Economic patterns are vital in assisting economies in making predictions.
Augustine Lujan
Economic patterns are vital in assisting economies in making predictions. In a pure market economy, economists use data from economic models such as inflation and employment. Econometrics and various data patterns are inherently incorporated in economic science to track economic progress or downfall. The data used is a sample, not the entire population. They conduct intense statistical tests in the regression analysis process to determine the interaction of economic variables. The Leading Economic Index (LEI) is concurrently used to assess economic patterns in future economies. The index helps businesses and investors in making investment decisions (Jalles et al., 2018). Economic conditions are connected to economic statistics to provide an overall prediction of the economy.
The Philips curve is an economic indicator depicting the inflation and unemployment state-relationship in the economy. Economists believe the curve is a perfect fit in assessing economic growth since inflation and unemployment are the primary variables in the economy. Moreover, the curve helps understand employment rates concerning inflation rates. It is essential in short-run decision-making since economic participants are fully aware of the aggregate process based on inflation rates (Coibion et al., 2018). Additionally, the model incorporates monetarists’ views since the expected inflation rates are crucial in making investment decisions.
As a business person, economic variables such as inflation and employment rates prediction are paramount in decision making. For example, inflation forecasting helps business persons significant lags involved in monetary policy transmission. The knowledge helps in maintaining price stability in both short-term and long-term decisions. According to the Philips curve, there exists an inverse correlation between inflation and unemployment. Their interaction delves into a serious relationship which helps economists assess the overall economy (Siami-Namini & Namin, 2018). Predictive economic information is important to policymakers since the data is used to forecast changes in demand and economic variables impacting the changes.
References
Jalles J. T, An, Z. & Loungani, P. (2018). How well do economists forecast recessions? International Finance, 21(2), 100-121. https://doi.org/10.1111/infi.12130 (Links to an external site.)
Coibion, O., Gorodnichenko, Y., & Kamdar, R. (2018). The formation of expectations, inflation, and the Philips curve. Journal of Economic Literature, 56(4), 1447-91. https://www.aeaweb.org/articles?id=10.1257/jel.20171300 (Links to an external site.).
Siami-Namini, S., & Namin, A. S. (2018). Forecasting economics and financial time series: ARIMA vs. LSTM. arXiv preprint arXiv:1803.06386. https://arxiv.org/abs/1803.06386
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