Editing Behavioral economics (section)

=====Labor markets=====

Labor markets differ substantially in the Global South compared to high-income countries because of higher rates of informal employment, self-employment and casual labor. For instance, an experiment that randomly assigned workers to industrial jobs in Ethiopia found that workers quickly quit or move to different sectors.<ref>Blattman, Christopher and Stefan Dercon. The impacts of industrial and entrepreneurial work on income and health: Experimental evidence from Ethiopia. American Economic Journal: Applied Economics, l0(3):l-38, 2018.</ref> This low preference for full-time jobs is driven by unpredictable demands on one’s time where workers prefer flexibility to be able to meet family demands. On the other hand, US workers show little valuation of work hours flexibility.<ref>Mas, Alexandre and Amanda Pallais. Valuing alternative work arrangements. American Economic Review, l07(l2):3722-59, 2017.</ref> Given less formal contracts and fixed schedules, workers are more prone to behavioral biases. Self-control problems are especially relevant in labor markets. For instance, many low-income workers in India are inebriated on the job because they are self-employed.<ref>Schilbach, F. (2019). Alcohol and self-control: A field experiment in India. American economic review, 109(4), 1290-1322.</ref> Without external monitoring or standardized hours, self-employed individuals must rely on internal discipline, which is often limited. Evidence from Indian data-entry workers shows that many voluntarily opt into contracts that penalize them for underperformance—known as dominated contracts—in order to commit themselves to working harder.<ref>Kaur, Supreet, Michael Kremer, and Sendhil Mullainathan. Self-control at work. Journal of Political Economy, l23(6):l227-l277, 2015.</ref> This suggests that workers are aware of their own time-inconsistency and use commitment mechanisms to increase productivity. Additionally, many workers engage in income-targeting behavior, adjusting labor supply based on daily financial needs rather than wage levels. For example, bicycle-taxi drivers in Kenya work longer when they have specific cash needs but do not reduce labor supply when given cash in the morning, indicating reference-dependent preferences focused on earned income.<ref>Pascaline Dupas, Jonathan Robinson, Santiago Saavedra,
The daily grind: Cash needs and labor supply,
Journal of Economic Behavior & Organization,
Volume 177,
2020,
Pages 399-414,
ISSN 0167-2681,
https://doi.org/10.1016/j.jebo.2020.06.017.</ref>

Behavioral frictions also extend to the workplace environment. While noise and heat are common in urban areas of the Global South, workers often underestimate how these factors affect their productivity, reflecting [[bounded rationality]]. In Kenya, exposure to moderate increases in noise significantly reduced textile output, yet workers were unaware of the impact and unwilling to pay for quieter conditions even when earnings depended on output.<ref>Dean, Joshua T. 2024. "Noise, Cognitive Function, and Worker Productivity." ''American Economic Journal: Applied Economics'' 16 (4): 322–60.
DOI: 10.1257/app.20220532</ref> Similar results are found for heat exposure in Indian factories, where temperature reductions improved output but were only implemented to save energy, not to boost productivity.<ref>Achyuta Adhvaryu, Namrata Kala, Anant Nyshadham; The Light and the Heat: Productivity Co-Benefits of Energy-Saving Technology. ''The Review of Economics and Statistics'' 2020; 102 (4): 779–792. doi: https://doi.org/10.1162/rest_a_00886</ref> These findings show that misperceptions about environmental effects on work performance can lead to suboptimal decisions by both workers and firms.

Wage-setting also reflects behavioral elements. In informal labor markets, wage rigidity persists despite the absence of formal institutions like unions. In Indian agriculture, wages rise with positive productivity shocks but are rarely reduced when shocks are negative, due to fairness concerns and social norms.<ref>Kaur, Supreet. (2019) Nominal Wage Rigidity in Village Labor Markets. ''American Economic Review'',  109 (10): 3585–3616. https://doi.org/10.1257/aer.20141625</ref> Similarly, low-wage offers are accepted more often when made privately rather than publicly, as workers face social pressure to reject “unfair” wages in public settings.<ref>Breza, Emily, Supreet Kaur, and Nandita Krishnaswamy. 
 Coordination without Organization: Collective Labor Supply in Decentralized Spot Markets. Working Paper. 2018.</ref> Furthermore, even small wage differences within work teams can reduce attendance and productivity, not only among lower-paid workers but also among those paid more, indicating that inequality itself demotivates workers through social comparison.<ref>Breza, Emily, Supreet Kaur, and Yogita Shamdasani. The morale effects of pay inequality. ''Quarterly Journal of Economics'', l33(2):6ll-663, 2018.</ref>

Behavioral constraints are also relevant for female labor-force participation (FLFP), which remains low in many developing countries. Psychological factors such as low [[self-efficacy]] and misperceptions about social norms contribute to this. In India, an intervention to raise self-efficacy significantly increased women’s employment,<ref>McKelway, Madeline. Women’s self-efficacy and women’s employment: Experimental evidence from India. Working Paper. 2018.</ref> while in Saudi Arabia, correcting men’s beliefs about their peers’ support for women working outside the home led to greater spousal support for job-seeking.<ref>Bursztyn, L., González, A. L., & Yanagizawa-Drott, D. (October 2020). Misperceived social norms: Female labor force participation in Saudi Arabia. ''American Economic Review''. 110 (10): 2997–3029. https://doi.org/10.1257/aer.20180975</ref> These findings show how behavioral interventions can shift labor supply decisions, particularly for marginalized groups.