I provide online behavioral economics tutoring for graduate students in the Los Angeles and San Francisco Bay Area metros. I regularly work with students from programs at UCLA, USC, UC Irvine, and Caltech, as well as UC Berkeley, Stanford University, UC San Francisco (UCSF), and other UC and private universities. All tutoring is delivered online; I do not maintain a physical office in these cities.
Behavioral economics combines economic theory, psychology, and empirical methods to explain decision-making that deviates from classical rational-choice models. At the graduate level, students often struggle with translating behavioral concepts into formal models, understanding experimental design, and interpreting empirical results without overstating claims.
I help you connect theory to evidence. That includes understanding behavioral preferences, modeling bounded rationality, designing or analyzing experiments, and writing results that meet graduate standards in economics, public policy, and applied social science programs.
Speak Directly With the Tutor
If behavioral models feel intuitive but hard to formalize—or your empirical results are difficult to explain—reach out directly. You’ll speak with the tutor who works through the theory and data with you.
Call/Text: 510-398-0006
Email: tutor@californiagraduatetutor.com
What Behavioral Economics Tutoring Covers
- Foundations of behavioral economics
- Bounded rationality and heuristics
- Prospect theory and reference dependence
- Time inconsistency and present bias
- Risk, uncertainty, and loss aversion
- Social preferences: fairness, altruism, reciprocity
- Behavioral game theory
- Experimental and quasi-experimental methods
- Behavioral policy and program evaluation
Core Behavioral Models (MathJax Standard)
In expected utility theory, individuals maximize:
\[ \mathbb{E}[U] = \sum_{i} p_i \, u(x_i) \]
Prospect theory modifies this framework by introducing a value function defined over gains and losses relative to a reference point:
\[ V = \sum_i \pi(p_i) \, v(x_i – r) \]
where \(r\) is the reference point and \(\pi(\cdot)\) is a probability weighting function. We focus on how these assumptions change predictions and how they are tested empirically in graduate-level research.
Empirical Behavioral Economics
Many graduate courses emphasize empirical behavioral economics, including lab experiments, field experiments, and observational data analysis. I help students understand:
- Experimental design and randomization
- Identifying behavioral treatment effects
- Interpreting treatment heterogeneity
- Behavioral mechanisms vs reduced-form results
- Ethical and external validity considerations
A Graduate-Level Behavioral Economics Workflow
- Clarify the behavioral mechanism of interest
- Translate intuition into a formal model
- Design or evaluate an experiment
- Estimate behavioral effects carefully
- Check robustness and alternative explanations
- Interpret results without overclaiming
- Write theory and empirical sections clearly
Related Economics & Statistics Support
Need Help Making Behavioral Results Make Sense?
If you want help connecting behavioral theory to data—and explaining results clearly at a graduate level—reach out directly.
Call/Text: 510-398-0006 | Email: tutor@californiagraduatetutor.com