Mitsuru Mukaigawara
@mitsurumu.bsky.social
ID physician, Political scientist, Applied statistician. PhD Candidate in Government and AM Candidate in Statistics @harvard.edu.
mitsurumukaigawara.com
mitsurumukaigawara.com
We propose a spatiotemporal causal inference framework that fully leverages microlevel, granular data. ATE, heterogeneity, and mediation — all in one framework. Now with updated results and visualizations!
🚨New paper🚨: Are you interested in key debates about civil war and counterinsurgency? Like questions about causal inference but wish you had a better method for dealing with spillover and carryover effects? Then check out our new paper:
arxiv.org/abs/2504.03464
arxiv.org/abs/2504.03464
Spatiotemporal causal inference with arbitrary spillover and carryover effects: Airstrikes and insurgent violence in the Iraq War
Social scientists now routinely draw on high-frequency, high-granularity ''microlevel'' data to estimate the causal effects of subnational interventions. To date, most researchers aggregate these data...
arxiv.org
November 7, 2025 at 4:56 PM
We propose a spatiotemporal causal inference framework that fully leverages microlevel, granular data. ATE, heterogeneity, and mediation — all in one framework. Now with updated results and visualizations!
New working paper: “Survey Estimates of Wartime Mortality,” with Gary King, available at gking.harvard.edu/sibs. We provide the first formal proofs of the statistical properties of existing mortality estimators, along with empirical illustrations, to develop intuitions that guide best practices.
July 30, 2025 at 1:34 AM
New working paper: “Survey Estimates of Wartime Mortality,” with Gary King, available at gking.harvard.edu/sibs. We provide the first formal proofs of the statistical properties of existing mortality estimators, along with empirical illustrations, to develop intuitions that guide best practices.
Excited to present our poster on spatiotemporal causal inference at #PolMeth 2025. Looking forward to seeing many of you there!
Paper: arxiv.org/abs/2504.03464
Package: github.com/mmukaigawara...
Paper: arxiv.org/abs/2504.03464
Package: github.com/mmukaigawara...
Interested in causal inference using high-frequency, fine-grained geospatial data? Check out our 2025 PolMeth poster on spatial-temporal causal inference, designed by the wildly talented @mitsurumu.bsky.social. We examine the effects of US airstrikes and civilian harm on insurgent attacks in Iraq
July 8, 2025 at 4:17 AM
Excited to present our poster on spatiotemporal causal inference at #PolMeth 2025. Looking forward to seeing many of you there!
Paper: arxiv.org/abs/2504.03464
Package: github.com/mmukaigawara...
Paper: arxiv.org/abs/2504.03464
Package: github.com/mmukaigawara...
Reposted by Mitsuru Mukaigawara
Interested in causal inference using high-frequency, fine-grained geospatial data? Check out our 2025 PolMeth poster on spatial-temporal causal inference, designed by the wildly talented @mitsurumu.bsky.social. We examine the effects of US airstrikes and civilian harm on insurgent attacks in Iraq
July 8, 2025 at 12:47 AM
Interested in causal inference using high-frequency, fine-grained geospatial data? Check out our 2025 PolMeth poster on spatial-temporal causal inference, designed by the wildly talented @mitsurumu.bsky.social. We examine the effects of US airstrikes and civilian harm on insurgent attacks in Iraq
Reposted by Mitsuru Mukaigawara
New paper alert (hey, I can't doom scroll all the time): This one's on doing causal inference with "microlevel data" where we suspect that the treatment has spatial spillover & temporal carryover effects. We illustrate our new approach + package w/ application to US counterinsurgency efforts in Iraq
Spatiotemporal causal inference with arbitrary spillover and carryover effects
Micro-level data with granular spatial and temporal information are becoming increasingly available to social scientists. Most researchers aggregate such data into a convenient panel data format and a...
arxiv.org
April 7, 2025 at 11:58 PM
New paper alert (hey, I can't doom scroll all the time): This one's on doing causal inference with "microlevel data" where we suspect that the treatment has spatial spillover & temporal carryover effects. We illustrate our new approach + package w/ application to US counterinsurgency efforts in Iraq
How can we identify causal effects using micro-level data? Our new framework estimates ATEs, probes causal mechanisms, and uncovers heterogeneity—all in one. We illustrate it with an analysis of airstrikes and insurgent attacks in Iraq. arxiv.org/abs/2504.03464
Spatiotemporal causal inference with arbitrary spillover and carryover effects
Micro-level data with granular spatial and temporal information are becoming increasingly available to social scientists. Most researchers aggregate such data into a convenient panel data format and a...
arxiv.org
April 7, 2025 at 11:32 AM
How can we identify causal effects using micro-level data? Our new framework estimates ATEs, probes causal mechanisms, and uncovers heterogeneity—all in one. We illustrate it with an analysis of airstrikes and insurgent attacks in Iraq. arxiv.org/abs/2504.03464
Reposted by Mitsuru Mukaigawara
Here's one example of how we used geocausal to estimate the effects of different distributions of US airstrikes in Iraq on insurgent attacks (open access):
academic.oup.com/jrsssb/artic...
academic.oup.com/jrsssb/artic...
December 4, 2024 at 3:46 AM
Here's one example of how we used geocausal to estimate the effects of different distributions of US airstrikes in Iraq on insurgent attacks (open access):
academic.oup.com/jrsssb/artic...
academic.oup.com/jrsssb/artic...
Reposted by Mitsuru Mukaigawara
Want to do causal inference using high-frequency geospatial data with temporal carryover or spatial spillover effects? We've created a new R package, geocausal, that lets you estimate counterfactuals at user-specified intervals for different distributions of a treatment
github.com/mmukaigawara...
github.com/mmukaigawara...
GitHub - mmukaigawara/geocausal: Causal inference with spatio-temporal data in R
Causal inference with spatio-temporal data in R. Contribute to mmukaigawara/geocausal development by creating an account on GitHub.
github.com
November 19, 2024 at 3:21 AM
Want to do causal inference using high-frequency geospatial data with temporal carryover or spatial spillover effects? We've created a new R package, geocausal, that lets you estimate counterfactuals at user-specified intervals for different distributions of a treatment
github.com/mmukaigawara...
github.com/mmukaigawara...
Reposted by Mitsuru Mukaigawara
New in AJPS with @carlynwayne.bsky.social @mitsurumu.bsky.social @profmholmes.bsky.social: how do group dynamics affect assessments of resolve and costly signals? #polisky
onlinelibrary.wiley.com/doi/10.1111/...
onlinelibrary.wiley.com/doi/10.1111/...
August 12, 2024 at 3:10 PM
New in AJPS with @carlynwayne.bsky.social @mitsurumu.bsky.social @profmholmes.bsky.social: how do group dynamics affect assessments of resolve and costly signals? #polisky
onlinelibrary.wiley.com/doi/10.1111/...
onlinelibrary.wiley.com/doi/10.1111/...
Reposted by Mitsuru Mukaigawara
Interested in doing causal inference with spatio-temporal data? We've got a new R package, geocausal, that allows you to estimate causal effects + counterfactuals for super fine grained data over user-specified spatial + temporal windows.
Download it here. (Paper TK soon).
polisky
Download it here. (Paper TK soon).
polisky
GitHub - mmukaigawara/geocausal: Causal inference with spatio-temporal data in R
Causal inference with spatio-temporal data in R. Contribute to mmukaigawara/geocausal development by creating an account on GitHub.
github.com
October 12, 2023 at 12:59 AM
Interested in doing causal inference with spatio-temporal data? We've got a new R package, geocausal, that allows you to estimate causal effects + counterfactuals for super fine grained data over user-specified spatial + temporal windows.
Download it here. (Paper TK soon).
polisky
Download it here. (Paper TK soon).
polisky