scholarly journals A Regression Analysis of the probability of a recession and student loan debt utilizing data between 1993-2019

2020 ◽  
Author(s):  
Yash Patel ◽  
Pranav Krishnan
Keyword(s):  
Federal Reserve ◽  
Student Loan ◽  
Logistic Curve ◽  
Student Loan Debt ◽  
Euler’S Method ◽  
Federal Reserve Bank ◽  
Reserve Bank ◽  
Loan Debt ◽  
Exponential Regression Model ◽  
Near Future

Over 44.7 million Americans carry student loan debt, with the total amount valued at approximately $1.31 trillion (Quarterly Report, 2019). Ergo, consumer spending, a factor of GDP, is stifled and negatively impacts the economy (Frizell, 2014, p. 22). This study examined the relationship between student loan debt and the probability of a recession in the near future, as well as the effects of proposed student loan forgiveness policies through the use of a created model. The Federal Reserve Bank of St. Louis’s website (FRED) was used to extract data regarding total GDP per quarter and student loan debt per quarter ("Federal Reserve Economic Data," 2019). Through the combination of the student loan debt per quarter and total GDP per quarter datasets, the percentage of total GDP composed of student loan debt per quarter was calculated and fitted to a logistic curve. Future quarterly values for total GDP and the percentage of total GDP composed by student loan debt per quarter were found through Long Short Term Models and Euler’s Method, respectively. Through the creation of a probability of recession index, the probability of recession per quarter was compared to the percentage of total GDP composed by student loan debt per quarter to construct an exponential regression model. Utilizing a primarily quantitative method of analysis, the percentage of total GDP composed by student loan debt per quarter was found to be strongly associated[p < 1.26696* 10-8]with the probability of recession per quarter(p(R)), with the p(R) tending to peak as the percentage of total GDP composed of student loan debt per quarter strayed away from the carrying capacity of the logistic curve. Inputting the student loan debt forgiveness policies of potential congressional bills proposed by lawmakers found that eliminating 49.7 % and 36.7% of student loan debt would reduce the recession probabilities to be 1.73545*10-29% and 9.74474*10-25%, respectively.

scholarly journals A Regression Analysis of the probability of a recession and student loan debt utilizing data between 1993-2019

2020 ◽  
Author(s):  
Pranav Krishnan ◽  
Yash Patel
Keyword(s):  
Federal Reserve ◽  
Student Loan ◽  
Logistic Curve ◽  
Student Loan Debt ◽  
Euler’S Method ◽  
Federal Reserve Bank ◽  
Reserve Bank ◽  
Loan Debt ◽  
Exponential Regression Model ◽  
Near Future

Over 44.7 million Americans carry student loan debt, with the total amount valued at approximately $1.31 trillion (Quarterly Report, 2019). Ergo, consumer spending, a factor of GDP, is stifled and negatively impacts the economy (Frizell, 2014, p. 22). This study examined the relationship between student loan debt and the probability of a recession in the near future, as well as the effects of proposed student loan forgiveness policies through the use of a created model. The Federal Reserve Bank of St. Louis’s website (FRED) was used to extract data regarding total GDP per quarter and student loan debt per quarter ("Federal Reserve Economic Data," 2019). Through the combination of the student loan debt per quarter and total GDP per quarter datasets, the percentage of total GDP composed of student loan debt per quarter was calculated and fitted to a logistic curve. Future quarterly values for total GDP and the percentage of total GDP composed by student loan debt per quarter were found through Long Short Term Models and Euler’s Method, respectively. Through the creation of a probability of recession index, the probability of recession per quarter was compared to the percentage of total GDP composed by student loan debt per quarter to construct an exponential regression model. Utilizing a primarily quantitative method of analysis, the percentage of total GDP composed by student loan debt per quarter was found to be strongly associated[p < 1.26696* 10-8]with the probability of recession per quarter(p(R)), with the p(R) tending to peak as the percentage of total GDP composed of student loan debt per quarter strayed away from the carrying capacity of the logistic curve. Inputting the student loan debt forgiveness policies of potential congressional bills proposed by lawmakers found that eliminating 49.7 % and 36.7% of student loan debt would reduce the recession probabilities to be 1.73545*10-29% and 9.74474*10-25%, respectively.

scholarly journals Why Are Interest Rates So Low?

2013 ◽  
pp. 1-4
Author(s):  
Joseph G. Haubrich
Keyword(s):  
Interest Rates ◽  
Recent Work ◽  
Federal Reserve ◽  
Federal Reserve Bank ◽  
Reserve Bank ◽  
Work Done ◽  
Near Future

Interest rates have been at historical lows for some time now. There are many possible reasons why that is so. We make use of recent work done at the Federal Reserve Bank of Cleveland that allows us to look at individual components of interest rates and see which are exerting the biggest influence. Knowing why rates are where they are now helps to predict where interest rates will likely be in the near future.

The Federal Reserve Bank of Richmond

1942 ◽  
Vol 22 (4) ◽  
pp. 431
Author(s):  
S. Donald Southworth ◽  
C. G. Coit
Keyword(s):  
Federal Reserve ◽  
Federal Reserve Bank ◽  
Reserve Bank
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