STSTEER

Derivation of Hicksian Demand from Expenditure Minimization

Deriving the compensated (Hicksian) demand for a good from a utility function and a target utility level.

Question template

As a portfolio manager striving to balance my client's wealth between stocks, commodities, and real estate, I employ the utility function: utility func, where x1 is the quantity of stocks, x2 is the quantity of commodities, and x3 is the quantity of real estate. Given the market prices for stocks (p_1), commodities (p_2), and real estate (p_3), I aim to ensure a utility level of at least utility level. Numbers in the options are rounded to two decimal places. What represents the compensated (Hicksian) demand for stocks in this scenario?

Use it

from datasets import load_dataset
ds = load_dataset("narunraman/steer_me", "deriving_hicksian_demand")