Econometrics Model on Determinants of Adoption

Full Length Research Paper

Econometrics model on determinants of adoption and continued use of improved Soil and Water Conservation practices: the case of Boloso-Sore Woreda of Wolaita Zone, Ethiopia

Brkalem Shewatatek Hailu

Hawassa University, P.O.BOX 05, Awassa, Ethiopia; E-mail: [email protected]

Accepted 27 January, 2015

In the highlands of Ethiopia Soil degradation is a serious problem that threatens the sustainability of agriculture. Although efforts have been made to develop and promote several soil conservation technologies, their adoption has not been widespread. The major concern of this study was, to empirically examine the various personal, socio-economic, institutional and bio-physical factors that determine farmers’ decision on adoption and sustainable use of SWC technologies in Boloso Sore Woreda in SNNPR. A simple random sampling technique was employed to draw a total of 120 respondent households comprising 52 non-adopters and 68 adopters of SWC for the study. Descriptive statistics such as mean, standard deviation and percentages were used for analyzing the data. A binary logit model was employed to examine factors influencing the adoption and continued use of improved SWC. In this regard, a total of fourteen explanatory variables were included in the empirical model of which nine were significant. Among the major factors having significant influence on the adoption and continued use of improved SWC practices; education, farm size, slope and erosion levels, off-farm income, training and credit access have a positive and significant influence. Of these, the level of formal education in the household, training access and slope gradient of farm land were the most important in influencing the improved SWC adoption and continued use. Result of the study concluded that policy makers and development seekers must give due attention and high priority towards development of farmers’ capacity in improving the perception level that enables them to reflect attributes of an innovation. The survey results also indicated natural resource conservation policies that fail to account for inter household and inter-plot variation and the importance of physical factors (level of slope gradient and erosion) behind the use of soil conservation measures are unlikely to be effective.

Key words: Adoption, continued use, soil and water conservation, Logit Model; Boloso-sore woreda (Ethiopia).

INTRODUCTION

Background Agriculture in Ethiopia is the main source of livelihood and national income in the country, which accounts for 47 Ethiopia is one of the world’s earliest countries in percent of gross domestic product (GDP), 90 percent of civilization which is endowed with a distinct wide range of total export earnings, and more than 80 percent of agro-ecology that ranges from mountains and wetlands to employment which makes agricultural land an valley and desert with a bountiful diversity in topography, indispensable resource upon which the welfare of the climate and biological resources. Such diversity offers society is built. However, Agriculture remains potentially favorable conditions for humans to live, though predominantly subsistence, with smallholders cultivating the potential has remained largely untapped as noticed in more than 90 percent of total crop land and producing Wegayehu (2003). more than 90 percent of total agricultural output (World Scholarly J. Sci. Res. and Essay 36

Bank, 2003). main determinant factors affecting their adoption and The principal environmental problem in Ethiopia is land sustainable use of the technologies. Moreover, many of degradation, in the form of soil erosion, gully formation, the above studies lack the comparative evaluation of the soil fertility loss and severe soil moisture stress, which is indigenous and improved technologies with respect to the partly the result of loss in soil depth and organic matter suitability to the local conditions and none of the (Fitsum et al., 1999). Land degradation, owing mainly to achievements can also be extrapolated to the densely poor land management and high population density, is populated area of Bolos Sore Woreda of Wolaita Zone. the main cause of Ethiopia’s low agricultural productivity Therefore, it becomes essential to investigate the main and vulnerability to drought. It can be described as a determinant factors, that would assist in the formulation reduction of resource potential by a combination of and implementation of the policy and technology processes acting on the land; such as soil erosion by interventions designed to induce voluntary and continued water and wind, bringing about deterioration of the use of SWC measures in the study area. physical, chemical and biological properties of soil, which results in the soil’s inability to retain water, increased soil erosion and nutrient depletion (Maitima and Olson, 2001). OBJECTIVE OF THE STUDY The excessive dependence of the Ethiopian rural population on natural resources, particularly land, as a General objectives: means of livelihood is an underlying cause for land and other natural resources degradation (EPA, 1998; To examine/assess the various personal, socio- Wegayehu, 2003). The scale of the problem, however, economic, institutional and bio-physical factors that dramatically increased due to the increase in determine farmers’ decision on adoption and sustainable deforestation, overgrazing, over cultivation, inappropriate use of soil conservation technologies in Boloso Sore farming practices, and increasing human population. The Woreda. population density on arable land has more than doubled since 1950. Some 80 percent of the population still lives Specific objectives: in rural areas, mainly in the highlands, where an estimated 50 percent of the land is degraded (WFP, To describe the current soil conservation practices 2005). Removing vegetative cover on steep slopes (indigenous and/or improved) employed by farmers (slopes ranging between 15 and 50 percent) for To identify the most important factors that determine agricultural expansion, firewood and other wood farmers’ adoption decision on improved soil requirements as well as for grazing space has paved the conservation measures. way to massive soil erosion. Ethiopia loses annually 1.5 billion MT of topsoil from the highlands by erosion, which could have added about 1 to 1.5 billion MT of grain to the STUDY METHODOLOGY country’s harvest (Hurni, 1983 cited in Girma, 2001). Despite the severity of the problem, it is only recently Description of the Site that land conservation has received policy attention in the country, the Ethiopian government first recognized the Location severity of the soil degradation problem following the 1973/74 famines in Wollo which drew the attention of Boloso Sore is one of the 77 Woredas in the Southern external donors to land degradation problem and soon Nations, Nationalities and Peoples' Region of Ethiopia conservation become a priority (Berhanu and Swinton, which is located at about 420 km from Addis Ababa in 2003). Wolaita Zone, 7°05 ′N 37°40 ′E / 7.083°N 37.667°E Although, the government has taken different soil and (Wikipedia, the free encyclopedia, 2011). Part of the water conservation measures to mitigate land Semien Omo Zone, Boloso Sore is bordered on the south degradation problems in Ethiopia, the rate of adoption of by Sodo Zuria, on the southwest by Kindo Koysha, on the the interventions is considerably low. According to west by Loma Bosa, on the north by the Kembata Alaba information obtained from the Woreda BoA, in the study and Tembaro Zone, on the northeast by the Hadiya Zone, area there have been projects like especially, MERET and on the east by Damot Gale with the administrative and PSNP functioning since the past ten years, in the ten center at Areka. kebeles of the Boloso Sore Woreda. Review of relevant literatures points to the fact that a number of empirical Demographics studies have been undertaken on technology adoption under Ethiopian context (Table 1). However, no previous Based on figures published by the Central Statistical researches have been undertaken to assess and Agency (2005), the Woreda has an estimated total examine the extents to which farmers have adopted population of 358,694, of whom 182,983 were men and these improved soil conservation technologies and the 175,711 were women; 31,740 or 8.85% of its population Hailu 37

Table 1: Distribution of sample households in sampled kebeles.

Kebeles Household Total Size Sample Farmers Total Sample size Non -adopt er Adopter Dolla 984 16 23 39 Dengera-medelicho 1042 17 23 40 Gurmo-koisha 1480 19 22 41 Total 3506 52 68 120

are urban dwellers, which is greater than the Zone selected for the study because of the fact that the average of 8.5% (CSA, 2005). With an estimated area of improved SWC technology is widely popularized mainly 632.66 square kilometers, Boloso Sore has an estimated by MERET and PSNP projects. Three kebeles, namely population density of 567 people per square kilometer, Dolla, Dengere-medalicho and Gurmo-koisha were also which is greater than the Zone average of 156.5. purposively selected by considering the severity of land degradation, previous and current efforts undertaken to mitigate the problem and enhance the sustainability of Topography, climate and soil type mitigation measures. In addition, the diffusion and implementation of improved soil conservation Altitude ranges between 1800 and 2400 m.a.s.l., with technologies were undertaken only in dega and woyna undulating topography. Its slope ranges from 4 up to dega climatic zones, the selected kebeles are also found 60%. There are also seasonal and intermittent streams, in these two climatic zones. In this study simple random with steep slopes. The area receives an annual rainfall of sampling was selected as a preferred sampling method 1,578 mm and the mean maximum and minimum daily because each sample in the population has equal chance temperature are 25.4 0C and 13.4 0C. The rainfall is of being selected. In addition simple random sampling is bimodal with two growing periods, the small rainy season an appropriate sampling method when small scale (belg), extends from March to June. Main rainy season surveys (like the present study) are conducted, the (meher) has duration from July to the end of October. estimation of sampling errors and significance tests could The soils in the woreda vary from place to place but be based upon simple random sampling procedure. The nitosols are the common ones (Wikipedia, the free survey covered 120 household heads (68 from the encyclopedia, 2011). adopter and 52 from non-adopter household) randomly selected from the three kebeles. With regard to the Socio-economic and land use activities sampling technique, proportional random sampling technique was used to select sample respondents from The subsistence based living of the people in the area each kebeles (Table 1). are highly dependent on agriculture production in which it is not more than hand to mouth. They are using mixed farming system. The main land covers of the area are Data collection method perennials and seasonal crops such as; enset (a staple food of the area), coffee, cabbage, maize, haricot beans, For this study both primary and secondary data sources sorghum, barley and teff (Eragrostis teff), sweet potato, were used. The primary data was collected from sample Irish potato, taro, cassava and yam are important in the farmers and others such as Woreda experts and area. Crops like maize, haricot bean, enset, sweet potato development agents who have involved in soil and Irish potato are planted in the belg season. Crops conservation in the study area using both formal, informal like teff, wheat, Irish potato, haricot bean, and sweet surveys and transect walks. Beside these, the study also potato are planted in the meher season. Furthermore, employed information from secondary sources. vegetation covers in the area are natural and plantation Pilot study and transect walks across the village were forest. The natural as well as plantation forest consists of conducted in order to obtain environmental and economic low land coverage while plantation forest is mostly use profile and other necessary information on the types of monoculture system or exotic species. existing indigenous and improved SWC works undertaken. Prior to the formal survey focus group discussions METHODS OF DATA COLLECTION (FGD) were conducted in each of the three kebeles with people assumed to have sufficient information about the Sampling method general features of the area to acquire useful and detailed information, which would have been difficult to In the first stage, Boloso-Sore Woreda was purposively collect through the questionnaire survey. Based on the Scholarly J. Sci. Res. and Essay 38

information obtained and learnt experience from the ways; using descriptive statistics and econometric model. focus group discussion, questionnaire that was used latter in the formal survey was drafted and structured. The logit model Moreover, the questionnaire was pre-tested for its appropriateness and further improvements also amended Binary explanatory variables can be represented as before it was used in the formal survey. dummy variables and a binary choice model assumes Formal survey was then conducted using structured occurrences between two alternatives (in this case being questionnaires to gather information from sampled adopter or non-adopter of improved soil and water farmers’ households. The survey questionnaire included conservation practices). both open and close ended questions which were pre– There are several methods to analyze the data tested by administering it to selected respondents. involving binary outcomes. However, for this particular Subsequently, on the basis of the results obtained from study, logit model was selected. The linear probability the pretest, necessary modifications were made on the model (LPM) which is expressed as a linear function of questionnaire which was ultimately translated from the explanatory variables is computationally simple. English into Amharic. Enumerators or data collectors However, despite its computational simplicity, as were oriented and trained about the objectives of the indorsed by Gujarati (2004), it has a serious defect in that study, the types of data required, the number and types the estimated probability values can lie outside the of sample respondents to be interviewed before they start normal 0-1 range. Hence logit model is advantageous collecting the data and the collection of the data was over LPM in that the probabilities are bound between 0 undertaken with close supervision of the investigator. The and 1. Moreover, logit best fits to the non-linear enumerators selected for the survey were all speakers of relationship between the probabilities and the explanatory the local language, Wolaitigna. variables. The dependent variable in this case is a Beside these, the study also employed information from dummy variable, which takes a value of zero or one secondary sources which were obtained from various depending on whether or not a farmer is adopter or non- sources such as reports of MoA at different levels, CSA, adopter of improved soil and water conservation Woreda and Kebele Administrative Office, NGOs, practices. previous research findings, Internet and other published However, the independent variables are both and unpublished materials, which were found to be continuous and binary. In this study, logistic econometric relevant to the study. model was used to identify the factors (the independent variables) that affect farmers’ decision of adopting Model Specification, Variables Definition and Data improved soil and water conservation practices in the Analysis study area. According to Chatterjee and Bertran (1991) the cumulative logistic probability function is specified The data obtained from this study was analyzed in to two econometrically as:

(1)

= (2)

Where: logistic model once written in terms of the odds and log of odds (Hosmer and Lemeshow, 1989). The odds ratio is th Pi represents the probability of that i household making simply the ratio of the probability of being adopter of the a certain choice (in this case being either adopter or non- technology (P i) to the probability that the farmer would be adopter of improved soil and water conservation non-adopter (1-Pi). Therefore, the odds ratio will become: practices), for the given explanatory variables (X i); e represents the base of natural logarithms (2.718); th Xi represents the i household explanatory variables; ni represents the number of explanatory variables, i = 1, (3) 2, 3 …, n, and α and β are regression parameters to be estimated, However, the P i is non-linear, and therefore, to get where α is the intercept and β is the coefficients of X i linearity, taking the natural logarithms of odds ratio of Coefficient interpretation will be understandable if the equation (3), will result in the logit model as indicated in Hailu 39

equation (4) and the coefficient of the logit model and socio-economic characteristics. While the later presents the change in the log of the odds associated (LIMDEP 7, according to Gujrati (2004) has built-in with a change in the explanatory variables. routines to estimate the logit model at the individual level) was put into use only for econometric analysis, i.e. logistic regression model which was used to identify the most important factors that affect farmers’ adoption (4) decision of the sustainable use of improved SWC practices in the study area. Therefore, in the logistic model, as P (probability of the logit) goes from 0 to 1 which is not linear, Z (the logit) goes from −∞ to + ∞ (which has no boundary but linear). RESULTS AND DISCUSSIONS As the logit (Z) becomes negative and increasingly large in magnitude then the odds ratio decreases from 1 to 0 In this chapter reports on the findings of descriptive and and as Z becomes positive and increasingly large then econometric analysis in line with the different adoption the odds ratio increases from 1 to +∞. Coefficient categories are presented. interpretation will be understandable if the logistic model once written in terms of the odds ratio. The intercept is Descriptive Statistics Results the value of the log odds in favor of adopting/not adopting the SWC if the other independent variables are zero. As indicated above, the survey covered 120 household heads (68 from the adopter and 52 from non-adopter household) randomly selected from the three kebeles. VARIABLE DEFINITIONS The sample composed of 87% male headed households and 13% female-headed households. Dependent variables The mean age for the non-adopter (41) and adopters (40) was almost similar. The non-adopters had slightly Farmers adoption decision (ADPTOR): The dummy larger family size (7.37) than the adopters (6.68 persons). adoption decision whether to adopt or not adopt improved From a total of 61 (51%) illiterate household head soil and water conservation practices in the study area. respondents, about 33% and 67% were adopters and This variable is the dependent variable that is to be non-adopters, respectively. Adopters of improved SWC regressed in the Logistic linear regression model. The had an average o 24.75 years of farming experience. The dependent variable will take values of 1 if the farmer corresponding figure for the non-adopters was 25.81 decides to adopt the improved soil and water years. The average size of farmland owned by the conservation practices, and 0, otherwise in the survey sample respondents was 0.94 ha. Adopters owned, on time. average, almost similar farm size (0.94 ha) with that of the non-adopters (0.95 ha). Adopter and non-adopters Independent variables have similarity in the possession of grown major annual crops like wheat, barley, bean, haricot-bean, maize, teff, Different theoretical and empirical studies conducted sweet-potato, potato, and taro. From very limited types of elsewhere on factors influencing adoption of agricultural perennial crops grown in the study area, namely enset, technologies indicate the role of many personal, coffee, banana, avocado and mango, adopter relatively institutional, socio-economic and bio-physical factors in had higher possession of fruit perennial crops of banana, determining farmer’s adoption decision. The independent avocado and mango. The average size of livestock variables of the study were those which were expected owned by the sample respondents was 2.65. Non- (hypothesized) to have association with the adoption of adopters owned, on average, slightly larger livestock size agricultural technologies on basis of past research (2.72) than that of the adopters (2.60). The average off- studies, based on the literature by Gujarati (2004) and farm income of the sample respondents was 141.77 birr. prior knowledge of the study area. On average, non-adopter farmers earned birr 211.06 from off-farm activities as compared to only birr 88.78 for Data analysis adopter farmers. From a total of 120 respondent 70 (58%) owned farm The data collected from the farmers and other sources land with gentle slope followed by 31(26%) and 19 (16%) was analyzed using descriptive and econometric models. for flat and steep slopes respectively. Of the 31 For the analytical methodologies, two statistical packages household respondents who owned farm land with flat were used: SPSS 16 and LIMDEP 7 econometric slope, 30 (97%) were non-adopters of the improved SWC software. The former package was used for descriptive practices. On the contrary from a total number of 19 analysis which used counts, percentages, means, household respondents who owned farm land with steep standard deviations, chi-square and t-values in examining slopes, 17 (89%) were found out to be adopters of the farmers’ demographic, physical, institutional, attitudinal improved SWC technologies. Rill and gully erosion Scholarly J. Sci. Res. and Essay 40

Table 2: Maximum likelihood estimates of logit model

Variable Coefficient ( βj) Odds ratio Exp ( βj) Wald statistics Sig. CONSTANT -45.467 7.538 0.006 *** SEXHD 0.994 2.702 0.328 0.567 AGEHD 0.320 1.377 2.682 0.101 FAMSZ -0.770 0.463 5.412 0.020 ** EDUHD 7.734 2.28E3 8.259 0.004 *** FRMEXP -0.081 0.922 0.336 0.562 FARMSZ 2.563 12.970 4.530 0.033 ** SLOPGR 5.982 396.35 7.608 0.006 *** SOILFERT -0.324 0.723 0.064 0.800 EROTP 3.948 51.851 5.565 0.018 ** OFRMINC 4.582 97.711 5.008 0.025 ** EXTSRV 2.823 16.835 1.537 0.215 TRAINACS 9.661 1.57E4 8.415 0.004 *** CRDTACS 3.489 32.765 4.965 0.026 ** LH -1.123 0.325 5.332 0.021 ** 2 Log likelihood = 164.216 Chi-squared=133.59 *** Correctly Predicted=94.17 % 1 Sensitivity= 94.11 % 2 Specificity= 94.23 % 3

***, ** and * are significant at 1 percent, 5 percent and 10 percent probability level, respectively. 1Based on 0.5 cut value 2Correctly predicted users group based of 0.5 cut value 3Correctly predicted non-users group based of 0.5 cut value

problems were reported to be the major problems by 59 of the adopter farmers use indigenous cut-off-drains and (49%) and 21 (18%) of the household respondents diversion ditches respectively along with either of the respectively. Of these 44 (75%) and 19 (91%) were most commonly used improved fanya juu and soil bund adopters of the improved SWC practices. Considering structures. Indigenous biological conservation practices respondents’ perception on the existence of improved mainly the plantation of the perennial crops like banana SWC structures, about 92% and 78% of the household and forage crops was also observed integrated with the respondents had awareness about the existence of the improved SWC practices in 11.8 % of the adopter technologies and with the belief that they would bring farmers. From the 68 farmers which were documented as profit to them in the long run. About 85% of the sample adopters of the improved SWC practices, only 37 (54.4%) respondents reported that they had contact with were continuously using the technologies, with the rest agricultural extension agents, either in groups or either partially removing (26.5%) to be on the verge of individually. Fifty eight percent of the respondents non-adopters or totally removed (14.7%) the structures indicated that they had received trainings on soil and becoming non-adopters. The majority of farmers conservation practices and on how to undertake physical pointed out high cost (48.5%), decrement of farm size soil conservation measures in the past five years. From (22.1%), pest and disease problems (14.7%) and labor the total of 58 farmers who had taken the training 46 shortage (14.7%) as the main reasons for not keeping up (79%) of them were adopters with the corresponding the continued use the improved SWC structures. figure of 12 (21%) farmers being non-adopters. In this study credit access has positively affected adoption of improved SWC technologies in that from those who has ECONOMETRIC ANALYSIS got credit access (70%) the majority (77%) were adopters of the improved SWC technologies. Elaboration on explanatory variables The most widely used improved soil conservation technologies were improved soil bund, and fanya juu. The goodness-of-fit measurements of the model are also From a total of 68 adopter household respondents 19 given in the Table 3. The computed log likelihood ratio (28%) and 18 (27%) were users of soil bund and fanya statistics (Chi-square) exceed the Chi-square critical juu respectively and the other 19 (28%) adopter house values at 1 percent significance level confirming that the hold respondents were using either of these two independent variables taken together influence the improved structures along with biological conservation adoption of improved SWC technology. methods. The survey results showed that 14.7% and 17.6 Another goodness of fit measurement is computing the Hailu 41

ratio of number of correct predictions to total number of education, farmers' training centers, technical and observation for both adopters and non-adopters to find vocational schools should be enhanced. In the future the number of observations that are correctly predicted. during introduction of improved SWC, more focus and The method is based on the principle that if the estimated attention should be given to educated farmers who are probability of the event is less than 0.5, the event will not dynamic towards innovations and serving as a role occur and if it is greater than 0.5 the event will occur. The model to change the community. result shows that the logistic regression model correctly • Creating sufficient awareness to farmers about family predicted about 94.11 percent and 94.23 percent for planning in any development interventions performed adopters and non-adopters, respectively (Table 2). The by government and non-government organization is higher values of the sensitivity and specificity very vital. It would be better to acquaint the improved measurements indicate the better classification of the SWC technologies with other income generating and events using the specified model. food security assuring crops (eg. horticultural crops) The estimated coefficients of the logistic regression especially to household having more family size. model shows that out of the fourteen variables that were Empowering women participation has also a paramount hypothesized to explain factors affecting use of improved importance, since the burden of feeding the family is SWC technologies, nine (64.3%) of the variables were most of the time levied on the women’s shoulder. found to be significant, while the remaining five were not • SWC structures are more likely to be adopted and significant in explaining the variations in the dependent sustainably used if implemented and maintained on variable. From the nine statistically significant farm lands having steep slopes and high erosion independent variables 3 were statistically significant at intensity by giving the priority for it rather than less than 1% probability level and the rest 6 were employing them recklessly on fertile lands having no significant at 5% probability level. More specifically, the slope and erosion problems, because of limitations of coefficients of education level (EDUHD) of the household resources. head, slope gradient of farm land (SLOPGR) and training • Any program and policy aimed at rural development access (TRAINACS) on the improved SWC technologies has to give due attention and priority towards were significant at less than 1% probability level. The increasing the perception levels of farmers through coefficients of family size (FAMSZ), farm size (FARMSZ), organizing and facilitating experience-sharing programs erosion type/severity (EROTP), off-farm income at different levels. This implies the extension programs (OFRMINC), credit access (CRDTACS), and possession should give emphasis on establishing trainings and of livestock were significant at 5% probability level. Of the demonstration sites on SWC structures and the 14 explanatory variables hypothesized to influence benefits to create sharing of new ideas among the willingness of farmers’ to participate in soil conservation farmers by testing the technology at their own locality. practices, 5 variables (age of household head-AGEHD, • Due attention and policy consideration has to be given sex of household head-SEXHD, experience of the at improving off-farm income of farmers that can be household head in farming-FRMEXP, soil fertility status achieved through introduction of better and new of the farm-SOILFERT, and extension service access- technologies that can improve off-farm income, EXTSRV) were less powerful in explaining farmers' provision of timely available credit that help in willingness to adopt the improved soil conservation purchasing inputs and undertake supporting off-farm practices, as their coefficients were non-significant at 1% activities and establishment of infrastructure such as and 5% probability level. The coefficients of the five roads and networks for facilitating markets. variables were not statistically significant at the • Future intervention in SWC would be more attractive as conventional probability levels implying that they were the area of farm land is larger. If there is a necessity to less important in explaining the variability in the employ the conservation work in small farm lands willingness to adopt improved soil conservation practices. having high slopes and erosion problems, the existing The maximum likelihood estimates of the logistic improved SWC technology should harmonize regression model show that family size (FAMSZ), integration with high value and market demanding education level (EDUHD), farm size (FARMSZ), slope crops. This would bring profitable returns for the gradient (SLOPGR), erosion type (EROTP), off-farm farmers for the costs they incur for the construction and income (OFRMINC), training access (TRAINACS), credit maintenance works and increase their enthusiasm (CRDTACS) and livestock were important factors toward continued use of the technologies. influencing use of improved SWC practices by farmers. • Specific technology shouldn’t be enforced to be adopted by all farmers in a specific targeted area. Side by side effort should be made to appreciate and CONCLUSION strengthen the farmers’ area of interest and specialization rather than enforcing them to adopt • Training farmers through strengthening and thetechnology, which ultimately bring failures and establishing both formal and informal type of framers' misuse of funds. Scholarly J. Sci. Res. and Essay 42

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