UNITED STATES: In an era where economic disparity dominates global discourse, understanding the roots of inequality has become more crucial than ever. Swapnil Landge, a doctoral candidate in Economics at The Graduate Center, City University of New York (CUNY), is at the forefront of a research movement combining machine learning with labor economics to address this challenge. His groundbreaking research dives deep into the mechanisms of intergenerational mobility, exploring how the intangible transmission of skills and preferences—particularly those shaped by parental occupations—can condition the economic futures of children.
Using AI to Decode Economic Outcomes
Landge’s most recent work, “AI and Machine Learning Approaches for Identifying Parental Occupational Skills That Shape Children’s Career Choices,” represents a landmark in how economics is studied in the age of data science. Leveraging the predictive power of artificial intelligence, his research decodes how specific occupational skills are passed down—often unconsciously—from parents to children, influencing not just their career choices but also their earning potential.
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Rather than focusing solely on tangible factors like wealth and education, Landge’s model accounts for intangible transmissions: the everyday exposure to skills and professions children inherit merely by living in households with parents from particular occupational backgrounds. “If your father is a plumber, you’ll likely pick up plumbing skills. If your mother is a teacher, pedagogical communication may come naturally,” he explains.
This subtle but powerful transfer, often overlooked in traditional economic models, can help explain persistent patterns of occupational inheritance and, more critically, their connection to broader trends in income inequality.
Intergenerational Mobility and the Persistence of Inequality
At the heart of Landge’s research lies a central question: Why does inequality persist across generations? His other pivotal work, “Legacy of Labor: The Impact of Parental Jobs on Children’s Career Choices and Income Inequality,” builds a self-selection model to answer this. Using large-scale datasets, the study identifies individuals who enter the same occupations as their parents and evaluates whether such decisions result in positive or negative economic outcomes.
“Negative self-selection is a key concept here,” Landge notes. “It refers to individuals who, by following their parents’ professions, actually forgo better economic opportunities elsewhere. Understanding why they make these choices is critical for designing policies that can promote true meritocracy.”
These insights hold significant policy implications. If a large segment of the population is ‘stuck’ in parental occupations due to social, educational, or psychological barriers, it signals a low-mobility society—one where inequality is not just an outcome but a deeply rooted process.
A Scholarly Voice in a Growing Field
Landge’s findings have drawn attention beyond academic circles. His paper “Parents, Paths, and Paychecks,” soon to be published in the Journal of Business and Economic Studies, introduces transition matrices to map intergenerational occupational flows. The paper breaks new ground by quantifying how children of different socioeconomic backgrounds navigate (or fail to navigate) occupational hierarchies.
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His work has been presented at top-tier academic forums, including the Population Association of America, the Midwest Economics Association, and the IIIS/LIS Comparative Economic Inequality Conference in Luxembourg. He has also been honored with several fellowships, such as the CUNY Dissertation Fellowship and the Stone Center Junior Scholarship, and recognized as a Student Ambassador by the Association for Public Policy Analysis and Management (APPAM).
Teaching with Purpose
In parallel with his research, Landge is also an influential educator. He has taught Microeconomics, Business Statistics, and Labor Economics at Baruch College and Brooklyn College, bringing theoretical rigor and real-world relevance to his classrooms. His earlier career as a project manager with multinational giants like Procter & Gamble and Robert Bosch gives him a practical lens, helping students connect abstract theories to business realities.
“Teaching economics isn’t just about graphs and equations,” he says. “It’s about giving students tools to understand the world—and maybe even change it.”
The Influences Shaping Swapnil Landge’s Work
Landge’s passion for intergenerational mobility is deeply personal. Born in India, he grew up with a keen awareness of how the caste system historically dictated one’s professional and social fate. “If your parents were from a lower caste, you inherited not just their socioeconomic status but their occupation too,” he recalls. “That lack of mobility—though officially outlawed—still lingers in subtle ways.”
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This background inspired Landge to look beyond the obvious. While most intergenerational mobility research emphasizes quantifiable factors like income and education, Landge took a different path, focusing instead on the intangible elements—the soft skills, values, and occupational exposure that influence children’s decisions long before they choose a college major or apply for a job.
Theoretical Innovation Meets Policy Relevance
Working closely with his advisor, Stone Center Senior Scholar Miles Corak—renowned for his work on intergenerational mobility—Landge has developed a nuanced theoretical framework. His models go beyond binary outcomes and measure degrees of occupational alignment and deviation. They also test how career decisions correlate with hypothetical earnings in alternative career paths.
This allows Landge to assess how many individuals might be economically better off in different careers but remain in family occupations due to social pressures or lack of exposure. In doing so, he makes a compelling case for rethinking how society supports career guidance, vocational training, and public education.
“There’s a policy message in all of this,” he says. “If we want to address inequality, we have to start by expanding opportunity—not just by redistributing income, but by breaking occupational silos and giving young people the tools and exposure to pursue a broader range of careers.”
With his unique blend of empirical rigor and personal insight, Swapnil Landge is fast becoming a leading voice in economics, education, and social mobility. As inequality continues to dominate public debate, his research offers a powerful reminder: the roots of inequality often lie not in what we inherit financially, but in what we absorb culturally and skillfully—long before our first paycheck.
For policymakers, educators, and scholars alike, Landge’s work offers both a diagnosis and a roadmap. It challenges institutions to look beyond wealth and education when crafting interventions and to consider the deeply embedded occupational pathways that shape our economic futures.
In a world increasingly defined by automation, rapid economic shifts, and widening income gaps, the insights of researchers like Swapnil Landge are more than academic—they are essential. By blending the power of AI with the depth of economic theory, Landge is not only redefining how we study inequality but also how we might finally begin to solve it.
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