# MBA Decision and ROI Analysis: [Your name]

> A decision workbook for anyone asking "should I do an MBA, and which format?" It treats the degree as an
> investment: it values the earnings uplift with net present value (NPV), finds the internal rate of return
> (IRR) and the payback period, prices the opportunity cost of the salary you give up, and tests every
> assumption with sensitivity and scenario tables. It then puts the money answer next to the non-financial
> reasons, because most good MBA decisions rest on both. Source basis: standard capital-budgeting practice
> (Fisher 1930), human-capital theory (Becker 1964, Mincer 1974), signalling theory (Spence 1973) and the
> evidence on MBA returns (Arcidiacono, Cooley and Hussey 2008), plus dated facts from GMAC and US federal
> student aid sources checked in October 2026. Replace every [bracketed] value and every row marked *Example*.
> This is a planning aid, not admissions, legal, tax or financial advice.

<!--
Guidance: How to use this template
- Work in this order: section 1 (why you are asking), section 3 (your two paths in words), section 4 (numbers),
  section 5 (stress tests), section 7 (non-financial factors), section 9 (decision record). The numbers are
  not the decision; they tell you what you must believe for the MBA to pay.
- Keep one spreadsheet next to this document. Every formula below is written for Excel (Google Sheets and
  LibreOffice use the same names). Column letters match the layout in section 4.2.
- Use after-tax money throughout, and compare the MBA path with the realistic path you would follow without
  the degree, not with standing still.
- Every number in the worked example belongs to Lena Varga, a fictional product manager. They were computed in
  Python (numpy_financial) and cross-checked with an Excel formula engine. Replace them with your own.
- Related templates: mba/mba-funding-scholarship-plan (how to pay), mba/mba-budget-during-program (monthly
  cash plan), mba/mba-loan-repayment-plan (after graduation), mba/mba-program-comparison and
  mba/mba-school-list-strategy (which schools), mba/mba-npv-irr-card (the theory behind section 4),
  mba/mba-readiness-self-assessment, mba/mba-admit-decision (choosing between offers), finance/investment-appraisal,
  career/offer-comparison, personal/financial-plan and personal/decision-journal.
-->

## Document control

<!-- Guidance: This is a personal workbook. Record which version of your assumptions a decision used, so you can explain it later to a partner, sponsor or yourself. -->

| Field | Value |
|---|---|
| Document ID | [ROI-001] |
| Version | [0.1] |
| Status | [Draft / Reviewed / Decision taken] |
| Owner | [Your name] |
| Reviewed by | [Mentor, partner or financial professional you consulted] |
| Last updated | YYYY-MM-DD |
| Classification | Personal, confidential |
| Decision deadline | [YYYY-MM-DD, for example the first application round you are considering] |
| Spreadsheet file | [File name and location] |
| Currency and price basis | [USD, nominal amounts] |

## Contents

1. Purpose and the decision question
2. The decision process
3. Define the two paths
4. Financial model: NPV, IRR, payback and opportunity cost
5. Sensitivity and scenarios
6. Programme format options
7. Non-financial factors
8. Dated facts that affect the numbers
9. Decision record and timeline
10. Quality checklist and common mistakes

## 1. Purpose and the decision question

<!-- Guidance: Write the question you are actually answering. "Is an MBA worth it?" is too vague to analyse. "Does a two-year full-time MBA starting in [year] beat staying in my current track, given my goal of [goal]?" can be analysed. -->

An MBA is one of the largest single investments most people make after buying a home. For a two-year full-time
programme the cost has two parts of similar size: the money you pay (tuition, fees, relocation, extra living
costs) and the money you do not earn (two years of salary and the raises you would have received). The return is
also uncertain and arrives over decades, which is exactly the problem capital budgeting was built to solve:
bring every cash flow to one point in time with a discount rate, then ask whether the present value of what you
gain exceeds the present value of what you give up (Fisher 1930).

Two economic theories explain why the degree might raise pay, and they lead to different questions. Human-capital
theory (Becker 1964; Mincer 1974) says education raises productivity, so the uplift reflects skills you acquire:
ask what you will be able to do afterwards that you cannot do now. Signalling theory (Spence 1973) says the degree
mostly certifies ability that already existed, so the uplift reflects access to employers who screen on the
credential: ask whether the recruiters you want hire mainly through MBA programmes. Both effects are real, and
the evidence on MBA earnings suggests the raw salary gap overstates the causal return because people who enrol
differ from those who do not. Arcidiacono, Cooley and Hussey (2008) found that controlling for individual
differences generally reduced the estimated return, most of all at top programmes (full-time programmes outside the
top 25 were the exception in their data). Treat published "average salary uplift" figures as an upper bound for your
own case.

Write your decision question:

| Item | Your answer |
|---|---|
| Decision question | [Does a two-year full-time MBA starting in YYYY beat my realistic no-MBA path?] |
| Goal the MBA serves | [Career switch to X / acceleration in current function / entrepreneurship / international move] |
| Could the goal be reached without the degree? | [Yes, by ... / Partly / No, because ...] |
| Formats under consideration | [Two-year full-time / one-year full-time / part-time / executive MBA / online] |
| What would change your mind | [For example: post-MBA salary below USD 140,000, no scholarship, partner cannot relocate] |
| *Example* Lena Varga | Does a two-year full-time MBA beat staying a senior product manager, given a goal of moving into general management at a growth-stage technology company? |

## 2. The decision process

<!-- Guidance: Follow the loop. Most people stop after the first NPV; the value comes from the second and third passes, where you test the assumptions and add the non-financial factors. -->

```mermaid
flowchart TD
    A["Write the decision question"] --> B["Describe the no-MBA path and the MBA path"]
    B --> C["Estimate cash flows: costs, forgone salary, uplift"]
    C --> D["Compute NPV, IRR, payback"]
    D --> E["Sensitivity and scenarios"]
    E --> F{"Does the MBA pay under realistic assumptions?"}
    F -- "Yes" --> G["Score non-financial factors"]
    F -- "Only under optimistic ones" --> H["Change the plan: format, school, funding, goal"]
    H --> C
    F -- "No" --> I["Record why, revisit in 12 months"]
    G --> J{"Do the non-financial factors support it?"}
    J -- "Yes" --> K["Decision record and application plan"]
    J -- "No" --> I
```

The loop matters because the first model always contains optimistic numbers. Changing the plan (a one-year
programme, a school with a better scholarship, employer sponsorship, a part-time format) is often what turns a
marginal NPV into a clear one.

## 3. Define the two paths

<!-- Guidance: Describe each path in words before you put numbers on it. Name the job, employer type, city and likely title for each year. If you cannot describe the no-MBA path, you cannot price the opportunity cost. -->

The analysis compares two futures, not "MBA" against "nothing". The no-MBA path is your realistic career if you
do not apply: promotions, job changes and raises included. The MBA path is your realistic career with the
degree: the programme years, the summer internship, the first post-MBA job and the years after it. Only the
difference between the two paths is the return on the MBA. This is the incremental cash flow principle used in
any project appraisal: include only cash flows that change because of the decision.

| Year | No-MBA path (words) | MBA path (words) |
|---|---|---|
| 1 | [Current role, expected raise] | [Programme year 1, summer internship] |
| 2 | [Possible promotion] | [Programme year 2] |
| 3 | [Role] | [First post-MBA role, signing bonus] |
| 4 to 12 | [Trajectory] | [Trajectory] |
| *Example* 1 | Senior PM at a mid-size software company, 3% raise | Year 1 of a two-year programme, 10-week internship at a growth-stage firm |
| *Example* 3 | Senior PM, possible group PM title | Post-MBA role in a strategy and operations team, USD 30,000 signing bonus |

What to include and exclude:

- **Include** tuition and mandatory fees, health insurance only to the extent it exceeds what your employer pays
  today, books and case materials, relocation, required travel, the internship salary, forgone salary and
  forgone employer retirement contributions, signing bonuses, and the post-MBA salary path.
- **Exclude** living costs you would pay on either path (rent, food). Include only the difference, for example a
  more expensive city.
- **Exclude** sunk costs: test fees and application fees already paid do not change the decision.
- **Use after-tax amounts.** Salary differences are taxed; tuition usually is not deductible for a full-time
  student, and rules differ by country. Use a single effective tax rate for a first pass and refine it with a
  tax professional if the decision is close.

## 4. Financial model: NPV, IRR, payback and opportunity cost

<!-- Guidance: Build the spreadsheet in section 4.2 exactly, then replace the Example inputs. Keep inputs in one block so the sensitivity tables can point to them. -->

### 4.1 Formulas

The incremental after-tax cash flow in year $t$ is

$$
\Delta CF_t = (1-\tau)\left(W^{M}_t - W^{B}_t\right) - D_t
$$

and the decision measures are

$$
NPV = \sum_{t=1}^{T} \frac{\Delta CF_t}{(1+r)^t}, \qquad 0 = \sum_{t=1}^{T} \frac{\Delta CF_t}{(1+IRR)^t}
$$

| Symbol | Meaning | *Example* value |
|---|---|---|
| $W^{B}_t$ | Pre-tax earnings on the no-MBA path in year $t$ | $95{,}000 \times 1.03^t$ |
| $W^{M}_t$ | Pre-tax earnings on the MBA path in year $t$ (internship, salary, bonus) | see table 4.3 |
| $D_t$ | Direct costs of the programme in year $t$ (tuition, fees, relocation) | 97,000 and 91,000 |
| $\tau$ | Effective tax rate on the earnings difference | 0.28 |
| $r$ | Personal discount rate (your opportunity cost of capital) | 0.06 |
| $T$ | Horizon in years (programme years plus post-MBA years modelled) | 12 |
| $IRR$ | Discount rate at which NPV equals zero | computed |

Assumptions and limits. All cash flows are placed at the end of each year, which is what Excel's `=NPV` assumes
(it discounts the first value by one period). If you want exact dates, list each cash flow with its date and use
`=XNPV(rate, values, dates)` and `=XIRR(values, dates)`. The discount rate is personal: a reasonable range is the
after-tax interest rate on the money you will borrow at the low end and the expected return on a diversified
portfolio you would otherwise hold at the high end. IRR has a unique value only when the cash flows change sign
once (outflows first, then inflows), which is the normal shape here; if a later year turns negative (for example a
planned second degree), rely on NPV.

### 4.2 Spreadsheet layout

| Column | Content | Formula in row 2 (copy down to row 13) |
|---|---|---|
| A | Year $t$ | 1 to 12 |
| B | No-MBA earnings | `=$I$2*(1+$I$3)^A2` with I2 = 95,000 and I3 = 3% |
| C | MBA-path earnings | internship in year 1, 0 in year 2, then `=$I$4*(1+$I$5)^(A2-3)` from year 3 (row 4), plus the signing bonus in year 3 only |
| D | Direct costs | tuition plus fees, plus relocation in year 1, then 0 |
| E | Incremental after-tax cash flow | `=(C2-B2)*(1-$I$6)-D2` with I6 = 28% |
| F | Cumulative cash flow | `=SUM($E$2:E2)` |
| G | Discounted cash flow | `=E2/(1+$I$7)^A2` with I7 = 6% |
| H | Cumulative discounted | `=SUM($G$2:G2)` |

Summary cells: NPV `=NPV($I$7,E2:E13)` (no time-0 cash flow here, because every flow is placed at a year end);
IRR `=IRR(E2:E13)`; payback year `=MATCH(TRUE,INDEX(F2:F13>=0,0),0)` (returns 10, the first year the cumulative total
turns positive; the fractional payback is the previous year plus the remaining shortfall divided by that year's cash
flow, as in 4.3); break-even post-MBA salary with Data, What-If Analysis, Goal Seek (set the NPV cell to 0 by changing I4).

### 4.3 Worked example A: Lena Varga, two-year full-time programme (fully solved)

Inputs (*Example*): current salary USD 95,000 rising 3% a year; tuition USD 82,000 a year; fees, books and extra
health insurance USD 9,000 a year; relocation USD 6,000 in year 1; summer internship USD 28,000; post-MBA base
salary USD 150,000 in year 3 rising 4% a year; signing bonus USD 30,000 in year 3; tax rate 28%; discount rate 6%;
ten post-MBA years modelled.

| Year *(Example)* | No-MBA earnings | MBA-path earnings | Direct costs | Incremental cash flow | Cumulative |
|---|---|---|---|---|---|
| 1 | 97,850 | 28,000 | 97,000 | -147,292 | -147,292 |
| 2 | 100,786 | 0 | 91,000 | -163,566 | -310,858 |
| 3 | 103,809 | 180,000 | 0 | 54,857 | -256,000 |
| 4 | 106,923 | 156,000 | 0 | 35,335 | -220,665 |
| 5 | 110,131 | 162,240 | 0 | 37,518 | -183,146 |
| 6 | 113,435 | 168,730 | 0 | 39,812 | -143,334 |
| 7 | 116,838 | 175,479 | 0 | 42,221 | -101,113 |
| 8 | 120,343 | 182,498 | 0 | 44,751 | -56,362 |
| 9 | 123,953 | 189,798 | 0 | 47,408 | -8,954 |
| 10 | 127,672 | 197,390 | 0 | 50,197 | 41,243 |
| 11 | 131,502 | 205,285 | 0 | 53,124 | 94,367 |
| 12 | 135,447 | 213,497 | 0 | 56,196 | 150,563 |

Check one row by hand. Year 1: $(28{,}000 - 97{,}850) \times 0.72 - 97{,}000 = -50{,}292 - 97{,}000 = -147{,}292$.
Year 3 includes the bonus: $(180{,}000 - 103{,}809) \times 0.72 = 54{,}857$.

Results:

| Measure | Value | Excel formula |
|---|---|---|
| Total economic investment (years 1 and 2) | USD 310,858 | `=-SUM(E2:E3)` |
| of which forgone salary after tax | USD 143,018 | `=(B2+B3)*(1-I6)` |
| of which direct costs | USD 188,000 | `=SUM(D2:D3)` |
| less internship after tax | USD -20,160 | `=-C2*(1-I6)` |
| Undiscounted net gain over 12 years | USD 150,563 | `=SUM(E2:E13)` |
| NPV at 6% | USD 13,783 | `=NPV(6%,E2:E13)` |
| IRR | 6.89% | `=IRR(E2:E13)` |
| Simple payback | 9.18 years from the start of the programme | year 9 plus 8,954 / 50,197 |
| Discounted payback at 6% | 11.51 years | same method on column H |
| Break-even post-MBA base salary (NPV = 0) | USD 147,520 | Goal Seek on I4 |

Interpretation. The opportunity cost is the larger half of the investment: Lena gives up USD 143,018 of after-tax
salary against USD 188,000 of direct costs. On these assumptions the MBA earns 6.89% a year, just above her 6%
discount rate, so the NPV is positive but small. The break-even salary tells her what she must believe: a
post-MBA base salary above about USD 147,500, with 4% growth, for the degree to pay at 6% within twelve years. That
is a sharper question to research (class employment reports, conversations with people in the target role) than
"is the MBA worth it?".

### 4.4 Worked example B: the one-year programme (half solved)

Lena's second option is a one-year full-time programme (*Example*: tuition USD 98,000, fees USD 9,000, relocation
USD 6,000, no internship). She graduates after year 1 and starts the same post-MBA job in year 2 at USD 150,000
plus the USD 30,000 bonus. Fill the gaps.

| Item | Value |
|---|---|
| Year 1 incremental cash flow | $(0 - 97{,}850) \times 0.72 - 113{,}000 =$ [ ] |
| Year 2 incremental cash flow | $(180{,}000 - 100{,}786) \times 0.72 =$ [ ] |
| NPV at 6% over 11 years (one programme year plus ten post-MBA years) | USD 160,226 |
| IRR | [ ] |
| Simple payback | 5.15 years |
| NPV at 6% over the same 12 calendar years as option A | [ ] |

Questions to answer in writing: why does the one-year option look so much better on paper? Which assumption is
doing the work? (Hint: one fewer year of forgone salary and one more year of post-MBA earnings.) What risk does the
model leave out? (Hint: no internship, which most career switchers use as their route to a full-time offer.)

### 4.5 Exercise C: your own model (unsolved)

Build the table in 4.2 with your own inputs. Record the four results and the one assumption you are least sure of.

| Measure | Your value | Assumption you are least sure of |
|---|---|---|
| NPV at [r]% | [ ] | [ ] |
| IRR | [ ] | [ ] |
| Simple and discounted payback | [ ] | [ ] |
| Break-even post-MBA salary | [ ] | [ ] |

## 5. Sensitivity and scenarios

<!-- Guidance: Change one input at a time first (sensitivity), then change several together in a consistent story (scenario). Report the range, not only the base case. -->

### 5.1 Two-way sensitivity: post-MBA salary and discount rate

NPV in USD for Lena's two-year option, all other inputs at the base case. In Excel, put the NPV cell in the corner
of a grid and use Data, What-If Analysis, Data Table (row input I7, column input I4).

| Post-MBA base salary *(Example)* | r = 4% | r = 6% | r = 8% | r = 10% |
|---|---|---|---|---|
| 120,000 | -141,990 | -152,927 | -161,127 | -167,161 |
| 135,000 | -45,978 | -69,572 | -88,358 | -103,297 |
| 150,000 | 50,033 | 13,783 | -15,590 | -39,434 |
| 165,000 | 146,045 | 97,137 | 57,179 | 24,429 |
| 180,000 | 242,056 | 180,492 | 129,948 | 88,292 |

The NPV changes by roughly USD 83,000 for every USD 15,000 of starting salary at 6%, because the difference
compounds over ten years. The starting salary is the input most worth researching.

### 5.2 Horizon and growth

| Change *(Example)* | NPV at 6% | IRR |
|---|---|---|
| 5 post-MBA years modelled | -126,298 | -10.68% |
| 10 post-MBA years (base) | 13,783 | 6.89% |
| 20 post-MBA years | 287,489 | 14.21% |
| Post-MBA growth 2% a year | -52,441 | 2.01% |
| Post-MBA growth 6% a year | 87,025 | 10.88% |

The horizon is a judgement, not a fact. A long horizon makes almost any MBA look good, but the further out the
year, the less the MBA explains the gap between the two paths. A defensible base case uses ten post-MBA years and
shows twenty as an upside.

### 5.3 Scenarios and expected NPV

| Scenario *(Example)* | Assumptions | NPV at 6% | IRR | Payback | Probability |
|---|---|---|---|---|---|
| Pessimistic | Salary 125,000, growth 3%, no bonus | -171,566 | -8.39% | not within 12 years | 25% |
| Base | Salary 150,000, growth 4%, bonus 30,000 | 13,783 | 6.89% | 9.18 years | 50% |
| Optimistic | Salary 175,000, growth 5%, bonus 40,000 | 200,402 | 16.88% | 6.75 years | 25% |
| Probability-weighted | | 14,100 | | | |

Excel: `=SUMPRODUCT(NPV_range, probability_range)`. The expected NPV is close to the base case here, but the spread
from USD -171,566 to USD 200,402 is what matters for a personal decision: ask whether you could carry the debt in
the pessimistic case (see mba/mba-loan-repayment-plan).

### 5.4 Charts

NPV profile of the two-year option (the IRR is where the line crosses zero):

```vega-lite
{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
  "description": "NPV of the two-year MBA option by discount rate, Example data",
  "width": 380,
  "height": 220,
  "data": {"values": [
    {"rate": 0, "npv": 150563}, {"rate": 2, "npv": 94888}, {"rate": 4, "npv": 50033},
    {"rate": 6, "npv": 13783}, {"rate": 8, "npv": -15590}, {"rate": 10, "npv": -39434},
    {"rate": 12, "npv": -58816}, {"rate": 14, "npv": -74576}, {"rate": 16, "npv": -87385}
  ]},
  "layer": [
    {
      "mark": {"type": "line", "point": true},
      "encoding": {
        "x": {"field": "rate", "type": "quantitative", "title": "Discount rate (%)"},
        "y": {"field": "npv", "type": "quantitative", "title": "NPV (USD)"}
      }
    },
    {
      "data": {"values": [{"zero": 0}]},
      "mark": {"type": "rule", "strokeDash": [4, 4]},
      "encoding": {"y": {"field": "zero", "type": "quantitative"}}
    }
  ]
}
```

Cumulative undiscounted cash flow (the payback point is where the bars turn positive):

```vega-lite
{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
  "description": "Cumulative incremental cash flow of the two-year MBA option by year, Example data",
  "width": 380,
  "height": 220,
  "data": {"values": [
    {"year": 1, "cumulative": -147292}, {"year": 2, "cumulative": -310858}, {"year": 3, "cumulative": -256000},
    {"year": 4, "cumulative": -220665}, {"year": 5, "cumulative": -183146}, {"year": 6, "cumulative": -143334},
    {"year": 7, "cumulative": -101113}, {"year": 8, "cumulative": -56362}, {"year": 9, "cumulative": -8954},
    {"year": 10, "cumulative": 41243}, {"year": 11, "cumulative": 94367}, {"year": 12, "cumulative": 150563}
  ]},
  "mark": "bar",
  "encoding": {
    "x": {"field": "year", "type": "ordinal", "title": "Year from programme start"},
    "y": {"field": "cumulative", "type": "quantitative", "title": "Cumulative cash flow (USD)"}
  }
}
```

## 6. Programme format options

<!-- Guidance: Run the model once per realistic format. The format changes the opportunity cost far more than the tuition does. -->

| Format | Opportunity cost | Typical features to check | When it fits |
|---|---|---|---|
| Two-year full-time | Two years of salary | Summer internship, full recruiting cycle, deepest network | Career switchers, people who need the internship route |
| One-year full-time | One year of salary | Compressed recruiting, often no internship | Career accelerators with a clear target, people with strong existing networks |
| Part-time or evening | Little or none | Longer duration, often employer support, limited on-campus recruiting | People staying with their employer or industry |
| Executive MBA | Little or none | Experienced cohort, employer sponsorship common, weekend or modular schedule | Senior managers moving up rather than across |
| Online | Little or none | Flexibility, network depth varies widely | Learning goals over recruiting goals |

Run a row of the model for each format you would actually accept, and put the results side by side:

| Format *(Example)* | NPV at 6% | IRR | Payback | Main risk not in the numbers |
|---|---|---|---|---|
| Two-year full-time | 13,783 | 6.89% | 9.18 years | Post-MBA salary below break-even |
| One-year full-time (11-year horizon) | 160,226 | 22.17% | 5.15 years | No internship for a career switch |
| [Part-time] | [ ] | [ ] | [ ] | [ ] |

## 7. Non-financial factors

<!-- Guidance: Score these honestly. Many graduates say the network, confidence and options were worth more than the salary change, and others regret a degree they took for status. Weights should come from your goal in section 1. -->

| Factor | Weight (sum 100) | Score 1 to 5 | Weighted | Evidence |
|---|---|---|---|---|
| Skills you will use (finance, strategy, leadership, data and AI) | [ ] | [ ] | [ ] | [Courses and electives you checked] |
| Access to target employers and functions | [ ] | [ ] | [ ] | [Employment report, alumni conversations] |
| Network and peers | [ ] | [ ] | [ ] | [ ] |
| International mobility | [ ] | [ ] | [ ] | [See mba/mba-international-applicant-plan] |
| Personal and family situation (partner, children, health) | [ ] | [ ] | [ ] | [ ] |
| Time out of the workforce and its risk | [ ] | [ ] | [ ] | [ ] |
| Alternatives (specialised master's, certifications, internal promotion) | [ ] | [ ] | [ ] | [ ] |
| *Example* Access to target employers | 30 | 4 | 1.2 | Four alumni in target roles, internship hiring data in the school's report |

## 8. Dated facts that affect the numbers

<!-- Guidance: These facts change. Re-check each one on the official page before you rely on it and write the date you checked it. -->

- **Candidate trends (GMAC).** As of October 2026, the GMAC Prospective Students Survey 2026 report (March 2026,
  more than 4,200 candidates in 145 countries, calendar year 2025 data) reports that candidates are focusing more
  on skills and return on investment and less on career switching: 42% of global candidates wanted to use
  graduate business education to switch industry or function in 2025, down from 58% in 2022. Non-US candidates
  preferring to study in the United States fell to 28%, while 45% named Western Europe. Check the current report at
  [gmac.com](https://www.gmac.com/market-intelligence-and-research/research-library/admissions-and-application-trends/2026-gmac-prospective-students-survey-report)
  before you rely on it.
- **US federal student loans.** As of October 2026, for new borrowers from 1 July 2026 Grad PLUS loans are no
  longer available; the MBA counts as a general graduate programme, so Direct Unsubsidized Loans are capped at
  USD 20,500 a year and USD 100,000 in total, within a USD 257,500 lifetime federal limit (Parent PLUS excluded). A
  legacy provision covers some students already enrolled before that date. The fixed rate for graduate Direct
  Unsubsidized Loans first disbursed from 1 July 2026 to 30 June 2027 is 8.07%. If your funding gap exceeds the
  federal cap, the rest must come from savings, scholarships, sponsors or private lenders, often at different
  rates and terms: model it in mba/mba-funding-scholarship-plan. Check
  [studentaid.gov](https://studentaid.gov/) and the rate notice on
  [fsapartners.ed.gov](https://fsapartners.ed.gov/knowledge-center/library/electronic-announcements/2026-06-04/interest-rates-federal-direct-loans-first-disbursed-between-july-1-2026-and-june-30-2027)
  before you rely on it.
- **Outside the US.** Funding and tax treatment depend on the country of study and of residence. Check your
  country's official schemes, the school's financial aid page and, for tax, a qualified adviser.
- **School salary data.** Class employment reports change every year and use different reporting standards.
  Record the report year and the share of graduates who reported a salary next to any number you use.

## 9. Decision record and timeline

<!-- Guidance: Decide on a date, write what you decided and why, and set the date you will revisit it. A decision record protects you from re-arguing the same question every month. -->

| Item | Your entry |
|---|---|
| Decision | [Apply in Round X to schools ... / Defer 12 months / Do not apply, pursue alternative ...] |
| Base-case NPV, IRR and payback | [ ] |
| Pessimistic-case NPV and whether you could carry the debt | [ ] |
| Deciding factors (financial and non-financial) | [ ] |
| Conditions that would reverse the decision | [For example: no scholarship above USD 20,000 a year] |
| Revisit date | YYYY-MM-DD |

Timeline relative to the intended programme start (T):

| When | Step |
|---|---|
| T-24 to T-18 months | Write the decision question, build the first model, talk to five people on each path |
| T-18 to T-15 months | Research post-MBA salaries and employers, refine the model, plan tests (mba/mba-admissions-test-plan) |
| T-15 to T-12 months | Re-run the model per school and format, start funding research (mba/mba-funding-scholarship-plan) |
| T-12 to T-6 months | Applications by round, with the model as a check on the school list |
| T-6 to T-3 months | Admit decisions: re-run the model with actual scholarships (mba/mba-admit-decision) |
| T-3 months to T | Monthly cash plan for the programme (mba/mba-budget-during-program) |

## 10. Quality checklist and common mistakes

<!-- Guidance: Run the checklist before you share the model with anyone whose opinion matters to the decision. -->

Checklist:

- [ ] The no-MBA path is a realistic trajectory with raises and promotions, not a frozen salary.
- [ ] All amounts are after tax and in the same currency and price basis.
- [ ] Only incremental costs are included; sunk costs are excluded.
- [ ] The discount rate is stated and justified, and NPV is shown at more than one rate.
- [ ] IRR is reported only with a single sign change in the cash flows.
- [ ] The break-even salary is computed and compared with evidence.
- [ ] A pessimistic scenario is modelled, and the loan payment in that case is affordable.
- [ ] Dated facts carry the date checked and the official link.

Common mistakes:

1. **Ignoring opportunity cost.** For a two-year programme the forgone salary is often as large as the tuition.
2. **Comparing against a frozen salary.** The no-MBA path also grows; leaving out its raises inflates the return.
3. **Using pre-tax salary differences.** The uplift is taxed, so the return is lower than gross figures suggest.
4. **Treating average salary data as causal.** Selection explains part of the gap (Arcidiacono, Cooley and Hussey
   2008); use school averages as an upper bound.
5. **Excel `=NPV` timing.** `=NPV(rate, range)` discounts the first value one period. If you put a cash flow at
   time 0, add it outside the function: `=CF0+NPV(rate, CF1:CFn)`.
6. **Over-long horizons.** A thirty-year horizon makes almost every MBA look good; show the result at ten and
   twenty years.
7. **Counting living costs on one path only.** You eat and pay rent on both paths; include only the difference.
8. **Forgetting financing costs.** Loan interest during and after the programme is a real cost when the discount
   rate is below the loan rate; model it in mba/mba-loan-repayment-plan.
9. **Relying on IRR when cash flows change sign twice.** Multiple IRRs or none can result; use NPV.
10. **Letting the spreadsheet decide alone.** The non-financial factors in section 7 often decide close cases.

## My notes and next steps

<!-- Guidance: List the three pieces of evidence that would most change your model and who can give them to you. -->

| Next step | Owner | Due |
|---|---|---|
| [Talk to two people in the target post-MBA role about starting pay] | [Your name] | YYYY-MM-DD |
| [Check the latest employment report of each target school] | [Your name] | YYYY-MM-DD |
| [Build the funding plan for the top two options] | [Your name] | YYYY-MM-DD |

## Sources and further reading

<!-- Guidance: Add the employment reports and conversations you used, with dates. -->

Primary works:

- Fisher, I. (1930). *The Theory of Interest*. Macmillan.
- Becker, G. S. (1964). *Human Capital: A Theoretical and Empirical Analysis, with Special Reference to
  Education*. National Bureau of Economic Research and Columbia University Press.
- Mincer, J. (1974). *Schooling, Experience, and Earnings*. National Bureau of Economic Research.
- Spence, M. (1973). Job market signaling. *The Quarterly Journal of Economics*, 87(3), 355-374.
- Arcidiacono, P., Cooley, J. and Hussey, A. (2008). The economic returns to an MBA. *International Economic
  Review*, 49(3), 873-899.

Textbooks (further reading): Brealey, Myers and Allen, *Principles of Corporate Finance*; Berk and DeMarzo,
*Corporate Finance*. Open resource: OpenStax, *Principles of Finance* (CC BY-NC-SA 4.0).

Official and dated sources (checked 2026-10-28): GMAC, Prospective Students Survey 2026 report and GMAC Advisor
summary (April 2026); ETS, "New Federal Student Loan Rules Took Effect" (updated 1 July 2026); Federal Student Aid,
interest rates for Direct Loans first disbursed between 1 July 2026 and 30 June 2027 (June 2026).

## Answer key

<!-- Guidance: Check your answers to worked example B here. -->

Worked example B: year 1 = $-70{,}452 - 113{,}000 = -183{,}452$; year 2 = $57{,}034$; IRR 22.17%; NPV over the same
12 calendar years USD 191,209 (IRR 23.23%). The one-year option looks better because it removes a year of
forgone salary (about USD 72,600 after tax) and adds a year of post-MBA earnings; the model leaves out the lower
chance of a career switch without an internship and any salary difference between one-year and two-year
graduates in your target function.

## Revision history

| Version | Date | Author | Change |
|---|---|---|---|
| 0.1 | YYYY-MM-DD | [Your name] | First model from template |
| [0.2] | YYYY-MM-DD | [Your name] | [Updated with scholarship offers] |

## Standard and licence note

Based on standard capital-budgeting methods (net present value, internal rate of return, payback) and the cited
economic literature, with dated public facts from GMAC, ETS and US Federal Student Aid checked on 2026-10-28. The
text, examples and numbers are original and fictional; they are not affiliated with or endorsed by any business
school, test owner or government body. Check the current official pages before you rely on any fact. Template
licence: MIT.