Opening Statement Summary:
This paper explores the relationship between economic indicators, specifically the Dow Jones Industrial Average (DJIA), and the support rate for Kamala Harris in the 2024 U.S. presidential election. The authors use a linear regression model, incorporating past polling data and DJIA results from 60 and 90 days prior, to predict Harris's support rate. The paper is an attempt to demonstrate how predictive modeling based on economic trends can forecast political outcomes.
Strong Positive Points:
Timely and Relevant Topic: The focus on the upcoming U.S. presidential election and the use of economic indicators to predict political support is a highly relevant and timely subject.
Clear Use of Modeling: The authors clearly explain their use of linear regression to relate DJIA performance to Harris’s support rate. The model setup is straightforward, and the connection between economic performance and political support is well-motivated.
Critical Improvements Needed:
Lack of Data Exploration and Measurement: The section on measurement lacks detail. It is crucial to elaborate on how the variables (e.g., support rate, DJIA) are measured, what the dataset consists of, and how data from polls is aggregated.
Incomplete Results Section: The results section is currently empty. Without results, it is difficult to evaluate the effectiveness of the proposed model and the validity of its assumptions.
Suggestions for Improvement:
Strengthen Model Justification: The assumption that economic conditions reflected by the DJIA influence political support should be backed by previous studies. Include references and analysis to support this assumption.
Evaluation: The paper presents a timely and interesting topic, but it lacks sufficient empirical support for its modeling choices and does not yet present any results.
Estimated Mark（Out of a total of 126 points, only list deduction part）:
Class Paper: 0/1
Idealized Methodology: 7/10
Data: 5/10
Measurement: 3/4
Model: 5/10
Results: 6/10
Discussion: 7/10
Pollster methodology overview and evaluation:6/10
Miscellaneous: 2/3
Referencing: 1/4
Overall: 96/126
Reason：
Providing more data insights and empirical evidence would significantly improve the quality of the paper.
Opening Statement Summary: This paper explores the relationship between economic indicators, specifically the Dow Jones Industrial Average (DJIA), and the support rate for Kamala Harris in the 2024 U.S. presidential election. The authors use a linear regression model, incorporating past polling data and DJIA results from 60 and 90 days prior, to predict Harris's support rate. The paper is an attempt to demonstrate how predictive modeling based on economic trends can forecast political outcomes. Strong Positive Points:
Timely and Relevant Topic: The focus on the upcoming U.S. presidential election and the use of economic indicators to predict political support is a highly relevant and timely subject.
Clear Use of Modeling: The authors clearly explain their use of linear regression to relate DJIA performance to Harris’s support rate. The model setup is straightforward, and the connection between economic performance and political support is well-motivated. Critical Improvements Needed:
Lack of Data Exploration and Measurement: The section on measurement lacks detail. It is crucial to elaborate on how the variables (e.g., support rate, DJIA) are measured, what the dataset consists of, and how data from polls is aggregated. Incomplete Results Section: The results section is currently empty. Without results, it is difficult to evaluate the effectiveness of the proposed model and the validity of its assumptions. Suggestions for Improvement: Strengthen Model Justification: The assumption that economic conditions reflected by the DJIA influence political support should be backed by previous studies. Include references and analysis to support this assumption. Evaluation: The paper presents a timely and interesting topic, but it lacks sufficient empirical support for its modeling choices and does not yet present any results. Estimated Mark（Out of a total of 126 points, only list deduction part）: Class Paper: 0/1 Idealized Methodology: 7/10 Data: 5/10 Measurement: 3/4 Model: 5/10 Results: 6/10 Discussion: 7/10 Pollster methodology overview and evaluation:6/10 Miscellaneous: 2/3 Referencing: 1/4 Overall: 96/126 Reason： Providing more data insights and empirical evidence would significantly improve the quality of the paper.