GDP to Productivity outlook comparison between provinces

Thesis question:

What is the correlation between the increase of pages in federal regulation and the change in real GDP per capita in Canada  from 2019 to 2023 and is the relationship stronger than the relationship of interest rates and productivity. 

Hypothesis:

I hypothesise that as regulations increase in volume the GDP per capita will decrease and will have a negative correlation, and a larger negative correlation than CORRA (canadian overnight repo rate) interest rates correlation on gdp

Subquestions:

1. Will increases in provincial regulation correlate with decreases in labour productivity (measured as real provincial GDP per capita per hour worked), suggesting that higher regulatory burdens negatively impact both business performance and worker productivity?
2. Has real canadian gdp declined with regulation pages increasing
3. Will interest rates have a stronger correlation to the impact of GDP per capita

Defining population:  The population I am looking into is the population of Canada, populations of the provinces of ALB, SK , NL, BC, ONT ,QC, MB, NB, NS, PEI and the gdp of each province, the provincial average time of working and the federal gdp. I will also be taking the data for the Canadian overnight repo rate average. This data sample will span from 2020- 2024.

  Now that the number of regulations is standardized per 1000 people it shows a weak negative correlation of higher productivity being associated with lower regulation. Originally PEI had the fewest total regulations with low productivity. When considering the regulation per 1000 people of those in pei it has the highest regulatory burden per capita and lowest productivity. ⅔ of the most regulated have low productivity, out of the top 3 least regulated provinces, ontario alberta and BC all three have high productivity. 

Comparing the correlation coefficients:

Analyzing the number of regulations to the productivity of provinces alone showed almost no correlation with a weak positive bias (0.121 from the excel but I calculated 0.145)

Analyzing the number of regulations per 1000 people to the provinces productivity shows a moderate negative correlation( -0.496). This can prove that regulations per 1000 people to provinces productivity is more strongly correlated than the latter and that high regulatory burden can hinder a province’s economic productivity. 

What is the average productivity per province and what is considered above average. 

To find the answer for this I calculated the central tendency and spread and standard deviation.

Knowing that 68% of the provinces should be within one standard deviation (mean+or- standard deviation. That means the range to fall into one standard deviation is 50.09$/hr to 71.27$/hr

Now lets compare and see which provinces are below and above the line 

The provinces above: ALB, SK

Within: NL,BC,ONT QC, MB,NB

Provinces below: NS,PEI

Has real canadian gdp declined with Amount of national regulations increasingFederal reg to gdp

Table:

Graph: showing a strong negative correlation of productivity as regulations increase and a bar graph showing how much regulations have been increasing over 4 years since 2020

Calculation: line of best fit by 2030 we will have this many regulations and this will be our gdp

Conclusion: As regulations have shown to be increasing dramatically since 2020 to 2024 we have seen a strong negative correlation with national productivity. This can prove that an increase in regulation might have impacted productivity as my hypothesis proves. This can be true as increased regulation requires businesses to increase working hours on non gdp increasing activities causing a reduction in productivity ( dollars earned / hour of work federally) as a result.

Will interest rates have a stronger correlation to the impact of GDP per capitaInterest rate data

Table

Graph:

Conclusion: this graph looking at the correlation of average interest rates with productivity nationally shows that as interest rates increase the productivity of the country decreases as well. 

Scatter plot to find correlation:

Correlation coefficient for interest rate impact on federal productivity= 0.827

While the correlation coefficient for regulation increasing on federal productivity is 0.9984. 

With this data we can assume that the increase in regulation is more impactful to the productivity of our economy.

Comparing interest rates is important because that is the main tool to encourage and deter consumer spending and business investment into the economy. Lower interest rates show more productivity but I believe the manipulation of rates may work in tandem with a reduction of regulation during economic down turns to stimulate the economy through more encouragement of business investment especially if the correlation is seem to be larger than traditional attempts with interest rate manipulations. 

They both achieve the same goal of when inflation is high and governments want to regulate consumer spending and business investment. With regulation increases businesses are less likely to invest and expand due to an decrease of income per working hour decreasing productivity and slowing the economy and GDP output. This is seen by the dropping productivity correlations. When Interest rates increase, businesses are less likely to take out debt to further invest into the economy, slowing the economy shown by the dropping productivity. When inflation is low and the government wants to encourage business investment into the economy, lowering business regulations and interest rates are both shown to do that effectively as seen by increased productivity in both cases. This study showed that regulation nationally may have a stronger correlation and can be used as a government tool to stimulate or dampen productivity.

Conclusion: 

 I used three different questions to answer whether or not an excess of regulation was harming the GDP of Canada and whether or not controlling regulation can impact the economy the same way that interest rates do. My graphs showed the negative correlations between the amount of regulation and the productivity of different provinces. 

Biases that were presented were a lack of yearly data to make my findings consistent and more reputable. There are also so many different factors that could impact a gdp that more specifically correlated field studies on industries that are directly impacted by regulation would be stronger for correlation factors.

For the future I think I need to do a controlled focus of a whole province like New Brunswick or many small towns where we remove the concept of debt and interest and remove it completely with increases and decreases of bureaucracy. For this to work I would need to quantify how much increasing and decreasing regulation would impact my controlled group so I can assume future impacts. Could there be loan sharks of paperwork and bureaucracy? I want to operate a small town like Ottawa and make it like Singapore (which is 74$ usd/hr of productivity while Canada is at 54$/hr usd) shifting the sample group away from debt and towards a productivity based future. I think I need more of an economist’s education to fully understand the intricacies of what that would entail and how politics and society beliefs play a role.