The Consequences of Caste in Village India

On the role of culture in economic life

The lives of billions of people are dominated by the culture they were born into. Where you live, what you do, who you marry, and your obligations and duties are the product of rigid social norms and customs. These customs did not arise at random. They are adaptive, successful responses to a past environment. Many of them raised welfare in the past. Now, however, they are customs out of time. They prevent India – and developing countries all around the world – from achieving what is possible.

Nowhere is this more clear than in the rural agrarian village. Let’s call our village Rampur. It is in the north of India, somewhere outside Lucknow, in the Gangetic plain of Uttar Pradesh. It has a tight residential core of 20 acres in which 1,000 people reside, and surrounding fields of 300 acres of agricultural land. This village is fictional, but aside from it not existing, it is otherwise indistinguishable from thousands of other villages.

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Where people live is strictly delineated by caste and religion. There are four big hierarchical castes, or varnas, taken in order Brahmins, Kshatriyas, Vaishyas, and Shudras, and underneath everyone the untouchables, or Dalits. Each of these umbrella castes is divided up into jati, which traditionally correspond to occupations. Each jati has its own lane in the village, a gali. It looks something like this.

At the center of the village are the high caste individuals, the Thakurs (landowners) and Brahmins (priestly caste, though most are simply landowners). Further out are cultivator castes – Yadhavs, Kurmis, Lodhs, Kachhis, etc – each of whom have reputations for specializing in particular things (the Kurmis as tillers of the land and so on), and the service castes, of which there are many. They have a particular job that is theirs by tradition, the Nai being the barbers, the Lohar the blacksmiths, the Dhobi the washermen, and so on. Traditionally they would do these jobs at the command of the high caste individuals in exchange for shares of grain, but this part has broken down and they work for cash. I listed out the jatis which appear in our village of Rampur, but I emphasize that there are a lot of these. In the 2006 round of the Rural Economic Development Survey, in the 202 villages included, with 99,760 house total, there were 3,266 unique sub-castes.

The Dalits, formerly the untouchables, are outside the caste system, though they have their own particular castes. They live outside the village because they are dirty, and cannot ritually pollute the well. (It used to be that a village was centered around a single well, controlled by the high caste – to get water, a Dalit would have to get a high caste individual to draw it for him, taking care never to touch him, or to let his shadow fall across the high caste individual. Water access is much more common now, with millions of wells being installed starting in the 1970s.) Now the Dalits live in the outskirts, in a little hamlet, strictly downstream. The dirty jobs, like leatherwork and funerals, are reserved to them, but for the most part they are landless laborers. There are also government jobs and spots in higher education reserved for Scheduled Castes, Scheduled Tribes, and Other Backwards Castes, including the Dalits.

The Muslims live separately, but they retain their own castes. Christians are rare in Uttar Pradesh, and there are none in our village of Rampur, but for the sake of completeness I note that they are fairly common in the south of India, especially the parts exposed to trade, and they retain castes.

Each village, or a small cluster of villages, has its own local government, the gram panchayat. These exist mainly as administrators for various government benefits, and do not themselves levy taxes. Elections are held every five years. Voting is essentially along caste lines, but only the narrow castes. Within the backward castes, they are often fighting for the same resources earmarked toward them. Landowners and local elites are able to use their control of local resources to influence outcomes (Anderson, Francois, and Kotwal, 2015).

People only marry within their jati, the narrow occupational castes. This pattern of endogamy is ancient, dating back at least 2,000 years. (How do we know this? When people mate, they exchange whole chromosomes. When they form new gametes through meiosis, these chromosomes get chopped to bits and reassembled. We can infer from how “chopped up” people’s genes are how long it must have been since they last intermixed. For more, see (Moorjani et al., 2013)). The higher castes tend to have a greater proportion of Aryan ancestry, but this does not correspond to an American conception of race, with north-south geography being more important for that.

People never, however, marry within their village. Under no circumstances can someone marry another in the same village, and it would be as shocking as marrying your brother. Since these occur at arm’s length, “love marriages” are extremely rare. Less than 5% of marriages were chosen without the involvement of the parents. The bride goes to live with the groom’s family. Since this is a burden to them, a dowry must be paid.

The paying of a dowry is technically illegal, and has been since 1961, but it is universally ignored. This dowry is substantial – it essentially corresponds to an inheritance paid before anyone has died. A family might have to transfer several years worth of income. Conflicts over the size of the dowry are common. The receiving family does not want to take on the burden of the daughter without appropriate compensation. In our region of Uttar Pradesh, 2,000 women die every year over dowry disputes, and this is the tip of the iceberg of the violent extortion of the bride’s family.

Women rarely work formally, and this declines as families get wealthier. There is a strong norm against women working, and a stronger norm against working outside the house, where they cannot be supervised and might do something dishonorable with a man. Men are preferred to women at birth, and especially for later births to families without a son, there will be sex selective abortions and feticide of daughters.

Production revolves around the seasons, with two, sometimes three, crops planted. Water for irrigating the rice crop comes from the monsoon season, with the rain coming in early summer. This is harvested in September. Wheat, which is much more drought tolerant, is planted in November and harvested in March. Sometimes, a third crop of lentils can be planted immediately after the rice crop is harvested. The fields are plowed with oxen, which the Hindus cannot kill. They are kept for dairy, which is a source of both consumption smoothing and protein. Cows are sacred, and stray cattle are a persistent annoyance. The Muslims have an important role in doing the dirty work and slaughtering bullocks (in Uttar Pradesh, killing female cows is forbidden).

This cyclicality means that there is either lots of work to do, or very little. During the lean season, families draw down their savings, and try to find some form of work to do. The Indian government guaranteed 100 days a year of employment to rural households (now 125, as of 2025), mostly earthwork – digging ditches, irrigation canals, and the like. Other common jobs are firing bricks, or making textiles.

The other option is to migrate temporarily, working in the city for a season. Most people do not move permanently, but return to their home village at the end of the season. If one is willing to work for a longer period, they can go abroad to Saudi Arabia and the UAE, with at least several hundred thousand people doing this.

A day in the fields begins with walking out before dawn. It is customary to defecate now into the fields. In 2015, 55% of individuals reported open defecation in the countryside. Since this was something of an embarrassment to the national government, the Swachh Bharat Mission built toilets across India. However, the open defecation rate remains high, at around 28%. This has deleterious effects on the health of the community, and likely accounts for why children are still shorter than in Africa. Muslims are more likely to use toilets than Hindus, and their children are more likely to live, despite being poorer than Hindus, which indicates that what is driving this are customary beliefs about fecal matter being ritually polluting. Only the very lowest of the untouchables engage in cleaning out latrines. (Manual scavenging is, like dowry, both illegal and widespread.)

If they are a child, one would go to school. An ordinary school might look like this.

Enrollment is universal. Everyone, both male and female, goes to a school. The school they go to is not unlikely to be private, as around 35% of children in Uttar Pradesh go to private schools. (I am confident that higher figures are the result of people misreporting where they actually attend school). Private schools are more likely to be attended by boys within the family, and by richer castes. Females drop out much earlier than men. The main reason that they go to high school at all is to increase their prospects on the marriage market (Andrew and Adams, 2025), as they are unlikely to be working.

The government schools were notoriously unable to make teachers show up – Chaudhury et al (2006) reported on spot checks around the world. In India, a quarter of primary school teachers were not there when the enumerator dropped, and half of them were not teaching at the moment they dropped by. Across 3,000 schools, they could elicit exactly one case of a teacher being fired for absence.

Learning outcomes are poor. We are not entirely sure how poor, because India has only participated in one internationally comparable test, in 2009. They finished 71st out of 72 nations (beating only Kyrgyzstan), and have found lame excuses not to participate in any further testing. Most of the people in our village will be illiterate and innumerate. Across the whole of India, 45% of students in the 8th standard (about 13 years old) could solve arithmetic problems. The census figures, which will tell you that literacy is between 70 and 80%, are wrong, because they are purely from self-reported figures. If you actually ask people to read a text at the second grade level, they will perform much worse. In Uttar Pradesh, which is middle of the pack, 28% of children in third grade could read a second grade text in 2024 (Aser Report, p. 25) and this is actually a great improvement over the 6% who could in 2014. By the time we get to 8th grade, 67% of students in government schools can read a second grade text, and 45% can do division (p. 62-63).

Healthcare is similarly provided. There is an official, government provided healthcare network, and there are private providers. The government system is in three tiers, with local nurses for every few villages referring complicated cases up to primary health centers, and then up another tier to district hospitals. Nevertheless, private providers are common.The private providers are more expensive, but trade that for reliability. The Chaudhury et al survey found that 40% of healthcare workers were absent when they dropped by. This absence is aided and abetted by local political forces, who view it as an opportunity for patronage more than doing the job. Banerjee, Glennerster, and Duflo (2008), in the most caustic paper I have ever seen them write, characterized monitoring for attendance as like “putting a band-aid on a corpse”. When they installed time clocks to monitor attendance, within 18 months the treated places had either had the time clocks “accidentally” broken, or the now monitored absenteeism was excused by the local government.

Those are the important details of life in a rural Indian village. Who you marry and what you do are bound up with who you were born to. While the details are specific, the generalities are universal. Village life from Uganda to Thailand is fundamentally similar to one another, and the lessons we learn from one place can be ported to another. In the next section, we will cover how these customs arose, the problems that they solved then, and why they are bad now.

The principal concern of the farmer is risk. The crops cannot fail. If they fail, you die. It is much more important to avoid a catastrophic fall in income than to have a higher standard of living most of the time. So, people shade their decisions – they spend less on intermediate inputs, choose crops which are less dependent on rainfall, scatter their fields rather than have them all in one place, and invest in livestock with a low rate of return but which provide something all year round.

They also save, and when that isn’t enough, they importune their relatives. These obligations to provide to your relatives is a form of insurance, of immense quantitative importance and surprising effectiveness.

Robert Townsend (1994) proposes a simple test for full insurance, which he tests against a sample of rural Indian villages. If risk is perfectly shared across a village, then individual consumption should not vary after controlling for variance in aggregate consumption. He finds that the data rejects full insurance, but it comes remarkably close.

Townsend is agnostic as to what, exactly, the cause of the insurance is – it is sufficient, for his framework, that the risk be insured through something – but the best explanation for coming close to full insurance are the ties of caste. Kinship networks allow for the risk to be shared across many people. Your fields may have been obliterated by a freak hailstorm, but your neighbors’ fields were not, and certainly not the people in the same caste in other villages.

Townsend’s original paper is imperfect in two main ways, but they both point to him undermeasuring the extent of full insurance. First, the relevant unit is the kinship group, not the village. Munshi and Rosenzweig (2012) found that most transfers are between villages, if overwhelmingly within caste. The proper standard for full insurance is not village consumption, but average caste income across local villages. Second, Townsend is forced to make the assumption that the risk preferences of everyone are identical, or at the very least all come from the family of constant absolute risk aversion utility functions. If, however, some people prefer greater risks than others (in a way not captured by the demographic and income controls intended to sweep up some obvious confounds, like richer people having a greater stock of savings and thus inherently having smoother consumption) this will bias you away from accurately measuring full insurance.

Both of these imperfections in Townsend’s paper, however, suggest that informal insurance is even stronger than we thought. Both inject noise, and removing them makes the case stronger. The definitive treatment is Mazzocco and Saini (2012), who emphatically reject people having identical risk preferences, and while rejecting full insurance at the village level, cannot reject full insurance at the caste level.

But this insurance comes at a cost. It is not the insurance you sign with a company which has clearly defined obligations and benefits, but a latent claim of relatives against anyone who should come into money. It is a tax, and a punitive one.

Some of the idea of the magnitude can be given from a clever experiment conducted by Carranza, Donald, Grosset-Touba, and Kaur (2025), in the Ivory Coast. They offer cashew processors the option of a blocked savings account into which they can deposit a part of their paycheck. These savings accounts do not pay interest. They exist solely to prevent one from being able to access the money for nine months. It is surprising that anyone would take up the offer, and yet many do. Because they are working at a job with pay tied strictly to productivity, through a piece rate system, we can observe how much more people are willing to work when their relatives don’t know how much they’re making.

The effects are tremendous. Earnings rise 9.4%, and attendance rises 6.5%. These gains are observed only when family members don’t know about the accounts. When they do, very few people are inclined to take up the account, ruling out that this is about self-control for the worker. The implied tax rate of the family cannot be directly known without knowing the labor supply elasticity for the workers, but we can put bounds on it through estimates elsewhere. The high end estimates of the labor supply elasticity imply that the workers who took up the account faced a tax rate on the order of 65% of additional earnings, and the lowest tax rate it could plausibly be is around 20% of income.

This finding is extremely well-replicated. Frankly, you can just go out and talk to people and see that this is true, but there are also numerous lab experiments (e.g. Jakiela and Ozier, 2016). Munir Squires (2024) also does a lab experiment, and points out that the effects of the social tax are especially binding on those with the most skill. This misallocation, in his model, lowered productivity by a quarter. People will also borrow at a considerable interest rate money which they already have themselves in savings. Baland, Guirkinger, and Mali (2011) report that in their sample in Cameroon, a fifth of borrowers pay a net interest rate of 25% a year just to hide away their income.

The social obligations which sustain coinsurance make it much harder to migrate. If you move to a far away city, who are you going to marry? India is surprisingly non-urbanized for a country of its level of development. I believe that caste is substantially connected to this.

An illustration from Bangladesh, which is sufficiently similar for lessons there to apply to India. In the early 2010s, we got quite excited by some studies which subsidized people to migrate to the cities. Bryan, Chowdhury, and Mobarak (2014) found that a small subsidy caused 22% of households to send a migrant, greatly increasing their wages. Wages are just higher in urban areas. However, when we inquire into the deeper causes, as Lagakos, Mobarak, and Waugh (2023) do, we find that the main thing keeping people from moving is an enormous disutility from being in the city. What might this be? The soundest explanation, I think, is that you will lose access to your kinship networks, including your ability to marry.

(I explained this methodology in some detail under Kaboski and Townsend (2011) in an earlier post on microfinance, which I am naturally eager for you to read. Essentially you write down a model which from inspection seems to capture everything of importance, and simulate it over and over again until you match the data details of the period before the intervention. If your model is correct, then changing one of the parameters in line with the intervention – in this case, changing the cost of moving – should result in matching the data, and it does.)

Munshi and Rosenzweig (2016) test for who is likely to migrate, if castes are providing insurance. We would expect the people who are wealthier to send more migrants in order to escape the demand of their families, and for people in a worse position to stay. You might reasonably point out that we would expect richer families to differ in their skill, perhaps investing more into education, and so have a higher gain from migrating; but they sidestep this by pointing out that what matters is whether they are a rich family only relative to the rest of their caste. Holding income constant, you can see how much relative position matters for migration (quite a lot).

We also have some unexpected evidence from the United States. Ghosh, Hwang, and Squires (2023) infer the effect of cousin marriage bans in different U.S. states through changes in the frequency of same-surname marriages, which can stand in for cousin marriage. Places that had higher rates of cousin marriage are more likely to migrate off the farm and into higher-paying jobs, and are also more likely to live in homes for the elderly as a consequence of weaker family ties.

The need to maintain kinship networks leads inexorably to dowry, and the pattern of marriage in India. Marriages simply must be arranged in such a world. You cannot chance your children falling in love with someone outside of the caste, and the cultural separation needed to sustain endogamy without force is on the level of the Amish. In any case, once you have restricted your marriage prospects in each village to a cluster of 30 households, you would become hopelessly inbred. It would be too costly – more so in the past – to have people travel tens of miles just to interact with potential suitors, so instead it’s treated as a business decision and negotiated.

Daughters go to live with the groom’s family, and for this a price must be paid. This is not universal, however. Many other places have the sons live with the family of the daughter. The fundamental cause is the form of agriculture, and whether it requires the hoe or the plow. Hoe agriculture, commonly used for root crops, is labor intensive, but does not require anyone to be unusually strong. Women can do this, and in places with hoe agriculture, work in the fields. The plow, on the other hand, requires considerable upper body strength to operate. (It also reduces the need for weeding, which women and children might specialize in).

It is little surprise, then, that the direction of where people go to live, and where the price for marriage flows, varies with agricultural opportunities. Much of Africa pays a bride price, because much agriculture is hoe agriculture. Much of India – including our village of Rampur – is plow based agriculture, and women are not involved with cultivation. This has a long run effect on gender attitudes – Alesina, Giuliano and Nunn (2012) find that places which kept women in the house due to agriculture in the past have worse attitudes towards gender equality today, and that these norms are carried with them when they migrate elsewhere.

The payment of dowry is bound up with informal insurance. The timing of marriages are affected by droughts and other shocks. In India, a drought increases the age at which marriage occurs, while in Africa it decreases the age at which it occurs. In the former, the shock to savings means that the family must wait longer before they can afford it, while in the latter the family is more eager to sell the bride for cash to get by. Dowry thus forces families to maintain a stock of savings above what they would otherwise, and allows other people to make claims against it.

The transaction is not concluded when the dowry is paid on the wedding day. The groom’s family will continue to make claims, prompted by some necessity – sickness, Diwali, the breakdown of a motorbike – and backed up by the threat of violence against the bride. Violence against women is incredibly common in India, with 28% of women across the country reporting having been physically abused in the past year. About 5,700 women a year are killed due to disputes over dowry, with Uttar Pradesh accounting for 2,000 of them. The paradigmatic example is the bride burning, where the woman is covered in kerosene and set alight, with the aim of blaming it on a household accident or suicide. It’s a really ugly part of rural life, yet common. (I’ve received some pushback on this claim. Yes, 28% in the past year is correct. NFHS survey, page 680. The most common form is that 25% of women report being slapped by their husband.)

The low labor force participation rate among women can be thought of as the solution to a principal-agent problem. The groom’s family, in particular the mother-in-law, would like to extract surplus from the bride. Allowing her to work outside the house might well have higher potential earnings, but they are earnings which she could spend on herself, or transfer back to her family. Forcing her to work on unremunerated household tasks means that the family captures her whole surplus. If this model is right, then whether someone is mobile should be affected by whether the mother-in-law is alive, and indeed it is.

Paying dowry also means that it is easier to abuse the bride because the outside option of the bride is worse. She cannot return to her family – not when they have given much of their savings to pay for her to another family. So she stays, abused by the family. At least when she has sons, she’ll be able to exploit their wives!

I do not want to overstate the economic story too much. Much of the opposition to working outside of the house is plain old sexual jealousy. Kailash Rajah (2025) shows that women are much more likely to apply to or accept a job at a woman’s only work force, and that not going to the job is much more common among women with jealous husbands. And it’s entirely possible that the main problem is patrilocality, rather than the paying of a dowry per se, at least for domestic violence. And some of it is the compounding effect of parent’s beliefs about the future – with worse labor market outcomes expected, parents invest less in their children, who then are less likely to work. But there is no reason to expect women to be unable to work in India, and many reasons to think that this is making them poorer.

I am not convinced by the claim that there has been a major reversal in trend for female labor force participation in the past few years. Measured female labor force participation increased from from 24% to 47% between 2017 and 2023, but this was probably driven by changes in the definition of employment, where women doing activities like working in a small garden around the house or collecting firewood are now self-employed (Thakur and Chaudhary, 2024). In the cross-section, families which are wealthier have women who work less.

Who works is not the only thing affected by customary beliefs. Even among the men, who works which jobs are affected by custom. Jati are traditionally associated with very particular jobs, with different jati having feudal obligations to each other. People only performing the jobs of their forefathers is no longer as set as it once was. The modern economy is different enough, and outside options are good enough, that people are no longer bound to particular jobs. There is still, however, a considerable preference to not work jobs not associated with your caste.

Suanna Oh (2023) is a remarkably direct test of how much people are willing to pay to avoid out-of-caste tasks. They start by identifying what jobs are associated with which castes. They’re pretty narrow. For instance, the Dhoba are associated with washing clothes, but not with washing anything else. The Hari (who are untouchables, and universally agreed in the survey to be the lowest caste among those ranked) will sweep latrines, but will not sweep animal stalls.

Each person is hired for a default task without a caste connotation (assembling paper bags) and an additional task which is revealed in private. The experimenters vary the task that is offered, the wage at which it is offered, and the time spent doing it. The idea behind varying the time spent is that we want to be sure we are picking up the disutility from one’s identity being violated, rather than simply the disutility from exerting effort on that task.

People absolutely do not want to do lower caste jobs, and to a lesser extent don’t want to do higher caste jobs either.

They run a second experiment where they surprise people who they’ve hired to assemble paper bags with a request that they perform a task for a bonus. The results are even more astonishing – 43% of workers would refuse to do a task outside their identity for 10 minutes, even for 10 times their daily wage. It’s not a matter of effort expended, as it’s flat across the time increments. Instead, people have a conception of themselves as a person who does x and not y, and will not budge for filthy lucre. This tracks with historical evidence – Alexander Persaud (2023) found that immigrants to Fiji from high castes were willing to pay much more – 2 and a half years of wages – in order to return home.

This is pretty bad for society! We know from the United States that race and sex discrimination led to substantial misallocation of labor, and Hsieh, Hurst, Jones, and Klenow (2019) argue that 20 to 40% of growth between 1960 and 2010 can be explained by people reallocating to what their comparative advantage is. Cassan, Keniston, and Kleineberg (2022) pursue a similar exercise, and find that removing the caste preference for certain occupations could substantially raise income. I would like to point out that I disagree with much of their analysis, though. They are more pessimistic, because they believe that caste leads to greater training and skill accumulation in certain jobs. I agree that castes likely do do this, and that there is some role for training – Hardy and McCasland (2022) find that small firms in Ghana, for instance, have room for more labor, they just don’t want to pay the cost of finding a good one – but I am skeptical that their estimates of the returns to skill are actually reflecting skill, and not rents. In other words, people working in their parents occupation are more productive, in the sense that they earn more, but this need not reflect them actually being better at their jobs. Thankfully, though, the distortion is mostly in low-skilled jobs in the countryside, and once people enter the modern economy old caste preferences are of less importance. Still, though, caste preferences can keep people in the old economy by changing schooling choices – Munshi and Rosenzweig (2006) show that lower caste networks chose local language schooling, even though English language schooling enables people to work in better jobs.

Being in a kinship group allows them to act in a coordinated fashion, but this need not be good. Cooperation with your fellow man is certainly good in general, but it need not be if you are an army cooperating to invade another country. Similarly, the bonds of caste and family allow groups to extract rents from each other, a practice which is good when you alone do it and bad when everyone else does it.

For instance, wages are surprisingly sticky in Rampur. When rainfall is good and there is a positive demand shock for labor, nominal wages increase. When times are bad, they do not fall. It takes inflation to get rid of the high real wages. Until then, people are simply unemployed. (Note that one must be careful in dealing with self-employment. By and large, when someone is self-employed in a village, this is disguised unemployment). Supreet Kaur (2019) estimates that this nominal wage rigidity reduces employment by 9%, which is absolutely enormous, and like having the Great Recession but worse pretty much all the time.

This is not something which people are willing to abide by, if it weren’t for the transactions being observed and people being able to retaliate against those who break the norms. Breza, Kaur, and Krishnaswamy (2026) find that less than 2% of workers would accept a job 10% below the prevailing wage if it were proposed in public, but fully a quarter would if the offer is made in private, in the home. When they survey people as to why, they make it clear that it’s against the norms of the community to accept wages that undercut other workers.

This is a really big deal! Labor rationing is ubiquitous in Indian labor markets, with Breza, Kaur, and Shamdasani (2021) showing by inducing surges in hiring that pulling people out of the local labor market leaves wages unchanged in the lean months, but increases wages in the peak months. At least a quarter of self-employment is because they cannot find work at the prevailing wages.

Personal contact holding up collusive arrangements is likely widespread in the developing world although we do not know the full extent, as collusion is difficult to measure even with excellent data. Bergquist and Dinerstein (2021) find that maize traders will collude with those they know in order to hold up prices in Kenya, and Garima Sharma (2025) finds that wages for garment workers in Tirupur are held at minimum wage by collusive cartels of garment factories. It’s worth pointing out here that clusters of businesses in cities tend overwhelmingly to be run by people in the same kinship network.

It goes without saying that caste solidarity leads to discrimination. Soumitra Shukla (2026), working with multinationals hiring from elite Indian colleges, shows that despite lower-caste individuals being more likely to be promoted and less likely to leave, they are weeded out by higher caste interviewers before they can be hired. It is striking how people with unambiguous surnames get stricken early on, while people with ambiguous surnames are removed only after the interview stage. Going back to Rampur and villages like it, low caste households have much worse access to water for irrigation if someone from a higher caste owns the water supply – Siwan Anderson (2011) finds that lower caste water buyers would have yields 45% higher if they were in a village where the water supplier was also of the same caste. It is striking that trade could even break down in the water market, because the good to be traded and the contracts needed are so simple. In kinship based societies, though, people have limited trust. Moscona, Nunn, and Robinson (2017) show that in places in Africa with similar customs, they trust the central government and outsiders less.

I am inclined to say, however, that the predominance of family firms in India is not due to caste or custom, but would be solved by a change in the legal environment. Firms are by and large owned by members of an immediate family, not shared among people in the broader jati. The better explanation for this is the slowness of the legal system making it impossible to discipline recalcitrant managers except through extralegal channels. As I have argued before in “What’s the Matter with India”, there are simply not enough judges. But we must move on.

Laws against firing people may also have a caste origin. Being unable to migrate, except in a group, means people will be around their family, even in the same job. Relatedly, recruiting was historically dependent upon caste ties. A company would pay an agent to go back to his village/region, and convince as many men as he could to come work. Once there, they cannot be thought to be maximizing their own individual utility as much as the utility of the collective.

Before the formation of India as an independent nation, this inhibited the formation of industry. Pseudoerasmus has an excellent article arguing that workers would not permit the use of labor-saving machinery, even if it meant that their own wages were raised. The unemployment of their relatives was unacceptable. Reading that article is a handy corrective, by the way, to the notion that the controllers of capital are invariably the ones with power in a relationship. Strikes were frequent, as the Bombay Presidency did not wish to upset the colonial subjects by coming down against the workers. Behind this was, naturally, the bonds of kinship, which made organization possible.

What is permitted to be done is bound up by culture. Textile factories in India required many more workers, even when using identical production technologies, because of strong norms against doing too much. Gregory Clark (1987) argued that workers didn’t want to look after too many machines and would prefer to be idle, even if they could increase their wages. To quote a contemporary observer, “The operatives in this mill refuse to attend to more machinery. I watched two ring frames for three minutes; there was not a single end down, yet the workpeople would not look after more than one side. They said they were satisfied with the present wage, and that there were too many men who want work and cannot get it that it would be unfair if they were to attend to more machines.”

This is all backward. Obviously it would be great if people simply lived and worked and created without market imperfections. Bargaining over rents through collective action can be fine. But we’re pretty sure that, under any reasonable world, one should not start out by trying to haggle over meagre gains. As Itskhoki and Moll (2019) point out, the optimal policy under realistic frictions is one where the government actively favors capital holders and holds down the wages of laborers, at least until growth is achieved. Strikingly, this logic holds even if one does not care about the welfare of entrepreneurs in the slightest.

The logic behind it is fairly intuitive. Suppose that entrepreneurs face borrowing constraints, modeled as a requirement to post collateral. They are unable to borrow as much as would be profitable, being limited by their own savings, and accumulate less capital than is optimal. Having more money earlier on leads the entrepreneurs to use the profits to finance yet more borrowing. Arbitrarily favoring them at first, by taxing labor to fund them, actually raises worker wages because it raises the amount of capital they are working with.

This pattern of forced savings is a common thread in countries which made the takeoff into sustained modern growth. South Korea did it, trying to keep wages below 80% of inflation plus productivity growth. China is still doing it, and has an astonishingly low labor share of income.

India did something like this, to their benefit. The 1991 reforms, which abolished the License Raj and made access to outside capital much easier for Indian companies, are commonly thought of as the start of modern Indian growth, but if you look at the time series it starts earlier, in the 1980s. Rodrick and Subramanian (2004) argue that the Indian National Congress, which had hitherto been a mix of Cambridge socialists and agrarian rusticists in the line of Gandhi, lost the election in 1977 and upon returning to power felt that they had to have better relations with the big businesses.

Still, though, Indian labor law is incredibly favorable to workers, on paper. You essentially cannot be fired, ever, not without government permission. What good does this do the people who are never hired? This is something which could be changed, thankfully, but to my mind it traces back to kinship solidarity, and thus to caste.

For India to grow, the jati must break. Clan obligations are incompatible with a rich, modern society. It is not enough to trust your family. You have to trust at least everyone in your nation.

It is difficult to see what India can do to undo caste, however. I certainly do not expect this article to sway government policy, and the fabric of life cannot be easily upturned. What little I can hope for is this – at least when people come to America, you should leave caste behind. It should simply be in bad taste – fundamentally un-American – to think about it or care.

In the realm of policies which are possible for disrupting caste, the provision of insurance is likely the best one available. The status quo is to provide government insurance through a paid work guarantee in the rural villages, but leaves people unable to move and still be insured against idiosyncratic risk. This also means that aid is administered by the gram panchayat, which as noted much earlier in the essay, is dominated by caste clientelism and may strengthen caste. Instead, insurance should be available for purchase by all people, whether or not they own land. (The current system of crop insurance, the PMFBY, does not allow you buy insurance if you do not own crops! Good luck if you are a landless laborer who needs to be hired by farmers! Munshi and Rosenzweig (2014) find that selling insurance to landowners makes wage laborers actively worse off, as cultivators shift to riskier crops). In a related line, better weather forecasts will also reduce the risk that farmers face. Reducing risk is good for its own sake, but it is also good because it supplants the caste system.

I do not agree, however, with removing the extensive reservations for lower castes for government jobs and higher education. Or at least, I am unconvinced that it is that which is responsible for caste’s prominence in Indian life. There’s a lot of active discrimination out there. Calls for removing it strike me as a cynical claim for resources, rather than seriously believing that people would just stop thinking about caste if it weren’t for the reservation system.

This article has focused on India. I do not believe that the lessons we draw from here, though, are particular to India. I believe that they touch upon something common to agrarian, kinship societies all around the world. Having family ties is beneficial when nothing can change, the world is harsh and unfriendly, and better things aren’t possible. When things improve, they hold us back. They will be, in part, dissolved by progress – but for progress to happen, we need to dissolve them first.