{"id":61,"date":"2024-05-21T16:56:16","date_gmt":"2024-05-21T07:56:16","guid":{"rendered":"https:\/\/testwebsite7198.wordpress.com\/?page_id=61"},"modified":"2024-07-31T11:56:20","modified_gmt":"2024-07-31T02:56:20","slug":"courses","status":"publish","type":"page","link":"https:\/\/econdev.hiroshima-u.ac.jp\/wp\/?page_id=61","title":{"rendered":"Methods Sequence"},"content":{"rendered":"\n
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Alongside the required and elective courses, IEDP provides a structured compulsory methods sequence<\/strong> that allows masters students to gain the basic tools to analyze causal effects using experimental or observational data in the first year. These courses are designed to allow people without extensive statistics, economics, computer science, or data science backgrounds to conduct applied microeconomic analysis on a wide variety of topics. <\/p>\n\n\n\n

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“Causality” in Japanese is “\u56e0\u679c”, which comes from <<hetu-phala>> in Buddhist teaching. This is the doctrine that actions have consequences.
While we leave the discussion of the doctrine of dependent origination to theologians, we provide some means to test cause and effect in our impermanent existence using quantitative methods.
The concept of causality that we use is counterfactual causality<\/em>, an introduction to which can be found here:
https:\/\/mixtape.scunning.com\/04-potential_outcomes<\/a><\/figcaption><\/figure>\n\n\n\n

Before Enrollment<\/h2>\n\n\n\n

We highly recommend that students try to do some studying prior to enrollment if possible, to get the most of out of our program. The most important first step is to understand the basic intuition<\/em> of causal inference. For this, we recommend watching the Causal Inference Bootcamp<\/strong>, a series of short videos explaining the concept of counterfactual causality and different methods commonly used to estimate causal effects, before coming to IEDP and looking through the Casual Inference Mixtape<\/strong>. <\/p>\n\n\n\n

Many of our students use STATA<\/strong> or R<\/strong>, alongside other tools depending on the student’s research interest. We will provide a copy of STATA, which is proprietary (paid) statistical software package, but we also provide instruction on the R statistical\/data management programming language and RStudio, an IME for the language. Both R and RStudio are free and open source. We recommend that you at least install and understand the basics of R before arriving, though we will also provide instruction on how to set up and use R. <\/p>\n\n\n\n