Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Journal of Economic Methodology 12 (4):517-542 (2005)
This paper examines some economic forecasts made in late 1930 that were intended to predict economic activity in the United States in order to shed light on several methodological issues. We document that these forecasts were extremely optimistic, predicting that the recession in the US would soon end, and that 1931 would show a recovery. These forecasts displayed egregious errors, because 1931 witnessed the largest negative growth rate for the US economy in any year in the twentieth century. A specific question is what led forecasters to make such serious and substantial empirical errors. A second more general issue involves the methodology of forecasting. The 1930 forecasts were sometimes based on explicit analogies with previous serious business cycles. Modern forecasting approaches are based on techniques that may not be recognized as analogies. Using the 1930 forecasts, we examine the implicit?analogy content of forecasts, and what might render such implicit analogies valid or invalid. This 1930 forecast example also resonates beyond the confines of economic methodology because forecasts about the Great Depression are of continuing interest to the profession at large, and we produce a forecast series not previously available.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Nigel Harvey (2007). Use of Heuristics: Insights From Forecasting Research. Thinking and Reasoning 13 (1):5 – 24.
Peter Ayton, Alice Pott & Najat Elwakili (2007). Affective Forecasting: Why Can't People Predict Their Emotions? Thinking and Reasoning 13 (1):62 – 80.
Cheryl K. Stenmark, Alison L. Antes, Xiaoqian Wang, Jared J. Caughron, Chase E. Thiel & Michael D. Mumford (2010). Strategies in Forecasting Outcomes in Ethical Decision-Making: Identifying and Analyzing the Causes of the Problem. Ethics and Behavior 20 (2):110 – 127.
Michael D. Mumford, Chase E. Thiel, Jared J. Caughron, Xiaoqian Wang, Alison L. Antes & Cheryl K. Stenmark (2010). Strategies in Forecasting Outcomes in Ethical Decision-Making: Identifying and Analyzing the Causes of the Problem. Ethics and Behavior 20 (2):110-127.
Dana Cook Grossman & Heinz Valtin (eds.) (1999). Great Issues for Medicine in the Twenty-First Century: Ethical and Social Issues Arising Out of Advances in the Biomedical Sciences. New York Academy of Sciences.
Lauren N. Harkrider, Chase E. Thiel, Zhanna Bagdasarov, Michael D. Mumford, James F. Johnson, Shane Connelly & Lynn D. Devenport (2012). Improving Case-Based Ethics Training with Codes of Conduct and Forecasting Content. Ethics and Behavior 22 (4):258 - 280.
Nigel Harvey Teresa Ewart Robert West (1997). Effects of Data Noise on Statistical Judgement. Thinking and Reasoning 3 (2):111 – 132.
Arvid Strand & Petter Naess (2012). What Kinds of Traffic Forecasts Are Possible? Journal of Critical Realism 11 (3):277-295.
Barbara L. Neuby (ed.) (1998). Relevancy of the Social Sciences in the Next Millennium. The State University of West Georgia.
Guanchun Wang, Sanjeev Kulkarni & Daniel N. Osherson, Improving Aggregated Forecasts of Probability.
Added to index2012-02-20
Total downloads2 ( #373,409 of 1,144,057 )
Recent downloads (6 months)1 ( #140,193 of 1,144,057 )
How can I increase my downloads?