Figure 1: BRW Shock Series Jan 1994 to Dec 2017
Note: The BRW shock series is estimated from Equations (3) and (4). The navy vertical lines denote announcements of QE1, QE2, and QE3; the orange vertical lines denote the Operation Twist period; and the blue
line denotes Oct. 2015, the FOMC meeting prior to liftoff.
We display our monetary policy shock series in Figure 1. There are sizable movements before, during, and after the ZLB period.
Figure 2: GDP Growth Forecasts, Fed Minus Blue Chip
Note: Prior to December 2013, this is the average of the first four quarters ahead Greenbook forecasts less the corresponding Blue Chip forecasts. After January 2014, we use forecasts from the FOMC summary
of economic projections (SEP) because the Greenbook data is not yet publicly available. The Fed SEP are available four times per year-—in March, June, September, and December. For the other four FOMC meetings, we use the SEP from the previous FOMC meeting. We use the current year SEP forecast for
real GDP growth rate if the FOMC meeting happens in the first quarter of the year. Otherwise, we use the next year SEP forecast for real GDP Growth.
In Figure 2, we depict the difference between Fed and Blue Chip forecasts of real GDP growth, a standard proxy for central bank private information used in the literature.
Figure 3: S&P 500, the BRW Shock, and the JK Shock
Note: The S&P 500 returns are computed over a 30-minute window around FOMC meeting announcements. The blue dots represent the BRW shocks, and the orange triangles are the surprises of the 3-month
federal funds futures that are used by Jarocinski and Karadi (2018).
We depict in the scatterplot of Figure 3 daily returns on the S\&P 500 on FOMC announcement days against the BRW shock as well as the JK surprises -- FOMC announcement day high-frequency changes in the third Fed Funds futures contract.
Figure 4: Baseline SVAR Impulse Responses: BRW Shocks
Note: Structural VAR with monthly data, 5 endogenous variables and 12 lags. Variables are ordered as follows: cumulative BRW shock series, log industrial production, log consumer price index (CPI), log
commodity prices, and excess bond premium. Graphs show impulse responses estimated over different sample periods to a 100 basis point increase in the cumulative BRW shock series. Deep and shallow gray shaded areas are 68% and 90% confidence intervals produced by bootstrapping 1000 times,
respectively.
Figure 4 presents the impulse responses to a contractionary monetary shock using the full sample (1994-2017).
Figure 5: SVARs with Alternative Shock Series: BRW, NS, and Swanson
Note: BRW, NS and Swanson refer to cumulative BRW shock series, Nakamura and Steinsson (2018) shock series, and Swanson (2017) shock series, respectively. For these cases, variables are
ordered: the cumulative shock series, log industrial production, log consumer price index (CPI), log commodity prices, and excess bond premium. Graphs show impulse response to a 100 basis point increase in the monetary policy indicator series. Deep and shallow gray shaded areas are 68% and 90%
confidence intervals produced by bootstrapping 1000 times, respectively.
Figure 5 presents the impulse response results for the alternative shocks.
Figure 6: SVAR on Non-information Days (red) and Information Days (blue)
Note: Full sample-period estimation. FF3 is accumulated 3 month federal funds futures rate around the 30-minute FOMC announcement window according to the information day definition in
Jarocinski and Karadi (2018). The BRW shock is accumulated in the same way.
In Figure 6A, we replicate the results of Jarocinski and Karadi (2018) using their monetary policy surprise FF3. In Figure 6B we re-estimate using our new shock and find quite different results.
Figure A.1: BRW Shock Series IRFs using Jorda (2005) Local Projections Method
Appendix Figure A.1 presents the impulse responses to a contractionary monetary policy shock using the full sample (1994-2017).
Figure A.2: SVARs using shock series purged of the information effect
Impulse responses using the shock series of NS and Swanson are reported in Appendix Figure A2a-b, respectively. In the left panels, we depict point estimates and confidence bands from the VARs with the orthogonalized series. In the far right panels are IRFs using the original shock series. The middle column presents the comparison, omitting confidence bands for ease of viewing. For both NS and Swanson purged shocks, the positive responses of output to a contractionary policy shock are diminished compared to IRFs from the raw shocks. Indeed, the responses of shocks to the purged Swanson measure have conventional signs.
Figure B.1: BRW Shock Series for the Euro Area
Shock series estimated from Equations (3) and (4) using euro area data. The navy and gray bars are series normalized on 2-year and 5-year OIS rates, respectively.
Appendix Figure B.1 plots the two Euro area shock series together.
Figure B.2: Information Effect Counts
The information effect is defined as the co-movements of GDP forecasters and monetary policy surprises in the same direction. For each event, compute the percentage of forecasters that have information
effect.
In Figure B.2 we plot for each policy meeting date the number of forecasters whose outlook changed in the same direction as the policy surprise.
Figure C.1: BRW Shock Series and the Three Alternative Shock Series
The solid blue line represents the BRW shock series estimated from Equations (3) and (4). N&S Shock, the black dotted line, refers to the policy
factor shocks obtained from Nakamura and Steinsson (2018). Kuttner Shock, the solid black line, refers to the 30-minute fed funds rate changes around FOMC announcement obtained from Nakamura and Steinsson (2018). R&R Shock, which is the
blue dashed line, refers to the estimated shock series in Romer and Romer (2004).
Figure C.2: BRW Shock Series & Swanson's Shock Series
All navy bars are our BRW shock series estimated from Equations (3) and (4). Gray bars are benchmark shock series: SS_FFR, SS_FG, SS_LSAP, and SS_Sum, the shocks to
the federal funds rate, forward guidance, large asset purchases, and the sum of the three shocks, all from Swanson (2018).
Figure C.3: BRW and NS Shock Series
All navy bars are in the graphs are our BRW shock series estimated from Equation (3) and (4). N&S Shock refers to the policy factor shocks obtained from Nakamura and Steinsson
(2018), which are extended to 2017m12.
Figure C.4: Rolling Sample 1969m1-2017m1
rolling sample from 1969m1 to 2017m12, each of which has 15 years. 1 beta refers to the estimated coefficient from using the 1-year Treasury Rate as monetary policy indicator.
2 beta refers to the estimated coefficient from using the 2-year Treasury Rate as monetary policy indicator. 5 beta refers to the estimated coefficient from using the 5-year Treasury Rate as monetary policy indicator. 10
beta refers to the estimated coefficient from using the 10-year Treasury Rate as monetary policy indicator.
Figure C.5: Robustness Check: Influence of the Term Premium
Graphs show impulse responses to a 100 basis point increase in the cumulative BRW shock series. Deep and shallow gray shaded areas are 68% and 90% confidence intervals produced by
bootstrapping 1000 times, respectively.
Figure C.6: SVAR Impulse Responses with alternative IV
Graphs show impulse responses to a 100 basis point increase in the cumulative shock series. Deep and shallow gray shaded areas are 68% and 90% confidence intervals produced by bootstrapping 100
times, respectively.
Figure C.7: SVAR Impulse Responses with Simple Fama-Macbeth Shock
Alternative BRW shock series is aligned from the Fama-Macbeth procedure without IDH. The IRFs are estimated as above.
Figure C.8: SVAR Impulse Responses with PCA Shock
The PCA shock is constructed from applying the Nakamura-Steinsson estimation procedure to our data: extracting the first principal component of all BRW outcome variables (daily changes of 1 to 30-year
zero coupon rate around FOMC announcement days). The IRFs are estimated using the same approach as above.
Figure C.9: SVAR Impulse Responses with Tight-window(NS data) Shock
The tight-window(NS data) shock is constructed from using the Nakamura-Steinsson (2018) data with our econometric procedure. The underlying data include the 30-minute changes of the
current month Fed funds futures rate, the Fed funds futures rate immediately following the next FOMC meeting, and two, three, four quarter ahead euro dollar futures around the current FOMC announcement. The IRFs are estimated using the same approach as above.
Figure C.10: SVAR Impulse Responses with Tight-window(Full data) Shock
The tight-window shock is constructed using our econometric procedure with the Nakamura-Steinsson (2018) data plus some long term interest rate data.IRFs are estimated using the
same approach as above.