Labor & Health Economics Tutoring (Online Graduate Support for Los Angeles & San Francisco)

I provide online labor and health economics tutoring for graduate students in the Los Angeles and San Francisco Bay Area metros. I regularly work with graduate 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 Los Angeles or San Francisco.

Labor and health economics sit at the center of many graduate programs because they combine microeconomic theory, real policy questions, and empirical identification. Students often understand the intuition but struggle with formal modeling choices, interpreting empirical results, and writing defensible arguments about policy impacts without overstating causality.

I help you connect labor and health theory to data-driven evaluation. That can include labor supply/demand models, wage determination, human capital, discrimination frameworks, insurance markets, moral hazard, adverse selection, and policy evaluation designs such as difference-in-differences and instrumental variables.

Speak Directly With the Tutor

If you’re stuck on identification, unsure how to interpret coefficients, or trying to translate a labor/health policy question into a defensible model, reach out directly. You’ll speak with the tutor who works through the theory and empirical design with you.

Call/Text: 510-398-0006
Email: tutor@californiagraduatetutor.com

Speak Directly With the Tutor

What Labor & Health Economics Tutoring Covers

  • Labor economics theory: labor supply, labor demand, equilibrium, and elasticity
  • Human capital: education decisions, returns to schooling, and wage profiles
  • Wage determination: bargaining, compensating differentials, discrimination models
  • Policy analysis: minimum wage, EITC, unemployment insurance, paid leave
  • Health economics: health production, demand for care, utilization, outcomes
  • Insurance markets: moral hazard, adverse selection, risk pooling
  • Empirical methods: causal inference logic and program evaluation
  • Graduate writing: defensible assumptions, limitations, and interpretation

Core Labor & Health Frameworks (MathJax Standard)

Many applied labor and health economics papers begin with a reduced-form relationship:

\[ y_i = \beta_0 + \beta_1 x_i + \varepsilon_i \]

Here, \(y_i\) might represent wages, employment status, health utilization, or health outcomes, while \(x_i\) captures education, policy exposure, insurance coverage, or treatment assignment. The graduate-level question is whether \(\beta_1\) can be interpreted causally, and what assumptions are required for that interpretation.

Policy Evaluation: Difference-in-Differences (Conceptual)

A standard two-group, two-period difference-in-differences estimand is:

\[ \text{DiD} = (\bar{Y}_{T,1} – \bar{Y}_{T,0}) – (\bar{Y}_{C,1} – \bar{Y}_{C,0}) \]

We focus on how to argue for parallel trends, what can break it, and how to communicate limitations clearly.

Common Long-Tail Questions Graduate Students Ask

  • How do I interpret an elasticity in a labor supply model?
  • When should I use an IV strategy versus a DiD design?
  • How do I explain moral hazard versus adverse selection clearly?
  • How do I write about discrimination models without overstating conclusions?
  • How do I translate a policy question into a causal estimand?
  • How do I communicate identifying assumptions in a methods section?

A Graduate-Level Workflow

  1. Clarify the question: theory result, empirical estimate, or policy impact.
  2. Choose the framework: labor, health, insurance, or causal design.
  3. Define variables: outcome, exposure/treatment, timing, and controls.
  4. Check identification: selection, confounding, and assumptions.
  5. Estimate carefully: diagnostics, robustness, and sensitivity.
  6. Interpret responsibly: economic meaning and policy relevance.
  7. Write it up: clear assumptions, limitations, and conclusions.

Software Support

  • R: applied micro and health economics workflows
  • Stata: labor/health econometrics and post-estimation interpretation
  • SPSS: regression-based applied research workflows

Related Economics & Statistics Support

Need Help Making Labor or Health Results Defensible?

If you want a clear model, a defensible identification argument, and an explanation you can stand behind in a graduate class or research paper, reach out directly.

Call/Text: 510-398-0006   |   Email: tutor@californiagraduatetutor.com

Speak Directly With the Tutor