How do you make economic data and statistics interesting?

The most exciting thing about economics is making the data tell a story. Visualizations are essential to bring a story to life. Visualizations need to be readable and clear. Often, too much effort is placed on the design rather than the data. Infographics tell a story, but too many words and visuals distort and lose the reader. In my experience simple graphs go a long way in showcasing data and patterns. More importantly, a visualization needs to be self contained. There needs to be a simple explanation or a question that provokes the reader. What is the takeaway?

Once thing I always find helpful is creating bar charts or pie charts to compare economic indicators between different countries, regions, or sectors. This can provide valuable insights at a glance.

In my experience it is important to produce a wide range of visuals and then select only the few that really convey a message. Only these few selected items must be included in reports, briefs, working papers or other type of publications. During presentations and speeches, there is a need to further refine the number of visuals to showcase. A good rule is to include only those that are simple and that can be easily interpreted. When time to present is short, it is more impactful to capture the audience’s attention with a captivating speech rather than divert focus with a visual. That’s my two cents on visuals!

I agree, visuals are the best way to capture attention. Also another way is to find data that is at historic levels. But economic data isn't necessarily meant to be super exciting and often times markets are in a very "boring", relatively predictable cycle. I think visuals really probably are the best way to capture someone's attention, but being able to separate the forest from the trees is probably the best way in the long-term.

Make the data and the story something that the reader can relate to. Talking about how some component of the consumer price index has increased doesn't really resonate with anyone other than economists. (We're kind of weird that way, we get excited about that kind of stuff.) Instead, use the same data to say something that the reader can relate to. To say something like "...The consumer price index for fruits and vegetables has increased by 10%." and the reader's eyes glaze over. Instead, say something like "It will cost you 10% more to buy a bag of apples than it did a year ago." Include a simple line graph (price on the vertical axis and time on the horizontal) and the reader will pay attention.

Uma das coisas que acho mais relevantes é traduzir o “economês” para a vida real das pessoas, sem precisar banalizar os conceitos. Quem exagera no “economês” n?o sensibiliza o interlocutor para seu ponto de vista. Ninguém é obrigado a saber o que é “hiato do produto”, por exemplo. Agora, se você disser que é o quanto a economia opera abaixo ou acima da sua capacidade produtiva máxima e que se há folga nessa capacidade as empresas possuem maior dificuldade em repassar aumentos de pre?os, você traduziu um conceito específico à nossa profiss?o em algo muito prático em que as pessoas conseguem facilmente enxergar as aplica??es e as consequencias.

Data and numbers alone do not mean anything. One needs to identify trends/patterns and draw insights and eventually weave a story around those observations. How many times have you seen people zone out when presented with large tables and charts? Use data as a supplementary resource for your objective.

Telling economic data and statistic using stories is quite important: - It simplifies complexity - Builds a connection with the audience that makes sure they don't get bored of the economic jargons and leave. - Humanise data which is important for it to have greater meaning. Through the power of storytelling, even the most complex economic systems and financial models become easily understandable. By using relatable characters and concrete examples, abstract ideas are transformed into easily comprehensible concepts.

Powerful data stories are often the ones that humanize the data. Economic research in the housing market is a great example. A home isn't just a financial investment. Home buying is a deeply personal process of putting down roots and weighing long-term aspirations such as growing a family and maybe raising children. Contextualizing the individual journey that underlies the data breathes life into what could have been mundane statistics.

"Tell a story through data visualization" involves the art of transforming raw numerical information into compelling visual representations that narrate a story. By using data to craft real-world scenarios or case studies and presenting them through eye-catching charts, colorful graphs, or informative infographics, you create a powerful connection between economic statistics and people's lives. This approach not only simplifies complex data but also personalizes it, making it relatable and captivating. These visual stories not only help your audience understand economic concepts but also engage them by showing how data impacts their everyday experiences and the world around them.

I like doing this when I'm not sure about something complex especially. I think it's just generally beneficial all-around, plus it might strike up a conversation between other contributors. Nothing wrong with asking questions; economists with the best understanding are always looking for new information to absorb.

Asking questions is one of the most exciting ways of exploring economic/statistical data in a small group of enthusiastic learners.

Look and focus for ways in which it influences your everyday line of work, especially if your in a risk assessment type of role and how it affects your “risk appetite”.

Make VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY, VERY BIG charts.

I think the best data is laid out in a logical story that forces the consumer to interact as they go along. Having toggles that present data from different perspectives is an engaging way to get people thinking in a world full of stale KPI's that get visually represented the same ways over and over.

Not just analogies for remembering (which is a tremendous device), but also we need to remember that people are overwhelmed with information. If we can make it about them, see how the present data can or will impact them personally, then it becomes a lot easier for them to comprehend because they are vested. With skin in the game they have motivation to understand and take advantage of the information being presented!

Use simple everyday examples that are familiar to people around you. Most recent happening will help people understand things easily. Once people see the things around them and how it relates to everyday economics, it will make them open their economic senses and then any visual, popular statements, familiar graphs will ace their understanding and make it interesting for them to appreciate economics!

I would agree with this one. Comparing economic data from the current cycle relative to historic cycles can both be attention grabbing, but also informative as it gives others a sense of where a given part of the economy is at relative to a prior cycle and what the outcome wound up being.

The analogy that works the best - linking the data with everyday life of the audience or its recent experience. As everyone adds to the creation of economic data, it is always interesting to link the everyday actions and decision making with economic outcomes.

Similar to the story-telling strategy, using analogies is powerful yet bears the risk of misleading readers in unintended directions. An analogy is usually comprised of many elements that each carries cultural or habitual discrepancies. When articulating an analogy, the writer must be careful with the key point and the analogy that describing it.

I think it depends on your audience. If you really want to write a serious market outlook, there may not be a need for humor and instead objectivity. If you're just writing your thoughts, I think a little natural humor can maybe be a good thing sometimes. It really depends. If you're forcing jokes or just totally clowning around, readers may not take you seriously.

From a teacher - student perspective, humour makes the data more sticky. By sticky, I mean that the data is not easily forgotten by the students. The same is true for most audiences.

This segment is indeed crucial to maintain participants' attention and convey a message that they will understand at that moment. For instance, during lectures, I sometimes prepare a short 30-second clip from YouTube, like a situation from The Simpsons (explaining opportunity cost) or The Big Bang Theory (illustrating an experiment). These examples have yielded excellent results for me so far and have helped in understanding complex concepts.

I view this as kind of selling economic data. There isn't always a call to action in economic cycles. Often times the data is boring, predictable, and there's nothing to really say to excite the average retail investor (for example). I think a call to action can work strongly against you if you're forcing it, or if it comes off that way to readers. In my view, changing from an economics contributor to someone who seems like they're trying to sell something is a complete disaster.

I would rather say "highlight the problem the statistics reveals" or announce other important measures that could change the entire profile presented.

This definitely depends on your audience, but starting from the premise of this post which is how to make data interesting (assuming to those who don't already find it interesting) making it actionable is a must. A non-data-lover will want to know the "so what" of the data or we will quickly lose them. There is no one-size-fits-all to making data actionable. For example, different responses are warranted from job seekers and employers to a drop in the unemployment rate. One must, therefore, be keenly aware of our audience when we present data and provide a specific "so what", or some concrete examples of the practical implications of the data that apply to a wide range of decision makers.

When discussing economics, I think the most important thing for your audience is that it needs to be relatable. All things economics affects us all in some way or another. People need to understand how it affects them. For example, an Australian small business owner might not see how slower growth in China will affect him even if he or she does not deal with China - but that will impact on the Australian economy, the currency and customers of that business. I also find that if economics is presented in a way which is digestible and easy to understand people get past the idea of economics being "boring" or "confusing".

The statistics that shouldn't be overlooked: According to satistica, the world's youth, aged between 15-24 years old, outnumbered the people above age of 25 in terms of internet usage. With the worldwide youth population set to increase 7 percent by 2030 according to the UN, these stats should be a catalyst for making economic data more inclusive for the youth population around the globe. Inclusivity doesn't necessarily mean accessibility: Making economic data accessible doesn't make it accessible. Accessibility is only good when data is understood by a larger audience. To achieve that, data visuals should be produced in ways that they are easily grasped by a wider age range and enable them into making informed and educated decisions.

It's essential when communicating statistics and data to use, not one, but a combination of four communication intelligences to create maximum impact as taught by prof. Woodward at INSEAD: - Structure Create a logical sequence for using the data - Rationality Focus on key statistics to illustrate developments and magnitudes - Expressiveness Tell a story from the data, use examples - Visualisation Use images and metaphors to create senses of magnitude and importance of data. In essence, to make economic statistics interesting you need to combine Structural, Rational, Expressive and Visual communication qualities. A great example to study is Hans Rosling, the author of Factfullness, who was a master of using these techniques in combination.

Talk about single datapoints! Single out a few datapoints that represent the median case as well as extreme observations and tell their 'full story'. Quick example: What is the median in data on wages, what is the mean? Why are they different and what's the role of extreme observations then? Which values lie at the upper and lower end of the distribution and how much is this relative to median/mean? What do we know about these observations? E.g., which individual is represented by the mean/median of wages and extreme observations?

We undeniably depend on data for informed decision-making. However, without proper interpretation, raw data remains just that. It’s the skillful analysis and understanding that transform these figures into meaningful insights or discernible trends.