WPS2z8 3 POLICY RESEARCH WORKING PAPER 2813 The Collective Model of the Household and an Unexpected Implication for Child Labor Hypothesis and an Empirical Test Kaushik Basu Ranjan Ray The World Bank Office of the Senior Vice President H Development Economics March 2002 I POLICY RESEARCH WORKING PAPER 2813 Abstract Basu and Ray use the collective model of the household structure between the husband and the wife is least likely and show, theoretically, that as the woman's power rises, to send its children to work. An empirical test of this child labor will initially fall, but beyond a point it will relationship using data from Nepal strongly corroborates tend to rise again. A household with a balanced power the theoretical hypothesis. This paper-a product of the Office of the Senior Vice President, Development Economics-is part of a larger effort in the Bank to understand how gender affects development outcomes and to identify the causes of poverty. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Narin Jameson, room MC4-333, telephone 202-473-0677, fax 202-522-1158, email address njameson@worldbank.org. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at kbasu@mit.edu or ranjan.ray@utas.edu.au. March 2002. (26 pages) The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas abolit development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the auithors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Produced by the Research Advisory Staff The Collective Model of the Household and An Unexpected Implication for Child Labor: Hypothesis and an Empirical Test Kaushik Basu* and Ranjan Ray** Acknowledgements: The paper is part of the research project "Gender and Power Relations in the Household, Female Labor Supply and Child Welfare" coordinated by Kaushik Basu and sponsored by the World Bank. Ranjan Ray, also, acknowledges financial assistance from the Australian Research Council. We are grateful to Halsey Rogers for comments and to Gayatri Koolwal and Geoffrey Lancaster for research assistance and advice. *Department of Economics, M.I.T., Cambridge, MA 02142, USA; and Department of Economics, Corncll University, Ithaca, NY 14853, USA. Email: kbasu@mit.edu **School of Economics, University of Tasmania, GPO Box 252-85, Hobart 7001, Australia. Email: Ranjan.ray(utas.edu.au. THE COLLECTIVE MODEL OF THE HOUSEHOLD AND AN UNEXPECTED IMPLICATION FOR CHILD LABOR: HYPOTHESIS AND AN EMPIRICAL TEST Kaushik Basu and Ranjan Ray 1. Introduction The 'collective model' of the household assumes that a household maximizes a weighted average of the wife's and husband's utilities, where the weights capture each agent's 'power' or effectiveness in the decision-making process.' Hence, unlike in Becker's (1981) classic 'unitary model', any change in a variable that changes the balance of power in the household can lead to changes in the household's consumption pattern, even when the household's total income and all prices remain unchanged. There is a large literature that tracks exactly how changes in the balance of power changes a household's consumption. Thus there are studies which show that greater power to the woman results in better clothing for the children, less expenditure on tobacco, better nutrition for the children and so on.2 What has however been rarely studied is the relation between the balance of power in the household and the incidence of child labor.3 The present paper is focussed entirely on this relation. First, a theoretical model is developed to show that the balance of power in the household impacts on child labor in unexpected ways. It is argued that as the woman's power increases, child labor will first fall and then rise. The hypothesis is the result of an interesting theoretical process. It is 'See Chiappori, 1988; Browning and Meghir, 1991; Bourguignon and Chiappori, 1994; Browning, Bourguignon, Chiappori, and Lechene, 1994. 2Lundberg, Pollak and Wales, 1997; Kanbur and Haddad, 1994. 3Moehling (1995), Iversen (2001), Emerson and Portela (2001), and Basu (2001) constitute virtually the totality of the literature on this. 2 formally derived in Section 2. In Section 3 the hypothesis is empirically tested using household data from Nepal. The data yield robust corroboration of the hypothesis. These findings have important policy implications. They suggest that a household in which power is well balanced between the husband and the wife is least likely to send the children to work. In other words, if we are interested in curbing child labor and are dealing with a traditional society where women have very little power, we should try to empower women. However, our study also suggests that this relation is not monotonic. In other words, if we give too much power to the women, we can get a negative backlash with child labor rising once again. Section 4 comments on these and other policy implications. 2. Theory Consider a household consisting of a wife (agent 1), a husband (agent 2) and a child (agent 3). There are n goods in this economy. Let ui : 9I' -* 91, i = 1,2, be the utility function of agent i. The collective model claims that the household maximizes a weighted average of the utility functions of the two adults: Q 0u1(x) + (l-0)u2(x), (1) where 0 E [0,1 ] captures the balance of power in the household. As 0 increases the wife's power increases. In order to study the effect of the household's power structure on child labor, all we have to do is to admit child leisure as one of the goods in the vector x. Then if we define child labor as 1 rminus child leisure, the household's optimization will yield results on how much the child will be made to work. 3 To keep the analysis simple, we will assume that there are three goods - good 1, good 2 and child leisure. We will use e3 to denote the amount of work the child does. Hence 1 - e3 is child leisure. In this theoretical section, we will consider only the child's effort (assuming that the adults always work). Therefore, there should be no confusion in writing e for e3. Hence, the utility functions of the wife and the husband may be written as: ul =ul (xI, x2, l-e) U2 = u2(xI, X2, l-e). The two substantial assumptions that we would like to maintain are (A) the husband and the wife have different preferences over the two goods 1 and 2 and (B) both of them find it painful to send their children to work. Our main hypothesis, to wit, that as 0 rises, e will first fall and then rise, is largely a direct consequence of assumptions (A) and (B) (as we show below). Hence, in a sense our empirical test could be thought of as a test of the collective model of the household along with the restrictions that come with assumptions (A) and (B). Let us first explain the hypothesis intuitively, before turning to the formal derivation. Since both husband and wife consider it painful to send the child to work the household's evaluation of the cost of child labor remains unchanged no matter what the value of 0. This is simply another way of saying that the weighted average of the same 1 value is unaffected by changes in the weights. Next note that if 0 is 2 , the goods purchased by the household will not be ideal for either the man or the wife. Hence, if 0 is 4 -, and the child is sent out to work, the benefit of the goods bought by the additional income will benefit neither adult too much. Orn the other hand, if 0 = 1, the woman being the sole decision-maker in the household will direct the additional money earned by sending the child to work to purchase exactly the goods she finds valuable. Hence, sending the child to work would now seem more worthwhile. The same logic with the man being the sole decision-maker would hold if 0 = 0. Hence if 0 takes extreme values, the household will be more prone to make the child work.4 A simple model to formalize this idea may be specified as follows. We shall assume that there are two goods, 1 and 2, and the two adults, the woman (agent 1) and the man (agent 2), differ in their attitude towards the two goods. Agent 1 tends to like good 1 more. With e denoting the amount of work done by the child, let c(e) be the cost of work to the child, where c'(e):> 0, c"(e) > 0, for all e. We will assume, as explained above, that both parents feel the child's pain of labor. We capture these assumptions in a somewhat stylized manner by assuming that agents I and 2 have the following utility functions: ul = min{xl, ax2} - c(e) u2 = min{ax,, x2} - c(e) where a > 1. If we hold e constant and draw the indifference curves of the two agents in the goods space, xi being the amount of good i consumed by the household, we have a 4 We do not want to claim that our assumptions are beyond reproach. It is, for instance, possible to argue that, while both parents find child labor painful, they differ about what the child should do with the time saved by not working-one nay want the child to stuay, the other to play. This could dilute the zest of the 5 picture as in Figure 1. II and I2 denote indifference curves of, respectively, the woman and the man. If they both face the same budget constraint, for instance, the one shown on line AB in Figure 1, the woman would prefer to consume more of good 1. If a = 1 their relative preferences converge. Assuming that the price of both goods is 1 and child wage is w, the household's problem (using (1) above) is to maximize Q = 0 min{x1, ax2} + (1-0)min{axi, x2} - c(e) (2) subject to xi + x2 < ew + w (3) where w is the total income from non-child-labor sources. The main hypothesis that this paper sets out to test empirically is an outcome of solving the above maximization problem of the household. The result is here stated as a theorem and given a formal proof. In stating and proving the Theorem let us denote the solution to the household's maximization problem as: x, =x (O, w, w) X2 =x2(9,w,w) e =e(O, w, w) . Theorem 1: Starting from 0 = 0, as 0 rises the amount of child labor (i.e. e) initially falls and then rises. parents from keeping the child from work. Our hunch is that this difference will not be big enough to alter our hypothesis. In any case, one way to view the empirical test is as a test of this hunch. 6 Proof. First note that the following inequalities must always hold: ax2 2 x, (4) and ax1 -X2 (5) To prove this, note first that both (4) and (5) cannot be false, since a > 1. So, without loss of generality, assume (4) is violated. Then, given a > 1, it follows that ax, > X; (6) Hence (2) reduces to: Q = 0 a x2 + (l - O)x2 - c(e). Since (4) is false and (6) true, it is possible to raise x2 and lower x, while holding total household expenditure constant. Since this raises Q we have a contradiction. This proves that (4) and (5) must always hold. Hence (2) may be written as: Q = B xi + (l - )X2 - c(e) or further, by using (3), as: Q = Ox, + (1-O)(e-w+ w-x,j) -c(e) (7) The household's aim is to maximize this by choosing xi and e. From (7) it is easy to see that if 0> 1-0, or 0>1/2, (8) then the household will set xi as large as possible, to wit, xi = a x2, since we already know that, if the budget constraint is given by AB in Figure 1, the household will always A A A remain within line segment between points a and b; and that at point a, x, = ax2. This coupled with the budget constraint (3), gives uls 7 a x, =- (ew+w). l+a Inserting this in (7) yields Q) = O a (e + ) + (1- ) (ew )_- c(e) (9) I+a l+a Differentiating this with respect to e and setting it equal to zero, gives us the first- order condition: 1 w a - 10)+ 1+a Next consider the case where (8) is violated, that is O < 1/2. Then the household A will set xi as small as possible (i.e. at point b in Figure 1). Hence ax, = X2, which, along with (3), imply x, = (ew + w) /(1 + a). Inserting this in (8), we get 0 (ew + w) ( )a(ew + w) l+a l+a And from the first-order condition we obtain w(l - a) + aw = c'(e) (11) l+a Since c"(e) > 0, these first-order conditions automatically satisfy the second-order conditions. From (11) it is obvious that as 0 rises, e must fall, since 1 < a and c"(e) > 0. Hence starting from 0 = 0, up to 0 = 1/2, child labor falls as 0 rises. Beyond 1/2, as 0 rises further, (10) becomes the relevant condition and so child labor will begin to rise. l l Hence, what the theorem has shown is that the response of child labor to the index of power of the wife looks as in Figure 2. If the parameters were exactly as specified 8 above the figure would have been a perfect U. But in this case we illustrate a slightly distorted case, as explained below. Before venturing to empirical investigation, it should be clarified that there are other kinds of relations that can with a little ingenuity, be generated theoretically. By introducing a sharply diminishing marginal utility, the U-shaped relation can be altered. Some other possible relations are explored in Basu (2001). This is exactly what makes empirical work important in an area like this. On the basis of some very plausible assumptions we have here established the U-shaped relation. The assumptions we need are essentially that both parents are united about child labor being undesirable but they disagree on what is the ideal consumption basket for the household. The rest of the many assumptions we made were purely for expositional convenience. The exact U-shape, symmetric around V*= 12 is of course a consequence of the specific algebraic assumptions that we made. Also, in reality, the parents may have some difference of opinion about the cost of child labor. It could be that the mother considers this more costly than the father or vice versa. In such cases the U-shape can acquire some distortion, such as becoming, respectively, --shaped (tau-shaped) or J-shaped. In fact the case illustrated in Figure 2 is one where the above result is distorted by adding the feature that that mother finds child labor more painful than the father. Hence, at * - 0 child labor is higher than when 1. 9 3. Data and Results The data on child labor comes from the Nepal Living Standards Survey (NLSS) conducted in June, 1995 by the Household Survey Unit of the Central Bureau of Statistics (CBS). The latter (i.e. CBS) is under the National Planning Commission. The main objective of the NLSS is to collect data from Nepalese households and provide information to the government to monitor progress in national living standards and to evaluate the impact of various policies and programs on the living conditions of the population. The NLSS differs from other surveys that have been done in Nepal in gathering information on a variety of areas rather than focussing only on one area. The sample size for the NLSS is 3388 households. Further, this sample is divided into four strata based on the Geographic regions of the country: mountains, urban hills, rural hills and the terai. The questionnaire for the NLSS collected information at three levels: the household level, the individual level and information on specific items such as food items, land plots and type of crops. Table 1 presents the sample means, along with standard errors, of some of the key variables of interest in our study. To get a sense of where Nepal stands vis-a-vis other developing nations, note that the average number of children in a Nepalese household is somewhat lower than the comparable sample means in the data sets of Peru (3.84) and Pakistan (5.61) reported in Ray (2000, Table 3). Moreover, the gender balance between the number of boys and girls in the household is much more even than that reported for Peru and Pakistan. On average, the most educated female member enjoys less than half the educational experience of the most educated male member of the household. While the ratio of child labor hours to that of the adult male in Nepal (0.19) is somewhat higher 10 than that reported for Peru (0.12) and Pakistan (0.13) in Ray (2000, Table 3), the corresponding ratio of child labor hours to female labor hours in Nepal (0.24) is identical to that in Peru, but a good deal lower than that in Pakistan (0.60). The information on daily wages shows that a mild gender disparity in child wages in favor of girls is sharply reversed in adults (16-55 years) with the gap narrowing somewhat in the older age groups (56+). To put the theory to test, we need to locate a suitable variable that determines female bargaining or the amount of say that the female has in household decision- making. The detenninants of power are many but it seems reasonable to suppose that the more educated a woman is the more power she will have or, the greater the income contribution she makes to the household, the more say she will have in household decision-making. Accordingly, this study uses, as a measure of the female's bargaining power in the household, the ratio (0) of the educational experience (in years of schooling) of the most educated adult female member to the sum of the educational experiences of the most educated adult male and adult female members of that household. The empirical exercise, subsequently, establishes robustness of the qualitative impact of female bargaining power on chiild labor hours by using an alternative measure for such power, A~~~~~~~~~ namely, the share (9) of adult female earnings in total aduilt (i.e. non child) earnings. Table 2 compares the sample means of 0, 9 and of some other key indicators between households with and without working children. The following points are worth noting: (i) the female's share of the household's educational experience (0) is considerably lower A than her share of adult earnings (9), and (ii) the sharp fall in the ratio of rural to urban households from those with working children to those without suggests that the majority of Nepalese child laborers are in the rural areas. Table 3 provides information on the share (at sample mean) of adult female, adult male and child earnings in total household's earnings, and on how these shares vary between households with and without working children. The share of child labor earnings in total household earnings in Nepal (5.6%) is nontrivial and is very close to the figure (5.9%) reported for Pakistan and much higher than that for Peru (1.6%) reported in Ray (2000, Table 4). Note that in the subsample of Nepalese households with working children, the share of child earnings rises to over 20%. Let us now turn to the estimates. In the following discussion, we refer to el, e2, e3 as the aggregate labor hours worked, respectively, by adult females, adult males and children (0-15 years), and w1, W2, W3 are the corresponding daily wage rates. The empirical exercise centers around the estimation of child labor hours (e3) under alternative specifications. The basic child labor hours equation is specified as follows: e3h = PO + Pl1h + P2 O + P3(tPC)h + P4 n3h + 15 n4h + P6W3h + Ulh (12) where h denotes household, n3, n4 denote, respectively, the number of children in age groups 10-15 years and less than 10 years; tpc is the total per capita consumption. Note that tpc is used as a proxy for non child household income in the absence of reliable income information. Note, also, that as the estimated coefficients for ni (number of adult females) and n2 (number of adult males) turned out to be insignificant, they were omitted in the estimations reported below. The alternative specifications for the estimation of (12) are as follows. (A) OLS estimation of (12). (B) Estimation of (12) with Heckman correction for sample selection. 12 (C) Instrumental 'Variable Estimation (IVE) of (12) with tpc regarded as an endogenous regressor, and instrumented by a set of variables. The IVs used are: non child (i.e. adult) earnings, (adult earnings)2 , development region (DR, measured as a qualitative variable), rural/urban (RUR, measured as a dummy which takes the value 1 if household is rural, 0 if it is urban), n1 (no. of adult males), n2 (no. of adult females). (D) Simultaneous Equation Estimation, using 3 SLS, of a 5 equation system consisting of (:12) and the following 4 equations. (note: The household subscript, h, has been omitted for clarity) ei = yo + ylw! + y2w2 + y3N + y4 tpc + y5s + 7602 + U2 (13) e2 = CEO + a wl + CE2w2 + a-,N + a4tpc + a50 + C(602 + u3 (14) tpc = 8o + 81DR + 82RUR + 83n1 + 84n2 + 85n3 (15) + 86114 + 67WI + 88W2 + 89W3 + U4 0 = -o + E1DR+ G2RUR+ E3nI + E4n2 + E5n3 (16) + E6114 + E7W1 + E8W2 + E9W3 + U5 where N (=nj + n2 + n3 + n4) denotes the total number of household members, and (u2, U3, U4, U5) are the stochastic error terms. The 3 SLS procedure, used in estimating (D) [i.e. equations (12) - (16)], besides recognizing the endogeneity of 0, tpc, also, allows mutual feedback between equations (12) - (16) through the non diagonal (5 x 5) variance matrix of the estimated errors of the 5 equation system. As already noted, we investigate the sensitivity of our results to the variable used to measure the female's bargaining power by re-estimating (D) with 0 replaced by 0 ( = wjej/(wiei + w2e2)) in the equations. Since the focus of this paper is on e3 [equation (12)], we report, in case of (D), only the 3 SLS estimates of equation (12), while those of equations (13) - (16) will be made available on request. Table 4 presents the estimates of equation (12) under the alternative specifications (A) - (D). In addition, the table also reports the 3 SLS estimates of equation (12) in the 5 equations system [equations (12) - (16)], with 0 being replaced A by 9 as a measure of female power. The latter is referred to as specification E. Note, 13 incidentally, that the tables report robust standard errors correcting for an unknown form of heteroskedasticity. We, also, estimated a tobit regression model of the child labor hours, e3 [equation (12)]. The coefficient (left censored) estimates and standard errors of this model, referred to as specification F, are presented in Table 5. In this paper, we have defined an 'adult' as an individual aged 16 years and above. However, to examine robustness of our principal empirical results to the definition of an 'adult', in the Heckman and 3SLS estimates reported in Table 4 (ie., specifications B, D), an 'adult' is defined to be an individual aged 20 years and above. The following conclusions emerge from Tables 4, 5. (i) The magnitudes of the estimated coefficients are fairly sensitive to the specification. However, the direction of impact, i.e. the sign of the estimate, is generally quite robust. For example, the child wage rate (W3) and the number of girls, boys in the household (n3, n) have significantly positive impact on child labor hours. Similarly, rising household affluence (as measured by tpc) either significantly reduces child labor hours (as in specifications A, C, E, F) or has no significant impact (as in specifications B, D). (ii) Of particular interest in this study, are the estimated coefficients of 0, 02 A A (specifications A-D, F) and of 9,9 2 (specification E). Tables 4 & 5 confirm that, A while the magnitudes vary, the estimate of the linear coefficient (i.e. of 0, 9) is negative and highly significant and that of the quadratic coefficient (i.e. of 02, A 0 2) is positive and highly significant in most cases. The IV estimates of 0, 02 (specification C), which are both statistically insignificant, are the main exception. In other words, conditional on the other household characteristics remaining A unchanged, the relationship between e3 and 0 (or 9) is U shaped (or, more precisely, tau-shaped) exactly as predicted in the previous section. It is important to note that this U shaped relationship is quite robust to specification. A (iii) To throw further light on the impact of female's bargaining power (0, 9) on child labor hours, we plot the graphical relationship between the two under the alternative specifications (A) - (F), with the other variables held constant at the sample means. The graphs, presented in Figs. 3(a) - 3(f), all confirm that as we A move from a state of negligible female power (i.e. 0, 9 - 0) to one where it is A nearly absolute (i.e. 0, 0 - 1), child labor hours (e3) initially decline but, then, 14 increase, as women begin to dominate men in terms of their educational experience or their labor earnings. (iv) These graphs, also, largely agree on another interesting finding. While the initial A A decline in e3, with increasing 0 (or 9)., is reversed beyond a critical 0 (or 9), the A value of e3 at 0 = 0 = I is less than that at 0 = 9 = 0. In other words, child labor A hours, when male power is fully dominant (0 = 9 = 0), exceed that when female A power dominates completely (0 = 9 = 1). In other words, the incidence of child labor as a function of female power is i:-shaped. In closing we should mention that in this study we have made no effort to distinguish between male and female child labor. From the piecemeal evidence that is available on this we know that the gender of the child makes a difference; that the incidence of girl and boy labor can be very different and they may respond to different variables. However, our theoretical analysis suggests that even if the incidence of male and female child labor happens to be different, each one's response to changes in the structure of power in the household should be the same in the sense of both being tau- shaped. Nevertheless, this is a subject of interest and deserving of future empirical investigation. 4. Policy As awareness of the enormous problem of child labor worldwide has increased, there has occurred a rise in research trying to identify the determinants of child labor. This research has the value of informing policymakers how best to mitigate the problem of child labor. While studies have isolated factors such as parental income, parental education, school quality, incentives given for attending school, credit availability (see, for instance, Basu and Van, 1998; Basu, 1999; Ravallion and Wodon, 2000; Ray, 2000; 15 Baland and Robinson, 2000), there have been very few studies on the relation between the balance of power in the household between the husband and the wife and its impact on child labor. The results derived in this paper show that from the point of view of child labor it is best to have households where power is evenly balanced, that is, neither the man (and, more surprisingly) nor the woman should have a disproportionate amount of power. While previous studies have shown that higher parental education makes child labor less likely, our study shows that there are greater subtleties involved in this relation. While it may be better, ceteris paribus, to have more-educated adults, the incidence of child labor is kept at its lowest by achieving a more balanced level of education among the parents. Since most developing countries are characterized by a disproportionately low level of education and literacy among women, our study provides additional reason why female education ought to be emphasized in developing countries. 16 Table 1: Selected Household Characteristics in Nepal (Sample Mean) Characteristic Sample Mean(a) Number of children in the household 2.70 (2.08) Ratio of girls to boys 0.97 (1.12) Ratio of the most educated woman's educational experience to 0.46 that of the most educated man in the household(') (0.62) Daily Child Wages of Girls (10 - 15 years) Rs. 44.32 (38.33) Daily Child Wages of Boys (10 - 15 years) Rs. 38.70 (24.06) Daily Adult Wages of Females (16 - 55 years) Rs. 51.35 (47.71) Daily Adult Wages of Males (16 - 55 years) Rs. 86.42 (71.99) Daily Adult Wages of Elderly Females (56 years +) Rs. 51.46 (65.04) Daily Adult Wages of Elderly Males (56 years +) Rs. 61.31 (48.32) Ratio of child labor hours to adult female labor hours 0.24 (0.57) Ratio of child labor hours to adult male labor hours 0.19 (0.41) Rural (=1) or Urban Household (=0) 0.79 (0.41) a Figures in parentheses denote standard deviations. bMeasured in years of schooling. 17 Table 2: Comparison of Selected Household Characteristics Between Households With and Without Working Children Sample Mean(a) Characteristic Households with Households without Working Children Working Children (e3 > °) (e3 = 0) Woman's Share of Educational 0.40 0.39 Experience (0) (.31) (0.32) Woman's Share of Earnings (0) 0.27 0.29 (0.29) (0.29) Percentage of Total Consumption 0.0228 0.0289 Spending on Education (.043) (.053) No. of Adult Women (16 years and 2.89 2.64 above) (1.81) (1.67) No. of Adult Men (16 years and 3.02 2.71 above) (2.10) (1.89) No. of Girls (0 - 15 years) 1.91 0.51 (1.44) (0.80) No. of Boys (0- 15 years) 2.04 1.70 (1.76) (1.56) Rural (=1) or Urban (=0) Household 0.87 0.75 (0.33) (0.43) Adult Earnings Rs. 12.13 Rs. 21.94 (11.80) (22.41) aFigures in parentheses denote standard deviations. 18 Table 3: Shares of Household Earnings in Nepal Sample Meana Households with Households Household Member Working Without Working All Children Children Households (e3 > O) (e3 = O) Woman's Share 0.331 0.389 0.374 (.207) (.316) (.292) Man's Share 0.458 0.611 0.570 (.251) (.316) (.308) Child's Share 0.211 .056 (0.165) (.126) 'Figures in parentheses denote standard deviations. 19 Table 4: Estimates of Child Labor Hours Under Alternative Specificationsa Coefficient Estimate Coefficient Estimate Variable OLS Heckman IVb 3 SLSc Variable 3 SLSd (A) Correction Estimation Estimation Estimation (B) (C) (D) (E) Female's Share -0.145e -1.73e-7e -0.054 -0.974e Female's Share -0.278e of Adult (.061) (3.35e-8) (.069) (.480) of Adult (.110) Education (0) Earnings (0) 02 0.145' l.19e-7e 0.055 1.041 A 2 0.207e (.067) (3.40e-8) (.073) (.559) 0 (.100) Total per -9.2le-7e -2.79e-13 -4.26e-6e 7.98e-7 tpc -8.59e-6e capita con- (4.66e-7) (1.73e-13) (1.45e-6) (3.56e-6) (1.47e-6) sumption (tpc) No. of Girls .109' .1 14e .108e .130e n3 0.130e (n3) (.021) (0.017) (.021) (.007) (.007) No. of Boys .019e .01le .014e .021e n4 .016e (n4) (.007) (.005) (.007) (.005) (.004) Child Wage .013e .015e .013e .014e W3 .014e Rate (W3) (.002) (.001) (.002) (.0004) (.0004) Constant -.029 -.022 .002 -.025 Constant .071 (.021) (.013) (025) (.023) (.030) aRobust Standard Errors in parentheses. bHausman Test for Ho: Difference between OLSE (Specification A) and IVE (Specification C) is not systematic is: X52 = .08 i.e. Ho is not rejected. See text for a list of the instruments used. cBreusch Pagan Test for Ho: Variance Matrix for Specification D is diagonal is X2 = 246.332 i.e. Ho is rejected. dBreusch Pagan Test for Ho: Variance Matrix for Specification E is diagonal is X2 = 923.1 16 i.e. Ho is rejected. eStatistically significant at 5% level. 20 Table 5: Tobit Estirnatesa of C!iUd Labor Hours (Specification F) Variable Coefficient Estimate Female's Share of Adult Education (0) -0.649b (.269) 02 0.725b (.307) Total Per Capita Consumption (tpc) -.00003 Ib (6.68e-6) No. of girls (n3) 0.405b (.032) No. of boys (n4) .027 (.015) Child Wage Rate (W3) .030b (.001) Constant -1.136 (.086) aStandard Errors in Parentheses. bStatistically significant at 5% level. 21 References Baland, J.-M. and Robinson, J. A. (2000), 'Is Child Labor Inefficient?', Journal of Political Economy, vol. 108, 663-79. Basu, K. and Van, H. (1998), 'The Economics of Child Labor', American Economic Review, vol. 88, 412-27. Basu, K. (1999), 'Child Labor: Cause, Consequence and Cure with Remarks on International Labor Standards', Journal of Economic Literature, vol. 37, 1083-119. Basu, K. (2001), 'Gender and Say: A Model of Household Behavior with Endogenously- Determined Balance of Power', CAE Working Paper # 01-01, Cornell University. Becker, G.S. (1981), A Treatise on the Family, Cambridge, Harvard University Press. Bourguignon, F. and Chiappori, P.A. (1994), 'The Collective Approach to Household Behavior', in Blundell, R., Preston, I., and Walker, I. (eds.), The Measurement of Household Welfare, Cambridge, U.K.: Cambridge University Press. Browning, M., Bourguignon, F., Chiappori, P.A. and Lechene, V. (1994), 'Income and Outcomes: A Structural Model of Intra-household Allocation', Journal of Political Economy, vol. 102, 1067-96. Browning, M. and Meghir, C. (1991), 'The Effects of Male and Female Labor Supply on Commodity Demands', Econometrica, vol. 59, 925-51. Chiappori, P.A. (1988), 'Rational Household Labor Supply', Econometrica, vol. 56, 63-89. Emerson, P. and Portela, A. (2001), 'Bargaining over Sons and Daughters: Child Labor, School Attendance and Intra-household Gender Bias in Brazil', mimeo: University of Colorado at Denver. Iversen, V. (2001), 'Child Labour and Theories of the Family: The Case of Bargaining Peasant Households in Sub-Saharan Africa', mimeo: University of East Anglia. Kanbur, R. and Haddad, L. (1994), 'Are Better off Households more Equal or Less Equal?', Oxford Economic Papers, vol. 46, 445-5 8. Lundberg, S. Pollak, R. and Wales, T. (1997), 'Do Husbands and Wives Pool their Resources? Evidence from the United Kingdom Child Benefit Experience', Journal of Human Resources, vol. 32, 463-80. Moehling, C. (1995), 'Intra-household Allocation of Resources and the Participation of Children in Household Decision-making: Evidence from Early Twentieth-Century America', mimeo. Ravallion, M. and Wodon, Q. (2000), 'Does Child Labour Displace Schooling? Evidence on Behavioral Responses to an Enrollment Study', Economic Journal, vol. 110, C158-75. Ray, R. (2000), 'Child Labor, Child Schooling and their Interaction with Adult Labor: Empirical Evidence for Peru and Pakistan', World BankEconomic Review, vol. 14. 22 Figure 1: Indifference Curves X2 AL ~~~Slope a B \____ - Slope=- a~~~~~~ O A XI Figure 2: The Incidence of Child Labour e A2 0 0 23 Figure 3: Relationship Between Child Labor Hours and Female Power Under Alternative Specifications* Figure 3(a). OLS Child Labor (e3) 0.25 0.21 0.15 0.1- 0.05 - 0 0 0.2 0.4 0.6 0.8 1 Female Power (6) Figure 3(b). Heckman Model Child Labor (e3) 0.21321068 0.21321067 0.21321066 0.21321065 0.21321064 0.21321063 - 0.21321062 0.21321061 0.2132106 0 0.2 0.4 0.6 0.8 1 Female Power (0) * Child labor is measured in standard days. Other variables in each regression were held fixed at their mean value. 24 Figure 3(c). IV Model Child Labor l'e3) 0.194 0.192 0.19 -/ 0.188\/ 0.186 0.184-- 0.182 0.18 0.178 0.176 0 0.2 0.4 0.6 0.8 1 Female Power (6) Figure 3(d). 3SLS Model, 9 Child Labor (e3) 0.35 0.31 0.25 0.2 - / 0.15 0.1 - 0.05- 0- 0 0.2 0.4 0.6 0.8 Female Power (6) Note that the coefficients of 0,02 are both statistically insignificant [see Table 4]. Since the coefficients in the other models are significant, the insignificance here may indicate that the instruments are not the most appropriate. 25 Figure 3(e). 3SLS Model, 9 Child Labor (e3) 0.3 0.25 0.2 0.15 0.1 0.05 - 0 0.2 0.4 0.6 0.8 1 Female Power A Figure 3(f). Tobit Model Child Labor (e3) 0.5 0.4 0.3 0.2 0.1 0 0.2 0.4 0.6 0.8 1 Female Power (6) 26 Policy Research Working Paper Series Contact Title Author Date for paper WPS2791 The Static and Dynamic Incidence of Dominique van de Walle February 2002 H. Sladovich Vietnam's Public Safety Net 37698 WPS2792 Determinants of Life Insurance Thorsten Beck February 2002 A. Yaptenco Consumption across Countries Ian Webb 31823 WPS2793 Agricultural Markets and Risks: Panos Varangis February 2002 P. Kokila Management of the Latter, Not the Donald Larson 33716 Former Jock R. Anderson WPS2794 Land Policies and Evolving Farm Zvi Lerman February 2002 M. Fernandez Structures in Transition Countries Csaba Csaki 33766 Gershon Feder WPS2795 Inequalities in Health in Developing Adam Wagstaff February 2002 H. Sladovich Countries: Swimming against the Tide? 37698 WPS2796 Do Rural Infrastructure Investments Jocelyn A. Songco February 2002 H. Sutrisna Benefit the Poor? Evaluating Linkages: 88032 A Global View, A Focus on Vietnam WPS2797 Regional Integration and Development Maurice Schiff February 2002 P. Flewitt in Small States 32724 WPS2798 Fever and Its Treatment among the Deon Filmer March 2002 H. Sladovich More or Less Poor in Sub-Saharan 37698 Africa WPS2799 The Impact of the Indonesian Lisa A. Cameron March 2002 P. Sader Financial Crisis on Children: Data from 33902 100 Villages Survey WPS2800 Did Social Safety Net Scholarships Lisa A. Cameron March 2002 P. Sader Reduce Drop-Out Rates during the 33902 Indonesian Economic Crisis? WPS2801 Policies to Promote Saving for Dimitri Vittas March 2002 P. Infante Retirement: A Synthetic Overview 37642 WPS2802 Telecommunication Reforms, Access Antonio Estache March 2002 G. Chenet-Smith Regulation, and Internet Adoption Marco Manacorda 36370 in Latin America Tommaso M. Valletti WPS2803 Determinants of Agricultural Growth Yair Mundlak March 2002 P. Kokila in Indonesia, the Philippines, and Donald F. Larson 33716 Thailand Rita Butzer WPS2804 Liberalizing Trade in Agriculture: John S. Wilson March 2002 P. Flewitt Developing Countries in Asia and the 32724 Post-Doha Agenda WPS2805 To Spray or Not to Spray? Pesticides, John S. Wilson March 2002 P. Flewitt Banana Exports, and Food Safety Tsunehiro Otsuki 32724 Policy Research Working Paper Series Contact Title Author Date for paper WPS2806 Dirty Exports and Environmental John S. Wilson March 2002 P. Flewitt Regulation: Do Standards Matter to Tsunehiro Otsuki 32724 Trade? WPS 2807 The Role of Natural Resources in Benoit EBosquet March 2002 D. Duff Fundamental Tax Reforn in the 39506 Russian Federation WPS2808 A Capital Accord for Emerging Andrew Powell March 2002 E. Mekhova Economies 85984 WPS2809 On the Measurement and Impact of Robert D. Ebel March 2002 M. Morris Fiscal Decentralization Serdar Yilmaz 37285 WPS2810 Growth, Distribution, and Poverty Luc Christiaensen March 2002 N. Nouviale in Africa: Messages from the 1990s Lionel Demery 34514 Stefano Paternostro WPS2811 The Epidemiological Impact of an John Stover March 2002 H. Sladovich HIV/AIDS Vaccine in Developing Geoff P. Garnett 37698 Countries Steve Seitz Steven Forsythe WPS2812 Can Financial Markets be Tapped to Jerry Skees March 2002 P. Kokila Help Poor People Cope with Weather Panos Varangis 33716 Risks? Donald Larson Paul Siegel