B.A. Financial and Quantitative Economics candidate at CSU Chico with expertise in econometrics, statistical modeling, and economic forecasting. Specializing in Phillips Curve analysis and macroeconomic research.
I am Rowan Morkner, an Economics major with a Data Science certificate at California State University, Chico, passionate about applying economic theory, data analysis, and programming to solve complex business and regulatory challenges. My research focuses on econometric modeling, Phillips Curve analysis, and macroeconomic forecasting.
My professional experience spans from data science consulting at the Wildcat Data Hub to financial analysis at Ansil Investments, where I've developed expertise in econometric modeling, statistical analysis, and quantitative research using R, Python, and Stata.
A collection of my academic research in economics, econometrics, and forecasting
Interactive decision support tool for Central California rice growers comparing profitability of growing rice vs. fallowing and selling water rights. Integrates real-world data from NRCS SNOTEL stations, USDA price data, and CA DWR land use mapping with breakeven analysis, sensitivity modeling, and spatial visualization of 20,000+ rice fields.
This paper reviews the history and limits of economic forecasting, from the Phillips Curve to the Lucas Critique and modern DSGE and machine learning models. It argues that while forecasting guides policy, the complexity of economies and unexpected shocks make long-term accuracy inherently uncertain
This paper analyzes different versions of the Phillips Curve, comparing simple, expectation-augmented, and lagged models. Results show that basic models explain little, while adding expectations and lags captures the dynamic link between unemployment and inflation more effectively, offering insights into policy and forecasting.
This project estimates income inequality in the U.S. using household census data. By fitting a Lorenz curve with nonlinear regression and integrating the result, the Gini coefficient is calculated at about 0.42. The study demonstrates both computational and manual methods, illustrating how inequality can be quantified with statistical modeling.
Interested in discussing research opportunities or economic consulting roles
CSU Chico - B.A. Financial and Quantitative Economics
Data Science Certificate Program
Intern Data Science Consultant - Wildcat Data Hub
Economics Tutor - Chico State Economics Department