The data for Spain suggests that Okun's Law can be written as y = -0.3147x + 1.2821, where y is the change in unemployment rate and x is the GDP growth rate. What is the predicted... The data for Spain suggests that Okun's Law can be written as y = -0.3147x + 1.2821, where y is the change in unemployment rate and x is the GDP growth rate. What is the predicted change in unemployment if GDP grows by 2 per cent?

Understand the Problem
The question describes Okun's Law as it applies to Spain, giving a formula to calculate the change in unemployment rate (y) based on the GDP growth rate (x). Specifically, the formula is y = -0.3147x + 1.2821. The question asks to calculate the predicted change in unemployment (ie: solve for 'y') when the GDP grows by 2%, which means that x=2.
Answer
The predicted change in unemployment is $0.6527$ percentage points.
Answer for screen readers
The predicted change in unemployment is 0.6527 percentage points.
Steps to Solve
- Substitute the value of x into the equation
Substitute $x = 2$ into the equation $y = -0.3147x + 1.2821$. $$ y = -0.3147(2) + 1.2821 $$
- Calculate the product
Calculate $-0.3147 \times 2$ $$ y = -0.6294 + 1.2821 $$
- Add the values to get the value of y
Add the two numbers together. $$ y = 0.6527 $$
The predicted change in unemployment is 0.6527 percentage points.
More Information
Okun's Law describes the inverse relationship between unemployment and economic growth. In this specific case, it suggests that for every 1% of GDP growth, the unemployment rate decreases by approximately 0.3147%. The constant term (1.2821) could represent other factors influencing unemployment.
Tips
A common mistake is misinterpreting the question and, for example, not substituting the value correctly into the equation, or making a mistake during arithmetic calculations. Also understanding the relationship between x and y is important here.
AI-generated content may contain errors. Please verify critical information