## Abstract

Using an exhaustive database on academic publications in mathematics all over the world, we study the patterns of productivity by mathematicians over the period 1984–2006. We uncover some surprising facts, such as the weakness of age related decline in productivity and the relative symmetry of international movements, rejecting the presumption of a massive “brain drain” towards the US. We also analyze the determinants of success by top US departments. In conformity with recent studies in other fields, we find that selection effects are much stronger than local interaction effects: the best departments are most successful in hiring the most promising mathematicians, but not necessarily at stimulating positive externalities among them. Finally we analyze the impact of career choices by mathematicians: mobility almost always pays, but early specialization does not.

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## Notes

- 1.
To our knowledge, Borjas and Doran (2012) are the only ones to use the same source of data. They study the effects of the collapse of the Soviet Union and the influx of Soviet mathematicians after 1992 on the productivity of their American counterparts.

- 2.
- 3.
- 4.
- 5.
In all tables, *** means that the coefficient estimate is significantly different from zero at 1 percent level, ** at 5 percent and * at 10 percent.

- 6.
Recall that in our individual output measure, the impact of each paper is shared between the authors.

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## Additional information

We are grateful to *Mathematical Reviews*, published by the *American Mathematical Society*, for allowing us to use large data from their base to conduct the study presented here.

## Appendices

### Appendix 1: additional tables

See Tables 8, 9, 10, 11, 12,13,14,15,16,17, 18, 19, 20, 21, 22, 23 and 24 .

### Appendix 2: results based on the *Impact factor*

The data presented in this section are similar to those obtained in other parts of the paper. However, the basic indicators are based on the *IF* rather than on *MCQ*. More precisely, the weight attributed to each article is equal to the number of its pages times the *IF* of the journal where it is published, rather than the square of the *MCQ*.

Table 19 is the analog of Table 8.

Similarly, we have the analog of Table 9 in Table 20 with the impact of authors based on the *IF*.

We now consider the factors playing a part in a mathematician’s scientific productivity. Table 21 is the analog of Table 10 based on the *IF* rather than the *MCQ*.

The analog of Table 11 with the impact of authors based on the *IF* is in Table 22 . Finally, Table 23 is the analog of Table 7 based on the *IF*.

### Appendix 3: more on the data

Table 24 contain the list of journals used here. With each journal we list the total number of pages published in the sample period, the number of articles, the 2007 *M.C.Q*., the mean number of pages by article, and the mean number of authors by article. The code used for each journal (in the first column) should make it easy, for those who are familiar with the mathematical literature, to identify each journal.

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Dubois, P., Rochet, JC. & Schlenker, JM. Productivity and mobility in academic research: evidence from mathematicians.
*Scientometrics* **98, **1669–1701 (2014). https://doi.org/10.1007/s11192-013-1112-7

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### Keywords

- Faculty productivity
- Organization of research
- Peer effects in science

### JEL Classification

- D85
- I23
- J24
- L31