The Case of Japan. ESRI CEPREMAP Joint Workshop November 13, Bank of Japan

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1 New Monthly Estimation Approach for Nowcasting GDP Growth: The Case of Japan ESRI CEPREMAP Joint Workshop November 13, 2014 Naoko Hara Bank of Japan * Views expressed in this paper are those of the authors, and do not necessarily reflect the official views of the Bank of Japan. 1

2 Motivation Assess the current state of the economy Most comprehensive indicator = GDP Drawbacks: Longer publication lag (approx. 6 weeks) Lower frequency (Quarterly at the highest) Nowcasting GDP ( Now + Forecasting ) g) 2

3 Traditional: Bridge Models A few selected high frequency indicators Directly estimate a relationship between GDP and indicators Curse of dimensionality GDP 3

4 Recent Mainstream: Factor Models Many high frequency indicators (often hundreds) Compile the indicators into a few factors Need a set of relevant indicators GDP factors 4

5 Hybrid: Hara and Yamane (BoJWP 2013) Two selected high frequency indicators: IIP and ITA (manufacturing and services) Comprehensive collection of GDP source data Factors extracted from GDP source data GDP factors 5

6 BM, FM, and Hara and Yamane (2013) Bridge Models y n x i t i t t i 11 Factor Models r j j j 1 y f t j t t Hara and Yamane (2013) n r i f j t i t j t t i 1 j 1 y x f 6

7 Overview IIP, ITA, and GDP source data Have concurrent information on GDP Released after the end of each quarter Model: Static Target: One quarter past GDP Bańbura, Giannone, Modugno, and Reichlin (2013) Nowcasting covers the present, the recent futureandrecent recent past 7

8 Overview (cont.) Diversity of information: covering both demand and supply sides Find a group of variables that contain similar information Boivin and Ng (2006) Properties of the indicators matter in forecasting with factors 8

9 Preview of the Results Six weeks before the first release of GDP: More accurate than nowcasts by professional forecasters Two weeks before the first release of GDP: As accurate as those by professional forecasters Grouping indicators improves the model fit 9

10 Methodology 10

11 Model Structure Quarterly IIP & ITA GDP sources GDP (actual) GDP Nowcast Monthly IIP & ITA GDP sources Monthly GDP 11

12 Two Types of Indicators GDP source data n r i f j t i t j t t i 1 j 1 y x f IIP (manufacturing) GDP ITA (services) factors Orthogonal to IIP & ITA 12

13 Information in the Source Data GDP source data may be correlated with IIP and ITA dlog x dlog IIP ITA i i i i i tm, 0 1 tm, 2 tm, tm, i x tm, i tm, : i th source data : residual Residuals capture economic fluctuations uncorrelated with IIP and ITA 13

14 Coverage of GDP Source Data 473 of source data for early releases of GDP Supply side Demand side Industrial Shipments Current Survey of Selected Service Industries Current Survey of Commerce Consumption o Family Income & Expenditure Survey Trade Balance of Payment Investment Building Starts Others Industrial Inventories 14

15 Groups of Indicators Find a group of indicators that Consumption Investment contain similar information International trade Oh Other demand sided Supply side,..., p,..., p p c,1 c,6 c p,..., p p i,1 i,6 i p,..., p p x,1 x,6 x p,..., p p o,1 o,6 o p p p s,1 s,6 s 15

16 Quarterly Nowcasting Model y t 0 dlog IIP dlog ITA 1 t 2 p p p p p t c i x o s 3 t 4 t 5 t 6 t 7 t t We choose the combination which minimizes the AIC when regressing this equation 16

17 Monthly GDP Model ˆ 1 ˆ 3 ˆ dlog IIP ˆ dlog y tm, 0 Input monthly IIP, ITA & principal components ITA 1 tm, 2 tm, ˆ p ˆ p ˆ p ˆ p ˆ p c i x o s 3 tm, 4 tm, 5 tm, 6 tm, 7 tm, Monthly GDP Quarterly Nowcast 17

18 Dataset Target Main IIP: manufacturing ITA: services GDP (First release) Supplemental l GDP source data (For extrapolation) Survey Dt Data 18

19 Real time GDP Large and Frequent Revisions to Japan s GDP Real time data for real GDP: Updated version of Hara and Ichiue (JJIE 2011) 3 (q/q, %) First Quarterly Estimates Estimates of final vintage (As of March 8, 2013)

20 Data Flow Typical release dates (data for March) End of Early Late End of Early Mid March April April April May May Survey of Production Forecasts Manufacturing PMI (Japan) Reuters Tankan (mid March) Manufacturing Trade Balance of GDP IIP PMI (Global) Statistics Payments (Q1) CGPI Current Survey of Commerce Family Income & Expenditure Survey Building Starts CPI Current Survey of Production ITA 20

21 For Extrapolation: Survey Data Released much earlier than other indicators Can have useful information for nowcasting GDP Can also have information less related to recent GDP Only for extrapolating indicators with longer publication lags Markit/JMMA Japan Manufacturing PMI [Bloomberg] JPMorgan Global Manufacturing PMI [Bloomberg] Reuters Tankan [Thomson Reuters] Survey of Production Forecasts for the current month [METI] 21

22 Make a Balanced Panel Step 1 Step 2 Surveys IIP Surveys 2013/4 2013/5 2013/6 2013/4 2013/5 2013/4 2013/5 2013/6 IIP 2013/4 2013/5 2013/6 BP 2013/4 22

23 Estimation 23

24 Setup Sample period: 2004Q4 2012Q3 2004Q4 = start of chain weighted 1st release of GDP Data: as of January 31, 2013 Real time data for GDP: Updated version of Hara and Ichiue (JJIE 2011) Never use survey data on model estimation 24

25 Quarterly Model Estimates 3 (q/q % chg.) Adj. R Principal components Hara and Yamane (2013) Without PCs With PCs, no data grouping Index of Tertiary Industry Activity (ITA) Index of Industrial Production (IIP) Constant Official first QE Fit Principal components Data grouping improve the model fit 25

26 Performance Evaluation Replicate publication lags Six and two weeks before the first GDP release Six weeks before (End of March) Surveys IIP CGPI BP Two weeks before (Endof April) Surveys IIP CGPI BP Jan Jan Jan Jan Jan Jan Jan Jan Fb Feb Fb Feb Fb Feb Fb Feb Fb Feb Fb Feb Fb Feb Fb Feb Mar Mar Mar Mar Mar Mar Mar Mar 26

27 Professional Forecasts: ESP Forecast Published by the Japan Center for Economic Research (JCER) Average of GDP forecasts from about 40 professional forecasters Publish nowcasts six and two weeks before the first GDP release Updated monthly since May

28 Forecast Errors: ESP Forecast 2.0 (q/q, % points) Two weeks before the official release Six weeks before the official release weeks before 2 weeks before the first GDP release the first GDP release RMSE Source: ESP Forecast, Japan Center for the Economic Research 28

29 Forecast Errors: Hara and Yamane (2013) 2.0 (q/q, % points) Two weeks before the official release Six weeks before the official release weeks before the first GDP release 2 weeks before the first GDP release RMSE (ESP)

30 An Application: Nowcasting Second QE Main IIP: manufacturing ITA: services Target Corporate investment GDP Survey (2nd release) Supplemental l Dt Data GDP source data 30

31 Forecast Errors: Second QE (q/q, % points) Hara and Yamane (2013) Professional forecasters week before the second GDP release Hara and Yamane (2013) 0.12 Professional Forecasters 0.19 Source: Bloomberg, Nikkei 31

32 Conclusion Hbid Hybrid of bridge bid models dland factor models dl Two selected high frequency indicators and numerous GDP source data A static model Grouping indicators improves the model dlfit Performance: equal or better than nowcasts by professionals 32