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Unemployment and Inflation

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Unemployment and Inflation

Following 2020, September 16, the press conference meeting led by Jerome Powell, the Federal Reserve Chair, intended to bid farewell to tight inflation controls. The idea was developed based on the argument that the policy change affirmed more labor market slack than rules or policy developers thought during the previous years. For years, the Philips curve (a theory that argues that inflation and unemployment are inversely correlated) was a guide to global central banks. However, when two decades passed with reduced inflation, coupled with unemployment shifting from low to high, central banks were compelled to revisit their policies despite coronavirus’s existence. It was at this point that the Phillips curve lost its function. In September, the Federal Reserve chair adopted a new strategy of abandoning the idea that there is a predetermined minimum degree of unemployment inflection point where inflation ignites. And rather, its focus got directed towards reducing shortfalls in employment settings by tolerating more and wider prolonged shifts of inflation from its long-term target of 2%. Through the new idea, central banks have helped find an optimal balance between inflation and unemployment.

While relating to the story above, recent research has presented crucial facts that microeconomics has greatly been affected by the idea of Philips curve theory concerning inflation and unemployment fluctuations. In this research, it was found out that a substantial negative trade-of-relation exists between unemployment and inflation. The validity of the Philips curve has been challenged. During the years 1861-1957, the Philips curve lost its reliability when the unemployment rate climbed up swiftly. Yet, inflation did not reduce as requiring as the curve forecasted it would be (Sovbetov, & Kaplan, (2019, p. ).  . The 2008 Great Recession also ignited focus on the Philips with the main emphasis on reasons of failure for an empirical relationship between unemployment and inflation. In an attempt to answer the question, “where did the Philips curve go awry?”   Herbart (2016, p. 10) notes that people have learned to foresee the future by using past experiences. In support of the argument above, Abraham Lincoln once noted that “on more than one occasion, you cannot fool all the people all the time” (Herbart, 2016, p. 10). Based on this insight, an economist should understand that a deceleration or an acceleration on the inflation rate can ultimately influence decision-makers to alter their expectations. Nevertheless, the expectations will lag behind the changes made on prices since the latter causes the former.

Based on these findings, the Federal’s decision to adopt a new approach and abandon the Philips curve’s ideas can be fruitful. Connecting the words of Abraham Lincoln and that of Herbart that people have learned to foresee the future through past experiences can guide the Federal into making better decisions. Also, with various history accounting for the failure of the Philips curve, much can be learned. As such, it would be a better move for the Federal to focus on reducing shortfalls of unemployment by tolerating more prolonged and wider shifts in inflation from its target of 2%. However, to account for a better way to understand unemployment and inflation, it is wise for the Federal to uncertain whether the selected policy will instead worsen by firing up inflation expectations or solving the problem. It’s also important to recognize those dislocated in downtowns, trying to shift from marginal to full-time employment.

 

 

 

 

References

Brown, R. (2020, September 16). The Fed’s final farewell to tight inflation control. Forbes. https://www.forbes.com/sites/randybrown/2020/09/16/the-feds-final-farewell-to-tight-inflation-control/#1d257d504fd6

Herbart, R. F. (2016). Failures of the Phillips Curve. Creative Science and Technology, 10-11.

Sovbetov, Y., & Kaplan, M. (2019). Causes of failure of the Phillips curve: Does the tranquillity of the economic environment matter? The European Journal of Applied Economics16(2), 139-154. https://doi.org/10.5937/ejae16-21569

 

 

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