Optimal Monetary Policy in a Two-sector Environmental DSGE Model
Oliver Holtemöller, Alessandro Sardone
IWH Discussion Papers,
No. 18,
2024
Abstract
In this paper, we discuss how environmental damage and emission reduction policies affect the conduct of monetary policy in a two-sector (clean and dirty) dynamic stochastic general equilibrium model. In particular, we examine the optimal response of the interest rate to changes in sectoral inflation due to standard supply shocks, conditional on a given environmental policy. We then compare the performance of a nonstandard monetary rule with sectoral inflation targets to that of a standard Taylor rule. Our main results are as follows: first, the optimal monetary policy is affected by the existence of environmental policy (carbon taxation), as this introduces a distortion in the relative price level between the clean and dirty sectors. Second, compared with a standard Taylor rule targeting aggregate inflation, a monetary policy rule with asymmetric responses to sector-specific inflation allows for reduced volatility in the inflation gap, output gap, and emissions. Third, a nonstandard monetary policy rule allows for a higher level of welfare, so the two goals of welfare maximization and emission minimization can be aligned.
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On Modeling IPO Failure Risk
Gonul Colak, Mengchuan Fu, Iftekhar Hasan
Economic Modelling,
April
2022
Abstract
This paper offers a novel framework, combining firm operational risk, IPO pricing risk, and market risk, to model IPO failure risk. By analyzing nearly a thousand variables, we observe that prior IPO failure risk models have suffered from a major missing-variable problem. Evidence reveals several key new firm-level determinants, e.g., the volatility operating performance, the size of its accounts payable, pretax income to common equity, total short-term debt, and a few macroeconomic variables such as treasury bill rate, and book-to-market of the DJIA index. These findings have major economic implications. The total value loss from not predicting the imminent failure of an IPO is significantly lower with this proposed model compared to other established models. The IPO investors could have saved around $18billion over the period between 1994 and 2016 by using this model.
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Why is Unemployment so Countercyclical?
Lawrence J. Christiano, Martin S. Eichenbaum, Mathias Trabandt
Review of Economic Dynamics,
July
2021
Abstract
We argue that wage inertia plays a pivotal role in allowing empirically plausible variants of the standard search and matching model to account for the large countercyclical response of unemployment to shocks.
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The Appropriateness of the Macroeconomic Imbalance Procedure for Central and Eastern European Countries
Geraldine Dany-Knedlik, Martina Kämpfe, Tobias Knedlik
Empirica,
No. 1,
2021
Abstract
The European Commission’s Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It was published first time in 2012 by the European Commission as a reaction to public debt crises in Europe. So far, the Macroeconomic Imbalance Procedure takes a one-size-fits-all approach with regard to the identification of thresholds. The experience of Central and Eastern European Countries during the global financial crisis and in the resulting public debt crises has been largely different from that of other European countries. This paper looks at the appropriateness of scoreboard of the Macroeconomic Imbalances Procedure of the European Commission for this group of catching-up countries. It is shown that while some of the indicators of the scoreboard are helpful to predict crises in the region, thresholds are in most cases set too narrow since it largely disregarded the specifics of catching-up economies, in particular higher and more volatile growth rates of various macroeconomic variables.
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Switching to Good Policy? The Case of Central and Eastern European Inflation Targeters
Andrej Drygalla
Macroeconomic Dynamics,
No. 8,
2020
Abstract
The paper analyzes how actual monetary policy changed following the official adoption of inflation targeting in the Czech Republic, Hungary, and Poland and how it affected the volatilities of important macroeconomic variables in the years thereafter. To disentangle the effects of the policy shift from exogenous changes in the volatilities of these variables, a Markov-switching dynamic stochastic general equilibrium model is estimated that allows for regime switches in the policy parameters and the volatilities of shocks hitting the economies. Whereas estimation results reveal periods of high and low volatility for all three economies, the presence of different policy regimes is supported by the underlying data for the Czech Republic and Poland, only. In both economies, monetary policy switched from weak and unsystematic to strong and systematic responses to inflation dynamics. Simulation results suggest that the policy shifts of both central banks successfully reduced inflation volatility in the following years. The observed reduction in output volatility, on the other hand, is attributed more to a reduction in the size of external shocks.
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Information Feedback in Temporal Networks as a Predictor of Market Crashes
Stjepan Begušić, Zvonko Kostanjčar, Dejan Kovač, Boris Podobnik, H. Eugene Stanley
Complexity,
September
2018
Abstract
In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.
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Macroeconomic Trade Effects of Vehicle Currencies: Evidence from 19th Century China
Makram El-Shagi, Lin Zhang
Abstract
We use the Chinese experience between 1867 and 1910 to illustrate how the volatility of vehicle currencies affects trade. Today’s widespread vehicle currency is the dollar. However, the macroeconomic effects of this use of the dollar have rarely been addressed. This is partly due to identification problems caused by its international importance. China had adopted a system, where silver was used almost exclusively for trade, similar to a vehicle currency. While being important for China, the global role of silver was marginal, alleviating said identification problems. We develop a bias corrected structural VAR showing that silver price fluctuations significantly affected trade.
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Much Ado About Nothing: Sovereign Ratings and Government Bond Yields in the OECD
Makram El-Shagi
IWH Discussion Papers,
No. 22,
2016
Abstract
In this paper, we propose a new method to assess the impact of sovereign ratings on sovereign bond yields. We estimate the impulse response of the interest rate, following a change in the rating. Since ratings are ordinal and moreover extremely persistent, it proves difficult to estimate those impulse response functions using a VAR modeling ratings, yields and other macroeconomic indicators. However, given the highly stochastic nature of the precise timing of ratings, we can treat most rating adjustments as shocks. We thus no longer rely on a VAR for shock identification, making the estimation of the corresponding IRFs well suited for so called local projections – that is estimating impulse response functions through a series of separate direct forecasts over different horizons. Yet, the rare occurrence of ratings makes impulse response functions estimated through that procedure highly sensitive to individual observations, resulting in implausibly volatile impulse responses. We propose an augmentation to restrict jointly estimated local projections in a way that produces economically plausible impulse response functions.
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