The Effect of Temporary Co-location on Knowledge Flows

# The Effect of Temporary Co-location on Knowledge Flows
## Evidence from NIH Study Sections
### Wei Yang Tham The Ohio State University
### October 13, 2018

---

## Discovery of The Double Helix

Central figures: Watson, Crick, Wilkins, and Franklin

**In 1951, Watson saw Wilkins present at a conference in Naples**

This encounter prompted Watson to move to Cambridge and change the direction of his research

---

## Research Question

Vast literature on spillovers, long-term interactions

"Cricket spills over into business" - Enrico Moretti's *The New Geography of Jobs*

What is the effect of short-term interactions on collaboration and knowledge diffusion?

Does networking have scientific value (collaborations, knowledge diffusion)? Or just "private" value (finding a job)?

???

If you're a policy maker trying to encourage more knowledge diffusion then knowing scientific/private distinction is important
    
---

## Empirical challenges
 
Data on short-term interactions is hard to find

Endogeneity of colocation - people aren't randomly in the same place

Measurement

<!--

## Related work

Boudreau et al (2017): scientists randomly assigned to breakout sessions more likely to apply for grant together

Campos, Leon, McQuillin (2018): Cancellation of major political science meeting due to hurricane led to reduction in coauthoring

Chai (2014): effect of conference 
@waldinger2018frontier
-->

---

## My approach

Quasi-experimental

Repeated interactions

Long-term outcomes

---

## Setting

---

## NIH study sections

NIH panels that evaluate grant applications

Convened by a Scientific Review Officer from the NIH

Organized around topics e.g. "Acute Neural Injury and Epilepsy", "Cellular Signaling and Regulatory Systems"

---

## Criteria for reviewer selection

1. Expertise

1. Study section must have enough breadth to cover its scientific area

---

## Permanent vs. Temporary Members

Permanent members serve 4-year terms, 3 meetings a year

Temporary members are recruited on an ad hoc basis

Temporary memberships are sometimes used as tryouts for permanent membership

---

## What happens in a study section?

Each application is assigned 3 reviewers

Reviewers present their assessment of the application and discussion opens up to rest of panel

**What potential is there for knowledge diffusion?** What do reviewers actually talk about?

---

## Are reviewers different enough?

"I was always a minority, a clinical cardiologist, not an engineer. **So it was my job to defend cardiology science and explain it**" - Dr. David Sahn, Oregon Health Sciences University

---

## Do they learn from each other?

"I've come away grateful for the opportunity and consciously aware that **I learned some new science** and developed skills to **interact with people with different attitudes and opinions**" - Dr. Alice Clark, University of Mississippi

???

Suggests

1. reviewers are not entirely familiar with each other's fields
1. there are learning opportunities within the reviewing process

---

## Intellectual similarity

If scientists are too similar, may already be familiar with each other's work

If scientists are too distant, may be harder to use each other's knowledge

Effects may vary by intellectual similarity and could be non-monotonic

---

# Data

---

## Study section rosters

List of reviewers who attended a particular meeting for a particular study section

---

## Author-ity

Dataset of disambiguated author names ("John Smith" problem)

Derived from MEDLINE, repository for biomedical literature

---

## Citations

Clarivate Analytics Web of Science

---

<!--
## Data

## Setup

Scientist pair (not ordered): `$(i, j) \equiv (j, i)$`

Pair-year panel

---

## Sample

Over 14000 individuals matched out of 19000

235 study sections

Each panel has 29 members on average

Time period: 1992 to 2010, but most meetings observed are in 2006 or earlier

---

# Estimation

---

## Identification

Limit to permanent members of study sections

Make use of fixed 4-year terms

---

## Identification

---

## Treatment intensity

---

## Identifying assumption

Use reviewer-pairs who served within 3 years of each other

If scientists `$i$` and `$j$` served on a study section, *when* they were on the study section is exogenous

---

## Model

`$$y_{ij, t} = \sum^{10}_{k = -10}\beta_k 1(K_{ij, t} = k)1(N_{ij} \in \{1, 2, 3\}) + \gamma_t + \delta_{ij} + \epsilon_{ij, t}$$`

`$k \equiv$` number of years since first colocation

`$N_{ij} \equiv$` number of years of overlap

`$y_{ij,t} \equiv$` number of times `$i$` and `$j$` have cited each other

`$\delta_{ij} \equiv$` pair fixed effects

`$\gamma_t \equiv$` year fixed effects

---

## Results

---

## Pre-trends

---

## Pre-trends

---

## Post-treatment

---

## Post-treatment

---

## Post-treatment

---

## 95% confidence intervals

```
NULL
```

---

## Discussion

Repeated interactions matter - familiarity matters, not just awareness

Effects may be persistent

---

## Future work

Other outcome variables of interest: collaborations, text measures of intellectual distance

Compare results for temporary members

Estimate specification with more structure

---

## Conclusion

Repeated short-term interactions matter

Some evidence (not shown) that heterogeneity matters

---

## Feel free to reach out!

weiyang.tham@gmail.com

@wytham88