Economic forecasting

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For related topics, see Forecasting.

Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit—or at a more disaggregated level, for specific sectors of the economy or even specific firms.Economic forecasting is a measure to find out the future prosperity of a pattern of investment and is the key activity in economic analysis. Many institutions engage in economic forecasting: national governments, banks and central banks, consultants and private sector entities such as think-tanks, companies and international organizations such as the International Monetary Fund, World Bank and the OECD. A broad range of forecasts are collected and compiled by "Consensus Economics". Some forecasts are produced annually, but many are updated more frequently.

The economist typically considers risks (i.e., events or conditions that can cause the result to vary from their initial estimates). These risks help illustrate the reasoning process used in arriving at the final forecast numbers. Economists typically use commentary along with data visualization tools such as tables and charts to communicate their forecast.[1] In preparing economic forecasts a variety of information has been used in an attempt to increase the accuracy.

Everything from macroeconomic,[2] microeconomic,[3] market data from the future,[4] machine-learning (artificial neural networks),[5] and human behavioral studies[6] have all been used to achieve better forecasts. Forecasts are used for a variety of purposes. Governments and businesses use economic forecasts to help them determine their strategy, multi-year plans, and budgets for the upcoming year. Stock market analysts use forecasts to help them estimate the valuation of a company and its stock.

Economists select which variables are important to the subject material under discussion. Economists may use statistical analysis of historical data to determine the apparent relationships between particular independent variables and their relationship to the dependent variable under study. For example, to what extent did changes in housing prices affect the net worth of the population overall in the past? This relationship can then be used to forecast the future. That is, if housing prices are expected to change in a particular way, what effect would that have on the future net worth of the population? Forecasts are generally based on sample data rather than a complete population, which introduces uncertainty. The economist conducts statistical tests and develops statistical models (often using regression analysis) to determine which relationships best describe or predict the behavior of the variables under study. Historical data and assumptions about the future are applied to the model in arriving at a forecast for particular variables.[7]

Sources of forecasts[]

Global scope[]

The Economic Outlook is the OECD's twice-yearly analysis of the major economic trends and prospects for the next two years.[8] The IMF publishes the World Economic Outlook report twice annually, which provides comprehensive global coverage.[9] The IMF and World Bank also produces Regional Economic Outlook for various parts of the world.[10]

There are also private companies such as The Conference Board and Lombard Street Research that provide global economic forecasts.[11]

U.S. forecasts[]

The U.S. Congressional Budget Office (CBO) publishes a report titled "The Budget and Economic Outlook" annually, which primarily covers the following ten-year period.[12] The U.S. Federal Reserve Board of Governors members also give speeches, provide testimony, and issue reports throughout the year that cover the economic outlook.[13][14] Regional Federal Reserve Banks, such as the St Louis Federal Reserve Bank also provide forecasts.[15]

Large banks such as Wells Fargo and JP Morgan Chase provide economics reports and newsletters.[16][17]

European forecasts[]

The European Commission also publishes comprehensive macroeconomic forecasts for its member countries on a quarterly basis - Spring, Summer, Autumn and Winter.[18]

Combining Forecasts[]

Forecasts from multiple sources may be arithmetically combined and the result is often referred to as a consensus forecast. A large volume of forecast information is published by private firms, central banks and government agencies to meet the strong demand for economic forecast data. Consensus Economics compiles the macroeconomic forecasts prepared by a variety of forecasters, and publishes them every month. The Economist magazine regularly provides such a snapshot as well, for a narrower range of countries and variables.

Forecast methods[]

The process of economic forecasting is similar to data analysis and results in estimated values for key economic variables in the future. An economist applies the techniques of econometrics in their forecasting process. Typical steps may include:

  1. Scope: Key economic variables and topics for forecast commentary are determined based on the needs of the forecast audience.
  2. Literature review: Commentary from sources with summary-level perspective, such as the IMF, OECD, U.S. Federal Reserve, and CBO helps with identifying key economic trends, issues and risks. Such commentary can also help the forecaster with their own assumptions while also giving them other forecasts to compare against.
  3. Obtain data inputs: Historical data is gathered on key economic variables. This data is contained in print as well as electronic sources such as the FRED database or Eurostat, which allow users to query historical values for variables of interest.
  4. Determine historical relationships: Historical data is used to determine the relationships between one or more independent variables and the dependent variable under study, often by using regression analysis.
  5. Model: Historical data inputs and assumptions are used to develop an econometric model. Models typically apply a computation to a series of inputs to generate an economic forecast for one or more variables.
  6. Report: The outputs of the model are included in reports that typically include information graphics and commentary to help the reader understand the forecast.

Forecasters may use computational general equilibrium models or dynamic stochastic general equilibrium models. The latter are often used by central banks.

Methods of forecasting include Econometric models, Consensus forecasts, Economic base analysis, Shift-share analysis, Input-output model and the Grinold and Kroner Model. See also Land use forecasting, Reference class forecasting, Transportation planning and Calculating Demand Forecast Accuracy.

The World Bank provides a means for individuals and organizations to run their own simulations and forecasts using its iSimulate platform.[19]

Issues in forecasting[]

Forecast accuracy[]

There are many studies on the subject of forecast accuracy. Accuracy is one of the main, if not the main criteria, used to judge forecast quality. Some of the references below relate to academic studies of forecast accuracy. Forecasting performance appears to be time dependent, where some exogenous events affect forecast quality. As expert forecasts are generally better than market-based forecasts, forecast performance depends on several factors: model, political economy (terrorism), financial stability etc.

In early 2014 the OECD carried out a self-analysis of its projections.[20] "The OECD also found that it was too optimistic for countries that were most open to trade and foreign finance, that had the most tightly regulated markets and weak banking systems" according to the Financial Times.[21]

Forecasts and the Great Recession[]

The financial and economic crisis that erupted in 2007—arguably the worst since the Great Depression of the 1930s—was not foreseen by most of the forecasters, even if a few lone analysts had been predicting it for some time (for example, Nouriel Roubini and Robert Shiller). The failure to forecast the "Great Recession" has caused a lot of soul searching in the profession. The UK's Queen Elizabeth herself asked why had nobody noticed that the credit crunch was on its way, and a group of economists—experts from business, the City, its regulators, academia, and government—tried to explain in a letter.[22]

It was not just forecasting the Great Recession, but also its impact where it was clear that economists struggled. For example, in Singapore Citi, argued the country would experience "the most severe recession in Singapore’s history". The economy grew in 2009 by 3.1% and in 2010, the nation saw a 15.2% growth rate.[23][24]

List of regularly published surveys based on polling economists on their forecasts[]

Organization name Forecast name Number of individuals surveyed Number of countries covered List of countries/regions covered Frequency How far ahead the forecasts are made for Start date
Blue Chip Publications division of Aspen Publishers Blue Chip Economic Indicators[25] 50+[25] 1 United States Monthly[25] ? 1976[25]
Consensus Economics Consensus Forecasts over 700[26][27] 115[26][27] Member countries of the G-7 industrialized nations, the Eurozone region as well as various economies in Western Europe, the Middle East, Central Asia, Africa, Asia Pacific, Eastern Europe, Latin America and the Nordic countries.[26][27] Monthly[26][27] 12 months to 10 years 1989[28]
Federal Reserve Bank of Philadelphia Livingston Survey[29] ? 1 United States[29] Bi-annually (June and December every year)[29] Two bi-annual periods (6 months and 12 months from now), plus some forecasts for two years 1946[29]
European Central Bank ECB Survey of Professional Forecasters[30][31] 55 ? Euro zone Quarterly[30] Two quarters and six quarters from now, plus the current and next two years 1999[30][31]
RFE Resources for Economists ? ? Global Economic Outlook Quarterly Two quarters and six quarters from now, plus the current and next two years 1949

See also[]

Footnotes[]

  1. ^ Wells Fargo Economics-Multiple Examples of Reports Using Data Visualization-Retrieved July 15, 2015
  2. ^ French, J (1 March 2017). "Macroeconomic Forces and Arbitrage Pricing Theory". Journal of Comparative Asian Development. 16 (1): 1–20. doi:10.1080/15339114.2017.1297245.
  3. ^ French, J (2016). "Economic determinants of wine consumption in Thailand". International Journal of Economics and Business Research. 12 (4): 334. doi:10.1504/IJEBR.2016.081229.
  4. ^ French, J (11 Dec 2016). "The time traveller's CAPM". Investment Analysts Journal. 46 (2): 81–96. doi:10.1080/10293523.2016.1255469.
  5. ^ French, J (20 July 2016). "Back to the Future Betas: Empirical Asset Pricing of US and Southeast Asian Markets". International Journal of Financial Studies. 4 (3): 15. doi:10.3390/ijfs4030015.
  6. ^ French, J (December 2017). "Asset pricing with investor sentiment: On the use of investor group behavior to forecast ASEAN markets". Research in International Business and Finance. 42: 124–148. doi:10.1016/j.ribaf.2017.04.037.
  7. ^ Ramanathan, Ramu (1995). Introductory Econometrics with Applications-Third Edition. The Dryden Press. ISBN 978-0-03-094922-7.
  8. ^ "Forecasting methods and analytical tools - OECD".
  9. ^ IMF-World Economic Outlook-April 2015
  10. ^ "Regional Economic Outlook". IMF. Retrieved 2020-11-22.
  11. ^ "TS Lombard". Economics Politics Markets. Retrieved 2020-11-22.
  12. ^ Congressional Budget Office-The Budget and Economic Outlook 2015-2025-January 2015
  13. ^ Federal Reserve-Fed Chair Janet Yellen Speech-July 10, 2015
  14. ^ Federal Reserve-Monetary Policy Report-Retrieved July 2015
  15. ^ "Tracking the Recession - St. Louis Fed". research.stlouisfed.org. Retrieved 2020-11-22.
  16. ^ Wells Fargo Economics-Retrieved July 2015
  17. ^ JP Morgan Chase-Guide to the Markets Q3 2015 - Retrieved July 2015
  18. ^ "Economic forecasts". European Commission - European Commission. Retrieved 2020-11-22.
  19. ^ "ISimulate @ World Bank".
  20. ^ OECD forecasts during and after the financial crisis: a post mortem
  21. ^ Financial Times
  22. ^ British Academy-The Global Financial Crisis Why Didn't Anybody Notice?-Retrieved July 27, 2015 Archived July 7, 2015, at the Wayback Machine
  23. ^ Chen, Xiaoping; Shao, Yuchen (2017-09-11). "Trade policies for a small open economy: The case of Singapore". The World Economy. doi:10.1111/twec.12555. ISSN 0378-5920.
  24. ^ Subler, Jason (2009-01-02). "Factories slash output, jobs around world". Reuters. Retrieved 2020-09-20.
  25. ^ Jump up to: a b c d Moore, Randell E. "Blue Chip Economic Indicators". Retrieved April 13, 2014.
  26. ^ Jump up to: a b c d "Consensus Economics". Consensus Economics. Retrieved April 14, 2014.
  27. ^ Jump up to: a b c d "Consensus Economics (about page)". Consensus Economics. Retrieved April 14, 2014.
  28. ^ "Data For Institutional Investors". Consensus Economics. Retrieved April 14, 2014.
  29. ^ Jump up to: a b c d "Livingston Survey". Federal Reserve Bank of Philadelphia. Retrieved April 17, 2014.
  30. ^ Jump up to: a b c "ECB Survey of Professional Forecasters". European Central Bank. Retrieved April 13, 2014.
  31. ^ Jump up to: a b Juan Angel Garcia (September 2003). "An Introduction to the ECB's Survey of Professional Forecasters" (PDF). European Central Bank.

Further reading[]

External links[]

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