Effects of Labor Force and Unemployment Rates on Gross Domestic Product

SDSC1001/GE1356

Introduction to Data Science

Semester A (2024-2025)

Project Report

Abstract:

This project investigates the commonly held beliefs regarding the relationship between unemployment rates, labor force participation, and economic performance, particularly their effects on GDP growth. It is often assumed that higher unemployment negatively impacts economic health, while declining labor force participation, driven by lower birth rates and an aging population, threatens productivity. However, modern technological advancements such as automation could challenge these assumptions. Using statistical methods, including two-way ANOVA and visualization techniques, this project examines the relationship between unemployment, labor force participation, and the percentage change in GDP. By testing these variables' interaction and individual effects on GDP growth, this study provides more accurate insights into their roles in shaping economic performance, offering a deeper understanding of their implications for policy-making.

1. Introduction

1.1 Background

People always claim that when a country has a higher unemployment rate, that reflects the economy in that country is worse than before. Also, some professors argue that the labor force will decrease due to the lower birth rate and aging society. Productivity depends on the labor force. When production declines, this may affect the economy. Are they genuinely correct? The unemployment rate can be affected by other issues, not only the economy, and nowadays, production steps can be replaced by new technology such as robots. An essential step in testing the validity of these is to investigate their statistical effects on the % change in GDP (Gross Domestic Product) because GDP provides the information of the total value of production of all resident producing units of an economy and the % change in GDP offers the information of that economy having better or worse economic environment.  

1.2 Motivation

The motivation behind this project is to test the validity of commonly held beliefs about the relationship between unemployment, labor force participation, and economic performance. With technological advancements reshaping production and demographic shifts affecting the labor market, it is essential to investigate how these factors influence economic growth. Using statistical methods, including two-way ANOVA and visualization techniques, this project explores whether unemployment and labor force participation rates still play a significant role in shaping GDP growth and whether their interaction has a measurable impact. Understanding these relationships can provide more accurate insights into the health of an economy and inform. better economic policies.

2. Objectives

This project aims to test the hypotheses using statistical methods. In our project, we test the existence of the following objects in our data:

1. Negative relation between the % change in GDP and the unemployment rate

2. Positive relation between the % change in GDP and labor force participation rate

3. Significant effect of unemployment rate on the % change in GDP

4. Significant effect of labor force participation rate on the % change in GDP

5. Significant effect of the interaction of unemployment rate and labor force participation rate on the % change in GDP

3. Methodology

This project applies quantitative statistical techniques to investigate the relationship between unemployment rates, labor force participation, and GDP growth. First, relevant economic data on unemployment, labor force participation, and GDP changes will be collected from reliable sources, including government databases and economic reports. After data collection, preprocessing will ensure consistency and accuracy by cleaning and formatting the data, removing any outliers or anomalies that could skew the results.

Next, visualization methods will be employed to detect any visible trends or patterns in the relationships between the unemployment rate, labor force participation rate, and GDP change. These visualizations will offer a preliminary understanding of potential correlations between the variables. The core of the analysis involves applying a two-way ANOVA to test the effects of unemployment and labor force participation rates, as well as their interaction, on the percentage change in GDP. This statistical approach will help determine if significant relationships exist between the variables and how they interact to affect economic growth.

Finally, the results from the statistical analysis will be interpreted to assess whether the data supports the traditional assumptions about unemployment and labor force participation’s impact on GDP. The study will evaluate the negative relationship between unemployment and GDP change, the positive correlation between labor force participation and GDP change, and the interaction between these variables. The findings will provide a more nuanced understanding of these economic factors in the context of modern technological advancements and help inform. future policy decisions.

3. Results and Discussion

The scatter plots (Figures 1.1–1.4) illustrate the relationship between unemployment rates and labor force participation across four countries: Hong Kong, Japan, China, and the US. Each figure presents distinct trends, highlighting the varying economic dynamics in each region. Figure 1.1 (Hong Kong) shows a weak positive correlation between unemployment and labor force participation. This suggests that as labor force participation increases slightly, unemployment rates also rise, indicating that a growing labor force in Hong Kong may not necessarily reduce unemployment, potentially due to structural issues within the job market.

In contrast, Figure 1.2 (Japan) shows minimal changes in the unemployment rate as labor force participation fluctuates, suggesting a relatively stable labor market where unemployment is less affected by shifts in the labor force. This could indicate that Japan has reached a point of equilibrium where labor market conditions are more rigid and less responsive to participation changes.

Figure 1.3 (China) presents a weak negative correlation, where increases in labor force participation correspond to slight decreases in the unemployment rate. This suggests that higher labor force participation in China may be linked to better employment opportunities, possibly driven by economic growth or expansion in specific sectors. However, the effect is relatively modest.

Lastly, Figure 1.4 (US) shows a stronger positive correlation, where a higher labor force participation rate is associated with a notable rise in unemployment. This indicates potential structural challenges in the US labor market, where increased participation may lead to more competition for jobs, especially in specific industries or skill sets.

These results demonstrate that the relationship between labor force participation and unemployment varies significantly across different countries. In some cases, such as China, higher labor force participation may benefit employment, while in others, such as the US, it may be linked to increased unemployment. These findings suggest that country-specific factors, such as economic policies, market structure, and demographic trends, play a critical role in shaping the labor market's response to changes in participation. Further statistical analysis, including two-way ANOVA, will be required to assess these relationships' significance and impact on broader economic indicators, such as GDP growth.

Figure 1: Scatter Plots Showing the Relationship Between Labor Force Participation and Unemployment Rates in Hong Kong, Japan, China, and the US

Table 1 provides additional insights into how unemployment and labor force participation rates are categorized into three groups (A, B, and C), representing high, medium, and low levels of unemployment. For example, in Group A (highest unemployment rate), 33.3% of the population falls within the highest range of unemployment. In contrast, labor force participation rates are divided among levels (X, Y, and Z). The table helps to illustrate the distribution of unemployment and labor force participation across various economic contexts.

  Table 1 Categorization of Unemployment Rates and Labor Force Participation Levels Across Different Groups