Category: Business

Everything has an opportunity cost. An MBA, for example, costs about fifty to eighty thousand dollars, but that’s just the face value. It turns out, by taking two years off of work to go to school, you are also sacrificing the earnings you could have had from those two years, not to mention any promotions, raises or job experience that would have come along with it. If we’re thinking about lifetime earning potential, we can calculate the incremental earnings that you’d need from the MBA in order to break-even on the investment. Of course, all of these calculations should always be done ex-ante (prior to enrollment) because otherwise, we’re falling prey to the sunk-cost fallacy, and that will only make us regret a decision we’ve already made.

For example, let’s say that your MBA will cost $75,000 up front and that you are currently making $50,000 per year annually at your current job. What incremental salary increase would you need in order to account for the opportunity cost of the MBA?

First, we have to calculate an appropriate discount rate for our money. In this case, we can probably use , the market’s rate of return because if we choose not to put the money towards an MBA, we could instead put it in an Index Fund or another similar investment vehicle, where it would grow at around the market interest rate.

Based on the July 2018 numbers, the market risk premium is about 5.38%. Notice that we didn’t just use the Implied Market Return of 7.69%, this is because we need to subtract the Risk-free rate in order to account for the incremental risk.

Let’s round down to 5% for simplicity. Assuming we’re starting our MBA in January of 2019 and Finishing in December of 2020 (2 years) with a cash outflow of $37,500 in 2019 and 2020 and sacrificed earnings of $50,000 in each of those years. We can calculate the future value (FV) of that money in 2021 as follows:

Our periodic payment, , is $87,500, our discount rate,, is 5% and our number of periods, , is 2. That leaves us with the following:

Assuming we’re able to land a job on day 1 after graduation, how much more do we have to make in our careers to make up for the opportunity cost of the MBA? For that, we can use another annuity formula to calculate the periodic payment required over a given number of years to equal a certain present-value amount.

Let’s say that we will have a 30-year career and that our market risk premium stays the same at 5% (the historical average for Canada is closer to 8%, however, let’s be conservative and stick with 5%). Substituting in these values to our formula with PV = $179,375 r = 5% and n = 30, we find that the payment, P, is:

So, we need to make an additional $12,000 per year every year for the rest of our careers, because of the MBA, in order to make up for the opportunity cost of the program.

If that seems realistic to you, maybe you should consider an MBA.

Of course, if we’re being really clever, we should probably also include a risk premium for our MBA. There is not a lot of data out there to suggest what the probability of completing an MBA is, but we can assign some probabilities to our equation for reference. Let’s say that there’s a 60% chance that the market will be strong when we complete the MBA and we’re able to find a job that pays $62,000 per year right out of the MBA program. There is also a 20% chance that we’ll make the same amount as we made before the MBA program $50,000 per year, a 10% chance that we’ll make $75,000 per year after the program and a 10% chance that the market for MBAs tanks and we’ll make below $40,000 per year when we graduate.

How do we make a decision with all these different possible outcomes? Simply multiply the probabilities by the annual salaries and add them together to find the probable result. If these numbers are correct we’re looking at an equivalent salary of $58,700 per year coming out of the MBA program. Of course, these numbers are completely made-up, but if we find numbers like these in our real-world evaluation, the logical decision from a financial perspective would be to reject doing an MBA because the cost is outweighed by the potential gains.

According to PayScale, the average salary in Calgary for an MBA with a finance specialization is $87,500 per year, but the average salary for someone with a bachelor of science degree is over $75,800 per year. Based on these numbers, it might not make sense for someone with a science degree to do an MBA.

Of course, there are other intangible factors that come into play including career preferences, lifestyle, and happiness. These are all important and should definitely be factored into your decision.

Yes, this is a very hard decision to make but can machine learning algorithms help make these decisions easier for us? It should be possible to use machine learning algorithms to predict future earnings potential and even take into account qualitative variables like career preferences and working style to give us a better idea of which choices might be right for us.

It is my goal to understand the capabilities of machine learning models to assist in these types of financial predictions. Hopefully, in the next few weeks, I’ll have an update for you on whether this type of predictive capability exists and if it does, how to access it.

For now, good luck with your decision making! I did an MBA and I don’t regret it at all because it was the right decision for me. My hope is that this article has given you the tools to decide whether the decision might be right for you.

Everything has an opportunity cost. An MBA, for example, costs about fifty to eighty thousand dollars, but that’s just the face value. It turns out, by taking two years off of work to go to school, you are also sacrificing the earnings you could have had from those two years, not to mention any promotions, raises or job experience that would have come along with it. If we’re thinking about lifetime earning potential, we can calculate the incremental earnings that you’d need from the MBA in order to break-even on the investment. Of course, all of these calculations should always be done ex-ante (prior to enrollment) because otherwise, we’re falling prey to the sunk-cost fallacy, and that will only make us regret a decision we’ve already made.

For example, let’s say that your MBA will cost $75,000 up front and that you are currently making $50,000 per year annually at your current job. What incremental salary increase would you need in order to account for the opportunity cost of the MBA?

First, we have to calculate an appropriate discount rate for our money. In this case, we can probably use , the market’s rate of return because if we choose not to put the money towards an MBA, we could instead put it in an Index Fund or another similar investment vehicle, where it would grow at around the market interest rate.

Based on the July 2018 numbers, the market risk premium is about 5.38%. Notice that we didn’t just use the Implied Market Return of 7.69%, this is because we need to subtract the Risk-free rate in order to account for the incremental risk.

Let’s round down to 5% for simplicity. Assuming we’re starting our MBA in January of 2019 and Finishing in December of 2020 (2 years) with a cash outflow of $37,500 in 2019 and 2020 and sacrificed earnings of $50,000 in each of those years. We can calculate the future value (FV) of that money in 2021 as follows:

Our periodic payment, , is $87,500, our discount rate,, is 5% and our number of periods, , is 2. That leaves us with the following:

Assuming we’re able to land a job on day 1 after graduation, how much more do we have to make in our careers to make up for the opportunity cost of the MBA? For that, we can use another annuity formula to calculate the periodic payment required over a given number of years to equal a certain present-value amount.

Let’s say that we will have a 30-year career and that our market risk premium stays the same at 5% (the historical average for Canada is closer to 8%, however, let’s be conservative and stick with 5%). Substituting in these values to our formula with PV = $179,375 r = 5% and n = 30, we find that the payment, P, is:

So, we need to make an additional $12,000 per year every year for the rest of our careers, because of the MBA, in order to make up for the opportunity cost of the program.

If that seems realistic to you, maybe you should consider an MBA.

Of course, if we’re being really clever, we should probably also include a risk premium for our MBA. There is not a lot of data out there to suggest what the probability of completing an MBA is, but we can assign some probabilities to our equation for reference. Let’s say that there’s a 60% chance that the market will be strong when we complete the MBA and we’re able to find a job that pays $62,000 per year right out of the MBA program. There is also a 20% chance that we’ll make the same amount as we made before the MBA program $50,000 per year, a 10% chance that we’ll make $75,000 per year after the program and a 10% chance that the market for MBAs tanks and we’ll make below $40,000 per year when we graduate.

How do we make a decision with all these different possible outcomes? Simply multiply the probabilities by the annual salaries and add them together to find the probable result. If these numbers are correct we’re looking at an equivalent salary of $58,700 per year coming out of the MBA program. Of course, these numbers are completely made-up, but if we find numbers like these in our real-world evaluation, the logical decision from a financial perspective would be to reject doing an MBA because the cost is outweighed by the potential gains.

According to PayScale, the average salary in Calgary for an MBA with a finance specialization is $87,500 per year, but the average salary for someone with a bachelor of science degree is over $75,800 per year. Based on these numbers, it might not make sense for someone with a science degree to do an MBA.

Of course, there are other intangible factors that come into play including career preferences, lifestyle, and happiness. These are all important and should definitely be factored into your decision.

Yes, this is a very hard decision to make but can machine learning algorithms help make these decisions easier for us? It should be possible to use machine learning algorithms to predict future earnings potential and even take into account qualitative variables like career preferences and working style to give us a better idea of which choices might be right for us.

It is my goal to understand the capabilities of machine learning models to assist in these types of financial predictions. Hopefully, in the next few weeks, I’ll have an update for you on whether this type of predictive capability exists and if it does, how to access it.

For now, good luck with your decision making! I did an MBA and I don’t regret it at all because it was the right decision for me. My hope is that this article has given you the tools to decide whether the decision might be right for you.