Automated Author ProfileTakahashi, Yuya
Takahashi, Yuya
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 7.2 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This paper empirically studies firm's strategic exit decisions in an environment where demand is declining. Specifically, I quantify the extent to which the exit process generated by firms' strategic interactions deviates from the outcome that maximizes industry profits. I develop and estimate a dynamic exit game using data from the US movie theater industry in the 1950s, when the industry faced demand declines. Using the estimated model, I quantify the magnitude of strategic delays and find that strategic interactions cause an average delay of exit of 2.7 years. I calculate the relative importance of several components of these strategic delays. (JEL D92, L11, L82, N72)
Authors
- Takahashi, Yuya
This paper empirically studies firm's strategic exit decisions in an environment where demand is declining. Specifically, I quantify the extent to which the exit process generated by firms' strategic interactions deviates from the outcome that maximizes industry profits. I develop and estimate a dynamic exit game using data from the US movie theater industry in the 1950s, when the industry faced demand declines. Using the estimated model, I quantify the magnitude of strategic delays and find that strategic interactions cause an average delay of exit of 2.7 years. I calculate the relative importance of several components of these strategic delays. (JEL D92, L11, L82, N72)
Authors
- Takahashi, Yuya
This paper empirically studies firm's strategic exit decisions in an environment where demand is declining. Specifically, I quantify the extent to which the exit process generated by firms' strategic interactions deviates from the outcome that maximizes industry profits. I develop and estimate a dynamic exit game using data from the US movie theater industry in the 1950s, when the industry faced demand declines. Using the estimated model, I quantify the magnitude of strategic delays and find that strategic interactions cause an average delay of exit of 2.7 years. I calculate the relative importance of several components of these strategic delays. (JEL D92, L11, L82, N72)
Authors
- Takahashi, Yuya
This paper empirically studies firm's strategic exit decisions in an environment where demand is declining. Specifically, I quantify the extent to which the exit process generated by firms' strategic interactions deviates from the outcome that maximizes industry profits. I develop and estimate a dynamic exit game using data from the US movie theater industry in the 1950s, when the industry faced demand declines. Using the estimated model, I quantify the magnitude of strategic delays and find that strategic interactions cause an average delay of exit of 2.7 years. I calculate the relative importance of several components of these strategic delays. (JEL D92, L11, L82, N72)
Authors
- Takahashi, Yuya