Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(Forecasting Recession). Showing records 1 – 2 of 2 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Eastern Illinois University

1. Ngoc, Tran B. Forecasting Recessions in the U.S.A.

Degree: MA, Economics, 2019, Eastern Illinois University

Many economists have raised concerns about the next recession in the U.S., especially after the Great Recession in 2008. Many believe that the next recession will strike either this year (2019) or the next year (2020). This paper first analyzes different macroeconomic indicators such as Buffet Indicators, interest rate, unemployment rate, etc. In terms of modelling the data, a Probit model is applied to determine what variables can affect the probability of a recession. Then, going beyond whether or not a recession is likely at any time in future, a relevant question will be how long a time might elapse before the next recession will set in. This can be answered by using a Poisson model. Our results from the Probit model suggest that the government should focus on improving unemployment rate rather than interest rates by having more open policies for small businesses. In addition, the Poisson model forecasts that the next recession will likely occur in 2020. Advisors/Committee Members: Mukti P. Upadhyay, Ali R. Moshtagh, James R. Bruehler.

Subjects/Keywords: forecasting; recession; poisson; probit; Business

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ngoc, T. B. (2019). Forecasting Recessions in the U.S.A. (Masters Thesis). Eastern Illinois University. Retrieved from https://thekeep.eiu.edu/theses/4530

Chicago Manual of Style (16th Edition):

Ngoc, Tran B. “Forecasting Recessions in the U.S.A.” 2019. Masters Thesis, Eastern Illinois University. Accessed November 19, 2019. https://thekeep.eiu.edu/theses/4530.

MLA Handbook (7th Edition):

Ngoc, Tran B. “Forecasting Recessions in the U.S.A.” 2019. Web. 19 Nov 2019.

Vancouver:

Ngoc TB. Forecasting Recessions in the U.S.A. [Internet] [Masters thesis]. Eastern Illinois University; 2019. [cited 2019 Nov 19]. Available from: https://thekeep.eiu.edu/theses/4530.

Council of Science Editors:

Ngoc TB. Forecasting Recessions in the U.S.A. [Masters Thesis]. Eastern Illinois University; 2019. Available from: https://thekeep.eiu.edu/theses/4530


University of Alabama

2. Naidoo, Jefrey Subramoney. Forecasting recessions: convergence of information and predictive analytics.

Degree: 2010, University of Alabama

The purpose of this study is to augment the predictive power of conventional recession-forecasting models by examining the interrelationships among macroeconomic indicators, government information sources and performance data of public companies. The latter two information sources are collectively referred to as institutional artifacts in this study. Evidence was sought of a predictive relationship between institutional artifacts and macroeconomic vulnerability, and the ensuing associations were modeled to provide long-range predictive insights that will serve as a forewarning of impending recessions. The inclusion of public policy dialogue and corporate performance data as predictor variables in recession forecasting models not only extends the information paradigm associated with recession forecasting, but it also designates the unique contribution that this study makes to this area of research. To obtain a valid estimation of the predictive power of institutional artifacts, and to avoid falsely inflating their significance, the new variables were not modeled in isolation. Macroeconomic indicators published by government agencies and private institutions were retained as variables in the respective regression models used in this study. The study found that the current ratio and total debt to assets ratio of Fortune 500 companies, and congressional hearings on economic matters significantly predicted the movement of the yield spread twelve months ahead. The study also found that the odds of a recession increase by 1.06 times, or 6%, for every one unit of increase in the number of congressional hearings held, holding other variables constant. (Published By University of Alabama Libraries) Advisors/Committee Members: Wallace, Danny P., Aversa, Elizabeth S., Borrelli, Stephen A., Black, Jason E., Allaway, Arthur, University of Alabama. College of Communication and Information Sciences.

Subjects/Keywords: Electronic Thesis or Dissertation;  – thesis; Information Science; Economics, Commerce-Business; Business; Business Intelligence; Corporate institutional artifact; Forecasting Recession; Government institutional artifacts; Information; Predictive Model

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Naidoo, J. S. (2010). Forecasting recessions: convergence of information and predictive analytics. (Thesis). University of Alabama. Retrieved from http://purl.lib.ua.edu/21298

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Naidoo, Jefrey Subramoney. “Forecasting recessions: convergence of information and predictive analytics.” 2010. Thesis, University of Alabama. Accessed November 19, 2019. http://purl.lib.ua.edu/21298.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Naidoo, Jefrey Subramoney. “Forecasting recessions: convergence of information and predictive analytics.” 2010. Web. 19 Nov 2019.

Vancouver:

Naidoo JS. Forecasting recessions: convergence of information and predictive analytics. [Internet] [Thesis]. University of Alabama; 2010. [cited 2019 Nov 19]. Available from: http://purl.lib.ua.edu/21298.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Naidoo JS. Forecasting recessions: convergence of information and predictive analytics. [Thesis]. University of Alabama; 2010. Available from: http://purl.lib.ua.edu/21298

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.