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Modeling the Impact of Happiness and Behavioral-Economic Factors on Saving and Investment Willingness: Evidence from Individual Investors in Himachal Pradesh Using SEM

This study utilizes structural equation modeling on survey data from 400 individual investors in Himachal Pradesh to reveal that while economic and non-economic factors significantly influence saving willingness, only non-economic factors significantly impact stock investment willingness, whereas happiness and economic factors show no significant effect on investment or institutional saving behaviors.

Original authors: Chhaya Devi, Manoj Sharma, Yogesh Gupta

Published 2026-07-16

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Chhaya Devi, Manoj Sharma, Yogesh Gupta

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine your brain as a bustling city where two distinct neighborhoods compete for your attention. In one neighborhood, "Econ Town," everything is calculated with cold, hard numbers: income, interest rates, and the cost of living. In the other, "Feel Good City," the streets are paved with emotions, social vibes, and personal happiness. For a long time, economists thought Econ Town ran the whole show, assuming we all make money decisions like super-computers. But a newer field called behavioral finance suggests that Feel Good City is actually the mayor, often pulling the strings in ways we don't expect. This is the world of "happiness finance," a fascinating corner of science that asks a simple but tricky question: Does being happy make you more likely to save your allowance or buy a stock, or does it just make you want to spend it all on ice cream? Understanding this matters because if we know what really drives our wallet, we can build better systems to help people grow their wealth and secure their futures.

Now, let's zoom in on a specific study that decided to put these two neighborhoods to the test. Researchers from the National Institute of Technology in Hamirpur, India, decided to investigate how happiness, money factors, and social vibes influence the willingness to save and invest. They didn't just guess; they went out and asked 400 real people living in the mountain districts of Hamirpur and Una to fill out surveys. Think of this survey as a giant, detailed map where the researchers asked people about their income, how happy they felt, what their friends were doing, and whether they felt like saving or buying stocks. They then used a powerful mathematical tool called Structural Equation Modeling (SEM)—imagine it as a high-tech GPS that can trace the exact routes between different ideas—to see which factors actually led people to open their wallets for savings or the stock market.

Here is what their map revealed, and it's a bit of a plot twist. The study found that "Econ Town" is a very strong boss when it comes to saving. If people had more money or better access to banks, they were significantly more willing to put cash aside in financial institutions. The data showed a strong, clear path here, with the math confirming this link at a very high level of certainty. Similarly, "Feel Good City" and social vibes (like what your friends think or how confident you feel about money) were huge drivers for investing in stocks. If you felt capable and your social circle was talking about investments, you were much more likely to jump in.

However, the study also drew some big red "X" marks over some popular ideas. Even though we often think money makes us happy, or that happiness makes us rich, this research suggests the connection isn't that simple. The data showed that being happy didn't actually make people more willing to save in banks or invest in stocks; those paths were statistically insignificant. In other words, a happy person isn't necessarily a saver or a stock-picker just because they are smiling. Furthermore, the study ruled out the idea that pure economic factors (like interest rates) directly drive people to buy stocks. While money matters for saving, it wasn't the main switch flipping the "invest in stocks" button for these individuals.

The researchers were very careful with their confidence levels. They didn't just say "maybe"; they used rigorous statistical tests on their 400 responses to say that the links between non-economic factors and investment willingness were strong and real. They also confirmed that their model explained about 63% of why people wanted to save and 35% of why they wanted to invest. But they also admitted that for the links involving happiness and both saving and investing, the evidence simply wasn't there. The study concludes that while happiness is a wonderful thing, it might not be the secret sauce for getting people to invest in the stock market or save in banks. Instead, it seems that economic factors like income are the main drivers for saving, while what you know about money, how you feel about your ability to manage it, and what your friends are doing are the real heavy lifters in deciding whether to take a risk. This research offers a fresh, grounded look at how real people in a developing economy actually make financial choices, reminding us that sometimes the heart and the social circle matter just as much as the bank balance.

Technical Summary: Modeling the Impact of Happiness and Behavioral-Economic Factors on Saving and Investment Willingness

Problem Statement and Research Context
This study addresses a critical gap in behavioral finance literature regarding the determinants of individual saving and investment behavior in emerging economies, specifically India. While traditional economic models emphasize rational decision-making based on income, interest rates, and access to financial institutions, they often overlook the profound influence of psychological and non-economic variables. The paper posits that subjective well-being (happiness) and behavioral factors (attitudes, financial literacy, social norms) are pivotal yet underexplored drivers of financial decision-making. Specifically, the research seeks to understand the causal relationships between happiness, economic factors, and non-economic factors on an individual's willingness to save (WS) in financial institutions and their willingness to invest (WI) in the stock market. The study is situated within the context of Himachal Pradesh, India, aiming to provide empirical evidence from a developing economy where participation in formal financial markets remains uneven.

Methodology
The research employs a quantitative research design utilizing a cross-sectional survey approach.

Data Collection: Primary data was collected from 400 individual investors residing in the Hamirpur and Una districts of Himachal Pradesh between May and July 2023. The sample was selected using a non-probability convenience sampling technique, targeting working professionals, self-employed individuals, and business owners.
Instrumentation: A structured questionnaire was developed based on established behavioral finance frameworks (including the Theory of Planned Behavior and Life-Cycle Hypothesis). It comprised six sections: Economic Factors (10 items), Non-Economic Factors (11 items), Willingness to Save (6 items), Willingness to Invest (4 items), Happiness (4 items), and demographic details. Items were measured on a five-point Likert scale. The instrument was translated into Hindi and validated by academic experts to ensure cultural and linguistic accuracy.
Analytical Framework: The study utilized Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0. This method was chosen for its suitability in handling complex models with latent variables and smaller sample sizes.
Validation: The measurement model was assessed for reliability (Cronbach's alpha, Composite Reliability) and validity (Average Variance Extracted, Fornell-Larcker criterion for discriminant validity). The structural model was evaluated using bootstrapping (5,000 subsamples) to determine path coefficients, significance levels (t-values, p-values), effect sizes ( $f^2$ ), and model fit indices (SRMR, NFI).

Key Results
The structural equation modeling yielded the following significant findings:

Economic Factors:
- There is a significant positive relationship between economic factors (income, interest rates, institutional access) and the Willingness to Save (WS) in financial institutions ( $\beta = 0.635, p < 0.01$ ). This relationship explains a substantial portion of the variance in saving behavior ( $f^2 = 0.395$ ).
- Conversely, the relationship between economic factors and the Willingness to Invest (WI) in stocks was found to be insignificant ( $\beta = 0.078, p = 0.251$ ).
Non-Economic Factors:
- Non-economic factors (financial literacy, attitudes, social norms) show a significant positive relationship with Willingness to Invest (WI) ( $\beta = 0.540, p < 0.01$ ).
- These factors also significantly influence Willingness to Save (WS) ( $\beta = 0.188, p < 0.01$ ), though with a smaller effect size compared to economic factors.
Happiness:
- Contrary to some theoretical expectations, the study found no significant relationship between happiness and the Willingness to Invest ( $\beta = 0.038, p = 0.377$ ).
- Similarly, the relationship between happiness and the Willingness to Save was found to be insignificant ( $\beta = -0.005, p = 0.888$ ).
Model Performance:
- The model explains 63.3% of the variance in Willingness to Save ( $R^2 = 0.633$ ) and 35.4% of the variance in Willingness to Invest ( $R^2 = 0.354$ ).
- Model fit indices (SRMR = 0.074, NFI = 0.752) indicate an acceptable fit between the observed data and the theoretical model.

Key Contributions and Claims of Significance
The paper claims to make several foundational contributions to the understanding of investor behavior in India:

Integration of Behavioral and Economic Dimensions: The study successfully integrates economic and non-economic variables into a unified framework, demonstrating that while economic factors drive the capacity and willingness to save in formal institutions, non-economic factors (psychological and social) are the primary drivers of stock market participation.
Empirical Evidence on Happiness: The research provides empirical evidence that, within this specific demographic and regional context, subjective happiness does not significantly predict the willingness to save or invest. This challenges the notion that happiness is a direct, universal driver of financial risk-taking or accumulation, suggesting that other mediating variables may be at play.
Methodological Robustness: By employing PLS-SEM, the study offers a robust framework for assessing complex theoretical models in behavioral finance, moving beyond simple correlation to evaluate the simultaneous effects of multiple latent constructs.
Policy and Practical Implications: The findings suggest that to enhance financial inclusion and investment participation in developing economies, policymakers and financial institutions must look beyond traditional economic incentives. Strategies should focus on improving financial literacy, shaping positive saving attitudes, and leveraging social norms to encourage stock market participation.

Limitations and Scope
The authors maintain a modest stance regarding the generalizability of their findings. The study is limited to the Hamirpur and Una districts of Himachal Pradesh, which are characterized by higher literacy rates, and thus the results may not be fully representative of rural or less-educated populations across India. The use of convenience sampling and the exclusion of institutional investors further constrain the scope. The paper acknowledges that the "psychology of risk" showed no significant influence in this specific model and calls for future research to expand the demographic scope, incorporate additional variables (such as political and technological factors), and utilize experimental methods to deepen the understanding of investor behavior.

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