1. 14 December 2009 Using business tendency surveys to reduce revisions Jan-Egbert Sturm

2. 14 December 20092International Seminar on Early Warning and Business Cycle Indicators Underlying papers  Jacobs, J.P.A.M. and J.-E. Sturm (2005), “Do ifo indicators help explain revisions in German industrial production?”, in: Ifo Survey Data in Business Cycle and Monetary Policy Analysis, editors J.-E. Sturm and T. Wollmershäuser, Physica Verlag, 93-114.  Jacobs, J.P.A.M. and J.-E. Sturm (2008), The information content of KOF indicators on Swiss current account data revisions, Journal of Business Cycle Measurement and Analysis, 4:2, 163-183.  Graff, M. and J.-E. Sturm (2009), “The output gap revisited: Can survey data on capacity utilisation improve output gap estimates in real time?”, mimeo.

3. 14 December 20093International Seminar on Early Warning and Business Cycle Indicators Outline  Motivation  Increase the information contained in preliminary data by predicting future revisions  Real-time data sets  Industrial production in Germany(time series)  Current account statistics in Switzerland(system / time series)  Output gap estimates of the OECD(panel data)  Business tendency surveys  Ifo indicators for Germany  KOF indicators for Switzerland  Capacity utilisation rates in the OECD countries  Modelling strategy and empirical results  Concluding remarks

4. 14 December 20094International Seminar on Early Warning and Business Cycle Indicators Evaluation Real-time data FinalPartly revisedFirst-released Vintage Final data Economic forecast Political decisions Final dataPartly revisedFirst-released Time

5. 14 December 20095International Seminar on Early Warning and Business Cycle Indicators Real-time data sets  German industrial production (source: Statistisches Bundesamt) “Indizes der Produktion und der Arbeitsproduktivität im Produzierenden Gewerbe”, Fachserie 4, Reihe 2.1  Monthly real growth rates (for entire Germany)  Vintages: 1996:3–2003:10, Coverage: 1995:12–2003:8  Swiss current account statistics (source: Swiss National Bank, Oct. 2006)  Monthly vintages with quarterly (nominal) series –Income (exports) and Expenditures (imports) categories  Vintages: 1995:8–2006:9 (& 2007:7), Coverage 1995:Q2–2006:Q2  OECD output gap data (source: OECD Main Economic Indicators)  Bi-annual vintages with annual or quarterly series (for resp. 25 or 18 countries) –Estimates based on a production function approach –Output gap = (Y – Y*)/Y* ≈ y – y*  Vintages: 1995:6–2009:6, Coverage: 1996–2008 or 1995Q4–2009Q2

6. 14 December 20096International Seminar on Early Warning and Business Cycle Indicators ‘Final’ release data  Besides analysing first revisions, we concentrate on the final/total revision  The latter is conceptually more important  Will we ever have true final data?  Industrial production –Take most recent vintage as final release –Allow for at least two years between first and final release  Current account –Take most recent vintage as final release –Distinguish between different types of revisions Benchmark / Summer / Winter / Early / Other revisions  Output gap –Revisions do not appear to die out – no final release

7. 14 December 20097International Seminar on Early Warning and Business Cycle Indicators Industrial production: Comparing the first revision with the total revision Revision (in %-Points) -3.5 -2.5 -1.5 -0.5 0.5 1.5 2.5 3.5 1995:121996:061996:121997:061997:121998:061998:121999:061999:12 2000:062000:122001:06

8. 14 December 20098International Seminar on Early Warning and Business Cycle Indicators Industrial production: Systematic bias? Not significantly different from zero No systematic bias

9. 14 December 20099International Seminar on Early Warning and Business Cycle Indicators Current account: Data set up and revision processes JFMAMJJASONDJFMAMJJASONDJFMAMJJASONDJFMAMJJAS... 2000I II 2000III 2000IV 2001I II 2001III 2001IV 2002I II 2002III 2002IV 2003I II 2003III 2003IV 2004I II 2004III 2004IV 1st revision To be revised next summer 2nd revision 2nd winter revision 2nd summer revision To be revised next winter 3rd revision 3rd winter revision3rd summer revision 2004200520062003..Jun 2007 1st summer revision 1st winter revision F F F F F F F F F FFirst release Other revisions Benchmark revision Final data

10. 14 December 200910International Seminar on Early Warning and Business Cycle Indicators Current account: Significant biases? Looking at averages MeanSign.MeanSign.MeanSign. Total revisions Early revisions Summer revisions Winter revisions Benchmark revisions Other revisions Total revisions Early revisions Summer revisions Winter revisions Benchmark revisions Other revisions Relative to first release (in perc.) Income sideExpenditures sideCurrent account Levels in millions of CHF 371.610.29 -27.870.88 656.170.06 -4.120.95 -325.460.00 75.690.39 5.2%0.12 0.2%0.92 7.9%0.02 0.1%0.83 -3.4%0.00 0.5%0.54 1'795.710.00 292.870.10 1'800.390.00 119.020.14 -723.090.00 314.030.02 3.0%0.00 0.4%0.11 3.0%0.00 0.2%0.14 -1.2%0.00 0.5%0.01 1'424.100.00 320.750.01 1'072.200.00 123.130.18 -327.410.00 238.340.02 2.7%0.00 0.6%0.01 2.1%0.00 0.2%0.18 -0.6%0.00 0.4%0.02

11. 14 December 200911International Seminar on Early Warning and Business Cycle Indicators F4 F2F3F4 F1F2F3F4 F1F2F3F4 F1F2F3 F1F2 F1F2 F1F2 F1F2 F1F2 F1F2 F1F2 F1F2 F1F2 F1F2 F1F2 F4 F3F4 F3F4 F3F4 F3F4 F3F4 F3F4 F3F4 F3F4 F3F4 F3F4 Output gaps: Data setup and revision process: Annual data Source: OECD, calculations KOF JunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDecJunDec 1970 … 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Fx Rx Reference Period 2002 Forecast number x Release number x Vintages / Release Dates 20072008200919951996199719981999200020012003200420052006 R1R2R3R4R5R6R7R8 ……………………………………………………………………………

12. 14 December 200912International Seminar on Early Warning and Business Cycle Indicators Output gaps: Revision process of annual output gaps: avg.bal.panel Source: OECD, calculations KOF -0.5 0.0 0.5 1.0 1.5 1996199719981999200020012002200320042005 rev. 1 rev. 2 rev. 3 rev. 4 rev. 5 rev. 6 rev. 7 %-points

13. 14 December 200913International Seminar on Early Warning and Business Cycle Indicators Business Tendency Survey data  Business Tendency Survey data is not revised over time  Ifo Business Tendency Survey for Germany  Monthly survey covering 7,000 firms –“We judge our current business situation for product group X to be” Good / Satisfactorily / Bad  KOF Business Tendency Surveys for Switzerland  Monthly/Quarterly surveys covering 11,000 firms –Hotel nights foreigners (compared to last year & expectations) –Wholesale trade business situation –Industry business situation & stock of intermediate inputs  Capacity utilisation rates  Sources: European Commission, OECD, national sources  “The current level of capacity utilisation”

14. 14 December 200914International Seminar on Early Warning and Business Cycle Indicators Modelling strategy  Are data revisions predictable? Are first releases “informationally efficient”?   Rx-R1 y(t) =  +  y R1 (t) +  BTS(i,t) +  (t) –  Rx-R1 y(t) represent the revisions –Hypotheses:  = 0,  = 0,  = 0  Industrial production  Estimates of industrial production are based on survey results –For firms which do not respond on time, figures from previous month were taken –This leads to downward bias of first release of absolute growth rate  Current account  The two sides of the current account are highly correlated  Output gaps  Allow for fixed country effects and random time effect

15. 14 December 200915International Seminar on Early Warning and Business Cycle Indicators Industrial production: Relationship first release and first revision Revision (in %-Points) First release IP-growth

16. 14 December 200916International Seminar on Early Warning and Business Cycle Indicators Industrial production: Relationship Ifo indicator and first revision Δ Ifo Business Situation Partielle Revision (in %-Punkte)

17. 14 December 200917International Seminar on Early Warning and Business Cycle Indicators Current account: Goodness of fit (adj. R 2 ) Whole- sale Whole- sale Expected hotel nights by foreigners Change in hotel nights by foreigners (Y-o-Y) Business situation Stock of intermediateinputs Expected hotel nightsby foreigners Change in hotel nightsby foreigners (Y-o-Y)Business situation Stock of intermediateinputs HotelsIndustry Without any KOF indicators HotelsIndustry Without any KOF indicators

18. 14 December 200918International Seminar on Early Warning and Business Cycle Indicators Output gaps: Regression results: Annual data Revision 1 Cumulative Revision 2 Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7 Revision 1 Cumulative Revision 2 Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7 gamma gamma=0 -0.18 0.00 -0.25 0.00 -0.33 0.00 -0.30 0.00 -0.34 0.00 -0.29 0.00 -0.30 0.00 -0.15 0.00 -0.21 0.00 -0.30 0.00 -0.31 0.00 -0.36 0.00 -0.31 0.00 -0.30 0.00 Hausman LR-Test 0.00 0.01 0.11 0.00 0.78 0.00 0.21 0.00 0.36 0.00 0.30 0.00 0.07 0.00 0.39 0.020.03 0.110.03 0.39 0.00 0.60 0.00 0.26 0.00 Adj.R2 0.25 0.34 0.46 0.40 0.52 0.40 0.46 0.21 0.25 0.30 0.32 0.42 0.40 0.47 gamma gamma=0 F-Test Adj.R2 -0.15 0.00 0.020.26 -0.21 0.00 0.030.35 -0.31 0.00 0.48 -0.30 0.00 0.41 -0.36 0.00 0.53 -0.31 0.00 0.44 -0.33 0.00 0.50 -0.10 0.00 0.260.25 -0.14 0.00 0.710.27 -0.24 0.00 0.120.33 -0.26 0.00 0.090.35 -0.33 0.00 0.45 -0.32 0.00 0.43 -0.33 0.00 0.50 gamma gamma=0 -0.22 0.00 -0.30 0.00 -0.43 0.00 -0.37 0.00 -0.42 0.00 -0.37 0.00 -0.39 0.00 -0.17 0.00 -0.27 0.00 -0.39 0.00 -0.40 0.00 -0.46 0.00 -0.41 0.00 -0.41 0.00 delta delta=0 0.060.01 0.08 0.01 0.14 0.00 0.10 0.01 0.13 0.00 0.12 0.00 0.13 0.00 0.030.18 0.090.01 0.14 0.00 0.13 0.00 0.15 0.00 0.15 0.00 0.16 0.00 Hausman LR-Test 0.00 0.010.00 0.02 0.00 0.010.00 0.14 0.00 0.12 0.00 0.010.00 0.010.00 Adj.R2 0.26 0.36 0.50 0.42 0.54 0.42 0.49 0.21 0.27 0.34 0.35 0.45 0.44 0.50 Significant at a 1% level 282 257 232 200 #Obs. 307 282 257 232 200 #Obs. 279 254 229 200 304 279 254 229 200

19. 14 December 200919International Seminar on Early Warning and Business Cycle Indicators Output gaps: Regression results: Annual data Revision 1 Cumulative Revision 2 Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7 Revision 1 Cumulative Revision 2 Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7 gamma gamma=0 -0.22 0.00 -0.30 0.00 -0.43 0.00 -0.37 0.00 -0.42 0.00 -0.37 0.00 -0.39 0.00 -0.17 0.00 -0.27 0.00 -0.39 0.00 -0.40 0.00 -0.46 0.00 -0.41 0.00 -0.41 0.00 delta delta=0 0.060.01 0.08 0.01 0.14 0.00 0.10 0.01 0.13 0.00 0.12 0.00 0.13 0.00 0.030.18 0.090.01 0.14 0.00 0.13 0.00 0.15 0.00 0.15 0.00 0.16 0.00 Hausman LR-Test 0.00 0.010.00 0.02 0.00 0.010.00 0.14 0.00 0.12 0.00 0.010.00 0.010.00 Adj.R2 0.26 0.36 0.50 0.42 0.54 0.42 0.49 0.21 0.27 0.34 0.35 0.45 0.44 0.50 Significant at a 1% level #Obs. 279 254 229 200 304 279 254 229 200

20. 14 December 200920International Seminar on Early Warning and Business Cycle Indicators Conclusions  German industrial production growth:  Especially the first revisions have considerable size  Carry-over effect explains large part of first revision  Ifo indicator helps explain initial revisions  Swiss current account statistics:  Since end of the 1990s, revisions have increased in absolute size  We distinguish between benchmark, summer, winter, early and other revisions –Summer revisions are the most important  KOF indicators contain information on revisions  OECD Output gaps:  Revisions are of a similar magnitude as the output gap itself  During the period 1995-2005 output gaps have overall been revised towards their mean –Hence, revisions appear to be predictable  BTS data on capacity utilisation can partly explain revisions

21. 14 December 2009 30 th CIRET Conference, New York Economic Tendency Surveys and the Services Sector Hosted by The Conference Board, New York, NY

22. 14 December 200922International Seminar on Early Warning and Business Cycle Indicators Centre for International Research on Economic Tendency Surveys (CIRET)  The overall aim of CIRET conferences is to encourage and improve communication, exchange and co-operation between academics and practitioners who conduct economic surveys, analyse survey data and develop or make use of cyclical indicators  30 th CIRET Conference in New York:  October 13 – October 16, 2010  Economic Tendency Surveys and the Services Sector –Special Topic: Economic Tendency Surveys and Financial Markets  Submission Procedure  Abstracts deadline:February 28, 2010  Papers deadline:June 30, 2010  Further information to be found on: http://www.ciret.org