User:S Linn Linn/sandbox

Arthur F. Burns and Wesley C. Mitchell define business cycle as a form of fluctuation. In economic activities, a cycle of expansions happening, followed by recessions, contractions, and revivals. All of which combine to form the next cycle's expansion phase; this sequence of change is repeated but not periodic. ^[1]

Economic indicators are used to measure the business cycle: financial indicators, consumer confidence index, retail trade index, unemployment and industry/service production index. Stock and Watson claim that financial indicators’ predictive ability is not stable over different time periods because of economic shocks, random fluctuations and development in financial systems. ^[2] Ludvigson believes consumer confidence index is a coincident indicator as it relates to consumer’s current situations. ^[3] Winton & Ralph state that retail trade index is a benchmark for the current economic level because its aggregate value counts up for two-thirds of the overall GDP and reflects the real state of the economy. Cite error: A <ref> tag is missing the closing </ref> (see the help page). Banbura and Rüstler argue that industry production’s GDP information can be delayed as it measures real activity with real number, but it provides an accurate prediction of GDP. ^[4]

Series used to infer the underlying business cycle fall into three categories: lagging, coincident, and leading. They are described as main elements of an analytic system to forecast peaks and troughs in the business cycle. For almost 30 years, these economic data series are considered as "the leading index" or "the leading indicators"-were compiled and published by the U.S. Department of Commerce. ^[5]

Economists and investors alike speculate which series may lead the business cycle, providing advanced warning of changes and an advantage in information.

Commodity price shocks are considered to be a significant driving force of the US business cycle. ^[6] Hamilton (2008) said that in the post war era, a majority of recessions are connected to an increase in oil price. ^[7]

Notes

^ Arthur F. Burns and Wesley C. Mitchell. (1946). p.3. "Measuring Business Cycles."
^ Stock, J.H., & Watson, M.W. (1999). (pp. 3-14). "Business Cycle Fluctuations in US Macroeconomic Time Series", Amsterdam: Elsevier.
^ Ludvigson, S.C. (2004). (pp. 29-45). "Consumer Confidence and Consumer Spending. Journal of Economic Perspectives."
^ Banbura, A., & Rüstler, G. (2011). (pp. 333-342). "A Look Into the Factor Model Black Box: Publication Lags and the Role of Hard and Soft Data in Forecasting GDP. International Journal of Forecasting".
^ The Conference Board (2021). https://conference-board.org/data/bci/index.cfm?id=2151.
^ Gubler, M., & Hertweck, M.S. (2013). (p. 3-6). "Commodity Price Shocks and the Business Cycle: Structural Evidence for the U.S".
^ Hamilton, J. D. (2008). Oil and the macroeconomy, in S. N. Durlauf & L. E. Blume, eds, "The New Palgrave Dictionary of Economics".

[1] Arthur F. Burns and Wesley C. Mitchell. (1946). p.3. "Measuring Business Cycles."

[2] Stock, J.H., & Watson, M.W. (1999). (pp. 3-14). "Business Cycle Fluctuations in US Macroeconomic Time Series", Amsterdam: Elsevier.

[3] Ludvigson, S.C. (2004). (pp. 29-45). "Consumer Confidence and Consumer Spending. Journal of Economic Perspectives."

[4] Banbura, A., & Rüstler, G. (2011). (pp. 333-342). "A Look Into the Factor Model Black Box: Publication Lags and the Role of Hard and Soft Data in Forecasting GDP. International Journal of Forecasting".

[5] The Conference Board (2021). https://conference-board.org/data/bci/index.cfm?id=2151.

[6] Gubler, M., & Hertweck, M.S. (2013). (p. 3-6). "Commodity Price Shocks and the Business Cycle: Structural Evidence for the U.S".

[7] Hamilton, J. D. (2008). Oil and the macroeconomy, in S. N. Durlauf & L. E. Blume, eds, "The New Palgrave Dictionary of Economics".

[1]

[2]

[3]

[4]

[5]

[6]

[7]