You're faced with conflicting economic indicators. How do you navigate through the data for your research?

The economic environment is intricate, and the Bayesian approach is more suitable because the prior assumptions should consider that the outcome is uncertain, and events will unfold naturally, rather than according to our presumptions. Both indicators are probably important and should shift the priors.

One thing to understand is that data themselves do not tell the entire story. As economists, you will have to understand the context behind the data first. Only when the context is set does the data give you meaning.

When faced with conflicting economic indicators, I dive into the context first. I think about recent policy changes, global events, and industry shifts. I remember a project where the data was all over the place, and understanding the bigger picture really helped. I check if the indicators are showing short-term blips or long-term trends by comparing historical data. Cross-checking reliable sources gives me a clearer view, and I always differentiate between leading and lagging indicators to know if we’re looking at future trends or past performance. Staying open-minded is crucial. Conflicting data often means there's a deeper story, and by piecing together the context, I can draw informed, balanced conclusions.

Think of yourself as Sherlock Holmes of the economic world. Assess the context to understand the bigger picture—was there a major event that could be throwing off the numbers? Clues are everywhere, Watson.

Not all data is created equal. Treat your sources like you're picking avocados at the grocery store—only choose the best and freshest. Reliable sources are key to making sense of conflicting indicators.

It's also crucial to keep in mind that there may be spurious correlations. To take the given example, it could be that most of the increase in credit to the economy has been granted to companies for investments, rather than to households for consumption. In such a case, we would of course see a significant and positive correlation, whereas the real reason could be the increase in transfers received by households (which would mean that we would rather focus on the evolution of secondary income instead of credits).

Data correlation can be a game-changer. I remember working on a project where sales were dropping, and nothing made sense. By correlating customer feedback with sales data, we uncovered a pattern—product issues were spiking returns. This insight helped us fix the product and boost sales again. It's like turning confusion into pure gold!

One of the critical thing to check is which indicator is lagging and which is leading. Unemployment often lags, while M2 can lead.

Channel your inner data janitor and clean up those messy datasets. Correcting errors and ensuring accuracy will help you see the true story behind the numbers. A little data tidying goes a long way.

The example is falling money supply after COVID, it might decrease, but it also jumped by 40% in 2020, so after decreasing by 2% it is still higher than pre-covid levels by 38%, driving demand further.

Put on your detective hat and look for patterns. Trends can reveal what isolated data points can't. Analyze the ups and downs like you're reading a thrilling novel—what's the plot twist?

My suggestion is to use both old and new economic theories. I like to apply New Keynesian model, RBC, old approaches such as quantative money equation, and even IS-LM. If different theories starting from different assumptions arrive to the same answer, this is very valuable for forecasting.

Don't forget to consult the trusty old rulebook. Use economic theory as your compass to navigate through the data storm. Whether it’s supply and demand or Keynesian principles, theory can provide the guiding light.

I love the variety of schools, and while the modern theories make stronger emphasis on expectations, older theories focus on observable fundamentals. When they give the same answer, Bingo!

Gather a roundtable of perspectives like King Arthur and his knights. Consult different experts, read various analyses, and consider multiple viewpoints. The more angles you have, the clearer the picture becomes.