Income e inequalities .investment opportunities

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Draft: Not for quotation – 4.1 – Chapter 4 Inequality and investment 4.1 In a world where markets work perfectly, investment decisions should have verylittle to do with the income, wealth or social status of the decisionmaker. Whether aparticular piece of investment should be undertaken ought to be determined by the returnsit promises and the market price of capital, adjusted if necessary for the market price ofthe extra risk it entails. The logic is almost elementary. If someone has an opportunity tomake money, then it really does not matter whether she has the money—she can alwaysborrow what she needs, and if the risk bothers her, she can always sell shares in herbusiness on the stock market and buy safer assets with the money she gets from the sale.4.2 If this were indeed the world we live in, the distribution of wealth/income wouldhave no direct influence on the pattern of investment. There may still be an indirectinfluence, coming from the effect of wealth or income on savings decisions. It has beensuggested that the poor are less inclined to save than the rich, and as a result, aggregatesavings as a proportion of aggregate income may go up if the rich gain at the expense ofthe poor. This could affect investment decisions through the effect of the supply ofsavings on the price of capital. Inequality, in this Kaldorian view of the world (afterNicholas Kaldor, the Cambridge economist), would enhance growth, through it might yetbe a Pyrrhic victory. Kaldor worried about the inevitability of crises under capitalism,and he saw faster growth accompanied by burgeoning inequality as a recipe for ongoingcrises.4.3 The scope for a direct link between inequality and investment widenssubstantially once we give up the idea that markets, and especially asset markets, workanywhere close to perfectly. One of the great advances in development economics in thepast 15 years is the accretion of a substantial body of evidence on documenting how well(or badly) asset markets work in developing countries. It seems natural to start with thisevidence.How well do asset markets work?The market for credit4.4 A well-functioning credit market, as every student of basic economics knows, isone where there is a single interest rate and everyone can borrow or lend as much as hewants at that rate. The fact that anyone can borrow as much as he wants at the current rateis what explains the presumption of a separation between the wealth or status of theinvestor and the amount he invests. Whether he is rich or poor, well-connected or just offthe streets, an extra dollar of investment will be profitable for him if and only if the returnhe gets from it is more than the interest rate. If the interest rate is higher, he would bebetter off lending out that money if it was his own, or borrowing less if it were someoneelse’s. Therefore, two people with the same return on investment will end up investingthe same amount.1 1 Unless there are two different investment opportunities that have the exact same payoff, net of interest.
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Draft: Not for quotation – 4.2 -4.5 How close are real markets to this idealized market? Chambhar is a market townin Sindh, on the east bank of the Indus. In 1980-81 farmers from the area aroundChambhar got most of their credit from about 60 professional moneylenders. Based ondetailed data from 14 of these lenders and 60 of their clients (Aleem (1990)), the averageborrowing interest rate charged by these lenders seems to have been 78.5 percent. But ifthese farmers wanted to lend their money out, the banking system would only pay themabout 10 percent. It is possible, however, that they may not have been depositing in thebanks. An alternative measure of the deposit rate relevant for these farmers is theopportunity cost of capital to the moneylenders, which is 32.5 percent. In either case, itsuggests a gap of at least 45 percentage points between the borrowing and lending rates. 4.6 The borrowing rate also varied enormously across borrowers: The standarddeviation of the interest rate was 38.1 percent, compared with an average lending rate of78.5 percent. In other words, an interest rate of 2 percent and an interest rate of 150percent are both within two standard deviations of the mean. One possibility is that thesedifferences reflect differences in the default rate: perhaps the expected repayment is thesame for everybody, because those who pay higher rates are more likely to default. Alsothe expected repayment could be equal to the actual interest rate paid to the depositors, ifthe default rate is high enough. But default is actually very rare: the median default ratefor individual lenders is between 1.5 and 2 percent and the maximum is 10 percent.4.7 The same pattern—high and variable borrowing rates, much lower deposit ratesand low default rates—also shows up in the “Summary Report on Informal CreditMarkets in India” (Dasgupta, Nayar, and Associates (1989)). This report summarizesresults from a number of case studies commissioned by the Asian Development Bank andcarried out under the aegis of the National Institute of Public Finance and Policy. For theurban sector, the data are based on various case surveys of specific classes of informallenders: For the broad class of nonbank financial intermediaries called financecorporations, it is reported that the maximum deposit rate for loans of less than a year is12 percent while the minimum lending rate is 48 percent. These corporations offeradvances for a year or less at rates that vary from 48 percent a year to the utterlyastronomical rate of 5 percent a day. The rates on loans of more than a year variedbetween 24 percent and 48 percent. Default, once again, is only a small part of the story:default costs explain only 4 percent of total interest costs. The same report also tells usthat for hire-purchase companies in Delhi, the deposit rate was 14 percent and the lendingrate was at least 28 percent and could be as high as 41 percent. Default costs were 3percent of total interest costs.4.8 Table 4.1 reports borrowing rates from the rural version of the same report. Thiswas based on surveys of six villages in Kerala and Tamil Nadu, carried out by the Centrefor Development Studies, Trivandrum. Interest rates are high, but they are also variable.The rich (with Rs.100,000 or more in assets) get most of the credit (nearly 60 percent)and pay a relatively low rate (33 percent), while those with assets between Rs. 20,000 andRs. 30,000 pay rates of 104 percent and get only 8 percent of the credit. While notreported in the table, the average interest rate charged by professional moneylenders(who provide 45.6 percent of the credit) in these surveys is about 52 percent. While theaverage deposit rate is not reported, the maximum from all the case studies is 24 percent,
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Draft: Not for quotation – 4.3 -and the maximum in four out of the eight case studies is no more than 14 percent. In thecategory of professional moneylenders, about half the loans were at rates of 60 percent ormore, but another 40 percent or so had rates below 36 percent. Default rates were higherthan in the urban sector, but still cannot explain more than 23 percent of the interest costs. Table 4.1 Assets groups and loans, rural Kerala and Tamil NaduAsset group (RS)Average loan sizeAverage interestrate (percentage p.a)Cumulative proportionof credit0-5000799.845010.235000-10000116.6712010.7910000-15000633.373512.3115000-20000285.917113.9120000-3000066810421.9330000-50000652.55827.1550000-100,0001267.834841.34100,000 and above407533100**denotes one loan eachSource: Dasgupta, Nayar, andAssociates (1989). 4.9 The fact that credit access depends on social status, is also shown by Fafchamps’(2000) study of informal trade credit in Kenya and Zimbabwe. It reports an averagemonthly interest rate of 2.5 percent (corresponding to annualized rate of 34 percent) butalso notes that the rate for the dominant trading group (Indians in Kenya, whites inZimbabwe) is 2.5 percent a month while the blacks pay 5 percent a month in both places.24.10 None of these facts is necessarily surprising. Contract enforcement in developingcountries is often difficult, and it is not easy to get courts to punish recalcitrantborrowers.3 As a result, lenders often spend lots of resources making sure that their loansget repaid: it is plausible that these are the resources that drive a wedge between theborrowing rate and the lending rate. Indeed, Aleem (1990) actually calculates the amountof resources spent by lenders on monitoring borrowers and shows that they are enough toexplain the nearly 50 percentage point gap between the lending and borrowing rates in hisdata. Moreover, it is easy to imagine that borrowers who are easier to monitor will enjoybetter rates, which would explain why lending rates vary so much.4.11 Together, this body of evidence makes it very hard to believe that credit markets,at least in the developing world, are anywhere near the ideal market that would make thedistribution of wealth irrelevant for investment.The market for insurance4.12 The ideal insurance market is one in which people bear no avoidable risks. In asetting where a single village constitutes a separate insurance market closed to the rest ofthe world (so that only people in the village can insure other people in the village, insome kind of mutual insurance arrangement), this comes down to the requirement that 2 See also Gill and Singh (1977) and Swaminatan (1991).3 See Djankov and others.
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Draft: Not for quotation – 4.4 -individual consumption should respond only to aggregate (village-level) incomefluctuations, and not to fluctuations in the income of specific individuals. Put in blunterterms, your income fluctuations should not translate into fluctuations in your ownconsumption, as long as aggregate consumption is unchanged. Given that what anindividual does has very little impact on aggregate uncertainty, this means that wheninsurance markets work well, risk considerations should not have a significant impact onthe choices people make, irrespective of their wealth.4.13 While a perfect insurance market is a more complex object than a perfect creditmarket, and hence harder to detect, there have been attempts to test the prediction aboutthe irrelevance of fluctuations in your own income. The Côte d’Ivoire Living StandardsMeasurement Surveys from 1985 to 1987 provide panel data on the income andconsumption of up to 800 households, where each household is tracked for twoconsecutive years (1985 and 1986 or 1986 and 1987). The relation between changes inconsumption and changes in incomes is reported in table 4.2 separately for the three mainregions and separately for 1985-86 and 1986-87. The first row of the first block for eachyear reports the basic correlation between income and consumption: a fall in incomealways hurts consumption, though the coefficient varies between a low of 0.15 (a $1reduction in income means that consumption goes down by 15 percent) to a high of 0.46.The next row does the same thing, but now there is a village dummy intended to pick upany village-level changes in consumption. Remarkably, the coefficients on own income,which under perfect insurance should have fallen to zero once we controlled for village-level changes, almost do not budge at all.44.14 Not all the evidence is quite so pessimistic. Townsend (1994) used detailedhousehold-level data from four villages intensively studied by the International CropResearch Institute in the Semi-Arid Tropics (ICRISAT) in India, to see whether it isconsistent with the data. He found that while the data did reject the exact prediction, it didnot miss by very much. In other words, his evidence suggested that villagers do insureeach other to a considerable extent: movements in individual consumption in his dataseem largely uncorrelated with movements in income.4.15 Later work by Townsend himself based on data he collected in Thailand, turnedout to be less encouraging.5 Some villages seemed to be much more effective than othersin providing insurance to their residents. Townsend describes in detail how insurancearrangements differ across villages. While in one village there is a web of well-functioning risk-sharing institutions, the situations in other villages are different. In onevillage, the institutions exist but are dysfunctional; in another, they are non-existent; in athird, close to the roads, there seems to be no risk-sharing whatsoever, even withinfamilies.6 4 See Deaton (1997) for more details.5 See Townsend (1995).6 Fafchamps and Lund (2003) find that, in the Philippines, households are much better insured against some shocks than against others. In particular, they seem to be poorly insured against health risk, a findingcorroborated by Gertler and Gruber (2002) in Indonesia.
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Draft: Not for quotation – 4.5 – Table 4.2 The effect of income on consumption, Côte d’IvoireWest ForestEast ForestSavannahAll ruralOLS 1985-86No dummies0.290 (6.2) 0.153 (3.2) 0.368 (5.8) 0.259 (8.8)Village dummies0.265 (5.7) 0.155 (3.5) 0.373 (5.7) 0.223 (7.7)OLS 1986-87No dummies0.458 (8.8) 0.162 (5.3) 0.168 (4.0) 0.239 (10.4)Village dummies0.424 (8.1) 0.173 (5.6) 0.164 (3.8) 0.235 (10.1)Note: Absolute value of t-values are shown in brackets. The first row of each panel shows the coefficient onincome change of a regression of consumption changes on income changes. The second row reports the sameresult when village dummies are included in the regression. Adapted from: Deaton (1997), table 6.5, p. 381. 4.16 As for credit, it is possible that the failure of insurance has something to do withinformational asymmetries. It is not easy to insure someone against a shock that he aloneobserves, since he has every incentive to always claim that things had gone badly.However, as Duflo and Udry (2004) demonstrate, spouses in Côte d’Ivoire do not seem tobe willing to insure each other fully against rainfall shocks that affect them differentially.Since rainfall is obviously observable, the problem has to be elsewhere. One possibility isthat the problem is limited commitment. People may be happy to claim what waspromised to them when it is their turn to be paid, and then default when it comes for themto pay. This may be particularly easy in a setting where the social relations between theset of people who are insuring each other are not particularly close, perhaps explainingwhy Townsend found no insurance in the village closest to the road.The market for land4.17 The ideal land market is one where anyone can buy or lease as much land as hewants for as long as he wants at a price that depends only on the quality of the land (andthe length of the lease). Moreover, the lease should be at a fixed rent, so that the lessor isthe residual claimant on the produce of the land. The fact that land can be freely boughtand sold ensures that there is no particular advantage or disadvantage to owning land visa vis any other asset of comparable value. The fact that the lessor is a residual claimantmeans that the land is put to optimal use. In practice, both properties fail systematically. 4.18 Many developing (and some developed) countries have regulations about who canbuy land and how much or how little. Binswanger, Deininger, and Feder (1995) arguethat almost every developing country today went through a phase when it had regulationson land ownership intended to generate concentrated land ownership. By contrast, Besleyand Burguess (2000) provide a list of regulations from different states in India, each anattempt to limit the concentration of ownership in land.
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Draft: Not for quotation – 4.6 -4.19 Government policy also intervenes directly to limit transactions in land, with theostensible aim of preventing the accumulation of land in the hands of a few people. InEthiopia in the late 1990s, Deininger and others (2003) note, selling and mortgaging landwas against the law and while rentals were officially allowed (after being disallowed fortwo decades) local leaders and governments were free to restrict even these transactionsin land. For example, the region of Oromia allows farmers to rent out only up to 50percent of their holding and stipulates maximum contract terms of 3 years for traditionaland 15 years for modern technologies. 4.20 It is often unclear who has the right to sell a particular plot of land, since there isfrequently no single person/family with a clear, undisputed, legal title to the land. This, inturn, reflects the importance of encroachments and land grabs in the evolution of landrights, as well as the importance of custom in governing land relations, especially inAfrica. The recent popularity of land titling as a social intervention is a directconsequence of the growing recognition of this fact.4.21 Where lease contracts exist, they are not always of the fixed rent type, at leastwhen the land is used for cultivation. Many countries, including the United States, have along tradition of an alternative contractual form: sharecropping. Under sharecropping, thefarmer only gets a fraction of the produce of the land, but he does not need to pay a fixedrent. As Alfred Marshall pointed out more than one hundred years ago, this weakensincentives and reduces the productivity of the land, but the near universality ofsharecropping suggests that it is a response to a real need. There is some disagreementamong economists about the exact nature of that need.7 But it is plausible that the need isrelated to the fact that farmers are often poor, and making them pay the full rent whentheir crop does poorly is difficult and probably not desirable.4.22 Leaseholds in developing countries tend to be relatively short-lived. The norm isfor it to last either a year or a season. Longer leases are not unknown but rare. This mightreflect the fact that it is custom rather than law that secures most of these leases: perhapsit is too much to rely on custom to enforce leases of arbitrary length.The market for human capital4.23 One thing that makes the market for human capital obviously different from allthe other asset markets is the fact that many decisions about investing in human capitalare taken by parents (or other family members) for their children. In other words, thosewho are taking these decisions are often different from those who get the human capital.It is not hard to imagine why this separation might introduce important distortions intothe functioning of this market. We will come back to them in the next section.4.24 A second important feature of this market is that while human capital is an asset,it is not one that can be legally pledged or mortgaged, for the simple reason that pledgingyour human capital would be tantamount to selling yourself into slavery. This obviouslyconstrains people’s ability to borrow to finance investment in education. 7 See Banerjee (2000) for a discussion of the alternative views.
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Draft: Not for quotation – 4.7 -4.25 We also want the market for human capital to be one where the reward is entirelybased on the effective amount of human capital supplied and not on other attributes of theperson supplying the skills. Discrimination based on gender, caste, religion or raceobviously violates this, but so does a system of job allocation based on contacts. Untilvery recently, job discrimination based on gender was the norm all over the world, andthere is a dwindling but significant number of countries where such discrimination is stilleither legally or socially accepted. Moreover, even where such discrimination isexplicitly frowned upon, there is some evidence of continuing discrimination. The sameis true of race, caste and religion: Most of the discrimination (unless it is legallymandated affirmative action in favor of a historically disadvantaged group such as lowcastes in India and African-Americans in the United States) happens despite there beingexplicit laws against it.84.26 One reason why discrimination is so hard to eliminate comes from its sheerinsidiousness. Beliefs about difference get embedded in everyday attitudes and practicesin a way that neither the discrminator nor the discrminated against may be conscious of,even though it transforms how they both behave. This is what underlies the power of thestereotype. In a recent experiment, Stone, Perry, and Darley (1997) asked all participantsin their experiment (American Caucasians, hereafter referred to as Whites) to listen to thesame running account of an athlete’s basketball performance on the radio. Half theparticipants were led to believe that the target player was White, and half that he wasAfrican-American. The results indicated that information was less likely to be absorbedif it was discordant with the prevailing U.S. stereotypes that Whites are moreacademically talented than African Americans, and that African Americans are moreathletically gifted. The White target player was perceived as exhibiting less naturalathletic ability but more “court smarts.” The African-American target player wasperceived as exhibiting less court smarts but more natural athletic ability. 4.27 Such biases have also been documented in real world settings. A recent study ofthe effect of stereotyping on judgment finds that prison inmates with more Afrocentricfeatures receive harsher sentences than those with less Afrocentric features, controllingfor race and criminal history (Blair, Judd, and Chapleau (2004)).94.28 Bertrand and Mullanaithan (2003) show evidence from a field experiment provingbeyond reasonable doubt that there is a high degree of anti-African-Americandiscrimination in the United States. They sent the same resumes to a large number ofcompanies under either a stereotypically White name or a stereotypical African-Americanname, and found a 50 percent higher call-back rate when the name was White. The datasay that having a White name is worth as much as eight additional years of jobexperience. Moreover, the discrimination tended to be greater when the resumecorresponded to someone who was better educated, suggesting that investment in humancapital among African-Americans is probably significantly underrewarded. 8 A partial exception is the institutionalized discrimination in favor of Malays in Malaysia, which is not easy to justify on the grounds that the Malays have historically been disadvantaged. 9 See also Loury (2002) for a wide-ranging study.
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Draft: Not for quotation – 4.8 -4.29 A very different form of discrimination comes from the allocation of jobs basedon contacts. Munshi (2003) shows persuasive evidence that contacts are very important inthe allocation of jobs for migrant labor in the United States. The employment prospectsfor Mexican migrants in the United States, it turns out, are much better when they arefrom areas where there was an earlier outflow of migrants. In particular, quiteremarkably, it helps if they are from areas where rains had failed several years ago—pushing out a cohort of migrants to the United States. who help the later generations ofmigrants from that area to find jobs. On the other hand, and this is the clincher, it doesnot help to be from an area where rains had failed recently. In other words, we can bereasonably sure that it has nothing do with being from areas where rains sometimes fail.Wealth, status and investment behavior4.30 The fact that these asset markets rarely measure up to their ideal creates thepossibility that wealth and social status, defined as the position in society both inascriptive identity and in connections, will have an important influence on investmentdecisions.The effect of imperfect financial markets4.31 The imperfections in credit and insurance markets have immediate implicationsfor the relation between wealth and investment. First, the fact that the rate of interest ondeposits is much lower than the rate on loans means that the opportunity cost of capitalfor those who just want to invest their own money is much lower than the opportunitycost for those who have to borrow. This means that the wealthy will end up investingmuch more than the indigent, even if they face exactly the same returns on theirinvestment. Second, the fact that richer people face different interest rates and betteraccess to capital reinforces this conclusion, since it says that the wealthy have a loweropportunity cost when they too are borrowing. Third, there is the direct effect of the factthat the rich have better access to credit.4.32 We would therefore expect the poor to underinvest, certainly relative to the rich,but also relative to what would happen if markets functioned properly. The reason is thatsome of the non-poor actually end up overinvesting. The fact that the poor cannot borrowmeans that the non-poor cannot lend as much as they would like to (this is why depositrates in developing countries are often very low). And because they cannot lend, it makessense for them to keep investing in their own firms, even when the returns are low.4.33 The fact that the poor underinvest, and that the opportunity cost of capital to thenon-poor is thus lower than it would otherwise be, also changes the composition of theinvestors. In particular, firms that would be nonviable if markets functioned perfectlylevel (say, because the interest rate would be too high), can survive and even expandbecause markets are the way they are. In other words, the “wrong” firms end upinvesting.4.34 The lack of insurance has a similar effect on the pattern of investment. The factthat many insurable risks are uninsured means that one cannot take on an investment
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Draft: Not for quotation – 4.9 -without personally bearing a significant part of the concomitant risk. Indeed, bigcorporations able to sell their equity in organized equity markets may be the only“players” who can really hope to diversify away a large part of the risk of a particularproject. Given this and the reasonable assumption that the poor are more risk-averse, weare likely to be in the perverse situation where the poor who are more sensitive to a givenrisk may also find it hardest to reduce their exposure to risk. They are therefore likely toshy away from the riskier and higher return investments. This reinforces the predictionthat the poor underinvest.The effect of imperfect land markets4.35 The imperfect salability of land, of course, can hurt anyone who owns land. Butthe rural poor probably have more of their wealth in land than most people, and thereforemaking land nonsalable might be particularly harsh on them.4.36 The lack of an explicit title, and the insecurity of tenure more generally (caused,for example, by the short duration of leases and the possibility that the landlord mighthold them up by threatening to take the land away at the end of the lease), tends todiscourage investment on the land that is tenanted. From this point of view, it clearlyhelps if land is owned by the person contemplating the investment; the fact that most ofthose who work in agriculture tend to be too poor to buy out the land they are cultivatingis therefore a potential source of underinvestment.4.37 Moreover, when the tenancy takes the form of a share contract there is theproblem, already mentioned, that the tenant may have insufficient incentives to put in theright amount of effort.The problems with investment in human capital4.38 With investment in human capital, the primary concern is the fact that thedecision rights do not lie with the direct beneficiary of the investment. Gary Becker’sclassic formulation of the problem of investment in human capital avoids this problem byassuming that the family can borrow against the child’s future income, turning theproblem into a conventional investment decision. The amount invested in that scenariowill not depend on the family’s wherewithal.4.39 In the more plausible circumstance where parents cannot borrow against theirchildren’s future income, they might still hope that when he grows up and reaps thebenefits of their investment, he might feel it fit to pay them back by taking care of themin their old age, but they know that he has no legal obligation to do so. If he does, it iseither because he loves his parents or because society expects him to do so. But then it isnot clear that he would feel comfortable in entirely abandoning his parents if they failedto educate him. This is not to say that parents do not benefit by making their childrenricher, or even that they do not vicariously enjoy their children’s success, but to suggestthat investment in human capital may be driven as much by the parents’ sense of what isthe right thing to do, as by any calculation of costs and benefits.
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Draft: Not for quotation – 4.10 -4.40 Once we accept this premise, it becomes clear that children’s human capital is notvery different from any other consumption good, so richer families will tend to investmore in their children’s health and education. Also, as a consumption decision, humancapital decisions may be more a product of culture and tradition than of the coldcalculation of benefits. This is not to say that benefits are irrelevant, but theresponsiveness to them may not be as large as one might have expected.4.41 The perception of discrimination, conscious or otherwise, can also have animportant effect on investment in human capital. Those who, rightly or wrongly,consciously or otherwise, expect to be discriminated against in a particular labor marketwill tend to invest less in acquiring the type of human capital that the market rewards.Perversely, this could generate self-reinforcing behaviors. If members of thediscriminated group invest less in their own education, or in searching for employment,others might see this underinvestment as confirmation of their prejudice against thatgroup.4.42 Stereotypes can be self-fulfilling not only because they bias perceptions of thetarget of the stereotype, but also because they influence the behavior of the stereotypedindividuals. In an interesting experiment, Stone and others (1999) asked collegeundergraduate volunteers to complete a miniature golf course. The students’performance was measured by how many strokes were needed to put the ball in the hole:fewer strokes mean better performance. The variable that the experimenters manipulatedwas the description of the task. In one treatment, the task was described as a“standardized test of natural athletic ability.” In the other treatment, the task wasdescribed as a “standardized test of sports intelligence.” When the task was described as atest of natural athletic ability, the African-American participants performed better thanthe Whites: they averaged 23.1 strokes to complete the 10-hole golf course, comparedwith 27.8 for the Whites. But when the task was instead described as a test ofintelligence, the race gap was reversed: African-Americans averaged 27.2 strokes, Whites23.3. 4.43 One way to interpret the behavior revealed in this experiment is that socialideas—stereotypes about the talents of different social groups—impose bounds fromwithin. Whereas, under the rational, self-interest hypothesis, individuals change theirbehavior only when their preferences or external constraints change. The behavior of realindividuals depends as well on belief systems that society has impressed on them. Negative stereotypes create anxiety that may interfere with performance; that is why thepsychologist Claude Steele termed this kind of behavior “stereotype threat.”10 If deeplyinternalized, the beliefs underlying the stereotypes can affect early decisions aboutprospective careers, and attitudes toward society, by changing what Appadurai (2004)calls a person’s “capacity to aspire.” Positive stereotypes, conversely, boost self-confidence and may lead individuals to expend greater effort. 4.44 Stereotypes influence behavior twice—through their impact on individuals’ self-confidence, and through their impact on the way individuals expect to be treated. To 10 See the survey in Steele and Aronson (1995).
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Draft: Not for quotation – 4.11 -examine the effect of stereotypes on the ability of individuals to respond to economicincentives, Hoff and Pandey (2004) undertook experiments with low and high castechildren in rural north India. The caste system in India can be described as a highlystratified social hierarchy in which largely endogamous groups of individuals areinvested with different social status and social meaning. 4.45 In the first experiment, groups composed of three low-caste (“untouchable”) andthree high-caste junior high school students were asked to solve mazes and were paidbased on the number of mazes they solved. In one condition, no personal informationabout the participants was announced. In a second condition, caste was made salient byannouncing within the group each participant’s name, village and caste. In a thirdcondition, participants were segregated by caste and then each participant’s name, villageand caste were announced in the six-person group. 4.46 There was no caste gap in performance when caste was not announced (figure4.1). But increasing the salience of caste led to a significant decline in the averageperformance of the low caste, regardless of whether the payment scheme was piece rateor tournament. When caste was announced, the low-caste children solved 25 percentfewer mazes on average in the piece rate treatments, compared with the performance ofsubjects when caste was not announced. When caste was announced and groups werecomposed of six children drawn from only the low caste (a pattern of segregation that forthe low caste implicitly evokes their traditional outcast status), the decline in low casteperformance was even greater. A vertical line in the figure illustrates the statisticallysignificant caste gaps. While we cannot be sure from these data what the children arethinking, some combination of loss of self-confidence and expectation of prejudicialtreatment is likely to explain the result. Figure 4.1 Children’s performance differs when their caste is made salientSource: Hoff and Pandey (2004). Average number of mazes solved, by caste,in five experimental treatments012345678Piece Rate,Caste NotAnnouncedPiece Rate,CasteAnnouncedTournament,Caste NotAnnouncedTournament,CasteAnnouncedTournament,Caste Announcedand Segregatedhigh castelow caste
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Draft: Not for quotation – 4.12 -4.47 The expectation by the low-caste subjects of prejudicial treatment may be rationalgiven the discrimination that they experience in their villages. But the discriminationitself may not be fully rational. Cognitive limitations may prevent others from judgingstigmatized individuals fairly. The fact that people are bounded in their ability to processinformation creates broad scope for belief systems—in which some social groups areviewed as innately inferior to others—to influence economic behavior. If such beliefspersist, it will in general be rational for those discriminated against to underinvest (withrespect to others) in the accumulation of skills for which the return is likely to be lowerfor them. This rational calculation is additional to any reduction in their “capacity toaspire,” arising from the internalization of those beliefs.The evidence on underinvestmentIndustry and trade4.48 Direct estimates of marginal product show that there are a lot of unexploitedinvestment opportunities. Figure 4.2 plots a non-parametric relationships between firmearnings and firm capital in Mexico.11 Even ignoring the astronomical returns at the verylow values of firm capital, this figure suggests huge returns to capital for these smallfirms. For firms with less than $200 invested, the rate of returns reaches 15 percent permonth, well above the informal interest rates available in pawn shops or throughmicrocredit programs (on the order of 3 percent a month). Estimated rates of returndecline with investment, but remain high (7 percent to 10 percent a month for firms withinvestment between $200 and $500, and 5 percent for firms with investment between$500 and $1,000). These firms are thus all too small. Figure 4.2 Parametric returns $0-1,000 capitalSource: McKenzie and Woodruff (2004) 11 From McKenzie and Woodruff (2003), Figure 1. Model i adds controls for the owner’s education and demographic characteristics in the estimation of the relationship between firm size and returns. Model ii adds year and industry effects to Model i.
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Draft: Not for quotation – 4.13 -4.49 Trade credit is an important form of credit everywhere, perhaps especially wherethe formal institutions of the credit market are underdeveloped. Fisman (2001) looked atthe relation between access to trade credit and capacity use in a sample of 545 firms inCôte d’Ivoire, Kenya, Tanzania, Zambia and Zimbabwe. He finds that firms that get tradecredit from all its three main suppliers (on average, about one of the three suppliersprovides trade credit) have 10 percent better capacity use than firms that have no tradecredit. Moreover, the relation is much stronger in industries where it is important to carrylarge inventories.4.50 Such studies present serious methodological issues, however. The basic problemcomes from the fact that investment levels are likely to be correlated with omittedvariables. For example, in a world without credit constraints, investment will bepositively correlated with the expected returns to investment, generating a positive“ability bias”(Olley (1996). McKenzie and Woodruff attempt to control for managerialability by including the firm owner’s wage in previous employment, but this goes onlypart of the way if individuals choose to enter self-employment precisely because theirexpected productivity in self-employment is much larger than their productivity in anemployed job. Conversely, there could be a negative ability bias if capital is allocated tofirms in order to avoid their failure.4.51 Banerjee and Duflo (2004) take advantage of a change in the definition of the so-called “priority sector” in India to circumvent these difficulties. All banks in India arerequired to lend at least 40 percent of their net credit to the “priority sector,” whichincludes small-scale industry. In January 1998 the limit on total investment in plants andmachinery for a firm to be eligible for inclusion in the small-scale industry category wasraised from Rs. 6.5 million to Rs. 30 million. Banerjee and Duflo (2004) first show that,after the reforms, newly eligible firms (those with investment between 6.5 million and 30million) received on average larger increments in their working capital limit than smallerfirms. They then show that the sales and profits increased faster for these firms during thesame period. Putting these two facts together, they can estimate the the impact of theincreased access to working capital on the growth in profits. Even after allowing for thepossibility that the firms in the priority sector were paying less than the true cost ofcapital for the extra money from the bank, they estimate that the returns to capital in thesefirms must be at least 94 percent.4.52 A very different kind of evidence for underinvestment comes from the fact thatmany people pay the very high interest rates reported earlier. Given that this moneytypically goes into financing trade and industry, the presumption is that the peopleborrowing at these rates of often 50 percent or more must have a marginal product ofcapital that is even higher. But the average marginal product in developing countriesseems to be nowhere near 50 percent. One way to get at the average of the marginalproducts is to look at the incremental capital-output ratio (ICOR) for the country as awhole. The ICOR measures the increase in output predicted by a one-unit increase incapital stock. It is calculated by extrapolating from the past experience of the country andassumes that the next unit of capital will be used exactly as efficiently (or inefficiently) asthe previous one. The inverse of the ICOR therefore gives an upper bound for the averagemarginal product for the economy—it is an upper bound because the calculation of the
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Draft: Not for quotation – 4.14 -ICOR does not control for the effect of the increases in the other factors of production,which also contributes to the increase in output.12 For the late 1990s the IMF estimatesthat the ICOR is more than 4.5 for India and 3.7 for Uganda. The implied upper bound onthe average marginal product is 22 percent for India and 27 percent in Uganda.4.53 The fact that many firms in India have a marginal product of 50 percent or morewhile the average marginal product is only 22 percent or so, is strong prima facieevidence for the misallocation of capital. The firms with the marginal product of 50percent and more are clearly too small, while other firms (the ones who bring the averagedown to 22 percent) must in some sense be too large.4.54 A specific example of this kind of misallocation of capital comes from a study ofthe knitted garment industry in the southern Indian town of Tirupur (Banerjee andMunshi (2004); Banerjee, Duflo, and Munshi (2003)). Two groups of people operate inTirupur: Gounders and outsiders. The Gounders, who issue from a small, wealthy,agricultural community from the area around Tirupur moved into the readymade garmentindustry because there was not much investment opportunity in agriculture. Outsidersfrom various regions and communities started joining the city in the 1990s. 4.55 The Gounders have, unsurprisingly, much stronger ties in the local community,and thus better access to local finance. But they may be expected to have less naturalability for garment manufacturing than the outsiders, who came to Tirupur preciselybecause of its reputation as a center for garment export. The Gounders own about twiceas much capital as the outsiders on average. Figure 4.3a plots the capital stock ofGounder and outsider firms as a function of the age of the firm. It demonstrates thatGounder firms of all ages own more capital, though there is a strong tendency towardconvergence as the firms age. Figure 4.3b plots sales, once again as a function of age. Itis clear that the Gounders, despite owning more capital, lose their early lead in sales byabout year 5, and end up selling less. In other words, outsiders invest less and producemore. They are clearly more able than the Gounders,13 but because they are less cash-richand do not have the right connections, they end up working with less capital. 12 The implicit assumption that the other factors of production are growing is probably reasonable for most developing countries, except perhaps in Africa. 13 This is not because capital and talent happen to be substitutes. In these data, as is generally assumed, capital and ability appear to be complements.
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Draft: Not for quotation – 4.15 – Figure 4.3a Capital stock—net cohort effectsSource: Banerjee and Munshi (2004).Figure 4.3b ProductionSource: Banerjee and Munshi (2004).
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Draft: Not for quotation – 4.16 -Agriculture4.56 There is also direct evidence of very high rates of returns on productiveinvestment in agriculture. In the forest-savannah in Southern Ghana, cocoa cultivation,receding for many years because of the swollen shoot disease, has been replaced by acassava-maize intercrop. Recently pineapple cultivation for export to Europe has offereda new opportunity for farmers in this area. In 1997 and 1998 more than 200 householdscultivating 1,070 plots in four clusters in this area were surveyed every six weeks forabout two years. Figure 4.4 reports the distribution of profits on the traditional cassava-maize intercrop and on pineapples based on this survey.14 Pineapple productiondominates the traditional intercrop, and the average returns associated with switchingfrom the traditional maize and cassava intercrops to pineapple is estimated to be in excessof 1,200 percent! Yet only 190 out of 1,070 plots were used for pineapple. The authorssay that, “The virtually unanimous response to the question ‘Why are you not farmingpineapple?’ provided by our respondents was ‘I don’t have the money,’”15 though someheterogeneity between those who have switched to pineapple and those who have not,cannot be entirely ruled out. Figure 4.4 Distribution of per-hectare profits, (thousand cedis)Source: Goldstein and Udry (1999). 4.57 Evidence from experimental farms also suggests that, in Africa, the rate of returnsto using chemical fertilizer (for maize) would also be high. But the evidence may not berealistic if the ideal conditions of an experimental farm cannot be reproduced on actual 14 From Goldstein and Udry (1999), figure 4.15 From Goldstein and Udry (1999), page 38.
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Draft: Not for quotation – 4.17 -farms. Foster and Rosenzweig (1995) show, for example, that the returns to switching tohigh-yielding varieties were actually low in the early years of the green revolution inIndia, and even negative for farmers without an education. This is despite the fact thatthese varieties had been selected precisely for having high yields, in proper conditions.But they required complementary inputs in the correct quantities and timing. If farmerswere not able or did not know how to supply them, the rates of returns were actually low.4.58 Chemical fertilizer, however, is not a new technology, and the proper way to useit is well understood. To estimate the rates of returns to using fertilizer on farms inKenya, Duflo, Kremer, and Robinson (2003), in collaboration with a small NGO, set upsmall randomized trials on people’s farms. Each farmer in the trial delimited two smallplots. On one randomly selected plot, a field officer from the NGO helped the farmerapply fertilizer. Other than that, the farmers continued to farm as usual. They find that therates of return from using a small amount of fertilizer varied from 169 percent to 500percent depending on the year, though returns declined fast with the quantity used on aplot of a given size.4.59 Evidence for a different type of underinvestment in agriculture is in the negativesize-productivity relationship, the idea that the smallest farms tend to be the mostproductive (table 4.3). Each column of the table compares the productivity of small andlarge farms within a particular country.16 The gap is enormous: a factor of 6 in Brazil anda factor of 2.75 in Pakistan. It is smaller in Malaysia (1.5), but then the large farm inMalaysia is not very large. This is strong prima facie evidence that markets are somehownot allocating the right amount of land to those who currently farm the smaller plots. Table 4.3 Farm size productivity differences, selected countriesSource: Berry and Cline (1979). 4.60 The problem with this kind of evidence is that it ignores the many reasons whythe bigger farm may be inherently less productive—worse soil quality, for example. Evenso, similar, but somewhat less dramatic, results show up even after controlling for 16 Based on Berry and Cline (1979).
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Draft: Not for quotation – 4.18 -differences in land quality. Figure 4.5 shows the results of such an exercise.17 Eachstraight line in the figure represents the relationship between the profit-wealth ratio and ameasure of underlying risk, namely the standard deviation of the date of monsoon onset,for four size categories of farms. The data come from the Indian ICRISAT villages. Thefirst observation is that the profit-wealth ratio is the highest for the smallest farms, andwhen risk is comparatively low, the gap is more than 3:1. Because wealth includes thevalue of the land, the measure implicitly takes into account differences in the quality ofthe land, as long as land prices are a reasonable measure of land quality, which is notentirely clear, however. There are also residual doubts about whether the returns are wellmeasured—it is possible that the land of the smaller farms is degrading faster but thedegradation is not being counted while calculating the returns. Figure 4.5 Profit-wealth ratios and weather variability, by wealth and classNote: The onset date of the monsoon was the single most powerful of eight rainfallcharacteristics to explain gross of farm output. 4.61 The second notable fact about this figure is that all the lines slope down: whenrisk goes up, the average return goes down. In part this may be inevitable, but it may alsoreflect that the lack of insurance encourages people to avoid risky (but remunerative)choices.18 This is consistent with the fact that profitability falls faster for the poorerfarmers (who are less able to self-insure) as the risk goes up. Specifically, a one-standard- 17 Taken from Rosenzweig and Binswansger (1993).18 Some of the effects of lack of insurance may be quite subtle. Banerjee and Newman (1991) argue, for example, that the availability of insurance in one location (the village) and its unavailability in another (thecity) may lead to inefficient migration decisions, since some individuals with high potential in the city mayprefer to stay in the village to remain insured.
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Draft: Not for quotation – 4.19 -deviation increase in the coefficient of variation of rainfall leads to a 35 percent reductionin the profit of poor farmers, a 15 percent reduction in the profit of median farmers, andno reduction in the profit of rich farmers. The study also finds that input choices areaffected by variability in rainfall, and in particular, poor farmers make less efficient inputchoices in a risky environment.4.62 In related work, Morduch (1993) specifically investigated how the anticipation ofcredit constraint affects the decision to invest in high-yielding variety seeds. Using amethodology inspired by Zeldes (1989), he splits the sample into two groups, one groupof landholders expected to have the ability to smooth their consumption, and one groupthat owns little land, expected to be constrained. He finds that the more constrained groupdevotes a considerably smaller fraction of land to high-yielding variety seeds for rice andcastor.4.63 Another consequence of the lack of insurance is that it may lead households to useproductive assets as buffer stocks and consumption smoothing devices, which would be acause for inefficient investment. Rosenzweig and Wolpin (1993) argue that bullocks (anessential productive asset in agriculture) serve this purpose in rural India. They show,using the ICRISAT data, covering three villages in semi-arid areas in India, that bullocks,which constitute a large part of the households’ liquid wealth (50 percent for the poorestfarmers), are bought and sold quite frequently (86 percent of households had eitherbought or sold a bullock in the previous year, and a third of the household-yearobservations are characterized by a purchase or sale). Moreover they buy when they areflush with money and sell when they are broke. 4.64 Since people are not simultaneously selling and buying land, they are not sellingthese animals because they no longer need them for production. Indeed, Rosenzweig andWolpin estimate that from the point of view of production, most of these farmers shouldown two bullocks and never sell them. If they are selling, the reason is that they need themoney for consumption. The data suggest that, for poor or mid-size farmers there isconsiderable underinvestment in bullocks, presumably because of the borrowingconstraints and the inability to borrow and accumulate financial assets to smoothconsumption: almost half the households in any given year hold no bullocks (most of theothers own exactly two).194.65 There is also compelling evidence that sharecroppers lack incentives. Binswangerand Rosenzweig (1986) and Shaban (1987) both show that, controlling for farmer’s fixedeffect (that is, comparing the productivity of owner-cultivated and farmed land forfarmers who cultivate both their own land and that of others) and for land characteristics,productivity is 30 percent lower in sharecropped plots. Shaban (1987) shows that all theinputs are lower on sharecropped land, including short-term investments (fertilizer andseeds). He also finds systematic differences in land quality (owner-cultivated has a higherprice per hectare), which could in part reflect long-term investment. 19 The fact that there is underinvestment on average, and not only a set of people with too many bullocks and a set of people with too few, is probably due to the fact that bullocks are a lumpy investment, andowning more than two is very inefficient for production{there is no small adjustment possible at themargin.
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Draft: Not for quotation – 4.20 -4.66 On the impact of security of property, Do and Iyer (2003) find that a land reformthat gave farmers the right to sell, transfer or inherit their land use rights also increasedagricultural investment, particularly the planting of multiyear crops (such as coffee).Laffont and Matoussi (1995) use data from Tunisia to show that a shift fromsharecropping to owner cultivation raised output by 33 percent, and moving from a short-term tenancy contract to a longer term contract increased output by 27.5 percent.204.67 Security of property rights is often linked to the local power structure. Theconnection between inequalities in power and underinvestment is nicely exemplified bythe Goldstein and Udry (2002) study of investment in land in a setting where land isallocated by custom (rural Ghana). They show that individuals are less likely to leavetheir land fallow (an investment in long-run productivity of the land) if they do not hold aposition of power within either the hierarchy of the “village or the hierarchy of thelineage.” The problem is that the land gets taken away from them when it is lying fallow.Since women rarely hold these positions, women’s land is not left fallow enough and ismuch less productive than men’s. Human capital4.68 According to the report of the Commission on Macreconomics and Health (2001),returns to investing in health are on the order of 500 percent. But these numbers, arrivedat through cross-country growth regressions, are not as easy to interpret as what wouldactually happen if someone would invest an extra dollar in health. That said, there areclearly examples of specific health interventions that have enormous private and socialreturns. There is substantial experimental evidence that supplementation in iron andvitamin A increases productivity at relatively low cost. • Basta, Soekirman, and Scrimshaw (1979) study iron supplementation amongrubber tree tappers in Indonesia. Baseline health measures indicated that 45percent of the study population was anemic. The intervention combined an ironsupplement and an incentive (given to both treatment and control groups) to takethe pill on time. Work productivity among those who got the treatment increasedby 20 percent (or $132 a year), at a cost per worker-year of $0.50. Even takinginto account the cost of the incentive ($11 a year), the intervention suggestsextremely high rates of returns. • Thomas and others (2003) obtain lower but still high estimates in a largerexperiment, also in Indonesia. They found that iron supplementation experimentsin Indonesia reduced anemia, increased the probability of participating in thelabor market, and increased earnings of self-employed workers. They estimate 20 Another piece of relevant evidence comes from the effects of titling nonagricultural land. Field (2003) shows evidence from a land titling program in the slums of urban Peru which suggests that the lack of aclear title to the land where you have built your home reduces the ability of the household members to workoutside. Field hypothesizes that this is because someone needs to be home to defend the untitled propertyfrom expropriation by others. But she does not find any evidence that land titling improves access to credit.
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Draft: Not for quotation – 4.21 -that, for self-employed males, the benefits of iron supplementation amount to $40per year, at a cost of $6 per year.21• The cost-benefit analysis of a deworming program (Kremer-Miguel 2003) inKenya reports estimates of a similar order of magnitude. Taking into accountexternalities (due to the contagious nature of worms), the program led to anaverage increase in school participation of 0.14 years. Using a reasonable figurefor the returns to a year of education, this additional schooling will lead to abenefit of $30 over the life of the child, at a cost of $0.49 per child per year. Notall interventions have the same rates of return, however. A study of Chinesecotton mill workers (Li and others (1994) led to a significant increase in fitness,but no corresponding increase in productivity.4.69 Measured returns to private investment in education tend not to be quite so high.Banerjee and Duflo (2004) survey the cross-country evidence on Mincerian returns, andconclude that “Using the preferred data, the Mincerian rates of returns seem to vary littleacross countries: The mean rate of returns is 8.96, with a standard deviation of 2.2. Themaximum rate of returns to education (Pakistan) is 15.4 percent, and the minimum is 2.7percent (Italy).” But most of the educational benefits of deworming mentioned abovewould be captured by a child whose parents are willing to spend 50 cents on thedeworming medicine. This clearly offers a return much higher than the measuredMincerian returns at affordable absolute cost, though they are not strictly comparable,since deworming does not require the child to spend more years in school, but helps herget more out of the years she is already spending in school. However, when thedeworming medicine was offered free to the children, the take-up was only 57 percent. Inthis sense, it is clear that at least some causes of underinvestment have to be found in theway the family makes decisions, rather than in the lack of resources.4.70 The fact that a lack of connections alters the nature of human capital investment isnicely demonstrated in a recent paper by Munshi and Rosenzweig (forthcoming). Theyshow that while liberalization increased returns to knowing English, in families that hadconnections in the blue-collar sector compared with families that have no connections,there is a much bigger gap between girls and boys in the increase in enrollment inEnglish-medium schools. Why? Because girls never really expected to get these blue-collar jobs, while for their brothers, it depended on whether they had the right contacts.Inequalities and investment4.71 Four important points follow from this body of evidence: First, markets indeveloping countries are highly imperfect, and those who do not have enough wealth orsocial status tend to underinvest. The resources underused because of thisunderinvestment end up being used for some less productive purpose, reducing overallproductivity. In the example from the knitted garment industry in Tirupur, the Gounderswere overinvesting in their own relatively unproductive firms while the much more 21 This number takes into account the fact that only 20 percent of the Indonesian population is iron deficient. The private returns of iron supplementation for someone who knew they were iron deficient—which they can find out using a simple finger prick—would be $200.
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Draft: Not for quotation – 4.22 -productive firms of the outsiders were starved of capital. The land owned by Ghanaianwomen was getting degraded because they did not have the social status needed to holdon to the land during the fallowing peiod. This, once again, is a pure loss for society,since the fact that other people who do have status and can fallow their land as needed, isnot, in any way, compensating for the loss of productivity on the lands of the powerless.This creates a strong presumption that certain specific types of redistribution, byempowering certain people or increasing their access to resources or contacts, canpromote both efficiency and equity. 4.72 Second, this creates a bias in favor of those kinds of redistribution that target thespecific lack of access to resources or influence causing the inefficiency. In somesituations this will mean redistributing assets, but it also might mean redistributing accessto capital, perhaps by promoting of microcredit, strengthening women’s land rights oraccess to jobs and welfare programs, designing affirmative action programs to breakdown stereotyping and improving access to justice systems.4.73 Third, since investments build wealth and wealth makes it easier to invest in aworld where markets do not function very well, a little help can go a long way. Startingthe right business might be the biggest challenge once stated, it might propel itselfforward without any further help.4.74 Fourth, it is not clear that the beneficiaries from this kind of efficiency promotingredistribution have to be the poorest of the poor. Since the ideal is to promote productiveinvestments, the target should be those most likely to make these investments. Whetherthe poorest are the right people from this point of view is an empirical question, and onewhere the answer might depend on the set of economic opportunities available. 4.75 The microcredit community, in particular, has long debated this last issue, in thecontext of trying to decide whether microcredit is best instrument for helping the poorestof the poor. This clearly turns partly on whether the poorest are the ones who have theprojects with the highest returns, which would be the case if the poor and the less poorhave the same kinds of production functions, and there are diminishing returns inproduction. If, instead, the most productive technology in this area had a fixed cost ofproduction but (say) diminishing returns otherwise, giving access to more capital to thepoorest may not be very productive: Even with all the capital they can get, they may notbe able to cover the fixed cost. It may be more effective to help people who are slightlyricher, because with some help they may actually be able to start a business. 4.76 How good or bad is the assumption of decreasing returns in the productionfunction of an individual firm? As mentioned above, McKenzie and Woodruff (2003)attempt to estimate a production function for small Mexican firms. Their estimatessuggest that there are strong diminishing returns. Mesnard and Ravallion (2004) findweak diminishing returns using Tunisian data. However, estimating a production functionthat exhibits local increasing returns is inherently difficult. A firm is likely to grow (orshrink) very fast when it is in the region of increasing returns. So we will observe fewfirms in this region, and be likely to reject too often the assumption of local increasingreturns. Certainly the natural interpretation of the results in Banerjee and Duflo (2004),
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Draft: Not for quotation – 4.23 -showing close to 100 percent returns in medium-sized firms in India, is that there areincreasing returns over some range. 4.77 A corollary of this discussion is that the redistribution that maximizesproductivity growth is not necessarily the one that has the strongest immediate effect onpoverty. Nor is it the one that does most to reduce inequality. Indeed, except under veryspecial circumstances, this discussion tells us nothing about the relation between someglobal measure of inequality and the efficiency of resource use or investment. Considerthe case, discussed above, where the production function has a fixed cost but alsodiminishing returns. If all firms are equal and the maximum they can each invest is lessthan the fixed cost, no one will be able to start a firm. Increasing inequality will raise theproductivity of capital by making it possible for some firms to pay the fixed cost. Butsince there are also diminishing returns, there will be a point where any further increasein overall inequality would be counterproductive. 4.78 More generally, the effect of inequality will depend on the shape of theproduction function, and the size of the investment potential of the average personrelative to the fixed cost. Obviously the issue gets even more complicated if differentfirms have different production functions and productivity is correlated with the owner’swealth (as it might be if the owner’s education is an important input into production andricher people tend to be more educated).4.79 Several authors have tried to look for a systematic relation in cross-country databetween inequality and growth (presumably what investment is meant to achieve). A longliterature (see Bénabou (1996) for a survey) estimated a long-run equation, with growthbetween 1990 and 1960 (say) regressed on income in 1960, a set of control variables, andinequality in 1960. Estimating these equations tended to generate negative coefficientsfor inequality. But there are obvious concerns about whether such a relation could bedriven entirely by omitted variables. To address this problem, Li and Zou (1998), Forbes(2000) and others used the time series dimension of the Deininger and Squire data set tolook (effectively) at the effect of short-run changes in inequality on changes in growth.22The results change rather dramatically: the coefficient of inequality in this specification ispositive, and significant. 4.80 A recent review paper by Voitchovsky (2004) concludes that both these effectsare quite robust. Most studies that look at the cross-sectional relationship betweeninequality and subsequent growth over a relatively long period in cross-country data, andespecially those that use measures of asset inequality, find a negative relationship, oftensignificant.23 By contrast, most studies that look at the relation between changes ininequality and changes in growth, including several studies that do the analysis at thesubnational level within the same country, find a positive effect. 22 {Forbes, 2000 1601 /id} also corrects for the bias introduced by introducing a lagged variable in a fixed effect specification by using the GMM estimator developed by Arellano and Bond (1991). 23 Barro (2000) estimates a cross-sectional relationship between inequality and short-term growth and finds a negative realtion in poor countries but a positive relation in rich ones.
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Draft: Not for quotation – 4.24 -4.81 Both Banerjee and Duflo (2003) and Voitchovsky (2004) conclude that there is noreason to give one of these sets of results priority over the other. Indeed, both could beright. For example, in the short run policies that allow large cuts in real wages mightencourage investment, but in the long run the consequent increase in poverty might makeit harder for the population to maintain its human capital. Or both could be wrong. Thereare many reasons for both the cross-sectional and the time series evidence to bemisleading. • First, most of these papers estimate a linear relationship between the inequalityvariable and the growth variable, but as already pointed out one can easilyimagine situations where the true relationship is strongly nonlinear. Banerjee andDuflo (2003) regress changes in growth non-parametrically on changes ininequality and find the relationship to have an inverted U-shape. In other words,both reductions and increases in inequality seem to be accompanied by a fall ingrowth. • Second, as discussed in some detail by Voitchovsky, different countries measureinequality in different ways, and the measures are also not consistent over time.Moreover there is lot of guesswork and approximation that goes into everyestimate of inequality, all of which makes it hard to use it as an explanatoryvariable. • Third, there is the very difficult question of causality. What we take to be theeffect of an increase in inequality on the growth rate could as well be the effect ofwhatever caused inequality to go up (say, a new market opportunity). Theincrease in inequality may just be a symptom of some other underlying change. 4.82 This lack of clear-cut results is perhaps dissappointing, but it is worthemphasizing that our focus here has been on redressing specific inequities rather thansome overall measure of inequity. We are therefore more interested in specific instanceswhere redistribution had a clear beneficial impact on efficiency. 4.83 One such example comes from Operation Barga, a tenancy reform in the Indianstate of West Bengal in the late 1970s and 1980s. It has been known, at least since thework of the great Victorian economist Alfred Marshall, that sharecropping provides poorincentives and discourages effort. In such an environment, a government intervention thatforces the landlords to give their sharecroppers a higher share of the output than themarket would give them should increase effort and productivity. This is exactly whathappened in West Bengal, India, when a Left Front government came to power in 1977.The tenant’s share of output was set at a minimum of 75 percent as long as the tenantprovided all inputs. In addition, the tenant was guaranteed a large measure of security oftenure, which may have encouraged him to undertake more long-term investments on theland. Survey evidence shows that there was a substantial increase in both tenure securityand the share of output going to the sharecropper. The fact that the implementation of thisreform was bureaucratically driven, and proceeded at different speeds in different areas,suggests the possibility of using variation in the implementation of the reform to evaluate
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Draft: Not for quotation – 4.25 -its impact. The evidence suggests that there was a 62 percent increase in the productivityof the land (Banerjee, Gertler, and Ghatak (2002).4.84 A very different program, also promoting both equity and efficiency, had to dowith redressing the effects of intrafamily inequality. A long line of research claims thatboth income and expenditures are often controlled by the male members of the familyand that this leads to underinvestment, especially in the health and education of girls. Onefallout of the dismantling of the apartheid regime in South Africa was the extension ofthe South African social pension program to the black population. For children bornbefore the extension (in 1990 and 1991), height-for-age is, if anything, slightly lower infamilies where the grandmother will eventually get the pension (figure 4.6).24 But forchildren born after the extension, in 1992 and 1993, they are significantly taller (exceptfor the newborns). There is no difference between non-eligible families and familieswhere pension money goes to the grandfather. (Boys are essentially unaffected.) Theestimates suggest that receipt of the pension (the pension was about twice the per capitaincome among blacks) was enough to help girls bridge half the gap in height-for-agebetween South African and American children. Figure 4.6 Height-for-age of children living with eligible women, eligible men, no eligible member Source: Duflo, Kremer, and Robinson (2003). 4.85 The point from these examples is that it is possible to enhance both equity andefficiency. This is not to say that there is a necessary connection between the two: onecan easily imagine redistributions that hurt efficiency. But given the near universality ofmarket failures and underinvestment in poor countries, it should be possible, with acombination of good research and careful thinking, to identify opportunties forredirecting resources to poor people who are in a position to make very good use of them. 24 Taken from Duflo (2003).
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