Polity size and local government performance: evidence from India: Comments

Macartan Humphreys

So much to like here

  • Smart
  • Policy relevant
  • Rich theoretical questions and nice engagement with mechanisms
  • Very clearly done and cleanly written

So much good news!

My comments mostly marginal

RD

Identification uses fact that:

“villages whose population exceeds one thousand should be allocated into their own GP” 1995/ 2015

RD

  • Note heterogeneity on left (and in principle on right)
  • Note some non defined potential outcomes (missing blues)

Innovation

Two strategies:

For leavers:

\[\mathbb E_x\mathbb E_{i\in A_x}[y_{i}(x) - y_i(1000)]\] where \(A_x\) is the set of villages with population around 1000 in a GP of size \(x\).

For remainers

\[\mathbb E_x\mathbb E_{i\in B_x}[y_i(x) - y_i(x-1000)]\]

where \(B_x\) is the set of villages with neighbor village around 1000 in a GP of size \(x\).

Comparison

  • Strategy 1: is a drop from a given size to 1000
  • Strategy 2: is a drop from a given size by 1000

Note:

  • Strategy 1 captures the effects of being in a new smaller GP
  • Strategy 2 captures the effects of being in an old, now smaller, GP

Average effect of dropping by 1000 seems more interpretable than effect of dropping to 1000. More like a derivative!

Observations

Even with this cleverness:

  • Particular set of comparisons.
  • Unclear comparability across comparison groups

To discuss

  • How comparable are the average numbers between strategy 1 and 2? Quite different estimands.

  • How interpretible are differences between strata? these are not as-if random

To discuss

  • Substantive 1: How much of this could be novelty effects?

  • Substantive 2: Are there fixed costs per unit? Are smaller units more expensive with very diffuse costs? Interpretation if this is a transfer

Estimand of most interest?

  • Effect of reduction or optimal size?
  • Can you predict levels? (Have you considered more structural analysis also?)

Note on comparing interactions strategy 1 and 2

Clarifying this might help with interpreting interactions:

Interaction inferences: Consider the difference between

  • A: 1800 -> (800, 1000) and
  • B: 2800 -> (1800, 1000)

For the splitter B is a bigger shock than A

For the remainer A is a bigger shock than B

So

Inquiry:

  • Can you fill out the potential outcomes schedule?
  • Can you get a handle on when small is too small?

And

  • Can you challenge the novelty interpretation?

End

Small and curmudgeonly

  • Did you consider pre-registering

  • Rumps could be so small?

  • Comment strategy 2: Is taking size of largest the most efficient? Multiple leavers? Predicable population growth: can you use the prediction around 1000.

  • Tables and Figures in text please!

Theories

  • Collective action
  • Homogeneity of preferences
  • Competition

BUt:

  • Economies of scale
  • Capture
  • Externalities
  • Small talent pools