Price and income elasticities of demand for modern health care : the case of infant delivery in the Philippines

PHN- 8723 PHN Technical Note 87-23 PRICE AND INCOME ELASTICITIES OF DEMAND FOR MODERN HEALTH CARE: THE CASE OF INFANT DELIVERY IN THE PHILIPPINES by J. Brad Schwartz John S. Akin Barry M. Popkin December 1 987 Pop>ulation 1anc Human esurces iepar men Worild Bank The World Bank does not accept responsiCbilty for the vLews expressed nerein which are those of the author s) and should not be attributed to kte Wor Bank or to its affiliated organizations. The findings, interpretations, and conclusions are the results of research supported by the ank; tey l dc 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 World Bank or ts affiiiaies concerning the legal status of any country, territory, city area, or Gf its authorities, or coricerning the delimi tations of its boundaries, or natin affiliation. PHN Technical Note 87-23 PRICE AND INCOME ELASTICITIES OF DEMAND FOR MODERN HEALTH CARE: THE CASE OF INFANT DELIVERY IN THE PHILIPPINES ABSTRACT The study examines the economic determinants of the demand for infant delivery in the Cebu region of the Philippines. in the Philppinesl as an many low-income countries, there has been a major commitment by the pubLic sector to provide modern child delivery services to the generai population. Cost recovery through user charges can be an important method ot revenues to pay for much needed maternal an chila health services. e important potlcy question is whether charging for such services wil significantly deter the use of the services by mothers. In order to answo!- the question it is necessary to estimate the sensitivity of service use choices to both time and money prices and in full specified equations that control for other factors that affect the choice. Other important paho.lv questions relate to how service quall Lv can be improved to attract women K. use the services. This study proviaes some answers to tiose quesWrous fur boi.h urban and rural women living in the region of the secood LurgesL CLI in the Philippines. A unique data set with choice-speii money and time priies vmli Facility quality measures combined wiLh prospective daLa for ovar deliveries is used. A mixed multinomial LogiL technique is usea ror LK, estimation of the effects of choice-specific and unconditional househoid- specific factors on the choice of di ivery services. Price and income elasticities of the demand for types of infant delivery services are comnputed, and sinu at ions arp rarria -out K to( effects of other characteristics of deLivery service Prvtders on w0very method F choice. The resui:s suggest Ihat incre=ing in- availability of modern pubLic delivery practiKoners and Faciicius in ruy.. areas, increasing the hours that heath care facilities are cocn makinjg drugs available, and providing trained midwives for delivery wi increane the use of modern delivery services. Perhaps the most important Cindings are that the choice of delivery service type appears to ce relative!y insensitive to changes in both money prices and household ince,e. Prepared by: J. Brad Schwartz and Barry M. Popkin, The University of NorAh Carolina at Chapel Hill and the Carolina Population Center John S. Akin, The World BanR December 1987 I. INTRODUCT1O In the Philippines, a majority of births take place at home, and a significant proportion are either attended by a traditional midwife or friends and relatives of the mother. Women continue to choose this pattern of delivery despite large investments by the health sector in modern prenatal and obstetrical health service systems. Even though a large majority of the pregnant women have direct contact with modern delivery services, there appears to be a preference for traditional home deliveries. It turns out that this choice can to a large extent be explained by the characteristics of the modern and traditional delivery systems and the socioeconomic characteristics of the households. Important questions to be answered in order to make health policy decisions relate to how to provide and finance modern delivery care in low-income countries, specifically where traditional and modern health providers coexist. The factors that affect mothers' choices of types of health care are ultimately those choices that determine whether many infants live or die or are healthy or chronically ill. We examine the determinants of the choice of type of delivery care, including economic factors (such as money prices, time prices and household income), health facility characteristics, and delivery practitioner characteristics of both the traditional and modern delivery providers in one region of the Philippines. The sensitivity of the choice of birth delivery method to factors such as these has important implications for the placement, organization and financing of modern delivery services. The analysis emphasizes the factors most amenable to policy change by the government of the Philippines, such as the location of clinics and the money fees charged. The data come from a survey of health facilities and delivery practitioners combined with a survey of over 3,000 women who delivered babies during 1983-84 in the 4 Cebu region of the Philippines. In the next section we describe the traditional and modern delivery sectors in low-income countries, in the third we present an overview of the economic model that guides the analysis, and in the fourth we discuss the data and provide descriptive statistics. In the fifth section we discuss the estimation technique and the results of the multivariate analysis, and in the final present policy implications and conclusions. II. BACKGROUND The Traditional Sector Over two-thirds of the babies born in low-income countries are delivered by traditional birth attendants, who often are poorly educated and have no formal medical training. A national survey of traditional midwives conducted in 1974 in the Philippines found that over 50 percent had only elementary school training and most had either learned midwifery on their own or from relatives (Mangay-Angara, 1981; Akin et al., 1984). It is this lack of formal medical training which differentiates traditional midwives from modern medical professionals. The modern health sector consists mainly of physicians and nurses with university educations and licensed midwives with some formal medical training. The heavy reliance on traditional birth attendants in developing countries may be related to the heavy concentration of modern practitioners in urban areas and traditional ones in rural areas. Typically 60-80 percent of the population and 70-90 percent of the doctors reside in urban areas (Akin et al., 1984). The urban facilities at which these doctors work are often inaccessible (either for geographic or economic reasons) to the lower-income and rural populations. The traditional sector generally provides greater coverage of the rural population than does the modern sector. While in Asia and Africa the modern sector usually is physically accessible to only 10-30 percent of the population, in many 5 countries 100 percent of the population is within walking distance of a traditional midwife. It is not unusual for the population per practitioner ratio for traditional midwives to be only one-fifth to one-half that of modern practitioners. The traditional midwives are readily accessible to most of the population in almost all developing nations. The work of the traditional midwives is diverse. They not only deliver babies, but also assist women during the prenatal and postnatal periods, and are involved in a number of important aspects of maternal and child health care. During prenatal care they often: use massage to relax muscles, relieve discomfort, and estimate the progress of pregnancy. As delivery approaches, massage is used to position the fetus. . .During labor the traditional midwife may massage the woman and administer herbal beverages, . At delivery many midwives help to extract the baby and the placenta. [Simpson-Hebert et al., 1980, pp. J-444-445]. It is generally believed that some of the practices of the traditional birth attendants are harmful, and that many others, while probably harmless, are of uncertain effect. Harmful practices, or those which can be potentially harmful, include dietary restrictions, mishandling of the umbilical cord (associated with neonatal tetanus), misuse of drugs (e.g., heavy use of inappropriate antibiotics). postpartum feeding practices which exclude the feeding of colostrum, and incorrect responses to complications of pregnancy (Popkin et al., 1984). Both surveys of modern medical personnel and data from hospital records repeatedly identify neonatal tetanus as the major infant mortality risk associated with deliveries attended by untrained midwives (Mangay-Angara, 1981). Modern Obstetrical Care and Primary Health Care In the last decade there has been a major effort to expand modern health services in Third World countries. One major goal of the expansion has been the provision of inexpensive modern prenatal and delivery services. Usually, in planning 6 the allocation of these services, the planners have concentrated on simple formulas related to geographic distribution of health services rather than on how best to provide services, given the available resources and the benefits of alternative approaches. Few studies have documented the impact of changes in health facilities and practitioners on the proportion of deliveries attended by modern practitioners, and even fewer have evaluated the health effects of such changes. An exception is a project in the province of Bohol, Philippines, which implemented and evaluated a Taylor-Berelson maternal and child health and family planning project. In this case over the period of the project the availability of low cost modern care was found to lead to a decline from 67 percent to 1 percent in births attended by untrained midwives. Concurrent declines in the number of cases of neonatal tetanus and in the prevalence of many inappropriate delivery practices (e.g., the use of bamboo slivers to cut the umbilical cord) were observed (Williamson, 1982; Parado, 1979). Another study found that the introduction of modern care to the area led to a reduction in fetal deaths (Akin et al., 1984). The Realignment of Delivery Patterns For investments of the government in improved delivery services to achieve their objectives, it is essential that the determinants of the type of infant delivery be considered. Surprisingly few systematic studies have considered the factors associated with the choice of delivery services--be it for modern or traditional, public or private care. Elsewhere the authors have reviewed the existing studies and presented the results of a small case study of the factors associated with the choice of modern or traditional delivery services (Akin et al., 1984, 1986). That earlier research, based on an analysis of about five hundred births from the Bicol region of the Philippines concluded that the choice between a modern or traditional birth at-endant was made mainly on other than economic grounds. The important explanatory variables were found to be mother's education and urban residence. Previous studies including the earlier work of these authors, of choice of infani delivery method, have been based on small samples, and, more importantly. have failed to control for some important economic and quality of service characteristics of the a-ailable delivery service options. In this study we expand on previous work by analyz.,ng a large data set, which includes information not only on the socioeconoi.ic characteristics of the demanders of delivery services, but also on the economic cot- and service quality characteristics of all suppliers of delivery services in i-e community being analyzed. Moreover, because the data were collected on a prospect. a basis they represent a significant improvement over those for other studies based c trospective recall data. III. ECONOMIC DE '40DEL In this sect briefly outline a delivery service demand model which is detailed elsewhere n et al., 1984, 1986). We assume that a model for analysis of delivery services m take into account the facts that delivery services can be provided either publ.;ly or privately, either by untrained or trained practitioners. and either at home or away from home. In the model each type of delivery has an associated set of characteristics, including time and money prices, availability, and service quality. We assume that a woman maximizes her own well-being, which is a function of the health of her infant. The outcomes predicted as a result of this maximization process are that a woman's choice of type of delivery service will be determined by the prices, availability, and quality of the services plus a set of socioeconomic, demographic, and community factors. In general terms, the relationship between type of delivery used and the exogenous factors is as follows: Yi = f(Pi, Ti, Hi, Qi; Z)( where Yi = the ith delivery type; I = at home by relatives, at home by traditional practitioners, at home by modern public practitioners, at home by modern private practitioners, away from home (at clinics or hospitals) by modern public practitioners, or away from home by modern private practitioners (6 possible choices); Pi = cash price paid to delivery service provider of type i; Ti = time price of traveling between the delivery provider of type i and the woman's residence; Hi = the hours of availability for delivery service of type i; Qi = the perceived quality of delivery service of type i; and Z = the set of household and community characteristics (such as income, assets, education, insurance coverage, residence, and household composition) affecting the income available to, the time constraints of, and the knowledge and preferences of, the mother. IV. SURVEY BACKGROUND The study site is Metropolitan Cebu, an area embracing both the City of Cebu and rural areas of the Island of Cebu in the Central Philippines. Metropolitan Cebu is located on the eastern cost of Cebu Island and includes, besides Cebu City, coastal towns and a number of mountain villages. While basically of Malayan stock, the Metropolitan Cebu population (particularly in the urbanized areas) also contains people who are of Spanish and Chinese ancestry. Metro Cebu is composed of three administratively distinct cities (among them Cebu City, the second largest city of the country) and six other municipalities. At the time of the 1980 census, the administrative entities contained 243 barangays (the barangay is the smallest administrative unit in the Philippines, and, in the rural areas, is usually identical with a village) with 171,702 households and slightly more 9 than one million inhabitants. The barangay is the initial sampling unit for the survey from which the data are derived. Separate random samples taken from the universes of urban and rural metro Cebu barangays resulted in a sample of 17 urban and 16 rural barangays. All households in the 33 barangays were surveyed to collect data on all women who had births between May 1, 1983 and April 30, 1984. Baseline surveys were obtained during the sixth month of pregnancy for the 3,327 pregnant women who gave birth during the 12-month period. For the analysis of delivery patterns, the sample consists of 3,075 women for whom both baseline and birth information were collected and who delivered nontwin births. Of the 3,327 baseline women, 38 (1.1 percent) had stillbirths, 13 (0.4 percent) had miscarriages, 26 (0.8 percent) had twin births. 135 (4.1 percent) outmigrated between the baseline and birth interviews, and 17 (0.5 percent) refused birth interviews. An additional 57 women in the sample communities who gave birth during the 12-month period but either did not live in the communities during their pregnancy or were missed in the screening for pregnant women are omitted from this analysis. The public and private health facilities serving the 33 sample barangays also were surveyed. Included in the facility sample are all facilities and personnel located in each barangay, plus personnel and facilities located outside the barangays but identified by proximity to the barangay, by legal jurisdiction over the community (for public clinics and hospitals) or by barangay informants (on questions asked during the baseline) as servicing the sample households. In total, data from 48 modern public and modern private hospitals, clinics, and health center facilities and 88 private modern and traditional health practitioners were used in this analysis. In addition, data were collected from part-time government health facilities (Barangay Health Stations (BHSs)) located in 23 of the 33 barangays. 10 Variables The pattern of delivery choice across the six methods represented in the dependent variable is presented in Table 1. Table 2 describes each independent variable used. and Table 3 shows the mean. values and standard deviations of the independent variables. All variables are presented separately for urban and rural samples for reasons discussed below. Tables 1, 2. and 3 about here V. ESTIMATION METHOD AND RESULTS The dependent variable in the delivery model is in the form of a set of unordered, mutually exclusive categories. An appropriate statistical method for estimating the relationships is the mixed multinomial logit technique. This estimation procedure allows two types of independent (explanatory) variables to be used--conditional variables, such as the price of delivery, which differs in value for any given mother on the basis of choice made; and unconditional variables, such as mother's age, which do not change as a result of the choice. If we let Xij represent a vector of values for a set of independent variables (e.g., the set of prices in Table 1) that vary by choice (j = 1, 2, ..., N) and by woman (i = 1, 2, ..., M), and Zi represent a vector of independent variables that vary only by woman, then the log of the odds of any particular choice being made is: P(Y. = j) log Y(Xij - Xii) - .3Zij P(Y = 1) where the Y's represent coefficients associated with the choice-varying (conditional) independent variables. A positive value for a particular coefficient implies that the corresponding independent variable has positive weight in the individual's 11 indirect utility function (i.e., that an increase in the value of that variable is considered a favorable change by the individual), and that an increase in the value of that variable for a particular choice will make it more likely that the choice affected will be made. If, for example, the coefficient on the quality of delivery is positive this indicates that adding to the service quality at any type of provider will tend to increase the individual's likelihood of choosing to use that type of delivery service, and that because of this service quality increase the individual is able to obtain a higher level of welfare. The 3j coefficients vary by choice, and a positive value for a particular coefficient implies that as the corresponding independent variable increases, the probability that choice j will be chosen increases relative to other choices. The use of choice 1 in the denominator of the equation, as the basis for comparison of other choices defining the log odds, is arbitrary. All odds ratios can be computed, and we present all comparisons in our the results. The estimation of this model entails solving the above equations for probabilities and setting up a likelihood function. Details of the procedure can be found in Maddala (1983). Model Specification Issues A. Urban/Rural Residence Because urban and rural residents reasonably could behave differently in seeking delivery services we test for such differences. A likelihood ratio test of the null hypothesis, "no behavioral difference between urban and rural residents," is rejected at the 1 percent level of significance, indicating that the two samples do behave differently. Because of this structural difference we stratify the sample into urban and rural subsamples, and all results are presented for both urban and rural groups. 12 B. Distance to Facilities In the model, the travel time between the mother and practitioner represents the proximity of each delivery option, whether the mother chooses to travel to the practitioner or to have the practitioner travel to her home for delivery. The quantification of this variable is complex. From the mother we determine the specific facility of each type she would use and from the facilities we determine their populations served. We carry out an analysis of transportation patterns, topography and distance to estimate the travel time of each household to the relevant public, private or traditional facility. C. Choice of Prenatal Care The type of prenatal care chosen by the mother (traditional, public, or private practitioner) may be an important factor in the choice of delivery practitioner. However, it is not unlikely that the choices of prenatal care and delivery practitioner are jointly determined, and that the choice of prenatal care is therefore endogenous to the delivery model. A statistical procedure to correct for such endogeneity is to estimate the probability that each type of prenatal care is chosen by the mother and then enter these probabilities in the delivery model as lagged (pre-delivery) endogenous variables. Unfortunately, this procedure is impossible in the multinomial logit model because the error term assumptions for the instrumental variables violate the necessary logit model error assumptions. Because no perfect answer to the endogeneity problem in the logit model exists we carry out two alternative estimation procedures, each of which is consistent with a specific set of assumptions about the true model. We estimate a reduced form model, in which prenatal care type is not included as an explanatory factor, and assume the results and simulations to be appropriate if the choice of prenatal care actually is endogenous to the model. As an alternative we present estimation and simulation 13 results for a model in which the prenatal care choice is included as an exogenous explanatory variable, a model which is appropriate if in reality choice of prenatal care type is exogenous to the choice of type of delivery service. We compare the results from the two approaches. D. Qualifications of Delivery Practitioner In order to take into account the differences in quality of the delivery practitioners providing the actual delivery services under the alternative choices of delivery type, we include two binary variables that indicate whether 1) the actual practitioner has received little or no formal medical training (i.e., relatives and traditional practitioners) and 2) whether the practitioner who normally makes the delivery is a certified trained midwife. For infant deliveries performed at public and private facilities and for deliveries performed at home by practitioners from public and private facilities, we thus capture the effects both of having a practitioner with or without formal medical training, and of the practitioner providing the delivery services being or not being a trained midwife. The omitted dichotomous variable is defined as the practitioner performing the delivery being a doctor, a nurse, or a combination (team effort) of doctors, nurses, and midwives. In the sample, the second most common provider of a modern delivery next to a trained midwife, is a combination of practitioners. E. Lack of Data on Some Spouses There are nearly 200 observations where the spouse was not present in the household and no information was obtained for the spouse's education. In order to control for the presence of the spouse we have included a binary variable to indicate whether the father was present. As an additional variable we also have interacted this binary variable with father's education. 14 Multivariate Results Tables 4 and 5 present the results from estimation of the mixed multinomial logit model for both the urban and rural samples. The coefficients for the conditional variables indicate how changes in each of the variables affect the household's utility (welfare), and represent the effect of these factors irrespective of the delivery choice actually made. For example, because the coefficient on price is found to be negative for both the urban and rural samples, it follows that increasing the price of any of the delivery choices will decrease the utility of the household, and will decrease the probability of choosing that option for which price was increased, relative to the other delivery options. The coefficients on the unconditional variables, however, are allowed to differ for each delivery method choice, with the data being allowed to indicate how a change in each of these variables affects the probability of choosing each specific type of delivery. Tables 4 and 5 about here A. Money and Time Prices For the urban households, an increase in the money price of delivery services is a statistically significant and negative factor in the choice of delivery. For rural mothers, price is found to have a negative influence on the choice, but is not statistically significant. The negative coefficient findings suggest that an increase in the user charges for any type of delivery will tend to reduce the likelihood that type will be chosen. The relationship between travel time from the household to the delivery practitioner and the type of delivery chosen is also found to be negative for both samples, but is statistically significant only for the rural sample. This finding suggests that increased distance to a facility will reduce its usage in the rural areas. 15 An explanation of the lack of statistical significance for time (distance) prices in the urban areas is that the urban sample is relatively close to all delivery options (6.41 minutes, on average) and that there is little variation in the time required to travel across all options (2.44 minutes). It appears that in these urban situations, time spent to reach a practitioner, though negatively related to delivery choice, is not an important factor in the choice. The opposite is true for the rural households who live much farther away from all types of delivery care (24.99 minutes, on average) and for whom the variation in travel time to the choices can be great. For this rural sample, time is negatively related to delivery choice and the statistical tests suggest that it is an important factor in the choice. B. Hours of Availability of Services and Availability of Drugs The hours per week that each delivery choice is available is a positive and statistically significant factor for both the urban and rural samples, indicating that an increase in its hours of availability will increase the probability that any delivery option will be chosen. Whether or not drugs are available at the public and private facilities is entered as a quality of service variable, and, as expected, is positively related to delivery choice. The availability of drugs is statistically significant for the urban sample. but we have less confidence in the finding for the rural households. C. Training of Practitioner For the delivery practitioner either to be a midwife with no formal training or a formally trained midwife is found to be positively associated with the delivery service with which that practitioner is associated being chosen. This type of practitioner variable (midwife) is found to be statistically significant for both the urban and rural samples. The results suggest that households prefer delivery 16 services from midwives, whether they are formally trained o,r not, to deliveries performed by combinations of doctors, nurses, and midwives (the excluded category). D. Other Factors The re rs found for the unconditional variables (fa ;rs which do not change according to the delivery method chosen) may be interpreted as the influence of these factors on each delivery option relative to each other option. In most cases, household income and household assets are found not to be statistically significant factors in delivery method choice in either the urban or rural samples, although in the one exception, having greater income or assets does appear to increase the probability that deliveries away-from-home (at both public and private facilities) will be chosen. When the mother's education level increases she is seen to become more inclined to choose away-from-home delivery if she lives in an urban area, and to choose modern delivery if she is a rural resident. Having insurance coverage appears to increase the probability that modern private practitioner deliveries will be chosen, but to have little effect on other delivery choices. Simulation Results The interpretation of the meaning of the magnitude of the coefficients in a multinomial logit model is difficult because the estimated parameters are the logarithm of the ratio of two probabilities. Table 6 presents simulations performed using the logit estimates to obtain predicted probabilities. Probabilities of choices are estimated for hypothetical households having the sample means for all independent variables, and then changes in these probabilities are determined which result from changes in the specific conditional and unconditional variables. The simulation results are revealing because statistical significance of a relationship does not necessarily indicate that the effect of the independent variable on the dependent variable will be large. An effect could in fact be strongly significant 17 but almost infinitely small, and therefore not "significant" in the nonstatistical sense of the word. The simulations present the effects of changes in the characteristics of public delivery services on the choice of home and away-from-home delivery in order to examine the policy implication of such changes. The changes examined are in travel time, money price, hours of operation and drug availability-- the factors most likely to be affected by government service provision and financing decisions. To complete the picture, the effects of changes in factors less amenable to government policy manipulation, such as household income, assets, insurance coverage, mothers' education, and choice of prenatal care are also examined. Table 6 about here From the information presented in Table 6, we see that if each woman in the sample had a value for each independent variable set at its sample mean (see Table 3), approximately 27 percent of the urban sample and 73 percent of the rural sample would choose to deliver at home, with either a traditional practitioner or relative attending; about 26 percent of the urban sample and 17 percent of the rural sample would choose delivery at home with a modern public or private practitioner; and 47 percent of the urban and 10 percent of the rural would choose away-from-home delivery with a modern public or private practitioner. The simulation results, indicating expected changes in these average probabilities that result from changes in the explanatory variables, show that changes in money and time prices for public delivery services have differential impacts on women in the urban and rural samples. When the money prices of public deliveries, either at home or away, are increased by one standard deviation, the results indicate that there will be little or no change in the choices of delivery care made by the rural sample. The women in the urban sample also appear to be 18 relatively insensitive to moderate changes in money prices -,though the urban women are more responsive to changes in public delivery prices than are the rural. In the urban areas there is a relatively large tradeoff between traditional and public delivery; increases in the price of public delivery (especiilly away-from-home) increase the likelihood of the choice of traditional delivery. The simulation results for changes in the time prices of public practitioners indicate only limited responsiveness for the urban sample; the rural sample appears to be more sensitive to changes in time prices. When the travel time between the mother and a public practitioner for home delivery is increased by one standard deviation, the model predicts a decrease of about 0.09 in the probability that the mother will choose to use the public practitioner at home option. The results also indicate that women would be likely to switch to a traditional practitioner (-0.07) when such a distance increase to the public practitioner for home delivery occurred. Increasing the travel time to public facilities for away-from-home deliveries also appears greatly to decrease the probability of a rural woman choosing this option (-0.0377). (Note that the probability of this choice at the means is only 0.0445.) Often the degree of sensitivity of a dependent variable is represented by a measure called elasticity--the percentage change in the dependent variable resulting from a 1 percent change in the explanatory variable. Our results for changes in money and time prices and income are expressed as elasticities in order to make the comparisons more interpretable. The elasticity estimates indicate the changes in the dependent variable due to an equal percentage change in each of the explanatory variables. The elasticity results suggest that although many policy factors are statistically significant determinants of the choice of delivery, the choice is 19 relatively insensitive to many of the economic determinants (money prices. time prices, and income) of demand. Money Price Urban Rural Public, home -0.0733 -0.0074 Public, away -0.2368 -0.0520 Time Price Public, home -0.0999 -0.7771 Public, away -0.0932 -1.1648 Income Public, home 0.0739 -0.0224 Public, away -0.0219 0.1550 All money price effects are found to be in the inelastic range, indicating low responsiveness of the probability of choosing a modern public practitioner for delivery to a change in the price of these practitioners. The largest of these, -0.2368 for an urban away-from-home public facility delivery, indicates that the probability of choosing this option will decrease by 0.2368 percent for a 1 percent increase in price (that is, a 1 percent change in the mean price will lead to a change in the probability that is about two-tenths of one percent as large as the mean probability). Clearly, a policy designed to increase the use of modern publicly provided delivery services by decreasing money prices will be expected to do little to increase demand, just as an increase in prices to raise revenues will be expected to reduce usage very little. That time prices for the urban sample are also inelastic suggests that decreasing the time required to travel between public practitioners and urban expectant mothers also will have a minor effect. The elasticities of time prices for the rural sample, however, are seen to be much larger than those for the urban women, 20 with the travel time to public facilities actually falling in the elastic range. The elasticity coefficient suggests that a 1 percent decrease in the mean travel time to modern public facilities will increase the probability of choosing that option by 1.16 percent of its mean value. It appears that locating more public practitioners and facilities in rural areas could effectively increase the use of modern delivery in these areas. Furthermore, the simulation results shown in Table 6 suggest that decreasing the travel time to these modern public practitioners would lead primarily to a decrease in the use of traditional practitioners, while leaving the use of other (private) modern practitioners relatively unchanged. Household income is found to be inelastically related to delivery method choices for both the urban and rural samples. It is interesting to note that for the urban sample public facilities for away-from-home deliveries seem to be viewed as inferior goods, in that an increase in income tends to decrease the likelihood that this delivery option will be chosen. The simulation results suggest that if they experienced income increases mothers would substitute toward the use of private facilities and at home deliveries with public practitioners. Conversely, for the rural sample, at home public practitioner delivery seems to be viewed as an inferior good. An increase in income would tend to shift the pattern of delivery away from this public at home option toward home private and away-from-home both private and public delivery. The number of hours per week that public facilities are available is increased by 40 hours for the purpose of the simulation exercise. For the urban sample this change represents an increase to 168 hours per week (i.e., 24 hours a day availability) and is seen to significantly increase the odds that public away-from- home delivery will be chosen. The predicted 0.116 increase represents an increase of over S0 percent in the probability that a woman in the urban sample with mean 21 characteristics would choose this option. The rural sample also appears to be very responsive to increases in the hours of availability of public facilities. When hours of operatioi are increased from 60 to 100 hours per week, women become 0.0231 more likely to ch( ise this modern away-from-home option, an increase of over 50 percent of the pro'ability predicted at mean values. A dummy variible for whether drugs are available at the public facility is entered in the model as a proxy for the quality and range of services offered there. The simulation results indicate that adding drug availability at a public facility where drugs are not available will cause a relatively large increase in the probability that the public delivery option will be chosen. When drugs are made available the likelihood that this modern away-from-home option will be chosen is increased by 0.0482 fo the urban sample, representing an increase of about 25 percent of the predictes probability when all variables are at their mean values. For the rural sample ;ncrease is 0.0226, and represents a change of over 50 percent of the probai'. predicted at the mean values. In general, both - urban and rural samples are highly responsive to having trained midwives pert deliveries either at home or at public facilities away-from- home. For the urban s mp-e. having trained public midwives as the only practitioners to perform at-home deli aries would increase the probability of this option's choice by 0.0821. For away-frci-home deliveries at public facilities the result of having trained midwives as the p-actitioners is similar, a 0.0967 increase. For the rural sample, at-home public trained midwives are predicted to increase the probability of the choice of at-home publi delivery by 0.0716, and for away-from-home public delivery by 0.0276. In each >f these four cases the increase in the probability of choosing the delivery option .epresents over 49 percent of the predicted probability at sample mean values. Also, n each case large reductions in the likelihood of 22 selecting traditional delivery occurs. 't is obvious that for the Cebu samples trained midwives are highly regarded as birth attendants. If household income is increased by one standard deviation the model predicts that urban mothers will be more likely to choose both home deliveries by public practitioners and away-from-home deliveries at private facilities, although the magnitudes of these predicted changes are relatively small. For the rural sample an increase in household income is seen to increase the likelihood of both public and private away-from-home deliveries, as well as that of home deliveries by private practitioners. Increases in household assets appear to increase the probability of choice of the modern away-from-home option for the urban sample, and to shift the pattern of delivery away from the traditional types of delivery for the rural sample. In general, however, the magnitudes of the simulation results suggest that changes in household wealth do not affect the pattern of delivery to a large extent. The results for the effect of the mother's having insurance coverage indicate that insurance increases the likelihood of choosing home private, away public, and away private deliveries for members of both the urban and the rural samples. In the urban sample the largest response to insurance coverage is an increase of 0.0528 in the probability of the choice of public away-from-home deliveries, a change which represents about 25 percent of the predicted probability of choosing that option at mean values for all variables. For the rural sample insurance coverage is seen to greatly increase the probability of choosing public home, and both public and private away-from-home delivery. With coverage the probability of a home delivery with a public practitioner is doubled, and the predicted probability of public away-from- home deliveries is increased by 0.0290, roughly 65 percent of the expected probability at the means. The increase in private away-from-home deliveries (0.0273) 23 re-resents more than 52 percent of the mean expected probability of choosing t:.is option. Simulations to test the effect of increases in the mother's education (increasing the nuonber of years of education by one standard deviation) indicate that urban mothers who are more highly educated will be more likely to choose modern public and private away-from-home deliveries than will those with less education. Tn the rural sample, more highly educated mothers become more likely to choose modern practitioners. both at home and away-from-home, rather than relatives and traditional practitioners. Using the coefficient results from the alternative estimations, which included dummy variables for whether the woman had received prenatal care from a traditional, public. or private practitioner, simulations were performed to test the effect of the woman's choosing public prenatal care. The use of this model implies that choice of type of prenatal care is exogenous to the choice of delivery service model. For the urban sample the effect of using public prenatal care is seen to be a 0.1023 increase in the likelihood that a modern public away-from-home delivery is chosen, representing nearly a 50 percent increase over the probability of this choice when all variables are at their mean values. For the rural sample choosing public prenatal care increases the probability that a modern delivery, either away-from- home, at home, or from public or private practitioners will be chosen. The largest increase (0.1077) is for the probability of a home delivery with a public practitioner, an increase of 68.5 percent over the probability at the means. The increase in the probability of choosing delivery at a public facility for those who use public prenatal care is also relatively large (0.0241), representing a 54 percent increase over the probability at the means. For the rural sample the effect of using public prenatal care is to decrease the likelihood of choosing a traditional delivery 24 by 0.0988, a decrease of 15.3 percent of the probability at the mean values. For the urban sample, the largest effects of using public prenatal care are reductions in the probabilities of choosing both at-home (-0.028) and away-from-home (-0.05) private practitioner delivery. IV. Summary and Policy Tmnlications The provision of modern birth delivery services has been a major concern in many low-income countries. This study examines the determinants of the choice of delivery in the Cebu region of the Philippines. The study focuses on the effects of money prices, time prices, characteristics of delivery services and socioeconomic characteristics of the households on the choice of type of delivery care, especially modern delivery care. A unique data set, with choice-specific money and time prices and facility quality measures, designed expressly for this analysis and providing prospective information for over 3,000 mother-infant pairs is used. The estimation technique allows us to examine the effect of delivery choice-specific factors as well as unconditional household-specific factors. Important results related to money and time prices of delivery and other factors crucial for policy making clearly emerge. The results suggest that the choice of delivery service type is relatively insensitive to changes in money prices. A policy designed to increase the use of modern publicly provided delivery services by decreasing money prices would be expected to do little to increase demand for these services. Conversely, an increase in the money price for modern publicly provided delivery services for cost recovery purposes would be expected to decrease usage very little. The results found for the travel time price of infant delivery suggest that in urban areas decreasing the travel time between expectant mothers and modern public delivery services also would have a minor effect on the use of these services. In rural areas, however, decreasing the travel time between expectant mothers and modern public delivery 25 services by locating practitioners and facilities nearby would increase the use of modern delivery services. in addition to increasing the accessibility of public delivery practitioners and facilities in rural areas, other public policy changes, including increasing the hours of operation, increasing the availability of drugs, and providing trained midwives at public facilities are found to cause increases in the use of modern delivery services. 26 REFERENCES Akin, J.S.; C. Griffin; D.K. Guilkey; and B.M. Popkin (1984). The Demand for Primary Health Care in the Third World (Totowa, NJ: Littlefield, Adams and Company). Akin. J.S.; C. Griffin; D.K. Guilkey; and B.M. Popkin (1986). "The Demand for Primary Health Services in the Bicol Region of the Philippines." Economic Development and Cultural Change, 34(4):755-782. Maddala, G.S. (1983). Limited Dependent and Qualitative Variables: Econometrics (Cambridge: Cambridge University Press). Mangay-Angara (1981). "Philippines: The Development and Use of the National Registry of Traditional Birth Attendants." In The Traditional Birth Attendant in Seven Countries: Case Studies in Utilization and Training, edited by A. Mangay- Maglacas and H. Pizurki. Geneva: World Health Organization Public Health Papers no. 75, pp. 37-70. Parado, J. P. (1979). "EMperiences in the Bohol MCH/FP Project." In Maternal and Child Health Family Planning Program: Technical Workshop Proceedings, October 31-November 2, 1979, New York City. New York: International Programs, The Population Council, pp. 86-99. Popkin, B.M.; M.E. Yamamoto; and C.C. Griffin (1984). "Traditional and Modern Health Professionals and Breast-Feeding in the Philippines." Journal of Pediatric Gastroenterology and Nutrition 3:765-76. Simpson-Hebert, Mayling; Phyllis T. Piotrow; Linda J. Christie; and Janelle Streigh (May 1980). "Traditional Midwives and Family Planning." Population Reports, Vol. VIII, No. 22, Series J, pp. J-437-438. Williamson, N.E. (1982). "An Attempt to Reduce Infant and Child Mortality in Bohol, Philippines." Studies in Family Planning 13:106-17. 27 ACOWLEDGEXENT Funding for this paper was provided by t!e Population, Health, and Nutrition Department, the World Bank. The Cebu data collection effort is part of a collaborative research project between the Nutrition Center of the Philippines. directed by Dr. Florentino S. Solon; the Office of Population Studies. University of San Carlos. directed by Dr. Wilhelm Flieger: and a group from the Carolina Pnpulation Center. Funding for the project design and data collection was provided by the Nestle's Coordinating Center for Nutrition Resarch, Wyeth International, Ford Foundation, the U.S. National Academy of Science, the National Institutes of Health (contract number RI HDI9983A), and the Agency for International Development (AID). Lionel Deang, David Fugate, and Margaret Mauney are thanked for their extensive assistance. 23 Table 1. Pattern of Delivery Urban Rural Total Category Delivery Type N N 0 114 1. Relatives and friends, at home 130 5.45 64 8.84 194 6.25 2. Traditional practitioner, at home 511 21.77 460 63.54 971 31.62 3. Public practitioner, at home 405 17.26 112 15.47 517 16.83 4. Private practitioner, at home 200 8.48 14 1.93 214 6.94 5. Public practitioner, away from home 508 21.64 35 4.83 543 17.68 6. Private practitioner, away from home 597 25.40 39 5.39 636 20.68 TOTAL 2,351 100.00 724 100.00 3,075 100.00 1 Table 2 (continued) Cebuano Ethnic origin indicated by language spoken in the hou.-,nold (Ceb_ .,o spoken by both husband and wife = 1; othe-.se = 0). Electricity Whether the housencid has electricity (yes = 1; no = 0). Insurance coverage Whether the woman is covered by health insurance (yes = 1; no = 0). Wet season Whether the childbirth occurred during the rainy season (June-October = 1; otherwise = 0). Dry season Whether the childbirth occurred during dry months (February-April = 1; otherwise = 0). Private prenatal visit Whether a prenatal visit was made to a private practitioner (yes = 1; no = 0). Public prenatal visit Whether a prenatal visit was made to a public practitioner (yes = 1; no = 0). Traditional prenatal visit Whether a prenatal visit was made to a traditional practitioner (yes = 1; no = 0). 2 Table 2. Variable Descriptions DELIVERY SPECIFIC VARIABLES: Price The average price. in pesos, for each delivery type in each barangay are used as the prices facing women in each barangay. Travel time The time, in minutes, between the household and the delivery practitioner. Hours available The number of hours per week that the practit- ioner and/or facility is available. Drugs available Whether drugs are available at the public or private facility (yes = 1; no = 0). Untrained practitioner Whether the delivery practitioner has had formal medical training (yes = 0; no = 1). Trained midwife Whether the usual delivery practitioner at the public and private facility was a trained midwife (yes = 1: doctors, nurses. or combina- tions of doctors, nurses, and midwives = 0). INDIVIDUAL AND HOUSEHOLD CHARACTERISTICS Household income Annual household income, in thousands of pesos. Household assets Total value of assets, in thousands of pesos, owned by the household including land, housing, consumer goods, vehicles, etc. Mother's education Years of formal schooling. Father's education Years of formal schooling interacted with whether the father was present. Father present Whether the father is present in the household (yes = 1; no = 0). Mother's age Age in years. Children under age 6 Number of children between the ages 0-6 years. Females over age 13 Number of females in the household aged 13 and older. I Table 3. Sample Means and Standard Deviations of Independent Variables. Urban Rural All Variables Mean SD Mean SD Medn SD DELIVERY SPECIFIC VARIABLES: Price (in pesos) Relatives 43.66 (20.14) 27.36 (8.47) 43.64 (20.22) Traditional 56.96 (15.85) 48.33 (17.09) 54.92 (16.56) Public, home 51.27 (14.74) 41.17 (6.62) 48.89 (13.96) Private, home 66.98 (16.11) 66.37 (39.92) 66.83 (23.94) Public, away 169.80 (48.75) 162.13 (70.33) 167.99 (54.69) Private, away 426.81 (104.70) 378.04 (102.93) 391.94 (121.84) All 136.61 (28.28) 120.27 (13.80) 128.95 (25.40) Travel time (in minutes)' Traditional 7.27 (4.73) 24.15 (21.13) 11.25 (13.16) Public 11.23 (5.66) 32.51 (24.67) 16.24 (15.79) Private 4.39 (2.91) 30.15 (25.16) 10.46 (16.57) All 6.41 (2.44) 24.99 (15.21) 10.78 (11.04) Hours available (per week)2 Public, away 127.77 (53.06) 58.74 (42.25) 111.49 (62.09) Private, away 148.95 (36.16) 127.94 (42.76) 143.99 (38.85) Drugs available Public, away 0.51 (0.50) 0.53 (0.26) 0.51 (0.49) Private, away 0.45 (0.49) 0.36 (0.42) 0.43 (0.49) Untrained practitioners3 0.33 (0.06) 0.33 (0.06) 0.33 (0.06) Trained midwives Public, home 0.41 (0.49) 0.59 (0.49) 0.44 (0.50) Private, home 0.45 (0.50) 0.43 (0.48) 0.45 (0.47) Public, away 0.32 (0.47) 0.95 (0.21) 0.47 (0.50) Private, away 0.00 0.00 0.00 Table 3 (continued) Urban Rural All Variables Mean SD Mean SD Mean SD INDIVIDUAL AND HOUSEHOLD CHARACTERISTICS: Household income 0.30 (0.47) 0.19 (0.27) 0.28 (0.44) Household assets 14.25 (54.42) 5.76 (19.35) 12.25 (48.63) Mother's education 7.62 (3.29) 5.46 (2.29) 7.11 (3.31) Father's education 7.49 (3.41) 5.09 (3.01) 6.93 (3.51) Father present 0.94 (0.24) 0.95 (0.21) 0.94 (0.23) Mother's age 25.88 (5.84) 26.70 (6.46) 26.07 (6.00) Children under 6 1.49 (1.14) 1.67 (1.12) 1.53 (1.14) Females over 13 0.51 (0.90) 0.36 (0.76) 0.47 (0.87) Cebuano 0.91 (0.29) 0.95 (0.21) 0.92 (0.27) Electricity 0.60 (0.49) 0.18 (0.38) 0.50 (0.50) Insurance 0.12 (0.32) 0.05 (0.21) 0.10 (0.30) Wet season 0.50 (0.50) 0.47 (0.50) 0.49 (0.50) Dry season 0.18 (0.38) 0.20 (0.40) 0.19 (0.39) Private prenatal visit 0.24 (0.43) 0.07 (0.26) 0.20 (0.40) Public prenatal visit 0.53 (0.50) 0.47 (0.50) 0.52 (0.50) Traditional prenatal visit 0.47 (0.50) 0.58 (0.50) 0.49 (0.50) n 2351 724 3075 !Travel time for relatives assumed equal to zero. 2Hours available per week for at-home deliveries equals 168. 3Sample average across all choices. abe 4. Mithmal egit ~enuts - t Si~ &mple (t-Stats). ~txiotll Varli)les Priæ -0.0016 (-3.3W)** 'r~l -0.0» tine (-1.283) thrs 0.0149 avil,ble (12.386)** Ulk> 0.2621 analkble (3.174)** Wtriid 0.84f7 middfe (2.(8)** IT~x 0.5035 middfe (5.631)* l"/1W hRB IFRIV R1V RL RiD ~RIV IiV AL ll NRIV Ift 11") RI*Wi) g [g _ [g g_ _ [Eg Lg kg Lg kC _g g _ eg - g -__ . kg . Au k Nl ARB A NU» fnil IRB IItB IIIB IIRIV 1HiV IllV AIRIV NRIV HL tl~ilticmW Variables I~x cMd -0.637 -0.1153 0.23 -0.129 0.364 -0.~02 -0.3878 -0.4"A 0.0~9 -0.50» 0.0146 0.403 -0.99I) 0 4'77 0 5213 xx- (-1.065) (-0.396) (1.1f) (-0.341) (1.790)* (-1.529) (-1.387) (-1.075) (0.447) (0.,8) (0.036) (1.332) (-1.67)* (-1.7,16)* (0.8%li) liixud -0.0655 -0.002 -0.05 .0029 0.0007 -0.0030 -00()10 -0.0001 0.0032 -0.(0X6 -0.0w 0.0= -0(.3m -0.0w1 0 (X U) ats (-0.863) (-1.272) (-1.078) (-0.818) (0.519) (-0.454) (-0.30) (-04 ) (1.405) (-0.348) (-0.143) (1.0() (-0.7) 1 542) (0.31) M"Er's -0.1283 -0.1151 -0.0B10 -0.1452 0.11" -0.0173 -0.0M4 -0.0643 0.1936 0.0170 0.02B 0.239 -0 »D 0 2M 0 0129 ejratim (-3.132)* (-4.33>)** (-3.00)* (-4.35)*** (4.570)*** (-1.139) (-1.253) (-1.880)* (7.09B)*** (0.368) (0.B75) (7.5"6)* (.-5706)* ( 8.24)*- (0.331) 0.05s O. .068 -o0.M72 -0.0" 0.1325 0.~[ -0.0110 -001 0.187 0.0[um -o.0fTi9 0. 1"2 -0.1852 -0.21/ 0.0V1b «itatj (-1.316) (--2.618)* (-2.117)* (-1.01)* (5.118)*** (0.111) (.414) (-0.U) (6.678)* (0.170) (-0.237) (5.56)*** (-4.497)* (-7.210)*" (- 4).;i) Rtr 0.0007 0.3656 0.4238 0.3512 -1.8167 -0.331 -0.ffi82 -0.073 -2.2401 -0.3X5 0.0144 -2.169 1.8174 2.182 0.:-1tW ruCETt (0.064) (1.078) (1.285) (0.866i) (~5.645)** (-0.806) (~0.167) (-0.17r3) (-6.409)** (-0.g2) (0.(M1) (-5.148)** (3.7U3)*** (6.M7)** (0.740) Mtir's -0.0148 0.0[lm -0.(MXrl 0.0=3 0.0143 -0.0141 0.006 0.0060 0.0150 4 0.0D[T7 0.0091 U-0.»291 -0. 4(XX" O.fYn (-0^.79) (0.52) (-0.061) (0.3j5) (1.321) (-0."7) (0.5w) (0.442) (1.2B3) (-1.082) (0.08) (0.649) (-1.675)* (-.0.") (1.324) (h0ld1 0.1511 0.115 0.010 0.95 -0.1615 0.1(Y12 0.06~6 0.01~ -0.3834 0.0616 0(.3) -0.2510 0.3156 0.2710 -0 (i; urIr 6 (1.of5)* (1.912)* (0.741) (1.10f) (-2.616)** (1.149) (1.114) (0.5W0) (-3.10)* (0.(2) (0.342) (-3.119)*** (3.296)* (4.318)* ( 0.426) R~ules -0.168 -0.1150 0.010f -0.1921 0.0145 -0.1813 -0.1316 -0.Wffl 0.0179 0.73 0.070 0.225 -0.1992 -0.1l05 0. M(Y7 ~ar 13 (-1.112) (-1.348) (0.23) (-1.64)* (0.473) (-1.212) (-1.497) (-1.766)* (0.218) (0.1<1f) (0.613) (1.944)* (-1.333) (-1.U)* (0.:MI) (~xuw -0.9016 -0.5014 -0.340 -0.7133 -0.03) -0.52mT 0.1175 -O.32 -0.5% -0.1914 0.2118 -0.1%7 -0.0147 0.3~> 0.412 (-2.6M)** (-1.93)* (-1.546) (-2.480)* (-4.19)*** (-1.544) (-0.459) (-1.141) (-2.190)* (-0.5215) (0.1V7) (-0. ) (-0.015) (1.13) (1.2f7) Table 4 (an1tini) IIRB Wm) AvRiV fe, HIi) 11VIV S1V ff. ) IV 51, Wf) 1£g Ug Leg k fnlg 1.g -- Lg u¥ kg 11__ -- li___ g_ 1£9 1,1 ekgff C ELXtricity 4.4W' -0.4612 -0.2459 0.2m1 0.6ff8 -0.1914 ~0.2154 0.522 0.9317 -0.7144 -0.7374 0.4ul -1.124 -1 1471 0 (W,:0 (-1.90) (-3.Z14)* (-1.637) (1.481) (4.Wr)*** (-0.8ff) (-1.477) (2.771)*** (5.470)*** (-2.&e)" (-4.AM)- (2.0X)- (-4.7W)* ( *I.X)* (-0.lj) Imrcœ 0.3T/9 0.29%3 0.M 0.1312 0.4623 0.08 0.0151 -0.1480 0.1831 0.237 0.1611 0.311 -0 10M -0.1C) 0.0(m (1.012) (1.a61) (1.151) (0.418) (2.278)* (0.221) (O.0G3) (-0.462) (0.8m5) (0.W) (0.525) (1.0) (-0.302) 0.7&) (-o.lal) Wt seom -0.TIO 0.035 0.Mil -0.3B% 0.1968 -0.241 -.021 -0.4672 0.1177 0.231 O.42A5 0.518 -0.3618 -0.1(m 0.3)14 (-0.742) (0.2,14) (0.512) ( 2.014)* (1.350) (-1.(m) (-0.274) (-2.344)* (0.721) (0.87) (2.184)** (2.9M)* (1.15) (-0.OE7) (0.lI) Ity s01so 0.W3 0.50 0.3152 0.3916 -0.0318 -0.2816 0.1918 0.AM'1 -0.3(1 -0.3580 0.1184 -0.423 0.063 0.5417 0.4761 (0.112) (2.638)*** (1.540) (1.)* (-0.1&1) (-0.945) (1.014) (0.328) (-1.569) (-1.128) (0.534) (-1.731)* (0.211) (2.575)* (1.666)* **SgfIant at a = .01 SigWficant at a = .10 An lM = prt3eblllty of hce Mlixcy with relatives 'IRAD = ln ility of tme cilmsy with tralitkanl practitiar IfŒ = P~x liIty of toe Jelf~y with pblic rat.itl~a ItIRIV = p~hility of ue delumy with privdte ~tktIar På11 - ~Lillty of ~ f im te &llwry with [blic Itiar AiV - p~lllty of mjy fta toe &11ry with grikate pra:-tltlnrr T~le 5. Kilth Wnial rglt W 1t3 - Rjrul &mple (t-itat). ~ntky<mi Vri,,iA Prim -0.032 (-0.148) 'Th~l --0.0312 tift '(-8.639)*** lrs 0.3 amflLble (2.08s)** lhs 0.3"m aMil lale (0.963) lkitnr~n 1.3[83 Midvife (1.M3)* luxiw 0.49M middfe (1.811)* E ' IRWD IRB lffRlV AMIV RE 'umAD ItRIV ARIV la '140 RiV fa 'IP. IIMD leg Lcg [L g LekgLe Le g gL_g kg kg t_ ANIB ARB ARE 111N3 II IRB 1RD 1f1 llRIV IKVIV MaRIV NRMV PM[V lI. ditkal VrJables Ib~1ld -4.0138 -0.317 -0.3655 -1.~3 -0.19'" -3.(T8 0.0=8 -1.43M8 0.1752 -2.2414 1.4818 1.61a0 -3.ffi3 -0.1272 3.7,Y2 b~e (-2.512)* (-0.495) (-0.510) (-0.723) (-0.282) (-2.315)** (0.(7) (-0.U9) (0.238) (-0.788) (0.6ff) (0.47) (-2.391)* (-0.196) (2.4)** IbinnId -0.0311 -0.00~5 -0.016 0.00w 0.0100 0.003o -0.039 0.0110 0.0145 -0.0T6 -0.0150 0.0»5 -0.0111 -0.01ff) -0.174 assts (-0.00)) (-0.82) (-0.401) (0.290) (1.344) (0.183) (-0.351) (0.480) (1.367) (-0.281) (-0.66B) (0.1) (-0.619) (-1.900)** (0.4") Muttr's -0.3032 -0.1374 -0.039 0.132 -0.1716 -0.236 -0.O8M 0.15m -0.1321 -0.4234 -0.2576 -0.2918 -0.1316 0 a3 0.1 (M Eeatim (-3.1%)* (-1.795)* (-0.5) (0.881) (-1.863)* (43.459)** (-1.85M)* (1.282) (-1.792)* (-3.13)*** (-2.CM)* (-2.18)** (-1.454) (0.485) (2.58)* piar's 0.0112 -0.1230 -0.(U~ -0.U56 0.0193 0.~ -0.(Tff -0.0173 0.016 0.00ff8 -0.34 0.0918 -0.Om1 -0.1482 -0.1401 EklatI (0.118) (-1.680)* (-0.718) (-.568) (0.202) (0.933) (-1.372) (-0.141) (0.W97) (0.ffl8) (-0.445) (0.711) (-0.00) (-2.103)* ( 2.129)** *tir 1.4149 2.320M 1.3m 2.743) -0.3155 0.0619 0.96m0 1.3800 -1.85 -1.3270 -0.42a -3.W75 1.731 2.635 0.91W5 punIt (1.388) (2.720)* (1.5g) (1.02) (-0.313) (0.072) (1.50N) (0.86f) (-1.965) (-0.770) (-0.20) (1.79)* (1.724)* (3.2B4)** (1.240) ?1t1I's -0.R88C -0.018D 0.010 -0.156f 0.0480 -0.( -0.0191m -0.159 0.04ff 0..C(M 0.1388 0.M18 -0.1 (IB -0.WXæ 0.AUX (-1.50) (-0.567) (0.012) (-2.133)* (1.321) (-1.977)* (-0.U1) (-2.Z71)** (1.672)* (1.3ffi) (2.002)* (2.1D) (-3.0)** (-2.531>)* (1.616) (ildkrm 0.1330 -0.13 0. OM2 0.2701 -0.472 0.1237 -0.096 0.2549 -0.4845 -0.1442 -0.294 -0.749 0.1r2 0.4"49 V.1Ån kxw 6 (0.535) (-0.13D) (0.0L7) (0.709) (-1.950)* (0.741) (-0.2A(9) (0.816) (-2.410)** (-0.426) (-0.92) (-2.»)** (2.70)*** (2.448)** (-1.(W1) Rmles 0.3774 0.1(M* 0.0" -0.5" -0.3715 0.3510 0.13 -03/28 -0.3179 0.937 0.7123 0.1749 0.74F9 0.5374 0.2115 <Mr 13 (1.228) (0.679) (0.103) (-0.915) (-1.(1) (1.381) (0.81W) (-1.001) (-1.315) (1.5M8) (1.253) (0.282) (2.lff)** (1.810)* (-0.9Xr) Otn -0.2202 0.4230 0.(I161 -0.710 0.0382 -0. wr8 0.3?44 -0.8145 -0.06M 0.41C7 1.1399 0.7541 -0. 2T4 0.3*~9 0.fi22 (-0.301) (0.034) (0.156) (-0.751) (0.05)) (-0.546) (0.ffm) (4.10) (0.o) (0.529) (1.356) (0.7W) (-0.354) (a.I)) (1.183) Table 5 (anti) FEL MR4 IIB IrmII AMWi Ni I1W IIIV At RIV lu,i mm »[V M41 IM)4 g _ ._ lg kg 1_ k k _ g kg[£ g- Leg _ kgg lEg kg fn _£ lg U_ å1 3 E NE E ARE I 11 11x1 11B IIRIV mUV V NRIV IRIV 141 Elctricåty 0.4184 -0.1tl4 0.0ff1 0.2279 0.4726 0.33m -0.2MA 0.1429 0.3[16 0. 1" -O.3M53 0.2447 -0A13 -0.6109 -0.UM (0.7:0) (-0.349) (0.172) (0.290) (0.817) (0.752) (-0.786) (0.2M4) (0.PA1) (0.252) (-0.576) (0.3) (-0.101) (-1.48) (1.451) hr~xLC -0.3974 -0.50! -0.2716 00518 0.30 -0.1258 -0.2293 1.21 0.5814 -1.3521 -1.4556 -0.6159 -0.7m1 -0.8106 -0.10o (-0.WE) (-1.125) (-0.5m) (1.290) (0.574) ( 0.26) (-0.74) (1.80W)* (1.3:~) (-1.4)* (-2.26)** (-0.3) (1 1.32) (-2.0k1)* (-0.?Am) W.t sam 0.0115 -0.(w-m -O.M -1.1(07 -0.091 0.2138 0.1520 -0.9074 0.1632 1.1212 1.1 1.~106 0.0W -0.0112 -0(11118 (0.(03) (-0.1179) (-0.450) (-1.479) (-0.1T2) (0.563) (0.551) (-1.314) (0.372) (1.577) (1.6014) (1.444) (0.101) (-0.x23) ( 0.193) Ily a~n1 -0.3519 0.2733 -0.1991 -0.823 0.(218 -0.1528 0.4723 -0.6212 0.229 0.484 1.(m5 0.8121 -0.3737 0.2514 0.0251 (o.510) (0.481) (-0.334) (-0.835) (0.01) (-0.292) (1.318) (-0.711) (0.403) (0.47) (1.236) (0.80 (-0.5~) (0.50) (1.38) Siodficant at a - .01 SI foiant at a = .0 Slicflit at a = .10 ~ 141 = gnildlity of Im dlimy with mlatios 'RAD = pIn~tlity of his MIuy with tnlticnl ucti~ticr 1113 = pndiråulity of ine (kliwry with pilic pr-xtlticne IRIV - iAbilty of tulim 1hly with private ira-titi~x NIE = pxility of ay flxn lue däliey with lic practitl=r NIRIV pibillty of a fmy fn Ine el"y with private p:tiortI Table 6. Predicted Probabilities and Changes In Probabilities of Delivery Choice by residence. Urban Rural REL TRAD HPUB HPRIV APUB APHIV REL TRAD IPUB HPRIV APUB APRIV Probabilities at mean values of independent variables 0.0553 0.2130 0.1717 0.0930 0.2124 0.2546 0.0828 0.6455 0.1573 0.0166 0.0445 0.0533 Changes in probability for: Price increased by one standard deviation Public, home (51-66 for urban; 41-48 for rural) 0.0003 0.0010 -0.0037 0.0004 0.0011 0.0009 0.0 0.0002 -0.0002 0.0 0.0 0.0 Public, away (170-218 for urban; 162-232 for rural) 0.0010 0.0424 0.0037 0.0017 -0.0142 0.0036 0.0001 0.0007 0.0002 0.0 0.0010 0.0 Travel time increased by one standard deviation 111-16 for urban; 33-57 for rural) Public. home 0.0005 0.0022 --0.0078 0.0009 0.0024 0.0018 0.0071 0.0694 -0 0889 0.0008 0 0079 0.0037 Public, away 0.0004 0.0027 0.0024 0.0011 -0.0090 0.0024 0.0027 0.0259 0.0074 0.0003 -0 0377 0.0014 Hours available increased by one standard deviation Public, away (128-168 hrs/wk for urban; 60-100 hrs/wk for rural) -0.0081 -0.0343 -0.0304 -0.0141 0.1161 0.0292 -0.0016 -0.0159 -0.0045 -0.0002 0.0231 -0.0008 Drugs available changed Public, away --0.0034 -0.0142 -0.0126 -0.0059 0.0482 -0.0121 -0.0016 -0.0155 -0.0045 -0.0002 0.0226 -0.0008 Table 0 (continued) Urban Rural REL TRAD HPUB HPRIV APUB APRIV REL THAD HPUB HPHIV APUB APRIV Trained midwife changed (from 0-1) Public, home -0.0054 -0.0229 0.0821 -0.0094 -0.0249 -0.0195 -0.0057 -0.0538 0.0716 -0.0007 -0 0064 -0.0030 Public, away -0.0068 -0.0286 -0.0253 -0.0117 0.0967 -0.0243 -0.0019 -0.0189 -0.0054 -0.0002 0.0274 -0.0010 Household income increased by one standard deviation (from 0.30-0.77 urban; 0.19-0.46 rural) -0.0147 -0.0181 0.0199 -0.0080 -0.0073 0.0282 -0.0041 -0.0260 -0.0050 0.0025 0.0098 0.0228 Household assets increased by one standard deviation (from 14-69 urban; 6-25 rural) -0.0101 -0.0216 -0.0095 -0.0062 0.0223 0.0251 0.0006 -0.0236 0.0004 0.0021 0.0085 0.0120 Insurance coverage (from 0 to 1) -0.0053 -0.0281 -0.0134 0.0094 0.0528 0.0153 -0.0025 -0.0869 0.0162 0.0166 0.0290 0.0278 Mother's education increased by one standard deviation (8-11 for urban, 5 8 for rural) --0.0150 -0.0564 0.0322 -0.0296 0.0225 0.1107 -0.0330 -0.0438 0.0337 0.0057 0.0116 0.0258 Prefntal care changed (from 0-1)' Public -0.0102 --0.0045 --0.0099 -0.0282 0.1023 --0.0495 -0.0469 -0.0988 0.1077 0.0035 0.0241 0.0104 'Note that simulations of the effects of public prenatal care are from a separately estimated model where prenatal care is assumud not to be jointly determined with the choice of delivery.