College Major Earnings Comparison Calculator

How this calculator helps with a major decision

Choosing a college major is never only about money, but money is still part of the picture. Students often compare majors because they are trying to balance several goals at once: interest in the subject, likelihood of finding good work, flexibility after graduation, and the ability to earn enough over time. This calculator focuses on one narrow part of that decision: projected earnings. It does not tell you what you should study. Instead, it helps you quantify one tradeoff so you can think more clearly about it.

The important idea is that salary is not just a single number. A major with a high first-year salary may stay ahead for decades, but a major with a lower starting point can sometimes catch up if raises and promotions happen faster. That is why this page asks for both a starting salary and an annual growth rate. A fair comparison needs both. The third input, career length, matters just as much because compounding needs time. A ten-year horizon can favor a different path than a thirty-five-year horizon.

Used well, the calculator becomes a scenario tool rather than a prediction machine. You can run a cautious case, a baseline case, and an optimistic case. You can model a shorter career, a career with slower advancement, or one where a technical major starts higher but a people-facing major grows more steadily. That habit of testing assumptions is usually more valuable than any one output number.

What each input means in plain language

Starting salary ($) is the annual pay you expect near the beginning of your full-time career in that major. For many people, this means the first year after graduation in a typical entry-level role. If you are comparing majors using public salary surveys, try to use figures from similar sources and the same geography. A salary pulled from a high-cost city is not directly comparable to a salary taken from a national median unless you adjust for that difference elsewhere.

Annual growth rate (%) is your estimate of how that salary changes from year to year. In practical terms, this rate rolls together normal raises, promotions, movement into better-paying specialties, and career progression. If one major tends to start lower but has stronger long-run upside, that shows up here. Enter the rate as a percentage, so 3.5 means 3.5% per year, not 0.035. The calculator converts that percentage internally before doing the math.

Career length (years) is the number of working years you want to model. This is not your age, and it is not necessarily the time until retirement in a formal sense. It is simply the window over which you want to add up earnings. A student planning to work from age 22 to age 57 might choose 35 years. Someone thinking about a shorter planning window, perhaps because they may return to school later, could use 10 or 15 years instead.

All three inputs should be read in annual terms. Starting salary is annual pay in dollars. Growth rate is annual percentage growth. Career length is annual count of years. Keeping the units consistent is what makes the output meaningful. If you compare two majors with a monthly salary estimate for one and an annual salary estimate for the other, the result will look precise but mean almost nothing.

It also helps to remember what this calculator is not measuring. It does not know whether one major requires graduate school, whether you will switch industries, whether you may work part time for a period, or whether one path comes with much higher debt. Those factors can be extremely important. This tool simply isolates earnings growth so you can see that one piece clearly before layering on everything else.

How the calculator turns the inputs into lifetime earnings

The calculation assumes each major starts at a first-year salary and then grows by the same percentage each year. In other words, the salary path is treated like a compounding sequence. That makes the comparison easy to inspect: you can see how much of the outcome is coming from the first salary level and how much is coming from the growth assumption.

The general idea behind many calculators can be expressed as a result R that depends on several inputs. The existing MathML below states that relationship in a very broad way, and it remains correct here because lifetime earnings are still just a function of the values you enter:

This specific calculator uses a more concrete version of that idea. If a major begins with salary S, grows by annual rate g, and lasts for n years, then total modeled earnings are the sum of each year's salary. That is a geometric series, which can be written compactly like this:

When the growth rate is greater than zero, the sum simplifies to the closed-form expression used by the calculator's JavaScript. When the growth rate is zero, the model falls back to a simple multiplication:

The weighted-sum MathML block below is also preserved from the original page. While it is a generic expression, it is still useful as a reminder that many real decisions depend on combining several factors. In a larger planning model, tuition, debt, taxes, or cost of living could be added as extra weighted components even though this calculator intentionally keeps the earnings model simple:

The biggest insight from the formula is simple: higher growth matters more as the time horizon gets longer. If the gap in starting salary is modest, a faster-growing career path can eventually overtake a slower one. If the gap in starting salary is huge, the higher starter may stay ahead even when the other major has stronger raises. That is exactly why changing the years field can be so revealing.

Worked example using the default values

Suppose Major 1 starts at $65,000 and grows at 3.5% per year, while Major 2 starts at $48,000 and grows at 4.2% per year. If you model a 35-year career, the calculator estimates roughly $4.34 million in lifetime earnings for Major 1 and about $3.68 million for Major 2. In this setup, Major 1 stays ahead because the starting salary advantage is large enough that the faster raise in Major 2 does not fully erase the gap over the chosen horizon.

That example is useful because it shows how not to overreact to a single rate. A higher annual growth rate sounds powerful, and it is powerful, but the rate operates on the salary level you start from. A lower salary growing faster does not automatically win. The size of the salary gap, the size of the growth gap, and the number of years all work together. Changing only one of those can change the story.

You can also use the same pair of majors across different planning horizons to see why timing matters. Over 10 years, Major 1 still leads by a wide margin because early salaries dominate. Over 20 years, the faster growth in Major 2 narrows the gap somewhat. Over 35 years, growth has had much more time to compound, but in this particular example the higher starting salary of Major 1 remains strong enough to keep the lead.

When you run your own numbers below, try changing only one field at a time. First hold career length steady and adjust the growth rates. Then keep the rates fixed and shorten or lengthen the career. That step-by-step approach makes it much easier to understand which assumption is actually moving the result.

How to interpret the result without overreading it

The main result tells you the modeled lifetime earnings for each major over the selected number of years. The summary table also reports an average annual salary, which is simply total modeled earnings divided by career length. That average is helpful when the lifetime totals feel abstract. It gives you a quick sense of the salary level implied by the full path.

If one major leads by a huge amount, the financial difference is meaningful and worth noticing. If the totals are very close, the practical conclusion may be that money alone should not decide the choice. In close cases, fit, persistence, graduation likelihood, graduate school plans, work-life balance, and debt can matter more than the small difference on the screen. A result that is only a few percent apart is often better treated as "roughly similar" than as a dramatic winner.

The scenario table below the result helps with that interpretation. It automatically compares a conservative case, the exact values you entered, and an accelerated-growth case by shifting each growth rate up or down by one percentage point. That is not a forecast of the future. It is a stress test. If one major only wins under very optimistic assumptions, you should recognize that fragility before making the decision feel settled.

Assumptions and limits you should keep in mind

This calculator intentionally uses a clean earnings model so the comparison stays understandable. That simplicity is useful, but it comes with limits. The output is best read as a structured estimate, not as a promise about your real career. Different industries, cities, graduate programs, and economic cycles can change the path substantially.

• Constant growth: each major is modeled with a steady annual growth rate. Real careers often have uneven raises, plateaus, promotions, and occasional setbacks.
• Nominal dollars: the calculator does not adjust for inflation, so the totals are nominal future earnings rather than inflation-adjusted purchasing power.
• No taxes or debt: taxes, tuition, student loan payments, and graduate school costs are excluded even though they can change take-home outcomes materially.
• No employment gaps: the calculation assumes uninterrupted earnings over the selected years. Career breaks, unemployment, internships, or part-time periods are not included.
• No regional adjustment: salaries in different cities may not be directly comparable once rent and living costs are considered.

A good way to use the calculator is to pair it with judgment. If one major produces slightly lower modeled earnings but aligns much better with your strengths and increases your chance of actually finishing the degree, that may still be the wiser path. On the other hand, if two majors feel equally appealing and one shows a durable financial advantage across conservative and optimistic scenarios, that is useful evidence too.

In short, treat the tool as a disciplined way to ask, "What would have to be true for one major to pull ahead?" That question is much more practical than searching for a single perfect answer. Run a few cases, compare the direction of the changes, and use the numbers as one informed input in a broader decision.