Abstract
We report results of a survey among active forecasters of the German business cycle. Using data for 82 respondents from 37 different institutions, we investigate what models and theories forecasters subscribe to and find that they are pronounced conservative in the sense that they overwhelmingly rely on methods and theories that have been well-established for a long time, while more recent approaches are relatively unimportant for the practice of business cycle forecasting. DSGE models are mostly used in public institutions. In line with findings in the literature there are tendencies of “leaning towards consensus” (especially for public institutions) and “sticky adjustment of forecasts” with regard to new information. A stable relationship between preferred theories and methods and forecast accuracy cannot be established.
Acknowledgements
We thank three anonymous referees, Ullrich Heilemann, Christian Pierdzioch, Christian Breuer, Lena Dräger, seminar participants at TU Chemnitz and Johannes Gutenberg Universität Mainz, as well as participants at the 1st annual workshop of the German Science Foundation (DFG) Priority Program 1859 “Experience and Expectations: Historical Foundations of Economic Behaviour” for helpful comments. Michael Braun (GESIS Leibniz Institute for the Social Sciences Mannheim) gave highly valuable comments on an early draft of the survey. We thank the DFG for financial support (project “Macroeconomic Forecasting in Great Crisis” within the Priority Program 1859).
References
Arbeitsgruppe alternative Wirtschaftspolitik (Memorandum-Gruppe) (2016), Memorandum 2016. Retrieved on2017-3-22: http://www.alternative-wirtschaftspolitik.de/veroeffentlichungen_der_arbeitsgruppe/memorandum_2016/index.html.Suche in Google Scholar
Ashiya, M. (2006), Forecast Accuracy and Product Differentiation of Japanese Institutional Forecasters. International Journal of Forecasting 22 (2): 395–401.10.1016/j.ijforecast.2005.07.003Suche in Google Scholar
Batchelor, D., P. Dua (1990a), All Forecasters are Equal. Journal of Business and Economic Statistics 8: 143–144.10.1080/07350015.1990.10509784Suche in Google Scholar
Batchelor, R., P. Dua (1990b), Forecaster Ideology, Forecasting Technique, and the Accuracy of Economic Forecasts. International Journal of Forecasting 6 (1): 3–10.10.1016/0169-2070(90)90093-QSuche in Google Scholar
Bertrand, M., S. Mullainathan (2001), Do People Mean What They Say? Implications for Subjective Survey Data. American Economic Review 91 (2): 67–72.10.1257/aer.91.2.67Suche in Google Scholar
BITKOM - Germany’s digital association (2016), Thema: ITK-Konjunktur. Retrieved on2017-3-22: https://www.bitkom.org/Marktdaten/ITK-Konjunktur/index.jsp.Suche in Google Scholar
Blanchard, O. (2017), On the Need for (At Least) Five Classes of Macro Models. https://piie.com/blogs/realtime-economic-issues-watch/need-least-fiveclasses-macro-models.Suche in Google Scholar
Blanchard, O.J., D. Leigh (2013), Growth Forecast Errors and Fiscal Multipliers. The American Economic Review 103 (3): 117–120.10.3386/w18779Suche in Google Scholar
Bofinger, P. (2016), German Macroeconomics: The Long Shadow of Walter Eucken, VOX - CEPR’s Policy Portal. http://voxeu.org/article/german-macroeconomics-longshadow-walter-eucken.Suche in Google Scholar
Carroll, C.D. (2003), Macroeconomic Expectations of Households and Professional Forecasters. The Quarterly Journal of Economics 118 (1): 269–298.10.1162/00335530360535207Suche in Google Scholar
Coibion, O., Y. Gorodnichenko (2012), What Can Survey Forecasts Tell Us about Informational Rigidities?. Journal of Political Economy 120 (1): 116–159.10.3386/w14586Suche in Google Scholar
Coibion, O., Y. Gorodnichenko (2015), Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts. American Economic Review 105 (8): 2644–2678.10.3386/w16537Suche in Google Scholar
Colander, D. (2017), Economists Should Stop Doing It with Models (And Start Doing It with Heuristics). https://www.aeaweb.org/conference/2017/preliminary/paper/9BiBSHD4.10.1057/s41302-017-0094-1Suche in Google Scholar
Consensus ForecastTM (2016), G7 and Western Europe.Suche in Google Scholar
Del Negro, M., F. Schorfheide (2013), DSGE Model-Based Forecasts. PP. 57–140 in: G. Elliott, C. Granger, A.B. Timmermann (eds.), Handbook of Economic Forecasting. vol. 2. Elsevier.10.1016/B978-0-444-53683-9.00002-5Suche in Google Scholar
DöHrn, R. (2014), Konjunkturdiagnose und -prognose: Eine anwendungsorientierte Einführung. Springer-Verlag.10.1007/978-3-642-36497-6Suche in Google Scholar
DöPke, J. (2000), Haben Konjunkturprognosen in Deutschland einen politischen Bias?. Schmollers Jahrbuch 120 (4): 587–620.10.3790/schm.120.4.587Suche in Google Scholar
DöPke, J., U. Fritsche, K. MüLler (2018). Has Macroeconomic Forecasting Changed after the Great Recession? Panel-Based Evidence on Accuracy and Forecaster Behaviour from Germany., Working Paper Macroeconomics and Finance Series No. 3. University of Hamburg, Department Socioeconomics.10.1016/j.jmacro.2019.103135Suche in Google Scholar
DöPke, J., U. Fritsche, B. Siliverstovs (2010), Evaluating German Business Cycle Forecasts under an Asymmetric Loss Function. OECD Journal: Journal of Business Cycle Measurement and Analysis 2010 (1): 1–18.10.1787/jbcma-2010-5kmlj35rx10sSuche in Google Scholar
DöPke, J., U. Fritsche, G. Waldhof (2017), Theories, Techniques and the Formation of German Business Cycle Forecasts: Evidence from a Survey among Professional Forecasters. Working Paper No. 2. DFG Priority Program Experiences and Expectations: Historical Foundations of Economic Behaviour (SPP 1859).10.1515/jbnst-2018-0018Suche in Google Scholar
Dovern, J., U. Fritsche, P. Loungani, N. Tamirisa (2014), Information Rigidities: Comparing Average and Individual Forecasts for a Large International Panel. International Journal of Forecasting. doi:DOI:10.1016/j.ijforecast.2014.06.002.Suche in Google Scholar
Dovern, J., U. Fritsche, J. Slacalek (2012), Disagreement among Forecasters in G7 Countries. The Review of Economics and Statistics 94 (4): 1081–1096. http://ideas.repec.org/a/tpr/restat/v94y2012i4p1081-1096.html.10.1162/REST_a_00207Suche in Google Scholar
Ehrbeck, T., R. Waldmann (1996), Why are Professional Forecasters Biased? Agency versus Behavioral Explanations. The Quarterly Journal of Economics 111 (1): 21–40.10.2307/2946656Suche in Google Scholar
European Central Bank (2009), Results of a Special Questionnaire for Participants in the ECB Survey of Professional Forecasters (SPF). Monthly Bulletin. 04–1–16.Suche in Google Scholar
European Central Bank (2014), Results of the Second Special Questionnaire for Participants in the ECB Survey of Professional Forecasters. Monthly Bulletin. 01–1–28.Suche in Google Scholar
FAZ (2016), Deutschlands einflussreichste Okonomen. http://www.faz.net/aktuell/wirtschaft/wirtschaftswissen/f-a-z-oekonomenranking-2016-die-tabellen-14417392.html.Suche in Google Scholar
Fildes, R., H.O. Stekler (2002), The State of Macroeconomic Forecasting. Journal of Macroeconomics 24: 435–468.10.1016/S0164-0704(02)00055-1Suche in Google Scholar
Fondsfrauen (2015), Chefvolkswirte-Liste, http://fondsfrauen.de/fondsfrauen/.Suche in Google Scholar
Fricke, T. (2016), Prognostiker des Jahres 2016 - die Langzeitauswertung. https:// neuewirtschaftswunder.de/.Suche in Google Scholar
Friedman, W.A. (2014), Fortune Tellers: The Story of America’s First Economic Forecasters. Princeton University Press.10.1515/9781400849864Suche in Google Scholar
Fritsche, U., A. Tarassow (2017), Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014. IMK Study.Suche in Google Scholar
Heilemann, U. (2012), Die Große Dichotomieist größer geworden: Zur Konjunkturprognose heute. PP. 183–196 in: A. Wagner, U. Heilemann (eds.), Empirische Makroökonomik und Mehr: Festschrift Zum 80. Geburtstag Von Karl Heinrich Oppenländer. de Gruyter.10.1515/9783110504927-012Suche in Google Scholar
Heinsohn, G., O. Steiger (2013), Ownership Economics: On the Foundations of Interest, Money, Markets, Business Cycles and Economic Development. Routledge.10.4324/9780203077467Suche in Google Scholar
Ketzler, R., K.F. Zimmermann (2013), A Citation-Analysis of Economic Research Institutes. Scientometrics 95 (3): 1095–1112.10.1007/s11192-012-0850-2Suche in Google Scholar
Krugman, P. (2000), How Complicated Does the Model Have to Be?. Oxford Review of Economic Policy 16 (4): 33–42.10.1093/oxrep/16.4.33Suche in Google Scholar
Lamont, O.A. (2002), Macroeconomic Forecasts and Microeconomic Forecasters. Journal of Economic Behavior & Organization 48 (3): 265–280.10.3386/w5284Suche in Google Scholar
Lawrence, M., P. Goodwin, M. O’ Connor, D. Onkal (2006), Judgmental Forecasting: A Review of Progress over the Last 25 Years. International Journal of Forecasting 22 (3): 493–518.10.1016/j.ijforecast.2006.03.007Suche in Google Scholar
LimeSurvey Project Team/Carsten Schmitz (2017), LimeSurvey: An Open Source Survey Tool. LimeSurvey Project/Hamburg, Germany. http://www.limesurvey.org.Suche in Google Scholar
Ma´Ckowiak, B., M. Wiederholt (2009), Optimal Sticky Prices under Rational Inattention. The American Economic Review 99 (3): 769–803.10.1257/aer.99.3.769Suche in Google Scholar
Malmendier, U., S. Nagel (2011), Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?. The Quarterly Journal of Economics 126 (1): 373–416. doi:10.1093/qje/qjq004.Suche in Google Scholar
Malmendier, U., S. Nagel (2016), Learning from Inflation Experiences. Quarterly Journal of Economics 131 (1): 53–87.10.1093/qje/qjv037Suche in Google Scholar
Mankiw, N.G. (2006), The Macroeconomist as Scientist and Engineer. The Journal of Economic Perspectives 20 (4): 29–46.10.3386/w12349Suche in Google Scholar
Morton, S.M., D.K. Bandara, E.M. Robinson, P.E.A. Carr (2012), In the twenty-first Century, What Is an Acceptable Response Rate?. Australian and New Zealand Journal of Public Health 36 (2): 106–108.10.1111/j.1753-6405.2012.00854.xSuche in Google Scholar
Ngo, H.Q., N. Potrafke, M. Riem, C. Schinke (2018), Ideology and Dissent among Economists: The Joint Economic Forecast of German Economic Research Institutes. Eastern Economic Journal 44 (1): 135–152.10.2139/ssrn.2622038Suche in Google Scholar
Niedersächsisches Institut für Wirtschaftsforschung (NIW) (2016), NIW erwartet eine vorübergehende Abschwächung des Wachstums der Niedersächsischen Wirtschaft. Retrieved on2017-3-22: http://www.niw.de/index.php/presse-detail/items/konjunkturletter-sommer2012.html.Suche in Google Scholar
Nienhaus, L. (2009), Die Blindgänger: Warum die Okonomen auch künftige Krisen nicht¨ erkennen werden. Campus Verlag.Suche in Google Scholar
Nordhaus, W.D. (1987), Forecasting Efficiency: Concepts and Applications. The Review of Economics and Statistics 69 (4): 667–674.10.2307/1935962Suche in Google Scholar
Nulty, D.D. (2008), The Adequacy of Response Rates to Online and Paper Surveys: What Can Be Done?. Assessment and Evaluation in Higher Education 33 (3): 301–314.10.1080/02602930701293231Suche in Google Scholar
Ottaviani, M., P.N. Sørensen (2006), The Strategy of Professional Forecasting. Journal of Financial Economics 81 (2): 441–466.10.1016/j.jfineco.2005.08.002Suche in Google Scholar
Otte, M. (2011), Die Finanzkrise, die Okonomen, der ”Crashprophet” und die Wissenschaft¨ von der Okonomie. Jahrbuch für Wirtschaftsgeschichte/Economic History Yearbook¨ 52 (1): 191–217.10.1524/jbwg.2011.52.1.191Suche in Google Scholar
R Core Team (2017), R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing/Vienna, Austria. https://www.R-project.org/.Suche in Google Scholar
Sims, C.A. (1998), Stickiness. Carnegie-Rochester Conference Series on Public Policy 49: 317–356.10.1016/S0167-2231(99)00013-5Suche in Google Scholar
Sims, C.A. (2003), Implications of Rational Inattention. Journal of Monetary Economics 50 (3): 665–690.10.1016/S0304-3932(03)00029-1Suche in Google Scholar
Sinclair, T. (2015), Old and New Challenges for Forecasting: Recessions, Booms, and Big Data. Preseantation given at the 16th IWH-CIREQ Macroeconometric Workshop Halle (Saale). Germany. https://www.iwh-halle.de/ueberdas-iwh/veranstaltungen/detail/detail/16th-iwh-cireq-macroeconometricworkshop-challenges-for-forecasting-structural-breaks-revision/.Suche in Google Scholar
Smith, N. (2017), Summing up My Thoughts on Macroeconomics. http://noahpinionblog. blogspot.de/2017/06/summing-up-my-thoughts-on-macroeconomics.html.Suche in Google Scholar
Stark, T. (2013), SPF Panelists Forecasting Methods: A Note on the Aggregate Results of A November 2009 Special Survey. Federal Reserve Bank of Philadelphia.Suche in Google Scholar
Stekler, H.O. (2007), The Future of Macroeconomic Forecasting: Understanding the Forecasting Process. International Journal of Forecasting 23 (2): 237–248.10.1016/j.ijforecast.2007.01.002Suche in Google Scholar
Wang, Y., T.-H. Lee (2014), Asymmetric Loss in the Greenbook and the Survey of Professional Forecasters. International Journal of Forecasting 30 (2): 235–245.10.1016/j.ijforecast.2013.07.017Suche in Google Scholar
Wieland, V., M. Wolters (2013), Forecasting and Policy Making. PP. 239–325 in: G. Elliott, C. Granger, A.B. Timmermann (eds.), Handbook of Economic Forecasting. vol. 2. Elsevier.10.1016/B978-0-444-53683-9.00005-0Suche in Google Scholar
Wissenschaftsrat (1998), Stellungnahme zu den Wirtschaftsforschungsinstituten der Blauen Liste in den alten Ländern - Allgemeine Gesichtspunkte. https://www.ratswd.de/download/3320-98-1.pdf.Suche in Google Scholar
Woodford, M. (2002), Imperfect Common Knowledge and the Effects of Monetary Policy. in: P. Aghion, R. Frydman, J. Stiglitz, M. Woodford (eds.), Knowledge, Information, and Expectations in Modern Macroeconomics: In Honor of Edmund S. Phelps. chap. Imperfect Common Knowledge.10.3386/w8673Suche in Google Scholar
Appendix A: List of institutions invited
i. Economic research institutes, that are formally politically and economically independent:
1. German Institute for Economic Research (DIW)
2. RWI - Leibniz-Institute for Economic Research
3. Halle Institute of Economic Research (IWH)
4. Kiel Institute for the World Economy
5. Ifo Institute – Leibniz Institute for Economic Research at the University of Munich
6. Institute for Employment Research (IAB)
ii. (Mostly) privately financed forecasting institutions:
7. Kiel Economics
8. FERI
9. Handelsblatt Research Institute
Döpke, Fritsche, Waldhof: Survey of professional forecasters
10. IHS Global
11. Hamburg Institute of International Economics (HWWI) [15]
12. Prognos
iii. Institutes that are financed by interest groups:
13. Macroeconomic Policy Institute (IMK)
14. Cologne Institute for Economic Research (IW)
iv. International organizations
15. International Monetary Fund (IMF)
16. European Commission (EC)
17. OECD
v. Political institutions or institutions within the process of economic policy advice
18. German Council of Economic Experts (Staff)
19. Federal Ministry for Economic Affairs and Energy
20. German Bundesbank
vi. Private Firms
21. Commerzbank
22. Deutsche Bank Research
23. Postbank Research
24. Allianz Economic Research
25. MM Warburg Research
26. Helaba Research
27. Berenberg Bank
28. DZ Bank
29. Societe Generale Research
30. Union Investment
31. Goldman Sachs
32. ING Bank Germany
33. Landesbank Berlin
34. Sal. Oppenheim
35. Deka Bank
36. IKB
37. NORD LB
38. Bayern LB
39. HSBC Trinkaus
40. LB Baden-Würtenberg
41. UniCredit
42. Morgan Stanley
43. PIMCO
44. Bremer Landesbank
45. Degussa
46. E.on
47. Collineo
48. SEB
49. Berliner Sparkasse
50. Bank J. Safra Sarasin
vii. Associations:
51. Bundesverband Deutscher Banken
52. Chambers of Commerce and Industry (DIHK)
53. Bundesverband der Deutschen Industrie (BDI)
54. Mechanical Engineering Industry Association (VDMA)
55. Bundesverband der deutschen Volks- und Raiffeisenbanken
Appendix B: Answers to free-text questions
Elements of the forecasting process
The following statements have been made in response to the question: ”Which of the following elements do you take into account in your forecasts?”under the category ”other”? (each item corresponds to one respondent)
”Okonometrische Modelle” (Econometric models)
”Konjunkturdaten vom aktuellen Rand (Aufträge, Produktion) sowie Entwicklung an den Finanzmärkte und Preisentwicklung für Rohstoffe” (Recent economic data (order inflow, production) as well as the development at financial markets and the prices of raw materials)
”Erfahrung” (Experience)
”Faustregeln” (Rules of thumb)
”Kurzfristige Konjunkturindikatoren” (Short-run business cycle indicators)
”Okonomische Theorie” (Economic theory)
”Politökonomische Erwägungen” (Considerations based on political economy)
”Wissenschaftliche Erkenntnisse” (Scientific insights), ”Institutionelle Kenntnisse” (Institutional knowledge)
”Historische Erfahrungen” (Historical experiences)
”Persönliche Einschätzungen” (Personal assessments)
”Politische Bedürfnisse der höheren Ebenen” (Political necessities of higher levels)
”Persönliche Prognoseerfahrung” (Personal forecasting experience)
”Daten, institutionelle Fakten” (Data, institutional facts)
”Marktentwicklung” (Market developments)
”Diverse Indikatoren (Industrieproduktion, Einzelhandelsumsätze, Aufträge, Kreditvergabe, … )” (Several indicators (industrial production, retails turnover indices, loans)
”Prognoseirrtümer der Vergangenheit” (Past forecast errors)
”Geldpolitik” (Monetary policy)
”Finanzmarktpreise” (Prices on financial markets)
”Erfahrungswissen” (Experience-based knowledge)
”Analysen unterschiedlichster Institute/Okonomen/Analysten” (Analyses of several institutes/economists¨/analysts)
”Eigene Unternehmensbefragung” (Own survey among firms); – ”Amtliche Statistik” (Official statistics).
Other methods
The following additional or alternative models have been mentioned (each item corresponds to one respondent) in response to the question: ”You have chosen ”Other methods” in the previous question. Please indicate briefly the method(-s) you have in mind and how often they are used.”
”Zyklusvergleich” (Comparison of cycles) and ”Nicht-parametrische Methoden” (Non-parametric methods)
”Faustregeln” (Rules of thumb) and ”Historische Elastizitäten” (Historical elasticities)
”Judgemental adjustments, Horizontal brainstorming”
”Eigene Umfragen” (Own surveys)
”Zyklenvergleiche” (Comparison of cycles)
”Eigene Unternehmensbefragung” (own business survey) (Note: we have skipped additional information to keep the anonymity.)
”Kurzfristprognose-Modelle (Faktormodelle, Brückengleichungen). Häufig und regelmäßig (alle 2 Wochen).” (Short-term forecasting models, factor models, bridge-equations, often and on a regular basis (every 2 weeks)).
Other theories
The following statements have been made in response to the question: ”You have chosen ”other theories” in the previous question. Please indicate briefly, which theories you have in mind and how important they are.”
”Debitismus” [16]
”Klassische Politische Okonomie(,) Marxismus” (Classical political economy, Marxism)
Reasons for forecast errors
The following additional possible reasons of forecast errors have been mentioned (each item corresponds to one respondent):
”Annahme unveränderter Politik” (Assumption of an unchanged policy)
”Hohe Komplexität: Die falschen Wirkungszusammenhänge hervorgehoben” (High complexity, the wrong causal relations highlighted)
”Die Zukunft ist unbekannt.” (The future is unknown)
”Unvorhergesehen Ereignisse, außer Naturkatastrophen.” (Unforeseen events except natural disasters)
”Prognosefehler bei exogenen Variablen, die als Input im Modell verwendet werden, z.B. Welthandel, Wechselkurs, Olpreis” (Forecast errors for exogenous variables, that are used as inputs for the model (e. g. world trade, exchange rates, oil prices)
”Die Frage ist allgemein formuliert, d.h. alle denkbaren Gründe sind irgendwann irgendwo einmal relevant gewesen” (The question is formulated too general, i. e. all possible reasons have been relevant at some place for a certain time.)
”Die Zukunft ist unbekannt.” (The future is unknown)
”Ferientage und Saisoneffekte falsch” (Trading days and seasonal effects wrong)
”Uberbewertung von persönlichen Eindrücken und Stimmungen” (Too much weight for personal im- pressions and sentiments) – ”Shit happens”.
”ökonomische Schocks treten auf, die per Annahme ausgeschlossen wurden.” (Economic shocks occur that have been ruled out by assumption)
Changes due to financial crisis
The following statements have been given in response to the question about what has changed in the forecasting process due to the Financial Crisis:
”Uberarbeitung bestehender und Schätzung neuer ökonometrischer Modelle (neue Indikatoren, Model Averaging)” (Overhaul of existing and estimation of new econometric models (new indicators, model averaging))
”Wir sind uns der Ungenauigkeit bewusster, denken in größeren Banbbreiten, legen mehr Wert auf Risikoszenarien” (We are more aware of inaccuracy, think in broader bandwidths, give greater emphasize on risk scenarios)
”Systematische Prognosefehlerevaluation” (Systematic forecast error evaluation)
”Literatur zur Prognose ist vielschichtiger geworden und erfordert eingehenderes Studium.” (The literature regarding forecasts has become more complex and demands in-depth studies)
”Vielfalt der Prognosemethoden und -modelle und Prognosekombination” (Diversity of forecasting methods, models, and combination)
”Wir schauen starker auf Unsicherheitsmaße, die auf Marktpreisen basieren. Außerdem beachten wir mehr die Bilanzen der Unternehmen und privaten Haushalte, weil laufende Bilanzbereinigungen das Wachstum schwächen. Schließlich sind Blasen wichtiger geworden.” (We are looking more strongly on measures of uncertainty, that rely on market prices. Moreover, consider more strongly the balance sheets of firms and private households, since balance sheet adjustments weaken economic growth. Finally, bubbles have become more important.)
”Anpassung der eigenen Befragungsmethodik (kürzerer Befraungszeitraum, schnellere Veröffentlichung)” (Adjustment of the own survey technique (shorter survey period, faster publication).)
Demotivation
The following statements have been given in response to the question, what possibly de-motivates forecasters (each item corresponds to one respondent):
”Konjunkturprognosen sind faktisch irrelevant.” (Business cycle forecasts are - in fact - irrelevant)
”Dass wenig Zeit für anderes bleibt” (That there is not enough time for other things)
”Die falsche Wahrnehmung über die Treffsicherheit von Konjunkturprognosen. In der Offentlichkeit¨ und bei Kollegen wird zu wenig anerkannt, wie unsicher (Schocks usw.) das Eintreten von Prognosen ist. Ferner wird dann auf fehlende Kompetenz geschlossen. Das trifft nicht nur auf die Offentlichkeit,¨ sondern auch auf andere Volkswirte anderer Bereiche zu.” (The wrong perception of the forecasts. The public opinion and the colleagues do not sufficiently recognize how uncertain (shocks etc.) the realisation of forecasts is. Moreover, from this it is concluded that forecasters are not competent. This does not only hold for the general public, but also for economist from other areas).
”Nichts” (Nothing).
”Politische Einflussnahme” (Political influencing)
”Das geringe Grundverständnis anderer Wissenschaftler und der Offentlichkeit für die Prognosearbeit (z.B. inhärente Prognosefehler, Aufwand Porognosen zu erstellen, Relevanz für andere Bereiche wie wirtschaftspolitische Bereiche” (The little understanding of other scientist and the public for forecasting work. (e. g., inherent forecast errors, the effort to produce forecasts, the relevance for other areas and areas of economic policy).
”Nichts davon in relevantem Maße” (Nothing of the above to a relevant extend)
”Die Datenqualitaet” (Data quality)
”Die geringe Prognosegüte” (The lack of forecasts accuracy)
”Ungünstiges Verhältnis von Aufwand (Daten-, Modellupdate, Text schreiben etc.) und Ertrag (Aufmerksamkeit i.S.v. ”in der wirtschaftspolitischen Debatte Gehör finden” (Unfavourable relation of effort (data and model update, writing text, etc.) and rewards (attention in the economic policy debate)
”Nichts” (Nothing)
”Keine” (None)
”Fehlprognosen” (Forecast errors)
”Nichts” (Nothing)
”Limited time budget”
”Der generelle Stress im Beruf” (The general stress in the job) – ”Druck bei Fehlprognosen” (Pressure in case of forecast errors).
Other remarks
At the end of the questionnaire, we asked in a free question for general comments, which may have occurred during answering the survey
”Die Fragen zu Fiskalmultiplikator, Mindestlohn etc empfinde ich als sehr problematisch, da das Situationsbedingte/der Kontext noch viel mehr abgefragt werden müsste” (I see the question regarding the fiscal multiplier, minimum wage etc. as very problematic, since the situational context should have been queried much more precisely)
”Beim langfristigen Fiskalmultiplikator hätte ich gerne die Möglichkeit gehabt, einen negativen Wert einzugeben.” (As regards the long-run multiplier I would like to had the opportunity to enter a negative value)
”Mir wären oftmals eindeutige Antwortmöglichkeiten wie ja/nein lieber als diese graduellen Abstufungen.” (I would have preferred clear-cut yes/no-answer opportunities instead of the graduations.)
”Makroökonomische Konjunkturprognosen sind weit mehr als nur eine möglichst treffsichere Punktprognose für BIP-Wachstum oder Inflation. Jenseits der kurzen Frist (1–2 Quartale) ist die Prognosegüte nicht anhand des Prognosefehlers festzumachen (einfache Vergleichsmodelle wie AR-Prognosen sind dort nämlich kaum zu schlagen), sondern anhand der Konsistenz und Stimmigkeit des Prognosegesamtbildes und seiner verschiedenen Komponenten (”Story” hinter dem Prognose-Basisszeario - dieses stellt die aus Sicht des Prognostikers wahrscheinlichste Entwicklung bedingt auf die exogenen Annahmen und auf die Annahme des Abklingens vergangener ökonomischer Schocks und des Ausbleibens zukünftiger Schocks dar” (Macroeconomic business cycle forecasts are much more than just as precise as possible a point forecast of GDP growth or inflation. Beyond the very short-run time horizon(1–2 quarters) forecast accuracy cannot be measured with a simple forecast error (since simple competing models like AR models are much better in this regard). Rather, forecasts have to be judged by the consistency and coherence of the underlying picture and its different components (the ”story” of the base-scenario of the forecast, which gives the most likely development in the eyes of the forecaster given the assumptions for exogenous factors and the unwinding of past economic shocks and the non-existence of future shocks))
© 2019 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Orginal Articles
- The Evolution of Immigrants’ Homeownership in Germany
- Theories, Techniques and the Formation of German Business Cycle Forecasts
- Calculating Gross Hourly Wages – the (Structure of) Earnings Survey and the German Socio-Economic Panel in Comparison
- The Role of Hours Changes for the Increase in German Earnings Inequality
- Book Reviews
- Julian Dörr Nils Goldschmidt Frank Schorkopf: Share Economy: Institutionelle Grundlagen und gesellschaftspolitische Rahmenbedingungen. Die Einheit der Gesellschaftswissenschaften im 21. Jahrhundert 1
- Caspari, Volker: Kontinuität und Wandel in der Institutionenökonomie, Studien zur Entwicklung der ökonomischen Theorie XXXIII, Schriften des Vereins für Socialpolitik, Bd. 115/XXXIII
- Lucas, Rainer Reinhard Pfriem Claus Thomasberger: Auf der Suche nach dem Ökonomischen – Karl Marx zum 200. Geburtstag
- Data Observer
- The Past, Present and Future of the German Record Linkage Center (GRLC)
- The Public Release Data of the Administrative Wage and Labor Market Flow Panel
- The German Socio-Economic Panel (SOEP)
Artikel in diesem Heft
- Frontmatter
- Orginal Articles
- The Evolution of Immigrants’ Homeownership in Germany
- Theories, Techniques and the Formation of German Business Cycle Forecasts
- Calculating Gross Hourly Wages – the (Structure of) Earnings Survey and the German Socio-Economic Panel in Comparison
- The Role of Hours Changes for the Increase in German Earnings Inequality
- Book Reviews
- Julian Dörr Nils Goldschmidt Frank Schorkopf: Share Economy: Institutionelle Grundlagen und gesellschaftspolitische Rahmenbedingungen. Die Einheit der Gesellschaftswissenschaften im 21. Jahrhundert 1
- Caspari, Volker: Kontinuität und Wandel in der Institutionenökonomie, Studien zur Entwicklung der ökonomischen Theorie XXXIII, Schriften des Vereins für Socialpolitik, Bd. 115/XXXIII
- Lucas, Rainer Reinhard Pfriem Claus Thomasberger: Auf der Suche nach dem Ökonomischen – Karl Marx zum 200. Geburtstag
- Data Observer
- The Past, Present and Future of the German Record Linkage Center (GRLC)
- The Public Release Data of the Administrative Wage and Labor Market Flow Panel
- The German Socio-Economic Panel (SOEP)