,
7 tweets,
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1/n
Thank you @PHuenermund for summarizing so vividly the Why-19 symposium. I agree with most of your observations and recommendations, especially those pertaining to causal inference in economics. Last week saw a huge interest on Twitter coming from economists, triggered
Thank you @PHuenermund for summarizing so vividly the Why-19 symposium. I agree with most of your observations and recommendations, especially those pertaining to causal inference in economics. Last week saw a huge interest on Twitter coming from economists, triggered
2/n
possibly by the challenge to analyze a causal chain using PO. While it unveiled the obvious advantages of DAGs in compactness, transparency and inference complexity, some bystanders might still have gotten the impression that one can do
possibly by the challenge to analyze a causal chain using PO. While it unveiled the obvious advantages of DAGs in compactness, transparency and inference complexity, some bystanders might still have gotten the impression that one can do
3/
without them through a heavy investment in PO training. Only passive on-lookers could come to such conclusion, not one who actually tries to analyze the chain using the two languages side by side. I therefore continue to advise readers: Do not rely on on-lookers, try to
without them through a heavy investment in PO training. Only passive on-lookers could come to such conclusion, not one who actually tries to analyze the chain using the two languages side by side. I therefore continue to advise readers: Do not rely on on-lookers, try to
4/
solve this problem yourself, from beginning to end, its not too hard, yet it reveals the essential differences between the two representations, one a direct mapping of your knowledge, the other a convoluted transformation of that knowledge. Next time an economist asks you:
solve this problem yourself, from beginning to end, its not too hard, yet it reveals the essential differences between the two representations, one a direct mapping of your knowledge, the other a convoluted transformation of that knowledge. Next time an economist asks you:
5/
"What do I get by using DAGs?" you will be able to assert first-handedly; you get the ability to answer certain questions that you would not be able answer otherwise, and these are questions that economists ask themselves 12 times a day: e.g., Is this variable exogeneous?
"What do I get by using DAGs?" you will be able to assert first-handedly; you get the ability to answer certain questions that you would not be able answer otherwise, and these are questions that economists ask themselves 12 times a day: e.g., Is this variable exogeneous?
6/
perhaps conditionally exogeneous? Is this parameter estimable using OLS? Does my model have testable implications? Are these two models statistically distinguishable, and more and more... I listed some in ucla.in/2mhxKdO,
Try them out, for fun and profit. They are not
perhaps conditionally exogeneous? Is this parameter estimable using OLS? Does my model have testable implications? Are these two models statistically distinguishable, and more and more... I listed some in ucla.in/2mhxKdO,
Try them out, for fun and profit. They are not
7/
meant to prove that economists do not know X or Y, but to entice them to enjoy the power of new tools, still absent from their textbooks. Conclusion: Do not rely on "On-lookers", listen to your own experience. Good luck, and Tweet if any questions. #Bookofwhy
meant to prove that economists do not know X or Y, but to entice them to enjoy the power of new tools, still absent from their textbooks. Conclusion: Do not rely on "On-lookers", listen to your own experience. Good luck, and Tweet if any questions. #Bookofwhy
