionable according to the common standards of interpretation.
The authors study the effects of forward looking communication in an environment of rising inflation rates on German consumers‘ inflation expectations using a randomized control trial. They show that information about rising inflation increases short- and long-term inflation expectations. This initial increase in expectations can be mitigated using forward looking information about inflation. Among these information treatments, professional forecasters‘ projections seem to reduce inflation expectations by more than policymakers‘ characterization of inflation as a temporary phenomenon.
Veronika Grimm, Lukas Nöh, and Volker Wieland assess the possible development of government interest expenditures as a share of GDP for Germany, France, Italy and Spain. Until 2021, these and other member states could anticipate a further reduction of interest expenditure in the future. This outlook has changed considerably with the recent surge in inflation and government bond rates. Nevertheless, under reasonable assumptions current yield curves still imply that interest expenditure relative to GDP can be stabilized at the current level. The authors also review the implications of a further upward shift in the yield curves of 1 or 2 percentage points. These implications suggest significant medium-term risks for highly indebted member states with interest expenditure approaching or exceeding levels last observed on the eve of the euro area debt crisis. In light of these risks, governments of euro area member states should take substantive action to achieve a sustained decline in debt-to-GDP ratios towards safer levels. They bear the responsibility for making sure that government finances can weather the higher interest rates which are required to achieve price stability in the euro area.
Central banks have faced a succession of crises over the past years as well as a number of structural factors such as a transition to a greener economy, demographic developments, digitalisation and possibly increased onshoring. These suggest that the future inflation environment will be different from the one we know. Thus uncertainty about important macroeconomic variables and, in particular, inflation dynamics will likely remain high.
The authors study the impact of dissent in the ECB‘s Governing Council on uncertainty surrounding households‘ inflation expectations. They conduct a randomized controlled trial using the Bundesbank Online Panel Households. Participants are provided with alternative information treatments concerning the vote in the Council, e.g. unanimity and dissent, and are asked to submit probabilistic inflation expectations. The results show that the vote is informative.
Households revise their subjective inflation forecast after receiving information about the vote. Dissenting votes cause a wider individual distribution of future inflation. Hence, dissent increases households‘ uncertainty about inflation. This effect is statistically significant once the authors allow for the interaction between the treatments and individual characteristics of respondents.
The results are robust with respect to alternative measures of forecast uncertainty and hold for different model specifications. The findings suggest that providing information about dissenting votes without additional information about the nature of dissent is detrimental to coordinating household expectations.
The authors focus on the stabilizing role of cash from a society-wide perspective. Starting with conceptual remarks on the importance of money for the economy in general, special attention is paid to the unique characteristics of cash. As these become apparent especially during crisis periods, a comparison of the Great Depression (1929 – 1933) and the Great Recession 2008/09 shows the devastating effects of a severe monetary contraction and how a fully elastic provision of cash can help to avoid such a situation.
The authors find interesting similarities to both crises in two separate case studies, one on the demonetization in India 2016 and the other on cash supply during various crises in Greece since 2008. The paper concludes that supply-driven cash withdrawals from circulation (either by demonetization or by capital controls) destabilize the economy if electronic payment substitutes are not instantly available.
However, as there is no perfect substitute for cash due to its unique properties, from the viewpoint of the society as a whole an efficient payment mix necessarily includes cash: It helps to stabilize the economy not only in times of crises in general, no matter which government is in place. The authors argue that it should be the undisputed task of central banks to ensure that cash remains in circulation in normal times and is provided in a fully elastic way in times of crisis.
The Russian war of aggression against Ukraine since 24 February 2022 has intensified the discussion of Europe’s reliance on energy imports from Russia. A ban on Russian imports of oil, natural gas and coal has already been imposed by the United States, while the United Kingdom plans to cease imports of oil and coal from Russia by the end of 2022. The German Federal Government is currently opposing an energy embargo against Russia. However, the Federal Ministry for Economic Affairs and Climate Action is working on a strategy to reduce energy imports from Russia. In this paper, the authors give an overview of the German and European reliance on energy imports from Russia with a focus on gas imports and discuss price effects, alternative suppliers of natural gas, and the potential for saving and replacing natural gas. They also provide an overview of estimates of the consequences on the economic outlook if the conflict intensifies.
High-frequency changes in interest rates around FOMC announcements are an important tool for identifying the effects of monetary policy on asset prices and the macroeconomy. However, some recent studies have questioned both the exogeneity and the relevance of these monetary policy surprises as instruments, especially for estimating the macroeconomic effects of monetary policy shocks. For example, monetary policy surprises are correlated with macroeconomic and financial data that is publicly available prior to the FOMC announcement. The authors address these concerns in two ways: First, they expand the set of monetary policy announcements to include speeches by the Fed Chair, which essentially doubles the number and importance of announcements in our dataset. Second, they explain the predictability of the monetary policy surprises in terms of the “Fed response to news” channel of Bauer and Swanson (2021) and account for it by orthogonalizing the surprises with respect to macroeconomic and financial data. Their subsequent reassessment of the effects of monetary policy yields two key results: First, estimates of the high-frequency effects on financial markets are largely unchanged. Second, estimates of the macroeconomic effects of monetary policy are substantially larger and more significant than what most previous empirical studies have found.
The term structure of interest rates is crucial for the transmission of monetary policy to financial markets and the macroeconomy. Disentangling the impact of monetary policy on the components of interest rates, expected short rates, and term premia is essential to understanding this channel. To accomplish this, we provide a quantitative structural model with endogenous, time-varying term premia that are consistent with empirical findings. News about future policy, in contrast to unexpected policy shocks, has quantitatively significant effects on term premia along the entire term structure. This provides a plausible explanation for partly contradictory estimates in the empirical literature.
Debt levels in the eurozone have reached new record highs. The member countries have tried to cushion the economic consequences of the corona pandemic with a massive increase in government spending. End of 2021 public debt in relation to GDP will approach 100% on average. There are various calls to abolish or soften the Maastricht rules of limiting sovereign debt. We see the risk of a new sovereign debt crisis in this decade if it is not possible to bring public debt down to an acceptable level. Our new fiscal rule would be suitable and appropriate for this purpose, because obviously the Maastricht criteria have failed. In contrast to the rigid 3% Maastricht-criterion, our rule is flexible and it addresses the main problem: excessively high public debt ratios. And it lowers the existing incentives for highly indebted governments to exert expansionary pressure on monetary policy. If obeyed strictly, our rule reinforces the snowball effect and reduces the excessively high debt ratios within a manageable period, even if nominal growth is weak. This is confirmed by simulations with different scenarios as well as with the hypothetical application of the new fiscal rule to eurozone economies from 2022 to 2026. Finally, we take up the recent proposal by ESM economists to increase the permissible debt ratio from 60 to 100% of GDP in the eurozone.
The authors present evidence of a new propagation mechanism for wealth inequality, based on differential responses, by education, to greater inequality at the start of economic life. The paper is motivated by a novel positive cross-country relationship between wealth inequality and perceptions of opportunity and fairness, which holds only for the more educated. Using unique administrative micro data and a quasi-field experiment of exogenous allocation of households, the authors find that exposure to a greater top 10% wealth share at the start of economic life in the country leads only the more educated placed in locations with above-median wealth mobility to attain higher wealth levels and position in the cohort-specific wealth distribution later on. Underlying this effect is greater participation in risky financial and real assets and in self-employment, with no evidence for a labor income, unemployment risk, or human capital investment channel. This differential response is robust to controlling for initial exposure to fixed or other time-varying local features, including income inequality, and consistent with self-fulfilling responses of the more educated to perceived opportunities, without evidence of imitation or learning from those at the top.
Conditional yield skewness is an important summary statistic of the state of the economy. It exhibits pronounced variation over the business cycle and with the stance of monetary policy, and a tight relationship with the slope of the yield curve. Most importantly, variation in yield skewness has substantial forecasting power for future bond excess returns, high-frequency interest rate changes around FOMC announcements, and consensus survey forecast errors for the ten-year Treasury yield. The COVID pandemic did not disrupt these relations: historically high skewness correctly anticipated the run-up in long-term Treasury yields starting in late 2020. The connection between skewness, survey forecast errors, excess returns, and departures of yields from normality is consistent with a theoretical framework where one of the agents has biased beliefs.