Report on the Interrelationship Between Economic Uncertainty and Socio-Economic Factors in High-Uncertainty Countries

Abstract

This report examines the causal and cointegrating relationships between economic uncertainty and key socio-economic indicators across 30 high-uncertainty countries. The analysis focuses on suicide rates, unemployment rates, economic growth, and trade openness, with a significant emphasis on the implications for the United Nations Sustainable Development Goals (SDGs). Utilizing Granger causality and Cointegration tests, the study identifies bidirectional causal relationships in several countries, including Kenya, Finland, Portugal, and Mexico. Key findings indicate that while economic uncertainty negatively impacts economic growth (related to SDG 8) and trade openness (related to SDG 17) in the long term, it paradoxically reduces suicide rates (related to SDG 3) and unemployment rates (related to SDG 8) over the same period. The report provides country-specific policy recommendations aligned with the SDGs to address the complex effects of economic uncertainty.

1.0 Introduction

Global market instability, pandemics, and geopolitical conflicts have elevated economic uncertainty, posing significant challenges to societal well-being and the achievement of the Sustainable Development Goals (SDGs). This uncertainty impacts critical socio-economic domains, including mental health, employment, and economic prosperity. This report investigates the complex, bidirectional relationships between economic uncertainty and four key variables: suicide rates, unemployment, economic growth, and trade openness. The analysis is crucial for developing targeted policies that support sustainable development, particularly in nations most affected by economic volatility.

1.1 Research Objectives

The primary objectives of this report are:

1. To determine how economic uncertainty causes changes in suicide rates, unemployment rates, economic growth, and trade openness in high-uncertainty countries.
2. To explore the reverse impact of these socio-economic variables on economic uncertainty in the same countries.

1.2 Contribution to Sustainable Development Goals (SDGs)

This study provides critical insights for policymakers to formulate strategies aligned with the UN’s Sustainable Development Goals. The findings and recommendations are tailored to address challenges related to:

• SDG 3: Good Health and Well-being (by examining suicide rates).
• SDG 8: Decent Work and Economic Growth (by analysing unemployment and GDP growth).
• SDG 9: Industry, Innovation, and Infrastructure (by linking uncertainty to investment and growth).
• SDG 10: Reduced Inequalities (by considering the disproportionate impact of unemployment on vulnerable groups).
• SDG 17: Partnerships for the Goals (by assessing the role of trade openness).

2.0 Literature Review and Theoretical Framework

The relationship between economic uncertainty and socio-economic outcomes is supported by several theoretical frameworks. Economic stress theory and Durkheim’s social integration theory link financial instability to deteriorating mental well-being, a core concern of SDG 3. Real options theory and job search theory explain how uncertainty leads firms to delay investment and hiring, thereby increasing unemployment and hindering progress toward SDG 8. Similarly, Keynesian economic theory posits that uncertainty reduces consumer and business spending, which directly inhibits economic growth, another target of SDG 8. This report builds on existing literature by examining these relationships through a bidirectional lens across multiple countries, filling a notable gap in current research.

2.1 Economic Uncertainty and Suicide Rates

Previous studies confirm that economic downturns negatively impact mental health, increasing suicide risk. This direct threat to SDG 3 (Good Health and Well-being) is particularly pronounced in high-performance economies. However, research on low- and middle-income countries is less conclusive, highlighting a critical area for investigation.

2.2 Economic Uncertainty and Unemployment

A strong positive correlation between economic uncertainty and unemployment is well-documented, with youth unemployment being especially sensitive. This relationship directly undermines SDG 8 (Decent Work and Economic Growth) and exacerbates inequalities, affecting SDG 10. This report explores the bidirectional nature of this link, which is often overlooked.

2.3 Economic Uncertainty and Economic Growth

Economic uncertainty is widely recognized as an inhibitor of economic growth, as it discourages investment and consumer spending. This dynamic is a major obstacle to achieving SDG 8 and fostering innovation as per SDG 9. The spillover effects from developed to developing nations further complicate this relationship.

2.4 Economic Uncertainty and Trade Openness

In an interconnected global economy, uncertainty disrupts supply chains and reduces international trade. This decline in trade openness can impede global cooperation and economic integration, which are central to SDG 17 (Partnerships for the Goals). The analysis considers how trade policy uncertainty specifically affects international commerce.

3.0 Data and Methodology

This report utilizes a quantitative approach, analyzing secondary data for 30 countries with the highest economic uncertainty in 2022. The dataset covers a 23-year period and includes 690 observations.

• Economic Uncertainty: Measured by the World Uncertainty Index (WUI).
• Socio-economic Variables: Data on suicide rates, unemployment rates, GDP growth, and trade openness were obtained from the World Bank Open Data repository.

The analysis employs two primary econometric methods to assess the interrelationships:

1. Granger Causality Test: To identify the direction of causal relationships (unidirectional or bidirectional) between economic uncertainty and the socio-economic variables.
2. Cointegration Test: To determine if a stable, long-run equilibrium relationship exists between the variables.

4.0 Results of the Analysis

4.1 Granger Causality Findings

The Granger causality tests revealed significant causal links between economic uncertainty and the selected socio-economic variables. Notably, bidirectional relationships were identified in several countries, suggesting a feedback loop where uncertainty affects socio-economic outcomes, and those outcomes, in turn, influence the level of uncertainty.

• Uncertainty and Suicide Rates: Bidirectional causality was found in Peru, Kenya, Haiti, Finland, and Kazakhstan.
• Uncertainty and Unemployment: A bidirectional relationship was identified in Latvia. Unidirectional causality from uncertainty to unemployment was prevalent in countries like South Africa, Mexico, and Spain.
• Uncertainty and Economic Growth: Kenya, Mexico, and Latvia exhibited bidirectional causality.
• Uncertainty and Trade Openness: Portugal and the Kyrgyz Republic showed bidirectional causality.

4.2 Cointegration Findings

The cointegration analysis confirmed the existence of long-run equilibrium relationships between the variables. The results present a nuanced picture:

• Negative Long-Run Relationship: Consistent with economic theory, higher economic uncertainty is associated with lower economic growth (hindering SDG 8) and reduced trade openness (impacting SDG 17) in the long run.
• Positive Long-Run Relationship: Counterintuitively, the findings suggest that in the long run, higher economic uncertainty is associated with lower suicide rates and lower unemployment rates in a majority of the countries studied. This may indicate adaptive societal or economic responses over time, such as the strengthening of social support systems (relevant to SDG 3) or growth in informal economies (relevant to SDG 8).

5.0 Conclusion and Policy Implications for Sustainable Development

This report confirms that economic uncertainty has a complex, often bidirectional, relationship with suicide rates, unemployment, economic growth, and trade openness. The findings underscore that economic uncertainty is a significant barrier to achieving multiple Sustainable Development Goals. However, the discovery of counterintuitive long-run relationships suggests that targeted interventions can mitigate negative impacts and foster resilience.

Based on the analysis, the following policy recommendations are proposed to align national strategies with the SDGs:

5.1 Enhancing Mental Health and Well-being (SDG 3)

• Governments in countries with a strong link between uncertainty and suicide (e.g., Latin American nations) should invest in accessible mental health services and suicide prevention initiatives.
• Public health campaigns should aim to destigmatize mental health issues, building social resilience during periods of economic instability.

5.2 Promoting Decent Work and Reducing Inequalities (SDG 8 & SDG 10)

• In regions where uncertainty drives unemployment (e.g., Europe, Africa), governments should invest in education and vocational training programs to enhance human capital, with a focus on youth and marginalized groups.
• Policies should be implemented to encourage the hiring of young workers, directly addressing Target 8.6 of the SDGs.

5.3 Fostering Sustainable Economic Growth and Innovation (SDG 8 & SDG 9)

• Developing nations, particularly in Latin America and Sub-Saharan Africa, should diversify their economies to mitigate the impacts of sector-specific shocks.
• Public investment in Research and Development (R&D) should be prioritized to drive innovation and sustainable growth, even during uncertain times.

5.4 Strengthening Global Partnerships Through Trade (SDG 17)

• Countries where trade openness can mitigate uncertainty (e.g., Brazil, Nepal, Kazakhstan) should pursue free trade agreements and invest in trade infrastructure.
• Least Developed Countries (LDCs) should leverage “Aid for Trade” initiatives to build capacity, create jobs, and boost exports, thereby enhancing their economic stability.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article explicitly connects its findings and policy implications to several Sustainable Development Goals. The analysis of economic uncertainty’s impact on suicide rates, unemployment, economic growth, and trade openness directly relates to the following SDGs mentioned in the text:

• SDG 3: Good Health and Well-being: The study’s focus on the interrelationship between economic uncertainty and suicide rates directly addresses mental health and well-being. The article notes that economic downturns can have a “detrimental impact on mental health, leading to the risk of suicide” and calls for policies related to mental health awareness and suicide prevention.
• SDG 4: Quality Education: The policy implications section recommends investing in “education and training programs” and expanding access to “quality education to build a skilled workforce.” This is proposed as a measure to increase the labor force and reduce unemployment, especially among youth.
• SDG 8: Decent Work and Economic Growth: This is a central theme of the article. The research investigates the causal links between economic uncertainty and core economic indicators like “unemployment rates” and “economic growth.” The policy recommendations aim to promote “sustainable economic growth” and reduce “youth unemployment.”
• SDG 9: Industry, Innovation, and Infrastructure: The article suggests that developing nations should invest in “trade infrastructure” and “Research and Development of new technologies” to foster sustainable growth and mitigate the effects of uncertainty.
• SDG 10: Reduced Inequalities: The policy implications highlight the need to implement policies that encourage hiring “marginalized groups, particularly women,” and ensure “social integration,” which directly aligns with the goal of reducing inequalities within and among countries.
• SDG 17: Partnerships for the Goals: The article advocates for international cooperation through “Aid for trade support agreements” and “free trade agreements” to help Least Developed Countries (LDCs) mitigate uncertainty and boost economic activity through enhanced trade.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the specific issues discussed and the policy recommendations provided, the following SDG targets can be identified:

1. Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being. The article’s analysis of “suicide rates” and its call for “mental health awareness campaigns and suicide prevention initiatives” directly support this target.
2. Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship. The recommendation to invest in “education and training programs” and “vocational training” aligns with this target.
3. Target 8.1: Sustain per capita economic growth in accordance with national circumstances and, in particular, at least 7 per cent gross domestic product growth per annum in the least developed countries. The study’s focus on “economic growth” and its relationship with uncertainty is central to this target.
4. Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal value. The analysis of “unemployment rates” is directly related to this target.
5. Target 8.6: By 2020, substantially reduce the proportion of youth not in employment, education or training. The article explicitly mentions this target in its policy implications section (“Aligning with Target 8.6: Reducing Youth Unemployment”) and discusses the high susceptibility of “youth unemployment” to economic uncertainty.
6. Target 9.2: Promote inclusive and sustainable industrialization and, by 2030, significantly raise industry’s share of employment and gross domestic product, in line with national circumstances, and double its share in least developed countries. The call for economic “diversification into varying economies” and investment in technology supports this target.
7. Target 10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status. The policy recommendation to encourage the hiring of “marginalized groups, particularly women” is a direct contribution to this target.
8. Target 17.11: Significantly increase the exports of developing countries, in particular with a view to doubling the least developed countries’ share of global exports by 2020. The article’s discussion on “trade openness,” “free trade agreements,” and increasing exports from LDCs aligns with the objective of this target.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article explicitly uses several quantitative variables in its analysis that serve as direct or proxy indicators for measuring progress towards the identified SDG targets.

• Suicide Rate: This is a primary variable in the study (“…explores the causal and cointegrating interrelationships among economic uncertainty and suicide rates…”). It directly corresponds to Indicator 3.4.2: Suicide mortality rate.
• Unemployment Rate: This is another key variable analyzed throughout the article (“…unemployment rates, economic growth, and trade openness…”). It is a direct measure for Indicator 8.5.2: Unemployment rate, by sex, age and persons with disabilities. The specific mention of “youth unemployment” also relates to Indicator 8.6.1: Proportion of youth (aged 15-24 years) not in education, employment or training.
• Economic Growth: The article consistently refers to “economic growth” and “GDP” as a measure of economic performance (“…uncertainty reduces economic growth…”). This aligns with Indicator 8.1.1: Annual growth rate of real GDP per capita.
• Trade Openness: The study analyzes “trade openness” by considering imports and exports (“…crucial for any country to carry out trade activities namely, import and export…”). This variable serves as a proxy for measuring a country’s integration into the global economy and its export performance, which is relevant to Indicator 17.11.1: Developing countries’ and least developed countries’ share of global exports.

4. Table of SDGs, Targets, and Indicators

Source: nature.com