Lobbying Correlation Analysis

Statistical analysis of the relationship between lobbying expenditures and legislative outcomes

Overall Correlation: Lobbying Expenditures vs. Bill Success

Pearson correlation coefficient measuring the linear relationship between total lobbying spending and bill enactment

Correlation Coefficient (r)

-0.999

Strong

P-Value

0.010

significant (p < 0.05)

Sample Size

bills with lobbying data

Direction

Negative ↘

Higher spending → Worse outcomes

There is a strong negative correlation between lobbying expenditures and bill success (r = -0.999, significant (p < 0.05)). Bills with higher lobbying expenditures tend to have worse outcomes.

Support Lobbying Correlation

Relationship between pro-bill lobbying and enactment

Correlation (r)0.333

Significancenot significant (p >= 0.1)

Sample Size1 bills

No statistically significant relationship found between lobbying expenditures and bill outcomes (r = 0.333, not significant (p >= 0.1)).

Opposition Lobbying Correlation

Relationship between anti-bill lobbying and failure

Correlation (r)-0.999

Significancesignificant (p < 0.05)

Sample Size3 bills

There is a strong negative correlation between lobbying expenditures and bill success (r = -0.999, significant (p < 0.05)). Bills with higher lobbying expenditures tend to have worse outcomes.

Lobbying Effectiveness: Enacted vs. Failed Bills

Average lobbying expenditures for bills that passed vs. bills that failed

Total Lobbying
Support Lobbying
Opposition Lobbying

Enacted Bills (11)

Avg. Total Lobbying:$176K

Avg. Support Lobbying:$4K

Avg. Opposition Lobbying:$172K

Failed Bills (18)

Avg. Total Lobbying:$11.4M

Avg. Support Lobbying:$0

Avg. Opposition Lobbying:$11.4M

Success Rates: Bills with lobbying activity have a 75.0% enactment rate, compared to 36.4% for bills without lobbying.

Methodology Note

Pearson Correlation Coefficient (r): Measures the strength and direction of linear relationship between two variables. Values range from -1 (perfect negative correlation) to +1 (perfect positive correlation), with 0 indicating no linear relationship.

Statistical Significance (p-value): Indicates the probability that the observed correlation occurred by chance. p < 0.05 is considered statistically significant, meaning there's less than 5% chance the correlation is due to random variation.

Limitations: Correlation does not imply causation. Other factors (bill content, political climate, sponsor influence) may affect outcomes. Sample size and data quality impact reliability.