Will the GOP tax plan be good for you? Graphs tell the story.

The GOP is promising their massive tax cuts will spur economic growth and increase wages. This is the “trickle-down economics” theory, based on the idea that when wealthy people have more money, they invest in companies that can now expand, hire more people and increase sales and wages.

It’s an interesting theory. But does trickle-down economics actually work in practice? Fortunately we have nearly 100 years of data on what happens to the economy and wages as tax rates change.

// Does the economy grow?

Since 1929, the top marginal tax rate has gone from a high of 94% under Roosevelt down to a low of 31% under George Bush Sr. And there is evidence that as you drop the marginal rate to 70% from 91%, indeed GDP does increase (1963-1981). But when Reagan cut the top marginal tax rate to 50% in 1981, we saw no change in economic growth. When he cut it again to 33% in 1988, the economy actually contracted.

Since Reagan’s tax cuts, we have seen three other changes to the top marginal tax rate. And a clear pattern emerges.

  • When Clinton raised the top rate to 39.6%, GDP increased.
  • When Bush Jr. dropped it again to 35%, GDP decreased.
  • When Obama raised it back to its current 39.6%, GDP increased.

Based on this brief analysis, it appears the optimal top marginal tax rate is about 50%. When you drop below 50%, you hurt economic growth. When you increase it, you improve economic growth. So it’s likely that a drop to 37% top marginal tax rate will lead to slower economic growth, not faster.

// Will it increases wages?

The theory is that when wealthier people have more money, they expand their business investments creating jobs and demand for workers, which raises wages. But when we look at how wages have grown since 1967, we see a different patterns. When the top tax rate was 70%, the top 20% of families had wage growth about the same as everyone else.

But look at 1982, when the top tax bracket fell to 50%. You can see how the blue line (wealthiest 20%) suddenly rockets away from the crowd. Wages for everyone are still increasing modestly, but the clear winner is the top 20%. Then in 1988, when the top bracket drops to 33%, we see the top 20% pull away even more, and especially the top 5% (black dotted line). In 2003, when the top tax rate drops to 35%, we now see the top 21%-40% of families (brown line) also start to pull away from the pack.

What you don’t see is the bottom 60% enjoying any of these gains. Why is the wealth not trickling down to everyone? Because when employers have more money, they don’t hand it out as pay raises out of the goodness of their hearts. They pay what the market will bear and keep the rest for their stockholders and owners.

// So what does trickle-down economics do?

So lower taxes don’t create jobs and don’t increase wages. What do they do?

The main thing lower tax rates do is make the wealthy more wealthy. Fortunately it doesn’t really hurt the bottom 60%. Their wages continue to increase modestly. And it does appear to help the middle class too, likely educated business professionals who now have more money to spend. But the truly wealthy, the top 20%, just accumulate more wealth.

We can see in this graph how much of the pre-tax income goes to the top 0.1% (that’s the top 1 in 1,000 families). The spikes are because so much of their income comes from the stock market, so when things are bad (2002, 2009) their pre-tax income suffers. But it recovers quickly when the stock market improves.

As the top marginal tax rate declines, the extra money gets trapped in the hands of the wealthy. They, in turn, invest in the stock market. We should expect to see the stock market explode if the GOP tax plan is approved. Again, anything below a 50% top marginal tax rate appears to be a magic number.

// Conclusion

There’s no evidence lowering taxes increases the economy or wages. There is a lot of evidence that it makes the wealthy wealthier while doing very little for the poor. Trickle-down economics is a fairy tale.

So will the new tax rate be good for you? If you’re in the top 40% of income earners, you will probably see your wages increase especially if you invest in the stock market which should have a bullish couple of years ahead.

But if you’re in the lower 60%, it will have virtually no effect. It won’t create jobs but it likely won’t kill many jobs either. And it won’t raise wages either.

The main benefits fall to the wealthy. The data is clear.

If you like these graphs, you’ll love my new book “Storytelling with Graphs” which I hope to publish soon. Subscribe to this blog to be alerted when it’s available.

Storytelling with a Stacked Bar Chart

The folks over at Storytelling with Data recently asked about stacked bar charts and they did a graph makeover. I’d like to tackle that same graph from the perspective of storytelling with graphs.

Now there’s a difference between data visualization and storytelling with graphs. Data visualization basically converts your data into a visual. Storytelling with graphs takes it a step further and draws some conclusion from the data, chooses the right graph to make that story clear and uses design principles to bring attention to that story.

Here’s the original hand-drawn data, and my best estimate to replicate it in Excel.

// Common Baseline
The secret to presenting data on stacked bar charts is to arrange the bars correctly, so you are comparing data along a common baseline. That typically means moving the most important data to the bottom of the stack, so you can accurately see small differences in the height.

For example, in this graph, you can see that “E” is increasing but has leveled off in t5-t6. You can especially see there has been a very slight increase in t6. You can also see that “D” has been declining. But the differences are less obvious because there is no common baseline. In t6, for instance, we can’t see if there was a slight increase or a slight decrease. So some of these smaller differences are harder to see.

Product “C” appears to be about flat. Product “B” appears to be growing. And Product “A” has had a sales spike in t3-t4 and sales are now receding toward pre-promotion levels. But all of these products have no common baseline and so there’s no way to accurately see small changes.

// The Story
I never design a graph until I know the story I’m trying to tell. At this point, the story appears to be “Product “E” is increasing and product “D” is decreasing, while overall sales are up”.

But notice something. The sum of Product “D” + Product “E” together are about the same across every time period. That suggests that sales of Product “E” are cutting into, or cannibalizing, sales of Product “D”. In other words, Product “E” is not growing the business, but simply shifting customers to a new product.

Where is the growth coming from? Product “B” and Product “A”. So I’m going to put those products as the next items in the stack.

I think of stacked bar charts like shelves on a bookcase. I want to stack my data so the important data is sitting on a shelf. For instance, I can see that Product “D” + Product “E” is basically stable. So if I stack those two products at the bottom, I will create a flat “shelf” to stack my next group. I’ll put Product “A” here.

Notice Product “C” is relatively flat so I could have left it at its current position. But it’s not an important part of this story so I’m going to tuck it at the top of the graph. Product “B” is growing and it would destroy this flat shelf on top of Products “D” and “E”. So Product “B” will also go above Product “A”.

// Color
Now I’ve got the bars stacked in the right order and now I can complete the story: “Product E sales are cannibalizing Product D, with most of the growth coming from Product A”. I typically start by using color.

Product “D” and “E” is one story and I’m going to signal that by using different shades of the same color blue. Product “A” is the second half of this story and I’m going to draw attention to that in a different color: orange. In fact, now I see that Product “B” is as much a growth driver as Product “A” so I’m also going to color code Product “B” orange.

I’m going to color code Product “C” gray. Graphs are complicated enough without having a lot of unnecessary color fighting for attention. In storytelling with graphs, gray is your friend. It allows you to have a lot of extra detail that whispers in the background.

// Finishing the Story
I’ve now found the story and I want to draw attention to that story so it’s quick and intuitive. A few finishing touches:
– I used darker colors where I want the eye to focus (Products “E” and “A”).
– I’m also going to add some arrows showing the directions of growth/decline.
– Make the gridlines a lighter gray – they don’t need to be prominent, just readable
– Make the y- and x-axis fonts smaller and more gray – again, they just need to be readable
– I’m also going to change the axis fonts to Segoe UI. The default is Calibri, but that makes your graph look like everyone else’s graph
– Delete the legend and add it directly onto the graph. No zig-zagging back and forth to read the legend
– Add the totals to the top of the stacked bar chart (add the total as one of the bars, then convert that into a line chart. Make the line color “no color” and add the data values)

The cherry on top is to put the main point in the title. Voila! Now the story is instantly clear using a stacked bar chart.

If you like this graph makeover, you’ll love my new book “Storytelling with Graphs” which shares all my secrets for drawing insights out of data and displaying data to tell a story. Subscribe to this blog to be alerted when it’s available.

About the author: Bruce Gabrielle is author of Speaking PowerPoint: the New Language of Business, showing a 12-step method for creating clearer and more persuasive PowerPoint slides for boardroom presentations. Subscribe to this blog or join my LinkedIn group to get new posts sent to your inbox.

Dataviz – How will a 20% import tax affect the U.S. and Mexico?

There’s been a lot of talk about Trump imposing a 20% tax on imports from Mexico to help pay for the wall. I don’t quite get this logic because it means U.S. businesses will be paying those taxes, and thus paying for the wall, not Mexico.

Anyway, as this conversation continues I thought it would be useful to really understand how much business goes on between the U.S. and Mexico, so I created this infographic. The U.S. is Mexico’s biggest trading partner, buying 73% of Mexico’s exports (Source). The pie charts, scaled to show absolute size of exports, show how crucial exports to the U.S. are for Mexico. But Mexico is the U.S.’s second-largest customer (behind Canada), so it would be damaging if Mexico retaliated with their own import taxes (Source). But Mexico clearly has more to lose.

mexico-exports-pie-charts

Notice also that most of the products that will get this new tax are cars, trucks and auto parts. About $100 billion according to this source, or about a third of their exports into the U.S. Is this just part of Trump’s strategy to force U.S. automakers to bring more jobs back into the U.S.?

Storytelling with Graphs cover

If you like this graph, you’ll love my new book “Storytelling with Graphs” which shares all my secrets for drawing insights out of data and displaying data to tell a story. I’m hoping to publish it in the next few months. Subscribe to this blog to be alerted when it’s available.

About the author: Bruce Gabrielle is author of Speaking PowerPoint: the New Language of Business, showing a 12-step method for creating clearer and more persuasive PowerPoint slides for boardroom presentations. Subscribe to this blog or join my LinkedIn group to get new posts sent to your inbox.