Working paper series / Institute for Monetary and Financial Stability
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195
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.
194
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.
193
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.
192
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.
191
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.
190
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.
189
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.
188
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.
187
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.
186
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.
185
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.
184
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.
183
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.
182
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.
181
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).
180
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.
179
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.
178
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.
177
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.
176
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.