monetary policy uncertainty

Therefore, in the long run, a country’s uncertainty is mainly influenced by its own uncertainty. (2019) used vine copulas to look at co-dependencies in Latin-American countries. In the presence The VIX, the stock market option-based implied volatility, strongly co-moves with measures of the monetary policy stance. We construct new measures of uncertainty about Federal Reserve policy actions and their consequences - monetary policy uncertainty (MPU) indexes. Q Rev Econ Financ 70:194–202, Tran TD (2019) Measuring the macroeconomic impact of uncertainty. Econ Lett 143:24–27, Istrefi K, Mouabbi S (2018) Subjective interest rate uncertainty and the macroeconomy: a cross-country analysis. We employ the IRU for all 9 countries (US, Germany, France, Italy, Spain, UK, Japan, Canada, and Sweden, denoted in this study, by U, G, F, I, S, UK, J, C, and Sw, respectively) and we analyze all of them. J Macroecon 57:317–337, Gupta R, Pierdzioch C, Risse M (2016) On international uncertainty links: BART-based empirical evidence for Canada. For example, the aggregate measure on the given frequency band d = (a, b) can be specified as. The data favors a model with two unspanned volatility factors that capture uncertainty about monetary policy and the term premium. The medium-term total spillover index is \(63\%\), which is higher than the short-term total spillover index, and close to that of DY. Here, the own spillover index for the US is much higher than in the previous two periods, where \(34.33\%\) of uncertainty spillovers received is from its own innovations. (2019) can only identify one-directional flows. The innovations to the US contribute \(14.06\%\) (compared to \(60.71\%\) in DY) of error variance when it comes to forecasting its own uncertainty. However, the own spillover index for the US is only \(12.32\%\). Discussion topic: monetary policy uncertainty. The effects of monetary policy on uncertainty are similar but somewhat weaker. Therefore, any changes in monetary policy in the US create movements in the dollar’s strength, which will result in other countries applying monetary policy to maintain the exchange rate. This points to a delayed reaction as the shock takes time to filter through the transmission mechanisms. For the time domain, we use the methodology created by Diebold and Yilmaz (2009, 2012, 2015) and for the frequency domain, we use Baruník and Křehlík (2018), which builds on the former methodology. The crisis period can be seen at an approximate index of 20 (corresponding to Jan 2009) for the 3-month bond yields and 68 for the 10-year bond yields. Entry i,j (\(i\ne j\)) in Tables 3, 4, 5, 6, 7, 8, 9 and 10 represents the estimated contribution to the forecast error variance of country j coming from shocks in country i. This analysis shows important conclusions. It is used to test for connectedness in financial markets (Diebold and Yilmaz 2009, 2012, 2015; Tiwari et al. All Rights Reserved. (2017). For example, in the DY results of the 3m3m dataset, the directional spillover index from the US to other countries (\(6.97\%\)) is higher than the spillover index from other countries to the US (\(4.37\%\)), indicating that the US acts as a net transmitter of monetary policy uncertainty. 21162, Rey H (2016) International channels of transmission of monetary policy and the Mundellian trilemma. $$\begin{aligned} Y_t= \sum _{i=1}^p \Psi _i Y_{t-i}+\epsilon _t \end{aligned}$$, $$\begin{aligned} Y_t=\sum _{i=0}^{\infty }A_i\varepsilon _{t-i} \end{aligned}$$, \(A_i=\Psi _1A_{i-1}+\Psi _2A_{i-2}+...\Psi _pA_{i-p}\), $$\begin{aligned} \vartheta _{ij}\left( H\right) =\frac{\sigma _{jj}^{-1}\sum _{h=0}^{H-1} \left( e_i^\prime A_h {\Omega }e_j\right) ^2}{\sum _{h=0}^{H-1} \left( \ e_i^\prime A_h {\Omega }{{A^\prime }_he}_i\right) } \end{aligned}$$, $$\begin{aligned} {{\widetilde{\vartheta }}}_{ij} \left( H\right) =\frac{\vartheta _{ij} \left( H\right) }{\sum _{j=1}^{N}{\vartheta _{ij} \left( H\right) }} \end{aligned}$$, \(\sum _{j=1}^{N}{{{\widetilde{\vartheta }}}_{ij} (H)}=1\), \(\sum _{i,j=1}^{N}{{\widetilde{\vartheta }}_{ij} (H)}=N\), \(i, j=1,2,\ldots , N,\ {\text{and}}\ i\ne j\), $$\begin{aligned} C(H) = \frac{\sum ^N_{\begin{array}{c} i,j = 1 \\ i\ne j \end{array}}{{\widetilde{\vartheta }}_{ij}(H)}}{\sum ^N_{i,j = 1}{{\widetilde{\vartheta }}_{ij}(H)}} \times 100 = \frac{\sum ^N_{\begin{array}{c} i,j = 1 \\ i\ne j \end{array}}{{\widetilde{\vartheta }}_{ij}(H)}}{N}\times 100 \end{aligned}$$, $$\begin{aligned} DS_{i\leftarrow j}(H) = \frac{\sum ^N_{\begin{array}{c} j = 1 \\ i\ne j \end{array}}{{\widetilde{\vartheta }}_{ij}(H)}}{N} \times 100 \end{aligned}$$, $$\begin{aligned} DS_{i\rightarrow j}(H) = \frac{\sum ^N_{\begin{array}{c} j = 1 \\ i\ne j \end{array}}{{\widetilde{\vartheta }}_{ji}(H)}}{N} \times 100. Our results are consistent with the literature, despite using a different measure for uncertainty. where \(A_i=\Psi _1A_{i-1}+\Psi _2A_{i-2}+...\Psi _pA_{i-p}\). Cynthia Wu gratefully acknowledges financial support from the IBM Faculty Research Fund at the University of Chicago Booth School of Business. 23411, Baker SR, Bloom N, Davis SJ (2016) Measuring economic policy uncertainty. Summary This thesis consists of three chapters that study the effects of monetary policy uncertainty and deviations from rule-based policy. 2017; Caggiano et al. This points to a delayed reaction as the innovations take time to filter through the transmission mechanisms. A particular difficulty has been the need to operationalise the concept in order to yield definitive policy recommendations. J Policy Model 39(6):1052–1064, Balcilar M, Gupta R, Jooste C (2017b) South Africa’s economic response to monetary policy uncertainty. Uncertainty contributes negatively to economic activity. The directional spillovers received by variable i from all other variables j are off-diagonal row sums (i.e., contributions from others) and are calculated as follows: and the spillovers transmitted by variable i to all other variables j are off-diagonal column sums (i.e., contributions to others) and are given by, Based on the connectedness measures of Diebold and Yilmaz (2009, 2012, 2015), Baruník and Křehlík (2018) consider the frequency dynamics (e.g., the short, medium, and long terms) in the measurement of connectedness and propose a new approach to assess the connectedness of variables in the frequency domain. Part of Directorate-General for Internal Policies . We calculate the net spillovers from Tables 3, 4, 5, 6, 7, 8, 9 and 10, which provide a decomposition of the total spillovers into those coming from (or going to) other countries. (2019). We develop a new method to measure economic policy uncertainty and test its dynamic relationship with output, investment, and employment. (2020) found financial uncertainty transmits the shocks that drive economic and real estate uncertainty. 21722, Nsafoah D, Serletis A (2019) International monetary policy spillovers. It is clearly shown that there are bi-directional monetary policy uncertainty spillovers between countries. The chart below plots the three newspaper-based MPU indices for the United States. The suspense around FOMC announcements. Monetary Policy Uncertainty and Economic Fluctuations, The 2020 Martin Feldstein Lecture: Journey Across a Century of Women, Summer Institute 2020 Methods Lectures: Differential Privacy for Economists, The Bulletin on Retirement and Disability, Productivity, Innovation, and Entrepreneurship, Conference on Econometrics and Mathematical Economics, Conference on Research in Income and Wealth, Improving Health Outcomes for an Aging Population, Measuring the Clinical and Economic Outcomes Associated with Delivery Systems, Retirement and Disability Research Center, The Roybal Center for Behavior Change in Health, Training Program in Aging and Health Economics, Transportation Economics in the 21st Century. We investigate the relationship between uncertainty about monetary policy and its transmission mechanism, and economic fluctuations. which captures the relative contributions to the total forecast error variance from spillovers of volatility shocks across variables. Springer Nature. where the spectral weight is \(\Gamma \left( d\right) = \frac{\sum _{i,j=1}^{k}{({{\widetilde{\vartheta }}}_d)}_{i,j}}{\Sigma _{i,j}{(\vartheta )}_{i,j}} =\frac{\sum _{i,j=1}^{k}{({\widetilde{\vartheta }}_d)}_{i,j}}{k}\), and \(C^d\) is the total connectedness measure on the connectedness tables \(({\widetilde{\vartheta }}_d)\) corresponding to the frequency band \(d=(a,b)\). A monetary policy framework for the European Central Bank to deal with uncertainty Monetary Dialogue November 2018 Policy Department for Economic, Scientific and Quality of Life Policies . We evaluate the information content of our index, and show that positive shocks to MPU raise credit spreads and reduce output. We find that, since 2008, economic policy uncertainty in the United States has been at a level approximately two times its long run average. The frequency analysis allows us to look at what happens to the spillovers between countries as time progresses using the full sample before we look at rolling window samples to graph the relationships. We consider bi-directional spillovers and follow the literature in using Diebold and Yilmaz (2009, 2012, 2015). Table 2 shows the net movements for all the countries, where a positive value represents a net transmission and a negative value indicates a net reception. Gupta, R., Lau, C.K.M., Nel, J.A. (2016) used the Bayesian Additive Regression Trees (BART) algorithm to look at international uncertainty spillovers on Canada, while Gupta et al. We found that there are MPU spillovers between the countries in our sample. The analysis does not fully account for time-varying aspects of uncertainty spillovers, future studies can use methods that do, like TVP-VAR instead of a normal VAR in the analysis. These spillovers vary with time, but the US, Germany, France, and Spain are consistent net transmitters over all the datasets. Baruník and Křehlík (2018) employ the spectral representation of GFEVD to define connectedness measures on different frequency bands of interest. As uncertainty spillovers vary with time, their response cannot be the same every time. We construct a new measure of uncertainty about Federal Reserve policy actions and their consequences, a monetary policy uncertainty (MPU) index. Hence, uncertainty measures reflect not only uncertainty about future monetary policy, but also uncertainty about future bank funding conditions and financial market stress. NBER Working Paper Series, No. The US, Germany, France, and Spain are the most consistent transmitters of monetary policy uncertainty, while Sweden and Japan are the most consistent receivers of uncertainty spillovers. 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. J Financ Econ 16(2):271–296, Biljanovska N, Grigoli F, Hengge M (2017) Fear thy neighbor: spillovers from economic policy uncertainty. Correspondence to This shows how monetary policy uncertainty affects other macroeconomic variables and can affect other economies not only through direct spillovers, but also through indirect channels.

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