Millets as a Sustainable Solution for Food Security: An Analysis of Global Research and Trade Trends

Summary: This study conducts a bibliometric analysis to explore global research trends on the interconnections between food security and millets. Recognizing the urgent challenges to food security posed by climate change, population growth, and resource scarcity, this analysis emphasizes millets—a resilient, nutrient-rich, and environmentally adaptable grain—as a potential crop to enhance food security and sustainability. Given millets' advantages, such as low water requirements, adaptability to marginal soils, and high nutritional value, there is growing international interest in integrating them into sustainable food systems. The analysis focuses on research from 1993 to 2024, obtained from the SCOPUS database, examining  primary search terms: "food security and millets." The study uses VOS viewer software to categorize keywords into thematic clusters, revealing research patterns across environmental, economic, and agricultural themes. Key findings demonstrate significant research gaps in millet-focused trade studies, despite the 2023 International Year of Millets, and underscore the need for further research to optimize millet production and trade strategies. By identifying gaps and potential areas for further investigation, this study offers insights for policymakers, researchers, and stakeholders interested in leveraging millet’s benefits to enhance global food security and build resilient food systems amidst climate challenges. This bibliometric approach is a tool for future studies on sustainable crop trade, guiding research toward holistic food security solutions that integrate underutilized but highly promising crops like millets.

1.     Introduction

Global food security has been a critical issue in the 21st century because of the increasing population, climate change, and finite natural resources, which have been challenging for the traditional agricultural system. As the nations collectively work towards taking action to achieve United Nation’s Sustainable Development Goal 2, targeting Zero Hunger globally, adaptable, resilient, and nutritional crops have become the need of the hour.  Millets, A group of small seed cereals, possess high nutritional value and are climate-resilient. Therefore, these crops can play an essential role in attaining SDG 2. (Antony Ceasar and Maharajan,2022).

The most popular types consumed are pearl millet (Pennisetum glaucum), finger millet (Eleusine coracana), and foxtail millet (Setaria italica). The unique properties of millets that make it valuable for global food systems that are facing growing risks of resources is that it is not a water-intensive crop like the staple crops (wheat and rice) (Ajatasatru, A., Prabhu, V., Pal, B.D. et al.,2024). With their ability to thrive in poor soils and under minimal water conditions, millets are well-suited to meet the dual challenges of climate resilience and food security. (Traore, B. et al,2021.).

The growing recognition of millets' role in food security has also spurred international collaborations to improve their cultivation and distribution. Trade partnerships and initiatives, such as the UN’s designation of 2023 as the International Year of Millets, highlight the importance of millets globally and promote research investments to enhance yield, quality, and distribution channels. These collaborations help standardize millet production and quality, making them more accessible to international markets and attractive to consumers. Furthermore, Millets are essential in enhancing global food security through international trade by diversifying food systems, boosting nutrition, and offering a sustainable and resilient crop alternative. (Hatem Chouchane, Maarten S. Krol, Arjen Y. Hoekstra,2018)Expanding millet trade benefits producing regions economically while providing a sustainable solution to global food challenges, fostering healthier diets, and building resilience against food insecurity.

This paper attempts to conduct a bibliometric analysis of the research work undertaken globally on ‘food security. This paper analyzes the scientific literature on the topic and understands the pattern of publication over the years in terms of keyword analysis of themes pursued over the years. Also, this paper studies the frequently used keywords on the topic and analyzes them through cluster analysis using the software Vosviewer. Overall, this bibliometric analysis can be used as a tool for future researchers to find future research potential through gaps in the current study. It will benefit the researchers in studying the potential of millets to contribute to global food security. Further, by investigating the role of millets in a sustainable, secure, and nutritious food system, this research contributes to the growing discourse on how underutilized crops can play a transformative role in addressing food security in an era of climate uncertainty.

 

2.     Research Methodology

To conduct the bibliometric analysis, the study was conducted over the food security research work conducted globally from the year the first article was published to 2024. Through the SCOPUS database, an initial search was carried out with different keywords: “food security” AND “millets”. To refine the results, only “Articles” limited to the “English” language and “all open access” were selected. This search resulted in extracting the dataset of 181 documents downloaded in .csv format to further analyze the results. The VOSviewer (bibliometric mapping software) was used to conduct the bibliometric analysis and has also been a widely used and accepted software in conducting bibliometric analysis tools.

3. RESULT AND FINDINGS

FOOD SECURITY AND MILLETS

This section analyzes the extracted data on “food security” AND “millet” in graphs and tables derived from the VOS viewer. The research and development of millets in food security was extracted through the process explained in Figure 1 above. In 1999, the first paper on the topic was published by Apili Ejupu, E.C., Makhura M.T., and Kirsten J.F., titled “Food security in a commercializing rural economy. During the extraction process, the first research work was published in 1999, the only document published in the year , and the latest was published in 2024.

 

Time Period	Total Articles	Keywords	No. of Citations
1999-2024	216	100	5,336

 

KEYWORD CO-OCCURRENCE ANALYSIS

The keyword analysis was conducted by uploading the data extracted from SCOPUS to Vosviewer. After selecting the Co-occurrence of all the keywords, 1932 keywords were derived from the uploaded documents. To make the results more relevant and refined, the threshold limit of occurrence of each keyword was set to 5, after which only 100 keywords made it to the final list. The following analysis was done on the refined keywords represented in Figure 1.

Figure 1: Keyword Co-occurrence of food security and millet.

The table1 categorizes research keywords into three different clusters, each color-coded and containing terms related to agricultural and environmental research themes The first cluster, that is, Red Cluster centres around climate adaptation, agricultural management, and food security, with significant focus on climate change (42 occurrences) and food security (101 occurrences). Terms such as "crop yield," "crop production," and "food supply" indicate a focus on enhancing agricultural productivity and resilience in response to climate-related challenges. Keywords like "adaptive management" and "farming system" emphasize sustainable agricultural practices that can help manage and mitigate climate risks. This cluster reflects research focused on climate-smart agriculture, aiming to ensure food security by enhancing crop resilience and management in vulnerable regions.

Table 1: Keyword Occurrence of Food Security and Millet

The green cluster has a strong biological and genetic research orientation, with terms related to plant genetics, genomics, and breeding. Keywords such as "genome," "genotype," "genome-wide association study," and "gene expression" point to molecular and genetic studies, which are essential for developing resilient crop varieties. Terms like "drought stress" and "finger millet" suggest that this research explores how crops can withstand environmental stresses. Locations such as India and Nepal hint at regions where this genetic research might be applied. The focus of this cluster is on understanding and enhancing genetic variability and plant resilience, with the ultimate goal of developing climate-resilient crops through genetic advancements.

The blue cluster is heavily centred on food and nutritional security as well as sustainable agriculture. Keywords such as "agriculture," "crop," "millet," "food grain," and "malnutrition" suggest a focus on crop production and the role of diverse crops in meeting nutritional needs. This cluster also emphasizes specific crops like maize, millet, sorghum, and soybean—important staples in many regions. Terms like "sustainability" and "sustainable agriculture" reflect a broader interest in promoting agricultural practices that are environmentally sound and can ensure long-term food security. The presence of "nutrients," "seasonal variation," and "water supply" highlights the research’s attention to the resource-efficient and nutritional aspects of crop production.

Together, these clusters illustrate a comprehensive approach to global food security that integrates adaptive management, genetic innovation, and sustainable agricultural practices. This interconnected research can help build resilient food systems that address the dual challenges of climate change and nutrition security.

TREND OVER THE YEARS

Over the years, the keywords used for the study of food security and millets have varied. In the initial year of 2018, more attention was given to rice as it was the food of choice, malnutrition, smallholder, genetic variability, Sahel, Mali, etc., as shown in Figure 2. 

 

Figure 2: Research trends over the years on food security and millet

In further years, the area of research changed towards maize, crop production, fertilizers, cultivation, crops, and nutrients. In recent years, the focus of the study has shifted towards climate effects, forecasting, pearl millet, finger millet, China, Africa, India, and agricultural ecosystems. This depicts a shift in focus from the issues that were more relevant in the past, such as smallholder and genetic variability, towards issues that are more prominent in recent scenarios, such as climate effect and millets.

CONCLUSION

The outlook for millets in international trade is promising, given the global emphasis on sustainable agriculture. Millets align with the UN Sustainable Development Goals, particularly SDG 2 (Zero Hunger) and SDG 13 (Climate Action), by offering a resilient crop option in water-scarce regions. Increased government and NGO support for millet production and processing in developing countries will likely drive growth. Additionally, initiatives focusing on improved storage, processing, and export infrastructure are expected to bolster the export potential for millet-based products.

However, no significant research has been done in this area to improve the performance of millets in international trade. Upon accessing the SCOPUS database, we find no research papers on the importance of millets in ensuring food security through international trade. International trade is critical in ensuring global food security by facilitating the movement of food and agricultural products across borders and addressing disparities in production capacity, climate, and resources among countries. For nations with limited agrarian output due to climatic constraints, arable land shortages, or seasonal variations, trade enables access to food resources that would otherwise be unavailable, ensuring a stable supply for their populations.

The clusters collectively depict a comprehensive view of global food security and agriculture, intersecting with economic, environmental, and social factors. In conclusion, this study highlights a critical research gap in millets, international trade, and sustainable food. By analyzing datasets from SCOPUS, we identified strong links between food security. Security, agricultural trade, and sustainable development, as well as between food security, millets, and climate change. Despite the recent global focus on millets, including the 2023 International Year of Millets, the literature on the role of international trade in promoting millet-based food security remains limited. Given their resilience to water scarcity and suitability for arid regions, millets hold significant agricultural trade potential for countries with limited water resources. Future research should, therefore, explore trade models that leverage millets to enhance food security and support sustainable development goals. Addressing this gap could contribute to resilient food systems worldwide, particularly in regions vulnerable to climate change and resource constraints. 

References:

1.     Marie-Julie Lambert, Pierre C. Sibiry Traoré, Xavier Blaes, Philippe Baret, Pierre Defourny, Estimating smallholder crops production at village level from Sentinel-2 time series in Mali's cotton belt, Remote Sensing of Environment, Volume 216, 2018, Pages 647-657, ISSN 0034-4257.

2.     Hatem Chouchane, Maarten S. Krol, Arjen Y. Hoekstra,Expected increase in staple crop imports in water-scarce countries in 2050, Water Research X, Volume 1, 2018, 100001, ISSN 2589-9147.

3.     Antony Ceasar, S., & Maharajan, T. (2022). The role of millets in attaining United Nation’s sustainable developmental goals. Plants People Planet, 4(4), 345–349. https://doi.org/10.1002/ppp3.10254

4.     Ajatasatru, A., Prabhu, V., Pal, B. D., & Mukhopadhyay, K. (2024). Economy-wide impact of climate smart agriculture in India: a SAM framework. Journal of Economic Structures, 13(1). https://doi.org/10.1186/s40008-023-00320-z

5.     Traore, B., Birhanu, B. Z., Sangaré, S., Gumma, M. K., Tabo, R., & Whitbread, A. M. (2021). Contribution of climate-smart agriculture technologies to food self-sufficiency of smallholder households in mali. Sustainability (Switzerland), 13(14).

6.     Davis, K. F., Chiarelli, D. D., Rulli, M. C., Chhatre, A., Richter, B., Singh, D., & DeFries, R. (2018). Alternative cereals can improve water use and nutrient supply in India. Science Advances, 4(7). https://doi.org/10.1126/sciadv.aao1108

7.     Apili Ejupu, E. C., Makhura, M. T., & Kirsten, J. F. (1999). Food security in a commercialising rural economy: Initial findings from a case study of two districts in uganda. Agrekon, 38(4), 827–838.

8.     Yiridomoh, G. Y., Bonye, S. Z., & Derbile, E. K. (2024). Reducing vulnerability to climate change among millet and sorghum farmers in Ghana: interrogating the contribution of climate-smart agriculture in northwestern Ghana. Frontiers in Sustainable Food Systems, 8.

9.     Leila Riahi ･Mériam Ben-Romdhane ･Ahmed S. Masmoudi. Industrial interests and requirements for improvement of pearl millet, a gluten-free and climate-smart underutilized cereal. J Plant Biotechnol (2024) 51:077-088

10.  Chhabra, I., & Kaur, A. (2022). A study of consumer behaviour towards products promoting health and sustainability. PUSA Journal of Hospitality and Applied Sciences, 8(1), 34-46.

11.  Vyas, S., Dalhaus, T., Kropff, M., Aggarwal, P., & Meuwissen, M. P. M. (2021). Mapping global research on agricultural insurance. Environmental Research Letters, 16(10). https://doi.org/10.1088/1748-9326/ac263d

12.  Jalgaonkar, K., Jha, S. K., & Mahawar, M. K. (2018). Influence of incorporating defatted soy flour, carrot powder, mango peel powder, and moringa leaves powder on quality characteristics of wheat semolina-pearl millet pasta. Journal of Food Processing and Preservation, 42

By
Palak Rawat

Ph.D. Scholar, Department of Economics, Manav Rachna International Institute of Research and Studies, Haryana.

To cite this article: Rawat, P. (2025, January). Millets as a sustainable solution for food security: An analysis of global research and trade trends. Eco-Bizz Department of Economics. https://ecobizzblog.blogspot.com/2025/01/millets-as-sustainable-solution-for.html

The Rise of Electric Vehicles: Paving the Way for a Sustainable Future

Summary

The automotive industry has changed dramatically with the move to electric vehicles (EVs), which is motivated by the pressing need to cut back on fossil fuels and greenhouse gas emissions. EVs have many benefits over conventional internal combustion engine (ICE) vehicles. They run on energy produced by fuel cells or rechargeable batteries. Notably, they have zero tailpipe emissions and are less expensive to operate, making them a desirable option for legislators and consumers. Furthermore, especially in crowded urban areas, their quieter functioning helps to lower noise and air pollution. This analysis outlines the current growth path of EV industries and existing policies to support this growth. 

History and Technological Progress
The first electric vehicle prototypes were created alongside the development of gasoline engines in the 19th century. However, the prevalence of ICE vehicles and battery technology constraints prevented EVs from becoming widely accepted. The performance and convenience of gasoline-powered cars dominated the electric vehicle market for many of the 20th century.
The late 20th century was a watershed for electric vehicles (EVs) due to developments in lithium-ion battery technology, heightened environmental consciousness, and pro-EV legislation. These advancements made EVs more feasible and consumer-friendly by enabling notable gains in battery efficiency, range, and charging infrastructure.
Businesses such as Tesla have been instrumental in transforming the electric vehicle market. In addition to capturing the premium EV market, Tesla has increased rivalry among established manufacturers by concentrating on high-performance electric vehicles and investing in charging infrastructure. The company's success has disproved the long-held belief that EVs are less capable than their gasoline-powered counterparts by proving that electric vehicles can provide both performance and sustainability.
Global EV Market
As of 2020, over 10 million electric vehicles were on the road worldwide, with battery-electric models propelling the market's growth. The worldwide EV market is dominated by various manufacturers, each helping to advance electric mobility. With distinct business plans and target markets, major competitors include Tesla (USA), BYD (China), Tata Motors (India), and Hyundai (South Korea).

 

Number of Electrical Vehicles Sales Across World (2019-2023)

SOURCE: https://www.statista.com/outlook/mmo/electric-vehicles/worldwide#unit-sales

Growth Rate

For the growth rate of the data from 2019-20 to 2023-24, we will calculate the annual compound growth rate (CAGR) for each category and the total. CAGR is useful for showing a consistent growth rate over a period.
The formula for calculating CAGR:
CAGR = [( Ending Value/Starting Value ) 1/Years]-1.
Starting Value: 2019-20
 Ending Value: 2023-24
 Years: 4
Here are the annual compound growth rates (CAGR) for Electric and Hybrid Vehicles over the 4 years (2019-20 to 2023-24):
Electric Vehicles: 53.60% per year
Hybrid Vehicles: 64.36% per year
Total: 56.57% per year
 This shows that Hybrid Vehicles are growing slightly faster than Electric Vehicles during this period, with both showing significant growth.

The Indian EV Market

India's demographic advantages—a sizable population and a young labour force—offer a unique chance for the development of electric vehicles. The Indian government has taken several steps to encourage the use of EVs after realizing their potential to support sustainable development.
One of the main initiatives is the [1] Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) scheme. It offers financial incentives to promote EV adoption and lessen reliance on fossil fuels. FAME II, the program's second phase, was launched in 2019 and increased funding for electric buses, two-wheelers, and charging infrastructure.
Notwithstanding the encouraging outlook, the Indian EV sector still confronts many obstacles. To ensure widespread acceptance, better battery technology must be[2] developed, a strong charging infrastructure must be established, and supportive laws must be put in place. The market must also address concerns about the source and disposal of battery raw materials, which may impact the environment.

Number of Electrical Vehicles Sales in India (2019-2023)

SOURCE: https://www.smev.in/statistics

Growth Rate

For the growth rate of the data from 2019-20 to 2023-24, we will calculate the annual compound growth rate (CAGR) for each category and the total. CAGR is useful for showing a consistent growth rate over a period.
The formula for calculating CAGR:
CAGR = [( Ending Value/Starting Value ) 1/Years]-1.
For example: Starting Value: 2019-20, Ending Value: 2023-24, Years: 4
The annual compound growth rates (CAGR) for each category over the 4 years (2019-20 to 2023-24):
2 wheelers: 143.55% per year
3 wheelers: 45.01% per year
4 wheelers: 148.36% per year
Buses: 70.79% per year
Total: 76.36% per year
This shows that four-wheelers and two-wheelers experienced the highest growth rates, followed by buses and the overall total.

Policies Supporting India’s Transition to Electric Vehicles (EVs)

The switch to electric vehicles (EVs) is a crucial part of India's aggressive goals to cut pollution and greenhouse gas emissions. To facilitate the EV transition, the Indian government has implemented several measures to encourage the adoption of EVs, boost production, and construct the infrastructure required for a cleaner, more sustainable transportation system.

FAME Scheme
The Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) program is a key component of India's EV policy framework. Introduced in 2015, the program uses subsidies and incentives to promote the use of EVs and lessen dependency on fossil fuels. The second phase, FAME II, was introduced in 2019, and financial incentives were increased to support charging infrastructure and electric buses, two-wheelers, and three-wheelers.

The scheme allocates around ₹10,000 crore over three years and focuses primarily on supporting public and shared transport electrification.

PLI Scheme for Advanced Chemistry Cells (ACC)
The Production-Linked Incentive (PLI) Scheme for Advanced Chemistry Cells aims to increase EV battery production in India to decrease reliance on imported batteries. The program offers financial assistance to businesses that set up battery production plants, promoting cost-cutting and innovation in EV battery manufacturing—two essentials for accessible and reasonably priced EVs.

PLI Scheme for Advanced Chemistry Cells (ACC)
To increase EV accessibility, the Goods and Services Tax (GST) on EVs was lowered from 12% to 5%, while the GST on conventional vehicles remained at 28%. Furthermore, under Section 80EEB of the Income Tax Act, people can deduct up to ₹1.5 lakh from their income taxes for the interest on loans they take out to buy EVs. These incentives increase EV sales and directly reduce customer expenses.

Observations

Two-wheelers' dominance in the EV market highlights their affordability and convenience for urban commuting.
The rapid growth of three-wheelers suggests their potential for commercial applications like deliveries and public transportation.
The increasing popularity of four-wheelers indicates a shift towards electric personal transportation.
The slower growth of buses could be attributed to factors like higher upfront costs and infrastructure requirements.

Reasons for the boom

Government Incentives: The Indian government has implemented various policies and subsidies to promote EV adoption and make it more affordable for consumers.
Environmental Concerns: Growing awareness about air pollution and climate change has driven demand for cleaner transportation options.
Technological Advancements: Battery technology, charging infrastructure, and vehicle design improvements have made EVs more practical and appealing.
Fuel Price Volatility: Rising fuel prices have made EVs a more cost-effective choice in the long run.

CONCLUSION

To sum up, the emergence of electric vehicles is changing the transportation industry by providing a sustainable substitute for conventional automobiles. EVs are positioned to play a significant role in combating climate change and promoting cleaner air thanks to their advantages for the environment, cost reductions, and technological developments. Electric vehicles can completely change the automobile industry if nations like India adopt electric mobility through encouraging laws and programs. We can create a more sustainable and environmentally friendly future for future generations by encouraging creativity and teamwork.

Sources

https://www.bcg.com/publications/2024/how-electric-two-wheelers-are-rapidly-gaining-popularity

https://assets.kpmg.com/content/dam/kpmg/in/pdf/2020/10/electric-vehicle-mobility-ev-adoption.pdf]

By

Shreyanshu Lamba, B.A. Economics (2022-25), SBSS, MRIIRS
&
Dr. Durairaj Kumarasamy, Associate Prof. and Head DoE, SBSS, MRIIRS

  

Predicting My Students' SGPA: From OLS to Machine Learning

Summary: This article highlights the importance of machine learning algorithms and traditional econometrics models. Using a classic classroom example, this article suggests that a student of economics should use both tools in economic modeling.  

While teaching econometrics, the fundamental challenge we face is to choose the perfect example or data to use while explaining econometrics and the importance of being present in class. Most of the time, I ended up using the classic example of grade points (GPA or SGPA) and how it is affected by attendance, IQ, internal marks, and so on. The example and the method to prove to my students that these factors are crucial for getting a good grade remained the same for the past few years. The mighty ordinary linear least square (OLS) regressions always do their tricks and show that the student will get lower grades if they perform poorly in the internal exams or have less attendance. However, I always questioned whether the OLS is the best model. In most cases, students are in their first year. I cannot teach them non-linear equations, time-varying state space, or any fancy model that may fit the data perfectly.

Figure 1: SGPA and Average Internal Marks of the students of the Department of Economics

An OLS model seems perfect for the data presented in Figure 1. However, the data has a higher dispersion at specific ranges, such as 60 to 70 or 87 to 94, which is a classic case of heteroskedasticity. One can remove these data points and label them outliers, but then the students will question my intention. So, removing data points or applying a complex model is not an option.

If a student who has an average internal mark of 65 approaches me and wants to know the predicted SGPA, I will use OLS to show that, based on the regression result of Table 1, the student will get an average SGPA of 4.9 with a mean squared error (MSE) of 0.93 and r²=0.81. However, as I mentioned, students in this cluster have a higher variation, which means my prediction may be misleading.

Table 1: Simple OLS result of SGPA on Average Internal Marks

Figure 2: OLS prediction of SGPA for the student with 65 average internal marks

In the era of data analytics and machine learning, I should use machine learning techniques to predict my students' SGPAs. One of the basic methods is the K-Nearest Neighbourhood algorithm. The idea is that we can predict the behavior of data by looking at its nearest neighbors. I used 20% of the data for testing and K=8 nearest neighbors to predict the SGPA of the student with 65 average internal marks. The prediction has changed to 5.23 with a mean squared error of 2.0 and r²=0.49, as depicted in Figure 3. I changed the value of K many times, and it remained above the predicted value of OLS.

Figure 3: K- Nearest Neighborhood prediction of SGPA for a student with 65 Average Internal Marks

The data's clustering behavior may still lead to wrong predictions. So, I used the decision tree algorithm, which is more appropriate when neighboring clusters display different patterns or the data has a more complex pattern. Using a basic decision tree algorithm, I predicted that the student with an average of 65 internal marks might get an SGPA of 6.28 with a mean squared error of 2.03 and r²=0.41, which is way above the OLS prediction (figure 4).

Figure 4: Decision tree prediction of SGPA for a student with 65 average internal marks

All three models have strengths and weaknesses; no one can claim that one model is better in all situations. As the literature has mentioned, there is always a trade-off between unbiasedness and standard error. So the investigator should be careful while using these models for forecasting or predicting a variable. Although machine learning algorithms are popular, OLS is a powerful and simple technique with a solid theoretical background. The overall relationship between Internal marks and SGPA or attendance and SGPA is positive and significant as predicted by the OLS. And remember, under all the assumptions of classical linear regression, OLS is still BLUE (Best Linear Unbiased Estimate). 

Please Note: Don’t take this post seriously. Econometrics is just for fun. (All Python codes are available in open sources.)

By

Dr. Akash Kumar Baikar

Assistant Professor, Department of Economics, SBSS, MRIIRS

The Ladder of Happiness Through Macroeconomic Fundamentals or Social Expenditure: A BRICS Perspective

 Summary:

In current geopolitics, the BRICS nations can set new standards for future economic development. This article explores how these countries should progress in their future development paths. Keeping happiness as an objective, this article suggests that social expenditures are much more critical than macroeconomic fundamentals.  

Figure 1: The Ladder of Happiness of BRICS nations from 2014 to 2023

Source: World Bank Open Data, The size of the bubble represents the level of the Cantril Ladder Index of that country in that year

Introduction

The Cantril Ladder, a simple yet effective tool for gauging subjective well-being, poses a straightforward question: "Imagine a ladder with the best possible life at the top step (10) and the worst possible life at the bottom step (0). On which step do you feel you personally stand at this time?"[1] By quantifying subjective experiences, this scale offers valuable insights into individual life satisfaction. While individual well-being is a complex interplay of personal circumstances and psychological factors, macro-level variables can significantly influence happiness. This study delves into the relationship between these broader economic factors and Cantril Ladder scores, focusing specifically on the BRICS nations as they represent a significant portion of the global economy. Understanding the factors that influence the happiness of their citizens is crucial for policymakers and researchers alike.

Our panel data analysis indicates that three key variables—GDP per capita, expenditure on health and education, and the unemployment rate—significantly influence Cantril Ladder scores within the BRICS nations. The following sections delve into the specific impact of each variable. 

Panel data analysis of BRICS countries

Table 1: Random effect regression result of the Cantril Ladder index on macroeconomic and social expenditure variables

	Model-1	Model-2
CPI	-.002 (0.003)	0.0032 (.002)
Log of GDP Per Capita	0.471** (0.189)	1.262*** (0.09)
Unemployment	-0.058*** (0.01)	-0.058*** (0.006)
Health Expenditure (% of GDP)	0.332*** (0.05)
Expenditure on Education (% of GDP)		0.629*** (0.057)
Intercept	-0.083 (1.79)	-8.61*** 0.996

***,**,* represent 1%, 5%, and 10% L.S. respectively, S.E. in the parentheses

As an indicator of wealth distribution, GDP per capita directly and significantly impacts citizens' happiness. As a country's average income rises, so does the general well-being of its people. Our analysis reveals that a 1% boost in GDP per capita leads to a statistically significant increase in the Cantril Ladder score. This suggests that income distribution is important to a country's happiness level.
However, the relationship between income and happiness is not always linear. Studies have shown that while increased income can boost happiness to a certain point, additional wealth may not significantly increase well-being beyond a certain threshold.
Unemployment, a scourge of modern economies, can cast a long shadow over individual well-being. Job loss can lead to a host of negative consequences, including financial insecurity, increased stress, and a diminished sense of purpose. These factors can significantly impact people's perceptions of their lives and, consequently, their Cantril Ladder scores. Our analysis reveals that a 1% increase in the unemployment rate is associated with a statistically significant 0.058 decrease in the Cantril Ladder score. This finding underscores the detrimental impact of unemployment on subjective well-being. Moreover, high unemployment rates can have broader societal implications, such as increased social unrest and political instability, further eroding people's sense of security and overall well-being.
Government investment in education and healthcare is a cornerstone of societal progress. By prioritizing these sectors, nations can foster long-term economic growth, enhance social development, and improve the overall well-being of their citizens. Our research shows that investing in education and healthcare can significantly boost people's happiness. A 1% increase in health expenditure is linked to a 0.33 increase in the happiness index, while a 1% increase in education expenditure is associated with a 0.629 boost in happiness.

The BRICS: A comparative analysis-  China's sustained economic growth and significant investments in education have contributed to a relatively stable Cantril Ladder score (Figure-1). In contrast, Brazil and Russia have experienced fluctuations in their scores, influenced by economic volatility and political uncertainty. India, despite rapid economic growth, faces challenges related to unemployment and inequality, which can impact its citizens' well-being.
In conclusion, while macroeconomic variables play a significant role in shaping individuals' perceptions of their lives, a holistic approach is necessary to understand the complex interplay between economic conditions and subjective well-being. Policymakers should consider not only economic growth but also social and environmental factors to promote sustainable and equitable development.

R code for the plot: Packages used- dplyr, ggplot2, gganimate

p <- ggplot(data, aes(x = GDPPerCapita, y = HappinessIndex, size = HappinessIndex, color = Country)) +

  geom_point(alpha = 0.7) +

  geom_text(aes(label = Country), vjust = 1.5, hjust = 1.5, size = 3) +

  scale_size(range = c(2, 12)) +

  theme_minimal() +

  labs(

    title = 'BRICS Countries: Happiness Index vs GDP Per Capita',

    x = 'GDP Per Capita',

    y = 'Happiness Index',

    size = 'Happiness Index'

  ) +

  theme(

    plot.title = element_text(hjust = 0.5)

  )

animated_plot <- p + transition_time(Year) +

  labs(subtitle = 'Year: {frame_time}')

References:

[1] OECD Guidelines on Measuring Subjective Well-being

By

Tisha Virmani

M.A. Economics (2024-26), Department of Economics, SBSS, MRIIRS, Faridabad

External Shocks and India's WPI Inflation

Summary: This article outlines the effects of external shocks and their impact on India's Wholesale Price Index (WPI) inflation. It analyzes the factors and channels contributing to inflation's volatile nature in recent years.