THEWORLDBANK Discussion Paper EDUCATION AND TRAINING SERIES Report No. EDT9 Participation in Schooling: Deferminants and Learning Outcomes In Nepal Dean T. Jamison Marlaine E. Lockheed December 1985 Education and Training Departrnent Operations Policy Staff The views presented here are those of the author(s), and they should not be interpreted as reflecting those of the World Bank.. Other Available EDT Discussion Papers EDTI General Operational Review B. Searle July 1985 of Textbooks EDT2 Does SENA Matter?--Some E. Jimenez August 1985 Preliminary Results on the B. Kugler Impact of Colombia's National Training System on Earnings EDT3 Higher Education K. Hinchliffe August 1985 in Sub-Saharan Africa EDT4 Planning of Education: G. Psacharopoulos August 1985 Where Do We Stand? EDT5 Evaluation in World Bank B. Searle, ed. August 1985 Education Projects: Lessons from Three Case Studies EDT6 Financing Technical Education C. Lee September 1985 in LDCs: Economic Implications from a Survey of Training Modes in the Republic of Korea EDT8 The Structure of Educational E. Jimenez August 1985 Costs: Multiproduct Cost Functions for Primary and Secondary Schools in Latin America EDT 9 Participation in Schooling: D. Jamison December 1985 'Determinants and Learning M. Lockheed Outcomes in Nepal EDT1O Classroom Uses of the J. Friend November 1985 Computer: A Retrospective View with Implications for Developing Countries EDT17 Childhood Malnutrition P. Moock December 1985 and Schooling in the Terai J. Leslie; Region of Nepal; Child D. Jamison Malnutrition and School Performance in China EDT20 Lending in Primary R. Romain November 1985 Education: Bank Performance Review, 1962-1983 (Continued on back cover) Discussion Paper Education and Training Series Report No. EDT9 PARTICIPATION IN SCHOOLING: DETERMINANTS AND LEARNING OUTCOMES IN NEPAL Dean T. Jamison and Marlaine E. Lockheed Education Policy Division Education and Training Department December 1985 The World Bank does not accept responsibility for the views expressed herein, which are those of the author(s) and should not be attributed to the World Bank or to its affiliated organizations. The findings, interpretations, and conclusions are the results of research or analysis supported by the Bank; they do not necessarily represent official policy of the Bank. The designations employed, the presentation of material, and any maps used in this document are solely for the convenience of the reader and do not imply the expression of any opinion whatsoever on the part of the tWorld Bank or its affiliates concerning the legal status of any country, territory, city, area, or of its authorities, or concerning the delimitation of its boundaries, or national affiliation. Abstract This paper examines the determinants of adult cognitive competencies and of child school participation in the Terai region of Nepal. Data on three generations from 795 rural farm households were analyzed. The results of the analysis are: 1) First generation (grandparent) landholdings, literacy and caste status were significant determinants of second generation "innate ability" as measured by the "Ravens Progressive Matrices" (RPM) test. 2) RPM was a significant determinant of second generation schooling. 3) Second generation schooling was a significant determinant of second generation literacy, numeracy, reading comprehension and attitudinal modernity. 4) Attitudinal modernity was a significant determinant of attitude toward school for all households, but not for the subset of households in villages for which school availability data had been obtained. 5) In these latter villages, there was no relationship between school availability and a positive attitude toward school. 6) Third generation child school participation was determined jointly by second generation landholdings, caste, schooling and numeracy, and attitudinal modernity, and the child's sex. 7) Girls were significantly less likely to have completed at least one year of school than were boys. 8) The presence of small children in the household only slightly decreased girls' chances to participate in school. 9) School availability had no tffect on child school participation. ACKNOWLEDGEMENTS This paper was prepared under the auspices of World Bank research project RPO 671-49, "Education and Rural Development in Nepal and Thailand," which was undertaken by World Bank staff and consultants in collaboration with staff of New ERA, a Nepalese research and consulting firm. A number of our colleagues -- Bal Gopal Baidya, Susan Cochrane, Joanne Leslie, Peter Moock and Rajendra Shrestha -- have provided valuable advice and assistance on various aspects of our work, and we wish to acknowledge our indebtedness to them. Erwin Chou and Kalpana Mehra provided expert computer assistance on all aspects of the work. Participation in Schooling: Determinants and Learning Outcomes in Nepal There Is substantial evidence that suggests that the level of attained adult education is related to such dimensions of development as individual earnings and employment in the urban labor markets,1 agricultural productivity,2 human fertility,3 and health and nutritional status4. Nonetheless, there are relatively few empirical studies of the mechanisms underlying these effects. In order better to understand education's effects on these development outcomes, this paper uses data from rural Nepal to examine education's effects on such potentially mediating variables as adult cognitive competencies5 and attitudes6. A further potentially important consequence of schooling and improved cognitive competence of adults is to increase the desire for schooling for their children, and this paper reports on Lhis and other determinants of school participatLon as well as Lts cognitive consequences. -2- This paper is organized as follows: Section 1 presents background material concerning the determinants of adult cognitive competencies and attitudes and of child school participation; Section 2 describes the data; Section 3 examines the determinants of adult attitudes and cognitive competencies; and Section 4 examines the determinants of child school participation. The fifth section summarizes our conclusions. 1. Background .1.1 Determinants of Adult Cognitive Competencies There have been numerous and diverse studies attempting to relate school outcomes to variations in the amount or quality of school inputs. The findings of these studies have sometimes been interpreted to imply that schools do not make a difference. Yet there Ls growing evidence that the number of years spent in school do affect both adult cognitive competencies and adult attitudes, which, In turn, are determinants of child school participation. While these studies provide little guidance concerning how to improve the quality of schooling, they do conclusively show the enduring impact of schooling on various dimensions of cognitive capacity. Relatively few of the available empirical studies of the effects of years of education are from less developed countries, and one purpose of this paper is to use data From Nepal to help fill this gap. Two recent revLews have summarized most of the relevant literature. Harnqvist7 has summarized studies from Lhe U.S. and Sweden, and Sheffield8 has summArized studies from a number of low-income countries. The overwhelmLngly consistent fLndlngs of Lhese studies was that years of schooling affected LLteracy,9 reading and writing,t0 numeracy,t' and modernity.12 -3- One important shortcoming of the available literature Ls that, with data gathered only on adults, it is difficult to ascertain the extent to which an observed correlation between completed schooling and cognitive competence may result in part from the plausible hypothesis that more innately able individuals both attend school longer and would in any case perform better on tests of adult competence. While it is difficult to assess with complete adequacy the extent to which this hypothesis is correct, by including a test of 'ability' along with our other, more achievement-oriented measures, we are in this paper in part ahle to control for this effect. 1.2 Determinants of School participation School participation in Nepal is low for all but primary school males, and total enrollment rates for children 9-15 are well below 20%. (Table 1). In general, littLle empirical work on the determinants of school enrollments in less developed countries has been conducted; Birdsallt3 provides a valuable overview of available evidence. Since near-universal male primary school enrollments are now common (though far from universal), much work has been directed toward explaLning female enrollments. Reviewing these studies, Bowman and Anderson14 cite five major determinants of female enrollments--ethnic and regional differences, caste differences, paternal occupatlion, paternal education, attitudinal modernity and such miscellaneous factors as foreign travel or language usage. Such factors have also been shown to be related to positive parental attitudes toward schooling for children. -4- Research on determinants of school participation in Nepal in particular Is very limited. Such research as does exist suggests that -- in addition to the factors cited by Bowman and Anderson -- household economic factors, student health and nutritlonal status,15 school availability, and school quality and relevance are all important. In the next subsections we discuss the factors commonly believed to affect school participation, with particular reference to conditions in Nepal. 1.2.1 School availability Lack of school supply could arise either because there is no school within walking distance, because the available schools are overcrowded or because the quality of available schooling is low. Walking distance. School availability in Nepal has Lncreased dramatically in the past 30 years. In 1951 there were 321 primary schools enrolling less than one percent of eligible children; in 1975 there were 8,708 schools enrolling 59 percent of the children;16 by 1982 the number of primary schools had risen to 9,404.17 Since there are large numbers of primary schools in Nepal It would seem Lhat distance to school Is not a major problem on the average. There probably Is, however, a substantial minority of primary school-age children In rural areas for whom distance to primary school Ls a problem. At the lower-secondary level there are fewer than a quarter as many schools, and distance to school may be more of a problem. Shrestha18 reports, however, that while dLstance to school was related Lo school part1itpation in Corkha District, lt was reported by parents In Jumla, OhankuLa and Chitawan Districts to be one of the least important reasons for not sendlng children to school. -5- Crowding. The average student-to-teacher ratlio Ls low for both primary and secondary levels (nationally only about 32; in the districts examined in this paper, 28 and 30). Thus, overcrowding probably poses no problem for most students at either level. School quality and relevance. Another important problem for primary and lower-secondary schooling, particularly in rural areas, is the students' lack of access to schooling that is relevant to their lives and of a quality sufficient to make attendance worthwhile. In the relatively few studies of determinants of school-leaving behavior in developing countries, poor quality of teachers has emerged as a principal reason for student's dropping out.19 School quality affects student dropout propensity both directly and through Increasing the incidence of repetition, which itself causes higher dropout rates. Direct evidence about the quality of learning in Nepal's primary schools Is limited. One recent study completed by the Institute of Education,20 however, suggests that the quality of learning Is quite low, and reflects the very poor conditions for learning: untrained teachers, Lnsufficient materials, and monotonous teaching methods. Many teachers lack the school-leaving certLificate earned after tenth grade graduation, and perhaps only one-third of all teachers have training beyond the tenth grade. Teaching matertals are scarce, although the impressive effort now underway to prepare and distribute textbooks and teachers' guides for all subjects at all grade Levels may help to Lmprove Lhe situation. TeachLng methods are traditional, vILh classes dominated by teacher lectures and unembellished readings from the textbooks. Students are expected to - 6 - respond chorally to the teacher's quesLions, to recite alould from their texts and, In general, to memorize. Students are rarely asked to relate the content of their lessons to their own experiences and perceptions, and rarely expected to analyze, synthesize, or consider questions of cause rather than questions of fact. Students are not encouraged to ask questions.21 1.2.2 Demand for schooling Lack of parental demand for education could arise from out-of-pocket costs for schooling, the opportunity cost of student's time, and/or parental attitudes regarding schooling. Out-of-pocket costs. These Include direct tuition expenses and the cost of books. Under Nepal's New Education System Plan, the government finances all of the primary teacher's salary and three-fourths that of a lower-secondary teacher, except In remote areas where all the costs of lower-secondary Leachers are borne by the government. It has been estimated that costs to the student for primary education are about Rs.15 per year for copybooks, pencils and examination fees. The addition of school uniforms, estimated to cost Rs,70 each, Lncreases the direct cost of primary school atLendance to Rs.90-300 annually. The costs to a lower- secondary student are about Rs.78 for copybooks, pencils, examination fees and books. Whlle students Ln remote areas will have teacher and book costs somewhaL more subsidized than these numbers would indicate, Lhey are far less easily able to afford cash expenditures of these amounts, as total household cash income In rural Nepal Ls only Rs.1500-Rs.2000 annually. 7- The out-of-pocket cash expenditures can he expected to be a significant barrier to students' access to schooling, particularly at the lower-secondary level. Shrestha22 found that low family income was the most important reason reported for parents not educating children ln the Chitawan District and the next most important reason in the Dhankuta District. Cost of student's time. At both the primary and lower-secondary levels, the time a rural student spends in school must frequently be at the expense of his or her doing useful work at home.23 Studies show that the demand for female child labor Is higher than the demand for male child labor. Acharya and Bennett24 report that in 8 representative districts in Nepal, girls aged 5-9 work 3.4 hours per day and that girls aged 10-14 work 7.3 hours per day, which is 50% more than boys In the same age groups work. A study of farm households in Kabre Palanchowk found that 25% of girls and 13% of boys aged 6-14 were employed ln farm labor.25 A study undertaken in Pokhara, Nepal, reported in Kasaju26 found that: "Youngsters who do not come to school need to work for their parents, ... need to support their family's economy and ... cannot complete the school because the number of hours they are required to stay at school does not match with the number of hours they can afford to spend. In a study, 'A survey of parental reasons for not sending their children to primary school Ln Pokhara Town Panchayat Area,' Nfr. tTpadhva has pointed out the need for a child to work Ln support of the family as one of the most frequently LisLed reasons for no-enrollment. The most frequentLy stated reason, states Mr. IUpadhva, was that Lhe parents did not see any value in educating yirls. This finding Is confirmed by Shrestha,27 who reports the primary reason for parents in Jumla, Gorkha and Dhankuta not wishing to educate their children as being a "lack of supporting members for household." That "girls are to be given away In marriage" was found to be the second most frequently mentioned reason for not educating girls in Jumla, Gorkha and Chitawan. Attitudes. According to Ministry of Education data, in 1977 only approximately 30% of the age cohort of female children were involved In primary schools. Female school enrollment in rural areas has been shown to be related to parental attitudes, particularly parental conservatism.28 The evidence from Shrestha and IJpadhya suggest that parental conservatism may be one factor restricting girls' education Ln Nepal. A recent study of parental attitudes in Dolkha, Bank and Kathmandu Districts reported that "The general notion of these parents about girls was that girls would not remain an asset to them all along, which Implies that higher investment on their education was not warranted from the practical point of view."29 1.3 The Causal Model In the present paper, we examine the effects of these factors across three generations. Figure I illustrates the causal structure. The variables In Boxes A-D are entirely exogenous and are assumed to affect second and third generation variables In Boxes F-H; the variables Ln Box E -first generation land hoLding and lLteracy-are also exogenous, but they are separated to clarifv the Lnter-generational structure of this model. The variables In Box A--dLstrict, caste and age-and Ln Box E are assumed to Influence '-nnate" abiLLty as measured by the Raven's Progressive 0 , I' I I0 I I 1 + - m1~~~I 1- H g | _ n B f @ fi v + * - | 1-h I * M ] QQ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~( I -~~~~~n I ~~0 I' I z I ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ S z s ! g~~~~~~~~~~~~~~~~~~~~~~2 § | ¢ § 1 2~~~~~~~~ - 10 - Matrices (RPM) test; this variable, combined with the exogenous variables, is assumed to influence the amount of schooling an individual receives, than the amount of land currently owned by the individual, and finally, the adult cognitive competencies of that individual. All the preceedlng variables taken together plus the availabiltiy of schools (Box B) are assumed to influence adult attitude toward school (Box G). Finally, all these variables, taken in combination with the number of children in the household (Box C) and the child's sex (Box D) are assumed to affect the third generation's school participation. 2. Data Data for this analysis were obtained from a survey of 795 households studied as part of a World Bank research project examining the effects of educatlion and agricultural extension on rural development. The site chosen for the project was determined by the major research objectives concernlng the effects of education on agricultural productivity. The households to be lnterviewed were chosen randomly within. each of six panchayats In two distrtcts--Bara and Rautahat. A list of owners of all dwellLngs Ln each panchayat was obtained from Lhe local rural health workers (these lists had been prepared In connection with the health programs). Then, uising a three-digit, random number Lable obtained from the Nepal CentraL Btureau of StatLstLcs, households to he LntervLewed were selected randomlv 4lLhLn a panchavat. until a 15% sample of households Ln each panchayat had So.n chosen (ten extra households per panchayat were chosen for replacemeLt). - 11 - The study households were visited three times, first in October- November 1977, next in January-March 1978, and last In April-May 1978. Field workers for the interviewing were recruited by the members of the New ERA research team In B.rgunj, Kalaiya (district headquarters of Bara) and Guar (district headquarters of Rautahat). The final field team comprised seven males and seven females, who worked in pairs. All the field workers spoke both Nepali and Bhojpuri; they translated the questions from Nepali (In which the instruments were written) to Bhojpuri in the field. Table 2 shows the calendar of data collection and indicates the overall nature of the data collected. Information obtained from the study households at one or more of the three field visits Includes data on household characteristics, agricultural productivity, fertility, nutritional status and various education measures of household members. The availability of primary and secondary schools in the sample villages, as well as the dLstance to primary and secondary schools, was obtained in May 1979. This information was available for 23 of the 28 villages studied. En this paper, data from three generations are analyzed, with first generation data on literacy and landholdings used to predict second generatLion cognitive competencies and first and second generation data used to predLct third generatLon school participation. In the former analysis, the record For the head of the household provides the unit of analysis, while Ln Lhe latter analysis both household and child records serve as units of analysis. A child was defined as a son or daughter of the household head, a nephew or niece of the household head, a grandchild - 12 - or great grandchild of the household head, or an adopted child. Younger sibs of Lhe head of the household, aunts or uncles, sisters-in-law, daughters-in-law, servants and unrelated children were excluded. These children are the third generation. Third generation data include a measure of school attendance as a deviation from the average attendance of the child's age cohort and an Indicator of the child's sex. The second generation is the child's parent who Is the head of the household. Second generation data Include information about this household head: the total number of years of schoolLng completed, a measure of literacy, a measure of numeracy, a measure of basic ability (The Raven's Progressive Matrices (RPM) Test), a measure of attitudinal modernity (a modified version of the short form of the Inkeles Overall Modernity (OM) scale), a measure of desire for schooling of male children, and the household landholdings. The first generation Is the head of household's father. First generation data include the literacy and landholdings of the child's paternal grandfather, as attributed to him by the head of household. District of residence and caste status are considered exogenous variables. Those variables analyzed in this paper are described in Table 3; the means, standard deviations and sample size for each variable are given in the sections of this paper in which they are analyzed. The analyses in this paper are restricted to (a) households with children ages 6-16 and having complete head of household data (N-282); (b) households with chiLAren ages 6-16, havlng complete head of household data sets and residinA Li villages for which school avallabillty data were obtained (N-213); (c) alL heads of households with complete data sets (N=369); (d) all heads of households with complete data sets residing Ln - 13 - villages for whom school avaliability daLa were obtained (N=285); (e) children ages 6-16 residing in households having complete data sets and residing in villages for whom school availability data was obtained (N-225). The determinants of second generatLion (adult) cognitive competencies and attitudes will he reported in Section 3 of this paper. Section 4 will present the results of two analyses of the determinants of third generation (child) school partLcipation, one conducted at the household level and one at the individual,child. level of analysis. 3. Determinants of adult cognitive competencies and attitudes 3.1 Methods of analysis We have ordered our variables recursively, starting with background characteristics of the individual and moving sequentially through the various variables that are explained. In this section we discuss only Boxes A, 3, E, F and G of Figure 1 and analyze data from the sample of all heads of households, whether or not school age children were Ln the household. We analyzed the data uslng the ordinary least squares linear regression of the Statistical Package for the Social Sciences.30 Our tables show the estimated regression coefficients below which in parentheses are the F-values Indicating the statistical significance of the estimated coefficient. The means and standard deviations of the variables used in these analyses are reported in Table 4. 3.2 Results The resulL of some of these analyses are presented Ln Tables 5-7 which show the eqtLmated determinants of second generation RPM - 14 - score, schooling, literacy, reading comprehension, numeracy, attitudinal modernity and attitude toward'school. In this section each table will be discussed separately. Raven's Progressive Matrices (RPM) score. The first column of Table 5 presents the results of a single multiple regression analysis of the effects of first generation landholding, first generation literacy, caste status and district of residence on second generation adult RPM score. This regression shows that first generation landholding and first generation literacy were both significant determinants of second generation RPM scores. It Is plausible, of course, that an individual's RPM score Is both an outcome of schooling as well as a determinant of schooling as we have modelled the situation. We thus properly have a simultaneous system which we have Identified In this case by assuming that the coefficient of schooling on RPM be zero. Though this is at best an approximation, it does have justlfication in that the lntention of the RPM is to measure 'Innate' ability and, In our sample, this intention seems to be partially fulfilled in that relative differences between males and females RPM scores are small compared to, say, numeracy scores.31 Schooling attainment. The second and third columns of Table 5 report the results of two multiple regression analyses to estimate the determinants of second generation school attainment. These regressions Indicate that school attainmenL was signLEcantly affected by first generation landholding and literacy, as well as by caste status. The effect of "Innate ahbliLV as measured by RPM score was also statistically significant, both consldered Lndependently (regression coefficient - .317; F - 96.765; r2 - .207) and in combination with the exogenous variables. - 15 - Overall more schooling was attained by younger persons with more literate and landed fathers from the Brahmin, Rajput and Kayastha castes and with higher "innate" abi-lity, than conversely. Higher-status caste members on the average attained nearly 4.5 more years of school than lower-status caste members; Individuals with literate fathers attained nearly 2 more years of schooling than Individuals with illiterate fathers; finally, older individuals attained fewer years of schooling than younger Individuals. Adult literacy. Second generation adult literacy was assumed to be a function of background characteristics, "Innate" ability and schooling. Although first generation landholding, literacy and caste had significant effects on second generation literacy when assessed Independently, these effects operated largely through second generation school attainment (Columns I and 2 of Table 6). Likewise the effects of RPM score on literacy were mediated by schooling. Overall, schooling alone accounted for 67% of the variance in second generation adult literacy; the inclusion of various exogenous and first generation factors in the regressions did little to Lmprove the overall estimation. Adult reading comprehension. Second generation adulL reading comprehension was also asstumed to he a function of background characteristics, "Innate" ability and schooling. Columns 3 and 4 of Table 6 report two of several alternative models of the determinants of second generation reading comprehension. From these regressions we see that the most significant predictor of reading comprehension ls school attainment. The effectq if hoth ElrsL generatton llteracy and second generatton RPM score, 4tatistically signLficant when considered Independently, disappeared when considered simultaneously with school attainment. - 16 - Numeracy. AgaLn, the significant effects of flrst generation literacy on second generation adult numeracy was through the school attainment of the second generation. Second generation school attainment accounted for 22% of the variance ln second generation numeracv, but unlike the models for literacy and reading comprehension, RPM score and age were also significant predictors of numeracy (Columns 5 and 6 of Table 6). Attitudinal modernity. Columns 7 and 8 of Table 6 show that the significant effects on second generation attitudinal modernity of first generation landholding, first generation literacy and caste remained significant when second generation schooling and RPM score were taken into account. Both second generation school attainment and RPM score were significant determinants of attitudinal modernity, and although the independent effect of each was reduced when both were considered simultaneously, each remained significant predictors of attitudinal modernity. Attitudes toward schooling. Second generation attitudes regarding third generation schooling were assumed Lo be determined by bot.h first and. second generation characteristlcs and by school availability. These effects were assessed twice, once on Lhe full sample of household heads and once on the household heads sample from villages for which school availability data were obtaLned. The results of these analyses are presented in Table 7. From the first column of Table 7 we see that, for all household heads, fLrst generaLLon LLteracy and second generatLon attitudinaL modernity were the only factors related to second generation attitude toward schooling. The second column of TabLe 7 reports the results of LhLs - 17 - analysis when It was repeated for the sample of household heads residing in villages from which school availability data were obtained. For this second sample, only landholding was a significant determinant of desire for schooling. This difference suggests that the two samples may not be similar. Column 3 of Table 7 presents the coefficients for four Indicators of school availability--the availability of primary schools in the village, the availability of secondary schools in the village, the distance to primary school and the distance to secondary school. It is evident that school availability was not a factor in determining desire for schooling for this sample. 4. Determinants of School Participation In this section we analyze the determinants of third generation (child) school attendance. The analysis is conducted first with the data aggregated at the household level and second with the data aggregated at the individual child level. The dependent measures for these analyses differ. At the household level, school participation was operationalized as the proportion of children ages 6-16 who completed at least one year of school (PCE 1); the mean value of this Indicator for all households having children ages 6-16 was 19.1%. At the individual level, school participatlion was operaLlonalized two ways; first as his or her deviation from the age specific mean school attendance for all children ln the sample (PCE 2); these means are shown in Table 8 and Indicate a low level of school attendance. In a second analysis, a dichotomous indLcator of school participation was used aq the dependent variable (CS). The means and - 18 - standard deviations of the variables used in the following analyses are presented In Table 9. 4.1 Data aggregated at the household level 4.1.1 Method Once again we have ordered our variables recursively. Referring back to Figure 1, the variables In Boxes A, E and B--school availability-- are entirely exogenous and are assumed to affect the variables in Boxes F- second generation cog-nitive competencies and attitudes--and G--second generation attitude toward school--both separately and in combination. These variables taken together with the number of children in the family and the child's sex are assumed Lo affect third generation school participation. These data were also analyzed using the SPSS ordinary least squares regression. 4.1.2 Results Because of the very low rates of enrollment in our sample, household school participation by children was operationalized as the percent of children In the household, ages 6-16, who completed any year of school. This measure provided overall statistics not dissimilar to national statistics for these districts (Table 10). Household determinants. As the first column of Table 11 indicates, household children's school participation was determined by Lhe household wealth (as Indicated by household landholdings), the schoolLng attained by household head, the numeracy of Lhe household head, the years of schooling of the household head, Lhe RPM score Of the household head, Lhe attitudinal modernity of Lhe househoLd head, the caste of the household and Lhe percent - 19 - female children. tWith the exception of percent female children, these effects were positive. To examine the question of whether rates of female participation in school were affected by the presence of young children in the household, we constructed the Interaction term PGC, or percent girls in household multiplied by the number of children 0-6 years of age. Introducing this term (which had a statistically signiflcant coefficient - -.088, F - 4.136) into the regression dramatically reduced the effect of the percent girls in the household on children's school participation, while increasing to statistical significance the effects of children aged 0-6 (coefficient = 5.518, F - 4.570). From this we concluded that girls were being utilized in the household to care for smaller children, rather than belng encouraged to attend school. The effects of the household heads' spouses cognitive abilities and modern attitudes were estimated in separate equations. These effects were limited to a positive effect of spouses' RPM score on children's school participation; spouses' modernity was not related to children's school participation. Attitude toward school effect. The second column of Table 11 reports the effects on school participation of entering the respondent's attitude toward schooling Lnto the regression. For heads of households (but not for spouses) attLLude toward schooling was worth approximately five percenL increased enrollment for each additional level of desired schooling beyond the primary level. Holding attitude toward school constant did ILttle to change Lhe relative impact of other household characterlstics on household children's school participation. - 20 - School availability effect. Two indicators of school availability were used in this analysis: presence or absence of a primary or lower secondary school In the village, and the distance to a primary or lower secondary school that served the village, should none he available In the village. As the third column of Table 11 indicates, holding household characteristics constant, neither primary nor secondary school availability was found to have a statistically significant effect on children's school participation, though the direction of the observed effect was generally what would be expected. We note, however, that school availability for this sample may be atypical for Nepal as a whole, Insofar as 68% of the households were located in villages reported to have primary schools and 20% were located In villages with lower secondary schools. The average distance to primary school was, furthermore, only .26 kosh, or about one-quarter mile. Household characteristics, attitude toward school, and school availability. As the last column of Table 11 indicates, when household characteristics, attitude toward school and school avallability were considered slmultaneously, the head of household's cognitive abilities and attitudes continued to affect children's school participation, as did the attitude toward schooling. School availability had no effect Independent of attitude toward school. For comparison purposes, it Ls interesting to note that being in a high caste group--a LoLaLly exogenous variable--was worth 36% more children's school partLcLpaRLon, whitle helng numerate-a potentially determined variable--was worth 23% for a perfect test, or 1.6% for each correct answer. Being modern was worth 2.5% mnore children enrolled for - 21 - each modern response. A positive attitude toward schooling was worth 4.3% more children enrolled for each level of schooling beyond primary desired. Assuming that each household with children had four school-aged children, two of which were females, each girl was worth 3.8% fewer children enrolled; if all the school-aged children were female, 15% fewer children participated in schooling. If primary school availability were a statistically significant factor--which It was not--a school in the village would be worth only 1.4% more children enrolled. 4.2 Data aggregated at the child level 4.2.1 Method Determinants-of third generaLion school participation were identified as a combination of fixed background characteristics, first generation factors, second generation factors Including a stated desire for third generation schooling, and school availability. The determinants of school participation at the child level of analysis were estimated in two ways; first using an ordinary least squares linear multiple regression approach with school participaton expressed as a continuous variable, and second using a logistic regression with school participation expressed as a dichotomous indicator. For the first analysis, the dependent variable was the child's deviation from the mean years of schooling completed by his or her age cohort. 4.2.2 Results of the linear multiple regression analyses Sixty-two different equations Lesting alternative specIfications for the determinants of Lhe child's school participation were estimated. - 22 - In general, first and second generation factors explained about 16% of the variance in third generation school participation, while third generation sex explained an additional four percent of the variance. Table 12 reports several of the more interesting specifications. First generation effects. The first column in Table 12 presents the coefficients for the effects on third generation school participation of first generation literacy and landholding, holding constant caste, district of residence and child sex. Although caste Is fixed, and may be considered exogenous, it is important to note that members of higher castes are substantially more likely to send their children to school; caste alone accounted for 5.1% of the variance In school attendance. First generation literacy accounted for 5.8% of the variance in third general school participation, while first generation landholding accounted for another 3.5% of the variance. Second generation effects. The second column Ln Table 12 presents the coefficients for the effects on third generation school participation of first generation landholdings and literacy; second generation RPM score, school attainment, cognitive compentencies, landholdings, att'itudinal modernity, and fixed background characteristics. In column three, the child's sex is also included. The most significant determinant of third generation school participation was the sex of the child, boys receiving on the average three quarters of a year more schooling than girls. 'Jhile both second generation RPM score and attitude toward school were sLgnlfLcant determinants of third generation school participatlon, the effects of attitude toward school were markedly reduced - 23 - when the sex of the child was included in the specification, suggesting that this attitude did not generallze to daughter's schoollng and was restricted to attitudes towards son's schooling. Effects of school availabiiity. Column 4 of Table 12 presents the results for the effects of school availability on child school participation, for the subsample of children for whom school availability data were obtained. Holding other variables constant, neither the presence or absence of either primary or secondary schools in the village, nor the distance to these schools had any effect on child's school participation. 4.2.3 Logistic regression analysis For this analysis, the dependent variable (CS) was a dichotomous indicator of whether or not the child had obtained any schooling. The means and standard deviations of selected variables, by child schooling status, is presented in Table 13. Several dozen logistic regressions were run; Table 14 reports the results of some of the more interesting ones. First generation effects. As was noted in the linear multiple regressions, the first column of Table 14 indicates that caste was a statistically significant predictor of child school participation, with members of higher castes being twice as likely Lo attend school than members of lower castes. Neither first generation literacy nor first generation landholdings were significant predictors of third generation school participation. Second generation effects. WLth first generation and exogenous variables held constant, the second column of Table 14 indicates that parental schooling and modern attltudes were strongly related to child - 24 - school participation; parental attitudes toward school were not related to child school participation Ln this analysis. Other exogenous effects. Columns 3-4 of Table 14 report the effects of two other exogenous factors on child school participaLion: child sex and school availability. Two variables related to child sex were created. The first, SEXC, was an Lndicator that the child was female in a household having other children ages 0-6 years; the second, SEXO, was an indicator that the child was a female in a household with no other small children present. In Columns 3 and 4 of Table 14 we see that the effect of being female was consistently negative, with girls three and one half to four and one half times less likely to attend school than boys. Small children in the household decreased the girls likelihood of attending school, but all girls were less likely to attend school than were boys. Two variables related to the availability of schools were created; these were similar to those used in the linear multiple regression. The first was whether or not a primary school was available in the village and the second was, if no primary school were available, Lhe distance to the nearest school. In this analysis, availability of a primary school in the village was not related to school participation. 5. Summary and conclusions This paper has examined the determinants of adult cognitive competencies and of chlld school participation In the Teral region of Nepal. Data on three generatLons from 795 rural farm households were analyzed. Four analysei were conducted: a linear multiple regression analysis of the determinants of adult cognitive competencies and attitudes, - 25 - a linear multiple regression analysis of the determinants of household child school participation, a linear multiple regression of the determinants of individual child school participation, and a logistic regression of the determinants of child school participation. The result of these various analyses are highly consistent and may be summarized as follows: 1. First generation (grandparent) landholdings, literacy and caste status were signifLcant determinants of second generation "innate ability" as measured by the Ravens Progressive Matrices (RPM) test. 2. RPM was a significant determinant of second generation schooling. 3. Second generation schooling was a significant determinant of second generation literacy, numeracy, reading comprehension and attitudinal modernity. 4. Attitudinal modernity was a significant determinant of attitude toward school for all households, but not for the subset of households in villages for which school availability data had been obtained. 5. In these latter villages, there was no relationship between school availability and a positive attitude toward school; only household landholding was a determinant of atLitude towards school. 6. Third generation child school participation was determined jointly by second generatLon landholdings, caste, schooling and numeracy, and attitudinal modernitv, and by the child's sex. 7. Girls were significantLy less likely to have completed at least one year of school than were boys. - 26 - 8. The presence of small chlldren in the household only slightly decreased girls' chances to participate in school. 9. School availability had no effect on child school participation. Data from the same households shed light on two other important determinants and outcomes of school. Moock and Leslie32 found that child nutritional status was posltively and significantly related to male and female school enrollment and to male grade attainment. Jamison and Moock33 found that grade attainment and numeracy improved the efficiency of rural farmers by economically meaningful amounts. A completely parallel study conducted at the same time in Thailand34 found generally similar results, with only one or two exceptions, most notably that schooling and ability affected parental aspirations for children's schooling. Table 1 School Attendance in Nepal by Sex and School Levela School Level Primary Lower Secondary Secondary Age of students 6-8 yrs. 9-12 yrs. 13-15 yrs. Total population 1,096,548 1,331,035 771,698 Estimated female 548,274 (50%) 665,512 (50%) 385,849 (50%) Estimated male 548,274 (50%) 665,512 (50%) 385,849 (50%) Total enrolled 769,049 226,639 82,158 Female enrolled 169,640 (22%) 41,788 (18%) 13,598 (17%) Male enrolled 599,409 (78%) 184,851 (82%) 68,560 (83%) Total enrollment rate 70% 17% 10% Female enrollment rate 31% 6% 4% Male enrollment rate 108% 28% 17% a Computed from Nepal: Primary education--a subsector study, Report No. 135, UNESCO, Paris, October 1978, Annex 1 and Annex 2. Table 2 Data Collection Information Round I Round 2 Round 3 (10-11/77) (1-3178) (4-5/78) 1. Household roster 1. Household roster (married) 1. Children health and nutrition status 2. 1Hoiseho1l Information 2. EducatLion tnformation for revised (including asseLs, members of household only health, and iion-farm (literacy, numeracy, modernity, income) Raven's Progressive Matrices) 3. Children's nutritional 3. Background, employment, and and health statis martLal status of members of household over 14 4. FertiliLy questlions for married women, parL of 4. Health, nutrition, and family Rautahat planning knowledge and aLtitudes 5. Fertility quesLions In married women, part of RautahaL and all of Bara Table 3 Description of VarLables Variable Name Variable Description DIST District Indicator: I = Bara; 0 = Rautahat FLAND Total land held by head of household's father, in Bighas: 1 Bigha = 0.676 hectares FLIT Indicator of head of household's father's literacy: I - literate; 0 - not literate Ci Caste indicator: I = head of household a member of one of the upper castes of Terai origin (e.g., Brahmin, Rajput, Kayastha); 0 - head of household member of other caste AGE Age of head of household, in years RPM Head of household's score on Raven's Progressive Matrices Test (range = 0 to 36) SYRS Schooling of head of household, In years of school completed HHLIT Indicator of literacy of head of household: 1 = literate, 0 - not literate HHNUM Numeracy score of head of household, as proportion correct of 14 items HHCOMP Reading comprehension score of head of household (range 0 to 3) MOD Head of household's modernity score (range - 9 to 18) SD Amount of schooling desired for boys in household: 0 - wL1l not educate child; I = as Long as child wants; 2 - up to high scho'l; I - up to Lntermediate; 4 = up Lo graduatLon; 5 heyond graduatii Table 3 (Cont'd) Description of Variables Variable Name Variable Description LAND Total land owned, In Bighas (1 Bigha = 0.676 hectares) PG616 Percent female of school age (6 to 16 years) children In household C06 Number of children 0-6 years in household PGC Interaction term: PG616 x C06 SEX Sex Indicator: 1 male, 0 = female SEXO Sex indicator: 1 female children in households with no other children ages 0-6; 0 - other SEXC Indicator: 1 - female children In households with other children ages 0-6; 0 other SAP School indicator: I = primary school available in village; 0 = no primary school In village SAS School indicator: I - lover secondary school available in village; 0 no lower secondary school in village DISP Distance to primary school (0 kosh; 0.5 kosh; 1.0 kosh) DISS Distance to secondary school (0 kosh; 0.5 kosh; 1.0 kosh) PCEl Percent of school age children (6-16) in hotusehold having completed at least one year of school PCE2 Child's school participation as a deviation from the mean years of schooL completed for his or her age cohort CS Schoollng LndLcAtor: I chLld completed at Least one year of schooi;0 - other Table 4 Means, Standard Deviations and Sample Sizes of Variables Analyzed in Section 3 All heads of h6useholds Heads of households in villages with schools (N 369) (N - 285) Variables Mean S.D. Mean S.D. District (DIST) 0.523 0.500 0.632 0.483 Father literate (FLIT) 0.117 0.321 0.112 0.316 Father land (FLAND) 4.414 8.191 4.016 6.186 Caste (Cl) 0.022 0.146 0.021 0.144 Schooling (SYRS) 1.390 2.990 1.435 3.122 Numeracy (HHNUM) 0.672 0.226 0.673 0.229 Reading comp (HHCOMP) 0.724 1.565 0.765 1.605 Raven's score (RPM) 13.453 4.307 13.491 4.233 Modernity (MOD) 13.621 1.774 13.520 1.728 Land (LAND) 1.913 2.977 1.841 2.491 Age (AGE) 41.713 12.342 41.663 12.139 Attitude toward school (SD) 2.328 1.090 2.291 1.073 Primary school (SAP) 0.653 0.477 Secondary school (SAS) 1.790 0.408 Distance to primary school (DISP) 0.279 0.409 Distance to secondary school (DISS) 0.798 0.568 Table 5 Determinants of Adult "Ability" (RPM) and Schooling (SYRS). (F-statistic Ln parentheses) Independent Dependent Variables Variables RPM SYRS SYRS FLAND 0.100 *** .092*** .082 *** (13.959) (29.753) (27.138) FLIT 2.796 *** 2.780*** 1.963*** (16.355) (40.724) (23.316) Cl 3.754 ** 4.989*** 4.477*** (6.618) (29.430) (28.136) DIST 0.984 * 0.476 .283 (5.485) (3.236) (1.366) RPM .204 *** (46.108) AGE .055 *** (30.877) C 12.089 0.302. 0.091 R2 0.140 .291 .419 Adj. R2 0.130 .283 .409 N 369 369 369 * p < .05 ** p < .01 *** p < .001 Table 6 Determinants of Adult Literacy (HHLIT), Reading Comprehension (HHMCOMP) Numeracy (HHNUM) and Attitudinal Modernity (MOD). (F-Statistic in parentheses) Independent Dependent Variable Variable HHLIT HHLIT HHCOMP HHCOMP HHNUM HHNUM MOD MOD FLAND .002 -0.006 -.001 0.025* (1.464) (0.696) (0.693) (5.379) FLIT .030 0.196 .047 0.865*** (0.447) (1.011) (1.763) (9.459) C1 .053 0.468 .032 1.594*** (0.337) (1.319) (0.190) (7.359) DIST .020 0.089 .013 -0.683*** (0.602) (0.625) (0.415) (17.612) AGE .001 -0.005 -.003*** -0.021*** (0.369) (1.281) (12.997) (9.184) SYRS .116*** .113*** .383*** 0.373*** .036*** .025*** 0.222*** 0.096*** (758.337) (417.409) (422.185) (232.472) (105.244) (31.966) (60.057) (7.440) RPM -.001 -0.008 *010*** 0.040 (0.169) (0.303) (12.725) (3.573) C .069 .040 .191 -.488 0.622 0.630 13.312 13.922 R2 .674 .677 .535 .542 .223 .281 .141 .258 Adj. R2 .673 .671 .534 .533 .221 .267 .138 .244 N 369 369 369 369 369 369 369 369 * p < .05 ** p < .01 *** p < .001 Table 7 Determinants of Second Generation Desire for Third Generation Schooling. (F-statistics in parentheses) Alternative Specifications Independent Variables (1) (2) (3) DIST 0.000 0.093 0.046 (n.000) (0.527) (0.094) FLAND 0.006 0.016 0.016 (0.382) (1.601) (1.476) FLIT 0.501*** 0.403 0.409 (6.673) (3.132) (3.179) Cl 0.089 -0.223 -0.262 (0.049) (0.226) (0.307) SYRS -0.045 0.018 0.017 (2.115) (0.235) (0.214) HHNITM 0.224 0.221 0.199 (0.573) (0.456) (0.363) HHCOM -0.021 -0.044 -0.041 (0.168) (0.612) (0.505) RAVENS 0.002 -0.009 -0.008 (0.015) (0.300) (0.209) MOD 0.072* 0.062 0.070 (3.852) (1.996) (2.483) LAND 0.003 0.082*** 0.081*** (0.018) (7.473) (7.184) AGE n.004 0.002 0.002 (0.598) (0.089) (0.100) SAP 0.459 (1.412) SAS 0.210 (0.802) DISP. 0.385 (0.713) DISS -0.087 (0.251) C 0.876 1.065 0.261 R2 .109 .136 .143 R2 .081 .102 .095 N 369 285 285 * p < .05 ** p < .01 p < .001 Table 8 Average Years of School Attended by Age Cohort Average Years of Age Cohort School Attended 6 years old 0.179 7 years old 0.273 8 years old 0.455 9 years old 0.471 10 years old 0.616 11 years old 1.621 12 years old 1.086 13 years old 1.133 14 years old 2.154 15 years old 2.292 16 years old 1.125 Table 9 Means, Standard Deviations and Sample Sizes of Variables Analyzed in Section 4 All children Children in villages (N 443) with schools (N =335) Variables Mean S.D. Mean S.D. District (DIST) 0.533 0.500 0.648 0.478 Grandfather literate (FLIT) 0.102 0.302 0.090 0.286 Grandfather land (FLAND) 4.504 8.777 3.609 4.073 Caste (Cl) 0.029 0.169 0.030 0.170 Father's schooling (SYRS) 1.519 3.036 1.591 3.206 Father's numeracy (HHNUM) 0.680 0.239 0.681 0.243 Father's reading 1.735 comprehension (HHCOMP) 0.847 1.662 0.925 Father's Ravens (RPM) 13.402 4.237 13.481 4.304 Father's Modernity (MOD) 13.529 1.697 13.548 1.679 Father's land (LAND) 2.213 3.488 1.936 1.985 Father's age (AGE) 43.713 10.779 43.713 10.752 Father's attitude toward school (SD) 2.139 1.112 2.128 1.110 Deviation from age mean 1.707 school (PCE 2) -0.075 1.699 -0.088 Child Sex 0.601 0.490 0.585 0.493 Primary school (SAP) 0.633 0.483 Secondary school (SAS) 0.203 0.403 Distance to primary school (DtSP) 0.300 0.421 Distance to secondary school (ntSS) 0.778 0.544 Table 10 School Attendance in Bara and Rautahat Districts, Comparing Nepal Ministry of Education Data with New Era/World Bank Survey Data School level Primary Lower Secondary Secondarv Age of Students 6-8 9-12 13-15 Ministry of Education Total population in Bara and Rautahat 52,627 26,679 24,186 Estimated female 26,314 13,339 12,093 Estimated male 26,314 13,339 12,093 Total enrolled 19,152 4,826 1,872 Female enrolled 2,948 (15%) 480 (10%) 148 (8%) Male enrolled 16,204 (85%) 4,346 (90%) 1,724 (92%) Total enrollment rate 36.4% 18.1% 7.7% Female enrollment rate 11.2% 3.6% 1.2% Male enrollment rate 61.5% 32.6% 14.3% New Era/World Bank Sample in Bara and Rautahata 355 417 225 Female sample 157 170 109 Male sample 198 247 116 Sample,completed some school 42 74 44 Female 7 (16.7%) 9 (12%) 8 (18.2%) Male 35 (83.3%) 66 (88.0%) 36 (81.8%) Female one year completion 2.2% 2.2% 3.6% Male one year completion 9.9% 15.8% 16.n% a All children in hotisehold, by ages 6-8, 9-12, 13-16. Table 11 Household Characteristics, Second Generation Cognitive Competencies, Attitudes and School AvaLlability as Determinants of Third reneration School Participation. Dependent variable is percent of school age children In household having completed at least one year of school (PCEI). (F-statistics ln parentheses) Independent AlternaLive Specifications Variables (1) (2) (3) (4) DIST 4.178 3.492 4.749 3.231 (1.524) (1.134) (1.461) (0.521) LAND 1.679** 1.683*** 2.773 ** 2.263 * (8.602) (9.157) (8.440) (5.489) AGE 0.237 0.173 0.209 0.192 (2.272) (1.281) (1.383) (1.145) SYRS 1.748* 1.343 1.348 1.352 (5.653) (3.511) (2.610) (2.557) HHNUM 21.777* 21.958** 22.256 * 23.160* (6.534) (7.105) (5.351) (5.876) RPM 1.054* 1.086* 1.112 * 1.131* (5.533) (6.276) (4.886) (5.122) MOD 3.358 *** 2.558 * 3.192 * 2.529* (10.143) (6.029) (6.540) (3.992) C1 33.607*** 33.753*** 33.661 ** 36.017 ** (10.454) (11.122) (9.298) (10.685) PG616 -0.224*** -0.128* -0.141 -0.154* (28.951) (3.927) (3.618) (4.323) C06 1.732 6.073* 3.583 4.166 (0.927) (5.838) (1.536) (2.100) PGC -0.097* -0.067 -0.070 (5.390) (1.828) (2.005) SD 6.069 *** 4.303* (16.55) (6.226) SAP 1.437 (0.114) SAS -2.145 (0.142) C -67.982 -71.986 -71.174 -70.783 R2 0.411 0.454 0.435 0.454 Adj. R2 0.390 0.430 0.404 0.415 N 282 282 212 212 * p < .05 ** p < .01 *** p < .001 Table 12 Determinants of Third Generation School Participation. Dependent variable is child's deviation from age cohort mean school attendance (PCE 2). (F Ln parentheses) Independent Alternative Specifications Variables (1) (2) (3) (4) DIST .411** .249 0.222 n.022 (7.863) (2.887) (2.293) (0.012) FLAND .032*** -.003 -0.002 0.043 (13.801) (0.030) (0.013) (3.277) FLIT .837*** 0.465 0.426 0.206 (10.647) (3.259) (2.734) (0.383) C1 2.277*** 1.366** 1.315** 1.420* (26.027) (8.412) (7.839) (5.442) SYRS 0.057 0.061 0.046 (2.061) (2.383) (0.880) HHNUM 0.799** 0.665 0.474 (5.051) (3.425) (1.240) HHCOMP 0.011 -0.002 0.042 (0.032) (0.001) (0.343) RAVENS 0.049** 0.051** 0.049* (5.916) (6.360) (4.145) MOD 0.066 0.053 0.083 (1.790) (1.145) (1.719) LAND 0.064 0.065 0.061 (2.986) (3.057) (1.484) AGE 0.011 '1.010 0.010 (2.672) (2.164) (1.222) SD 0.736*** 0.142* 0.051 (25.384) (4.477) (0.386) SEX .687*** 0.773*** 0.757*** (21.098) (27.864) (19.128) SAP -0.484 (0.809) SAS 0.045 (0.020) DISP -0.765 (1.492) DISS 0.280 (1.308) C -1.003 -3.559 -3.570 -3.291 R2 .197 .275 .282 .291 Adj. R2 .188 .255 .261 .253 N 443 433 433 335 * < .05 ** .< .01 ***(p < .001 Table 13 Means and Standard Deviations of Selected Variables, by School Attendance Status of Child School School Attendees Non-Attendees (N 69) (N = 361) Variables Mean S.D. Mean S.D. Exogenous District 0.652 0.480 0.507 0.501 Caste 0.159 0.369 0.006 0.074 First generation factors Literacy 0.275 0.450 0.064 0.245 Landholding 9.969 17.800 3.273 4.531 Second generation factors Age 43.768 11.661 43.859 10.672 Years of schooling 4.449 4.**O 0.920 2.259 Literacy 0.638 0.484 0.194 0.396 Comprehension 1.957 1.818 0.612 1.522 Numeracy 0.853 0.186 0.647 0.232 Raven's Progressive Matrices 17.087 5.575 12.665 3.536 Landholding 4.597 6.947 1.752 2.104 Modernity 14.764 2.167 13.278 1.461 Attitude toward schooling 2.667 1.421 2.022 1.005 Child factors Sex - X male 0.R99 0.304 0.529 0.500 Table 14 Logistic Regression Estimates of the Determinants of Third Generation School Participation. Dependent variable Ls dichotomous indicator of child schooling (CS). (t-statisttc ln parentheses) Independent Alternative specifications Variables (1) (2) (3) (4) DIST -1.345*** 0.478 0.655 0.664 (-6.653) (1.155) (1.334) (1.357) FLIT 0.488 0.678 -0.057 -0.106 (1.034) (1.241) (-0.078) (-0.145) FLAND -0.030 0.111** 0.079 0.097 (-0.974) (2.810) (1.618) (1.932) Cl 2.405** 1.333 2.917* 2.647 (2.757) (1.067) (2.073) (1.889) AGE -0.026 -0.016 -0.015 (-1.722) (-0.850) (-0.853) SYRS 0.231** 0.281** -0.275** (2.962) (2.778) (2.758). HHNUM 0.311 1.163 1.091 (0.308) (1.033) (0.979) RAVENS 0.036 0.030 0.026 (0.787) (0.558) (0.486) LAND 0.039 0.189 0.174 (0.451) (1.698) (1.573) MOD -0.211** -0.311** -0.303** (-2.611) (-3.018) (-2.952) HHCOMP -0.065 0.140 0.136 (-0.558) (0.929) (0.912) SD 0.124 0.485* 0.434* (0.823) (2.453) (2.221) SEXC -4.881*** -4.776*** (-4.872) (-4.773) SEXO -3.415** -3.451** (-2.623) (-2.6.51) SAP -0.254 (-0.576) DISP -0.363 (-0.654) N 326 326 326 326 Log Likelihood at conver- gence -181.9 -118.9 -89.57 86.51 Likelihood ratio 88.04 214.1 278.8 278.9 DF 322 314 311 311 * < < .05 ** < < .01 * .. K< .00 1 Footnotes 1. George Psacharopoulos, "Returns to education: An updated international comparison", Comparative Education, 1981, 17, 321-341. 2. Marlaine E. Lockeed, Dean T. Jamison & Lawrence J. Lau, "Farmer education and farm efficiency: A survey", Economic Development and Cultural Change, 1980, 29, 37-76. 3. Susan Cochrane, Education and fertility: What do we really know? (Baltimore, MD, John Hopkins UJniversity Press, 1978). 4. Susan H. Cochrane, Joanne Leslie & Donal J. O'Hara, "Parental Education and Child Health: Intracountry Evidence", Health Policy and Education, 1982, 2, 213-250. 5. J.R. Sheffield, "Retention of literacy and basic skills: A review of the literature" (Paper prepared for the Education Department of the World Bank, 1975). 6. Alex Inkeles and David H. Smith, Becoming modern (Cambridge, Mass.: Harvard TJniversity Press, 1974). 7. Kjell Harnqvist, "Enduring effects of schooling--a neglected.area in educational research", Educational Researcher, 1977, 6(1) 5-11. 8. Sheffield, Op. Cit. 9. Jennifer Noesjirwan, "Permanency of literacy in Indonesia", American Educational Research Journal, 1974, 1 93-99; George Psacharopoulos; Everett M. Rogers & L. Svenning, Modernization among peasants (New York: Holt, Rinehart and WInston, Inc., 1969); ProdLpto Roy & J.M. Kapoor, The retention of literacy (Delhi: MacMillan Company of India, Ltd., 1975); H. Schuman, Alex Inkeles, & David H. Smith, "Some psychological effects and noneffects of literacy In a new nation", Economic Development and Cultural Change, 1967, 16, 1-14. 10. M. Ahmed, "Retention of literacy skills in adults", Literary Work, 1973, 11, 43-53; G. Flores, "A study on functional ilLeracy for citizenship in the Philippines", Quarterly Bulletin of Fundamental Education, 1950, 2, 24-28; D. Kosak, "The problem of reading In elementary education", Adult Education, 1963, No. 5-6, 35-38; J. Landy-Tolwinska, "Farmer participants in literacy courses - Poland", Literacy Discussion, 1970, 1, 107-110; H.F. Lionberger & H.C. Chang, Communication and use of scientific farm information by farmers in two Taiwan agriculture villages (Columbia, Missourit University of Missouri, College of Agriculture, 1968). 11. Russell Beirn, David C. Kinsey and Noel F.McGinn, "Antecedents and Consequences of Early School Leaving: An Analytic Survey of Research Activities",. (Graduate School of Education, Harvard University: Occasional Papers in Education and Development, Number 8, 1972); G. Flores; J. Noesjirwan. 12. Alex Inkeles, "The school as a context for modernization", International Journal of Comparative Sociology, 1973, 14, 163-179; R. St,ltzman & I. Amnon, "The effects of schooling on psychologtLc-l moderniLy: A longttudtnal study" (Unpublished manuscrtpt, t'473). 13. Nancy Birdsall, "Child schooling and Lhe measurement of living standards" (Washington, D.C., World Bank Living Standards Measurement Study Working paper No. 14. February, 1982); Nancy Birdsall and Susan Hill Cochrane, "Education and parental decision-making: A two generation approach", in Lascelles Anderson and Douglas M. Windham (Eds.), Education and DeveloDment (Lexington, Mass: D.C. Heath, 1982), pp 179-210. 14. Mary Jean Bowman & C. Arnold Anderson, The participation of women in education in the third world" (Comparative Education Center, University of Chicago, October 1978). 15. Peter Moock and Joanne Leslie, "Childhood malnutrition and schooling in the Terai region of Nepal", Journal of Development Economics, in press. 16. Peter Sellar, David Sprague & Virgil Miedema, U.S. Aid to Education in Nepal: A 20-Year Beginning (U.S. Agency for InLernational Development, Kathmandu, 1981). 17. H.M.G. Nepal, Ministry of Education & Culture, Unpublished data, Kathmandu, 1983. 18. Rajendra B. Shrestha, Accessibility to educational opportunities in the remote areas (Center for Economic Development and Administration, Tribhuvan University Campus, Kathmanda, Nepal, 1976). 19. Beirn, Kinsey, and McGinn, Op. Cit. 20. CERtD/WE, Determinants of Edtucational Participation in Rural Nepal (Center for rducatLon Research, Innovation and Development. Kathmandu, 1983). 21. Barbara Butterworth, Dibya Karmacharya, & Richard Martin, Radio Education Teacher Training Program, Final Evaluation Report (Kathmandu, April 1983). 22. Shrestha, Op. Cit. 23. Birdsall; Birdsall & Cochrane, Op. Cit. 24. Meena Acharya & Lynn Bennett, "The Rural IWomen of Nepal: An Aggregate Analysis and Summary of 8 Village Studies", in The Status of Women in Nepal, Vol. II, part 9, 1981. 25. Anonymous. Equity and Discrimination Among Children: Household Decision-Making Strategies for the Provision of Schooling in Rural Nepal (Unpublished manuscript, 1983). 26. Prem Kasaju, "Learning to read and write: A major task for development", in M. Mohsin & P. Kasaju (Eds.), On education in Nepal, (National Education Committee, 1974). 27. Shrestha, Op. Cit. 28. Gwendolyn L. Lewis, A model of Turkish adults' educational aspirations for their children (Institute of Population Studies, Hacettepe University, Ankara, Turkey, 1978). 29. Prem Kasaju, Parents' Attitude Toward and Expectations from Education (Trlbhuvan UJniversity, Center for Education Research, Innovative and Development, Kathmandu, 1982). 30. Norman H. Nie, C. Hadlai Hull, Jean G. Jenkins, Karin Steinbrenner, & Dale H. Bent, Stastistical package for the social sciences (2nd edItion) (New York: McGraw-Hill., 1975). 31. Dean T. Jamison, Joanne Leslie, & Bal Gopal Baidya, "Determinants of the literacy and numeracy of adults in Lhe Terai region of Nepal" (Paper presenLed at the annual meeting of the Eastern Economic Association, Boston, May 1979). 32. Moock and Leslie, Op. cit. 33. Dean T. Jamison and Peter Moock, "Farmer education and farm efficiency in Nepal: The role of schooling, extension services and cognitive skills", World Development, 1984, 12, 67-86. 34. Susan Hill Cochrane and Dean T. Jamison, "Educational attainment and achievement tn rural Thailand", in A. Summers (Ed.), New Directions for Testing and Measurement: Productivity Assessment in Education (San Francisco: Jossey-Bass, 1982), pp. 43-59. Other Available EDT Discussion Papers EDT21 Teacher Training: A Review W. Haddad November 1985 of World Bank Experience EDT22 Institutional Development J. Auerhan, et al. November 1985 in Education and Training in Sub-Saharan African Countries