Looking at the figures, Long Beach is a region that forms a median price range within LA County.

According to Zillow, the median home price in Long Beach is around $780,000, with significant price variations between coastal and inland areas.

Calculating the data, with a 20% down payment, the loan principal would be $624,000, and the monthly principal and interest payment at a fixed rate of 6.75% for 30 years would be approximately $4,047. Applying California's property tax rate of about 1.1%, the monthly property tax is estimated at $715, and insurance costs around $133 per month, bringing the total housing cost to $4,896 per month.

Applying the DTI 28% rule, the required monthly income is about $17,484, which translates to an annual income of approximately $210,000. The median household income in LA County is reported to be around $80,000 according to census.gov, indicating a data gap of about 2.6 times.

Looking at the figures, coastal areas like Belmont Shore and Naples are more than double the median price, while inland areas like North Long Beach and West Long Beach are significantly lower, highlighting the disparity within the region. Actual listing prices show a wide distribution within the same city, ranging from the $400,000s to the $1.5 million range.

Compared to nearby Downey, Long Beach maintains a similar level, but is about 30-40% lower compared to high-priced areas like Irvine or Burbank. It is analyzed that port-related jobs and CSULB University support the local economy.

For dual-income households, each spouse would need to earn around $105,000 annually to reach the necessary threshold, which is slightly above the median income for LA County. Data suggests that dual-income households with stable port-related jobs fall within an accessible range.

In conclusion, while Long Beach offers opportunities for households close to the median income if they choose inland areas, significantly higher incomes are required for coastal regions. It is deemed a reasonable strategy to clearly define budget and desired living areas before narrowing down the options based on data.