My field of specialization is agricultural economics. I have dealt with a wide range of topics including production (land fragmentation, crop grading, technology adoption, etc.), environment (climate change, organic farming, environmental policy, etc.), development (Bhutan, human wildlife conflicts, economic growth, fertilizer quality, etc.), consumption (choice experiments) and trade. Despite the diversity of topics, my analytical approach has been consistent: I aim to convey messages through“numbers”.
Many issues addressed in agricultural economics are similar in essence but different in details. That is, while people tend to agree on the general direction, opinions often differ on the details. For instance, most people may agree that measures are needed to improve food self-sufficiency, but when it comes to the details—such as what kinds of policy measures should be implemented or how much subsidy should be provided—a variety of opinions emerge. God is in the details.
In such situations, numerical evidence becomes crucial. For instance, if we can present numerical evidence on the impacts of different policy measures, policy discussions would become much easier. I believe that one of our missions as researchers is to provide such evidence based on solid scientific methods. In our laboratory, we employ various quantitative approaches—such as econometrics, machine learning, and simulation analysis—to address diverse research questions.
Educational approach
Hot Discussion and Cool Research
Our laboratory seminars are jointly supervised by Professor Katsuhiro Saito, who specializes in theoretical analysis, and myself, focusing on quantitative analysis.
The first characteristic of our laboratory is freedom. Students are free to choose their own research topics. (Of course, we can also suggest topics based on your interests.) I encourage everyone to pursue the research topic that truly inspires them.
The second characteristic is that our seminars are highly active and engaging. Not only the presenters but also the audience members actively strive to offer constructive and thoughtful comments, fostering an atmosphere that is both open and stimulating.
Before joining the University of Tokyo, I conducted research at a government research institute, a university in the United States, and at an international organization in Europe. In all of these places, research seminars were held regularly. Compared to these seminars, I can confidently say that the intensity and passion of the discussions in our seminars are second to none.
The discussion skills and bonds formed here will surely become valuable assets for you, no matter what career path you choose after graduation.
For those interested in joining our laboratory, please visit my homepage to read the message for prospective students.
Vision for industry-academia collaboration
Feel Free to Consult with Us
We provide advice on various data analysis projects. Depending on the theme, joint research is also possible.
Keywords1 : Agricultural economics, econometrics, data science, big data, machine learning, regression analysis Keywords2 : Agricultural economics in general
