How do you check your economic assumptions for accuracy?

I usually look at the behaviors of the market, and common people to identify my assumptions. How each market player is acting is a really good place to start identifying assumptions. Finding the rationality of the involved party be it the market, government, or general public see the actions and where some of the identified parties might have an effect on other parties.

The first step is to identify and list all the hypotheses made in your economic analysis,. Clearly state the scope and purpose of your analysis, along with the main question or issue you’re addressing. Then, examine and validate each hypothesis through empirical evidence, statistical analysis, or logical reasoning. Rigorous testing helps ensure the reliability of your economic model and enhances the validity of your conclusions. Additionally, consider sensitivity analysis to understand the impact of variations in assumptions on your results, providing a more comprehensive evaluation of the economic hypothesis. For instance, in examining a specific field, align your assumptions with empirical studies exploring linked economics principles.

The first step is to identify the inputs and the outputs. What is in between are assumptions. But if you use garbage as inputs you have garbage as ouputs : garbage in garbage out. The data used is hence paramount for a model. This can be also said about the model used : garbage in garbage out. The model stems from assumptions. If you don't understand the assumptions, then you don't understand the model and you cannot interprete the results. Take the CPAM, do you know the asumptions used? If not check them on wikipedia and ask yourself if you agree with all of them.

Before making assumptions, first ask a question... or two. Why? How? When? And take it from there. Try to get an answer and formulate a thesis. Check the cumulative data. Test again... Next, ask more questions. Why do I care? Why? Does anybody else care? Test the tester. Next. Do my assumptions check out? Test again. Do they make "sense"? Double check. Then, whatever I learned or found out must be re-checked against the theoretical or empirical background/evidence. Does it check out? Does it make sense? Does "common sense" make sense anymore? What do the others think? Check again. Finally, publish your assumptions. Nothing better than sunlight to kill "vampire assumptions." And don't forget, keep checking and re-testing... just in case.

The first of them is the neoclassical model. One of the most important derivations of this model is the assertion that any country benefits when it moves from a situation of autarky to one of trade openness with other countries. It does not matter if the country is small or large, if it specializes in primary products or manufacturing. Everyone benefits thanks to the Ricardian principle of comparative advantage. One might wonder if the fact that any country benefits when it joins international trade is something universal and immutable, or just something that emerges after making some assumptions. Samuelson, in a conversation with the mathematician Stanislaw Ulam, showed him that the principle of comparative advantage was both true/real.

To compare hypotheses, assess their key elements such as assumptions, predictions, and methodologies. Identify commonalities and differences, considering how each addresses the research question. Evaluate empirical evidence or testing methods supporting each hypothesis. Communicate the comparative analysis transparently, highlighting strengths and limitations to guide further research or decision-making.

Communicate hypotheses clearly by stating them concisely and providing a rationale. Use accessible language, organize them logically, and consider visual aids for clarity. Be transparent about assumptions, acknowledge limitations, and encourage feedback for effective communication.

Following hypothesis validation and sensitivity analysis, interpret results. For example, if your study analyzes government policies’ impact on markets, interpret how policy variations influence outcomes. Draw conclusions; if sensitivity analysis indicates significant assumptions’ impact, discuss model volatility. Compare findings with existing literature. If aligning or diverging, highlight contributions to the ongoing discourse. Address study limitations; if data constraints affected precision, transparently acknowledge. Propose future research avenues, suggesting variables or areas for empirical investigation, encouraging continuous economic insights refinement.