The dual-axis line chart effectively compares the Average Hourly Earnings in Manufacturing (AHEMAN) with the Consumer Price Index (CPIAUSCL) over time. Here’s what you can observe:

• Average Hourly Earnings (AHEMAN) (blue line): This represents the average hourly wages of manufacturing employees in the U.S. Over the years, you can see a steady rise in wages, which reflects overall wage growth in the manufacturing sector. The most significant increases appear in recent decades, especially following economic recessions and recovery periods.

• Consumer Price Index (CPIAUSCL) (orange line): The CPI tracks changes in the price level of a basket of consumer goods and services. You can observe a similar upward trend in the CPI, indicating inflationary pressures in the U.S. economy. Periods of high wage growth often align with higher CPI levels, suggesting that rising wages may be contributing to inflation.

This comparison suggests a correlation between wage growth in the manufacturing sector and rising prices, highlighting how wage increases can lead to inflationary pressures over time.

This scatter plot shows the relationship between Average Hourly Earnings (AHEMAN) and the Consumer Price Index (CPIAUCSL) with the regression line superimposed. The plot indicates a strong linear relationship between the two variables, which is consistent with the high R-squared value from the OLS regression.

This visual representation confirms that as average hourly earnings increase, the consumer price index also tends to increase, which supports the hypothesis that wage growth is associated with inflation.

The Pearson correlation coefficient between Average Hourly Earnings in Manufacturing (AHEMAN) and the Consumer Price Index (CPIAUSCL) is approximately 0.9987. This indicates an extremely strong positive correlation between these two variables.

Given this strong correlation, it suggests that as the Average Hourly Earnings in Manufacturing increases, the Consumer Price Index tends to increase as well, and vice versa.

Given this strong correlation, it suggests that as the Nonfarm Employment Ratio increases, the Employment-Population Ratio tends to increase as well, and vice versa.

R-squared = 0.997: This indicates that 99.7% of the variance in CPIAUCSL is explained by AHEMAN. This is an extremely high level of correlation between the two variables.

Coefficient for AHEMAN = 11.5488: For every dollar increase in average hourly earnings, CPI is predicted to increase by approximately 11.55 units. This suggests a strong positive relationship between wage growth and inflation (as measured by CPI).

P-value for AHEMAN = 0.000: The p-value for AHEMAN is extremely low, indicating that the relationship between AHEMAN and CPIAUCSL is statistically significant.

F-statistic = 3.676e+05: The model has a very high F-statistic, which reinforces the strong statistical significance of the relationship.