Effect of Gender Quotas on Some Qualities of Elites

Context

"In 1993, a constitutional amendment was passed in India that called for a random* one-third of [the] village council leader, or sarpanch, positions in gram panchayat, to be reserved for women. The village council, which encompasses between five and fifteen villages, is responsible for the provision of local infrastructure - such as public buildings, water, and roads - and for identifying government program beneficiaries. Although all decisions in the village council are made by majority, the pradhan is the only full-time member and exercises significant control over the final council decisions. The village council is required to organize two village meetings per year, during which they present their proposed budget and report on their activities in the previous six months. The pradhan must also set up regular office hours where villagers can lodge complaints or requests."

via https://www.povertyactionlab.org/evaluation/influencing-provision-social-services-through-mandated-female-representation

*there is no mention of random. In fact, there is a separate callout that these seats can be allocated by rotation: "Not less than one-third (including the number of seats reserved for women belonging to the Scheduled Castes and the Scheduled Tribes) of the total number of seats to be filled by direct election in every Panchayat shall be reserved for women and such seats may be allotted by rotation to different constituencies in a Panchayat."

https://www.india.gov.in/my-government/constitution-india/amendments/constitution-india-seventy-third-amendment-act-1992

Hypotheses About the Effect of Gender Quotas on Quality of Elites

• Political Experience: Gender quotas in local electoral bodies are at least initially likely to cause candidates who are less experienced in politics. (In fact, that is one of the reasons for reserving seats for women.)

• Criminal Record: Given women commit crime at vastly lower rates than men, we expect quotas to cause candidates with smaller criminal record.

• Education: Given the inequalities in education, we expect gender quotas to cause less educated candidates (at least initially).

• Occupation: Again, given inequalities in opportunities to work, we expect gender quotas to cause candidates who are not working professionally and given differences in human capital (caused by inequality in education, etc.), more blue-collar jobs.

• Age: We expect gender quotas to cause younger candidates.

Some research suggests that how educated a politician is matters for growth (in certain contexts) (see here). Other research suggests that candidates with criminal records cause poverty. (see here).

Caveat = None of this is to say that the net output would be lower. In fact, there is plenty of research that suggests some positive consequences of reserving local body seats for women. The point may help with the interpretation of those effects.

Prior Research

See Table 3A here: https://www.nber.org/system/files/working_papers/w8615/w8615.pdf (Chattopadhyay and Duflo 2001)

See Table 8 and 9 here: https://vijayendrarao.org/papers/EDCC_Reservations_to_go.pdf (Ban and Rao 2008)

They find yet more dramatic differences even when constraining themselves to SC/ST seats where they argue the differences are likely smaller.

Results

Table 1: Bihar 2016 Sarpanch

reservation_status	prop_illiterate	prop_graduate_or_more	mean_age	n
अनारक्षित	0.02	0.15	46.86	17345
अनारक्षित(महिला)	0.08	0.04	41.35	13776
अनुसूचित जनजाति	0.01	0.05	44.53	293
अनुसूचित जनजाति(महिला)	0.05	0.02	38.03	62
अनुसूचित जाति	0.05	0.09	44.78	3976
अनुसूचित जाति(महिला)	0.11	0.02	39.31	2243
पिछड़ा वर्ग	0.03	0.09	46.19	4654
पिछड़ा वर्ग(महिला)	0.10	0.02	40.44	2683

Table 2: UP 2015

reservation_status	prop_illiterate	prop_college_or_more	n
अनारक्षित	0.08	0.26	73410
अनुसूचित जनजाति	0.10	0.19	620
अनुसूचित जनजाति महिला	0.26	0.23	699
अनुसूचित जाति	0.16	0.15	26875
अनुसूचित जाति महिला	0.32	0.09	17513
अन्य पिछड़ा वर्ग	0.11	0.20	34504
अन्य पिछड़ा वर्ग महिला	0.25	0.12	20819
महिला	0.21	0.15	32193

Table 3: UP 2021

reservation	prop_illiterate	prop_college_or_more	n
अनारक्षित	0.09	0.17	126028
अनुसूचित जनजाति	0.11	0.10	1034
अनुसूचित जनजाति महिला	0.21	0.07	678
अनुसूचित जाति	0.13	0.12	55808
अनुसूचित जाति महिला	0.24	0.07	29993
अन्य पिछड़ा वर्ग	0.10	0.15	64610
अन्य पिछड़ा वर्ग महिला	0.21	0.09	32028
महिला	0.17	0.11	62917

Table 4: Rajasthan Municipal

ward_cat	prop_hs_or_less	mean_age	n
gen women	0.73	41	396
general	0.64	42	870
obc	0.67	42	287
obc women	0.77	41	148
sc	0.67	40	203
sc women	0.80	35	104
st	0.68	39	50
st women	0.86	37	21
women	0.81	43	26

But Kerala provides a nice counter-example with very small differences

Table 5: Kerala

LGI Type	Reservation	hs_or_below	prop_bachelors	prop_masters_or_above	prop_other	n
Block	General	0.60	0.22	0.05	0.13	2478
Block	Woman	0.66	0.18	0.04	0.12	2988
Block	SC	0.71	0.09	0.03	0.16	446
Block	SC Woman	0.74	0.12	0.02	0.12	214
Block	ST	0.78	0.03	0.02	0.17	60
Block	ST Woman	0.91	0.03	0.03	0.03	32
Corporation	General	0.59	0.21	0.04	0.16	556
Corporation	Woman	0.47	0.30	0.08	0.15	551
Corporation	SC	0.66	0.17	0.00	0.17	35
Corporation	SC Woman	0.60	0.14	0.07	0.19	43
District	General	0.36	0.40	0.07	0.17	429
District	Woman	0.44	0.36	0.07	0.13	449
District	SC	0.57	0.27	0.00	0.16	51
District	SC Woman	0.38	0.38	0.15	0.10	48
District	ST	0.67	0.25	0.00	0.08	12
District	ST Woman	1.00	0.00	0.00	0.00	4
Grama Panchayat	General	0.69	0.12	0.03	0.15	20149
Grama Panchayat	Woman	0.72	0.12	0.03	0.13	22456
Grama Panchayat	SC	0.77	0.07	0.02	0.14	2924
Grama Panchayat	SC Woman	0.76	0.09	0.02	0.13	2250
Grama Panchayat	ST	0.79	0.03	0.01	0.18	425
Grama Panchayat	ST Woman	0.81	0.02	0.00	0.17	310
Municipality	General	0.68	0.16	0.05	0.11	3840
Municipality	Woman	0.68	0.17	0.04	0.10	3908
Municipality	SC	0.79	0.09	0.03	0.09	297
Municipality	SC Woman	0.70	0.14	0.05	0.12	307
Municipality	ST	0.83	0.06	0.00	0.11	18
Municipality	ST Woman	0.81	0.00	0.00	0.19	16