Welfare and productivity impact of adoption of biofortified cassava by smallholder farmers in Nigeria

Abstract In the bid to improve the productivity, welfare and vitamin-A intake of SSA farmers, Biofortified cassava was bred. This study examined the welfare and productivity impact of adoption of biofortified cassava using a cross-sectional data from smallholder farmers in Nigeria. We used instrumental variable regression to control for endogeneity. The results obtained from the study showed that adoption of biofortified cassava increased farm yield, farmers’ income and welfare outcomes of adopters of biofortified cassava. In addition, the distributional impact of the adoption of the biofortified cassava showed heterogeneity effect based on gender and farm size. Overall, the study suggests that since the largest proportion of the cassava farmers in Nigeria are mostly smallholder farmers, distribution and circulation of biofortified cassava stem cuttings should be targeted towards the smallholder farmers so as to improve their productivity, income and welfare and subsequently reduce their poverty status and ensure food security.

My research interests focus on the interface between environmental, resource base and agricultural production with a keen interest in agricultural technology adoption to enhancing agricultural productivity without compromising on equally important ecological, ethical, social and welfare goals. My research experience span across states and institutions in Nigeria having collaborate with different scholars across institutions in Nigeria. I have worked as a research assistant on assessment of Fadama III program in Nigeria and Biofortification reassessment. My quest is to understand why smallholder farmers has remained on a small scale of production and degree of commercialization over the years. I have also developed keen interest in understanding the reasons why many sub-Saharan African smallholder farmers are reluctant to adopt and invest in improved agricultural technology that will seemingly increase their productivity.

PUBLIC INTEREST STATEMENT
In an effort to increase the consumption of Staple foods fortified with vitamin A such as biofortified cassava; smallholder farmers must adopt and cultivate the technology. However, for agricultural technology to be adopted, it must promise an increased productivity to the farmers. This research investigates the welfare and productivity impact that smallholder farmers accrued by adopting biofortified cassava. Our results indicate that yield, income and welfare status of adopters of biofortified cassava increased significantly due to adoption of biofortified cassava. Our result also suggests that effort to increase the widespread adoption of biofortified cassava among the farmers should be pursued by the stakeholders, government and private agencies in Nigeria.

Introduction
Cassava is an important staple food in Nigeria. Cassava is a starchy crop, which contributes to the staples of millions in sub-Saharan Africa (SSA). According to Otekunrin and Sawicka (2019), about 177,948 million tonnes of cassava were produced in Africa. Nigeria is regarded as the world's largest producer of cassava with a total of about 20.4% of the world export in year 2017 (Otekunrin & Sawicka, 2019). Cassava is an essential component of the diet of about 70 million Nigerians (FAO, 2013). Nigeria, being the largest producer of cassava in the world is producing an average annual estimate of 45 million metric tons which had been translated into a major global market share of about 19% (Phillips et al., 2004).
However, the predominant cassava varieties in Nigeria were found to be deficient of the necessary nutrients as it has been regarded as starchy food. Nutrients such as Vitamin-A was found lacking in the normal white cassava and this has greatly contributed to the issue of malnutrition in Nigeria. Vitamin A deficiency has been posing a threat to human survival for a very long time and the world has put a lot of measures in place to combat this threat. According to Rice et al. (2004), several international organizations in the world such as United States Agency for International Development (USAID), United Nations Children Education Fund (UNICEF), World Health Organization (WHO) among others have been tirelessly working on how to upsurge this menace for a long period of time till present. Many special intervention programs have been implemented in developing countries; Nigeria inclusive. One of such intervention programs is the more recently biofortification-a term used to describe a breeding strategy that aims to increase the micronutrient content of staple food crops (Nestel et al., 2006). Through biofortification, staple food crops that are enriched with beta-carotene, a precursor of vitamin A in the body, have been bred. Bio-fortified cassava is one of these crops. The production of biofortified vitamin-A cassava started in 2011 with the intervention of the International Center for Tropical Agriculture (CIAT) and the International Institute of Tropical Agriculture (IITA) which were funded by Harvest Plus program. (Abdoulaye et al., 2015;Kolapo & Fakokunde, 2020;Kolapo, Olayinka et al., 2020;McNulty & Oparinde, 2015;Oparinde et al., 2016) Five years after the intervention program, statistics revealed that over 1 million of Nigerian farming households grows yellow cassava varieties that contains substantial quantities of vitamin-A even after processing (HarvestPlus, 2016;Kolapo, Ologundudu et al., 2020;Olatade et al., 2016). In Nigeria diets today, yellow bio-fortified cassava represents additional source of vitamin A (Saltzman et al., 2014). The biofortified cassava was produced to improve the nutrients of the consumers, increase the productivity and welfare of the farmers.
Biofortified cassava promised a greater yield and better income to farmers. To increase productivity, improved technology such as biofortified cassava must be adopted in the production process and the rate of adoption of a new technology is subject to its profitability, degree of risk associated with it, capital requirements, agricultural policies and socioeconomic characteristics of farmers (Afolami et al., 2015). The adoption of innovation is the last step in a decision process to make full use of an innovation having considered that such will impact positively on the likelihood of the adopter (Afolami et al., 2015). The significance of this study lies with the fact that increasing the productivity, income and welfare of the farmer through adoption of agricultural technology such as biofortified cassava has been a major cause of concern for the underdeveloped and developing countries including Nigeria for long period of time. According to Afolami et al. (2015) intensification of better agricultural production system is one of the ways of increasing the welfare of farmers and this can be achieved if farmers take advantage of improved crop varieties such as biofortified cassava.
Regardless, there is little empirical evidence on the impact of adoption of biofortified cassava to inform on-going debate on how effectively the adoption of biofortified cassava had increased productivity and welfare of poor smallholder farmers in Nigeria. In this study, we empirically ascertained whether the adoption of biofortified cassava in Nigeria increases productivity and improves welfare outcomes. Biofortified cassava yield and income from biofortified cassava production are used as a proxy for productivity outcomes in this study, while per-capita food, total, and non-food expenditure were used as indicators for welfare outcomes. We focus on productivity and welfare outcomes as they are the most important indicators in measuring the impact of adoption of improved technologies.
This study contributes to the literature on biofortification in the following ways: First, by focusing on one of the countries that first accepted biofortification in SSA, it investigates the enduring question of whether and to what extent adoption of biofortified cassava impacts productivity and welfare outcomes. To date, there is not a single study that evaluated the impact of adoption of biofortified cassava on productivity and welfare of smallholder farmers in Nigeria. In addition, this study is the first to evaluate the impact of adoption of biofortified cassava on welfare of smallholder farmers in Nigeria. Second, in an attempt to provide beyond average treatment effects, we examine the distributional impacts of the adoption of biofortified cassava focusing on two sources of heterogeneity: gender and farm size. In principle, the adoption of biofortified cassava, ceteris paribus, only improves the income of smallholder farmers. However, leakages and imperfect targeting may affect the access to biofortified cassava stem away from the intended smallholder farmers since they formed the majority of farmers in Nigeria. Under such circumstances, the adoption of biofortified cassava becomes beneficial on average by improving the productivity of commercial farmers albeit ineffective in addressing the needs of smallholder farmers. This study, therefore addresses this issue by estimating the overall average impact of the adoption of biofortified cassava as well as its distributional impacts. In estimating the overall average and distributional impacts of the adoption of biofortified cassava, we control for the potential endogeneity of adopting the biofortified cassava using Instrumental Variable (IV) regression approach.

Review of biofortification in Nigeria
Biofortification is defined as "the enhancement of micronutrient levels of staple crops through biological processes such as plant breeding and genetic engineering" (Onyeneke et al., 2019). Biofortification of staple crops represents a major strategy to tackle the problem of micronutrient deficiency and enhance the availability of vitamins and minerals for people whose diet are dominated by less dense nutrient food (Meenakshi et al., 2010). The development of bio-fortified crops will help complement efforts made by the Nigerian government to address vitamin A deficiency by delivering vitamin A through a staple food consumer eat on daily basis thereby meeting up the daily needs of vitamin A for children and women-most vulnerable group. Modified crops possibly may offer food-based interventions if fully adopted and accepted, and could reach the remote populations with micronutrient deficient diets. Cassava was mainly selected as the foremost crop for biofortification by 2011 in Nigeria, as it presented a feasible means for vitamin A delivery partly by reason of its well-known carotenoid content HarvestPlus, 2014).
The adoption pattern of the vitamin A cassava varieties followed through the plan made at its introduction in Nigeria in 2011. With ten (10) LGAs as target points within the four (4) pilot states (Oyo, Imo, Akwa Ibom and Benue) as entry points, the species was easily introduced using promotional and extension services strategies to farmers. Three states (Oyo, Imo, Akwa Ibom) out of the four pilot states where Southern states reflecting the density of the consumption trend of this crop in Nigeria, which also translates to its cultivation pattern due to soil types across Nigeria. Also, some adoption/acceptance studies showed that in comparison Oyo state had highest adoption rate of non-biofortified improved cassava varieties (Ayinde & Adewumi, 2016). However, the adoption pattern was seen to gradually spread first (reaching 6 villages each) among the entry states and by 2015 had translated to other States of Nigeria, covering more than several hectares of farmland cultivation (IIona et al., 2017;Kolapo & Abimbola, 2020). Coverage was also said to have exceeded the expected spread; where also the commercial (private sector) distribution has far exceeded the public sector (HarvestPlus, 2015). Some literature took into account the adoption pattern mostly at the various state levels, however not many. Udensi et al. (2011) assessed the adoption pattern of six improved varieties of cassava in Abia state; the biofortified pro-vitamin A variety (TME 419) among these emerged as one of the highest adopted variety across the state (36.7%), besting the local variety by a large margin. Also, Etuk and Umoh (2014) estimated the adoption levels of the pro-vitamin A biofortified cassava varieties in Akwa Ibom where they reveal a high rate of adoption by farmers within the State. Ayinde and Adewumi (2016) estimated the average adoption rate of pro-vitamin A biofortified cassava varieties to be about 38.72%. However, none of the studies on biofortified cassava in Nigeria has examined the distributional welfare and productivity impact of adoption of biofortified cassava in Nigeria necessitating the need for this research work so as to access whether adoption of biofortified cassava had significantly increased smallholder cassava farmer's yields, income and welfare outcomes.

Data source and econometric techniques
The study was carried out in Nigeria. This study uses a household survey cross sectional data collected by the researcher and well-trained data enumerators in 2019. A multi-stage sampling procedure was used to select sampled areas from each Local Government Areas and households from each selected sampled areas. A list of biofortified cassava farmers who purchased the biofortified stem was accessed from ADPs. Following the NBS recommendation for a nationally representative data collection (National Bureau of Statistics Nigeria (NBSN), 2010), 10% of the LGAs in each of the selected States and 5% of the total sampled areas per LGA were randomly selected. Finally, from the households in each of the selected sampled areas, eight farming households were randomly selected which resulted in a sample size of 3,497 households. The data were collected using well-structured questionnaire which was pre-tested before final enumeration. The survey questionnaire was designed to gather detailed information on socio-economic characteristics of households, input use and allocation, expenditure on food and non-food items, awareness of the biofortified cassava varieties, yield of biofortified cassava and adoption of biofortified cassava. In addition, extensive village-level data were collected on the incidence of shocks, prices of key inputs, among others. In terms of adoption of biofortified cassava, relevant data were collected on the level of awareness about the biofortified cassava as well as on farmers' decision to adopt the biofortified cassava. The data for this study were collected electronically using the "ODK Collect" App.

Econometric techniques
Establishing the impacts of adoption of improved agricultural technologies on various outcome is not an easy task. The improved technologies such as biofortified cassava stems are rarely distributed randomly across communities and among farmers. As such, identifying the causal impacts of adoption of an improved technology requires controlling for selection bias/endogeneity stemming from observable and unobservable factors. In non-experimental data, common approaches for identifying causal impacts include different matching techniques, fixed effects, and instrumental variable (IV) regression. In this study, we employed an inverse probabilityweighted adjusted regression (IPWRA) and IV regression approach due to the cross-sectional nature of data collected. We make use of the IPWRA estimator to achieve some robustness to misspecification of the parametric models (Imbens & Wooldridge, 2009;Robins & Rotnitzky, 1995;Wooldridge, 2010) instead of propensity score matching (PSM) where the estimates produce biased results in the presence of misspecification in the propensity score model (Robins et al., 2007;Wooldridge, 2007Wooldridge, , 2010Wossen et al., 2017).
IPWRA model estimates the outcome and treatment models as follows: Suppose that the outcome model is represented by a linear regression function of the form Yi ¼ αi þ θixi þ εifor {0 1} where Y i is the outcome variable of interest; xi a set of controls; α and θ are the parameter to be estimated; ε is the error term (Wossen et al., 2017). Furthermore, we employ linear regression to estimate ðα0; θ0Þand ðα1; θ1Þusing inverse probability-weighted least squares (Wossen et al., 2017) as follows: The average treatment effect (ATT) is then computed as the difference between Eqns. (1) and (2).
Where (α1) are estimated inverse probability-weighted parameters for households that adopted the biofortified cassava while (α0) are estimated inverse probability-weighted parameters for nonadopters. Finally, N represents the total number of biofortified cassava adopters. Ii is an indicator, which takes a value of 1 if the farmer adopts the biofortified cassava and 0 otherwise.
However, casual identification requires controlling for both observable and unobservable factors that influence adoption of biofortified cassava and productivity and welfare outcomes. Hence, estimates of Eq. (3) may yield biased estimates due to biases stemming from unobservable factors. Therefore, we employed an IV regression approach to control for the potential endogeneity of adoption of biofortified cassava (Wossen et al., 2017). There are several reasons for adoption of biofortified cassava to be endogenous. First, households that are either more or less productive than the average smallholder may choose to adopt the biofortified cassava. Hence, it is likely that adoption of biofortified cassava is correlated with poverty status, household income, or underlying features that influence these outcome variables Ricker-Gilbert et al., 2011, 2013Shively et al., 2012;Wossen et al., 2017). Second, there is a possibility that farmers who adopted the biofortified cassava share common intrinsic characteristics, such as poor/better farming skills and management abilities, which are likely to be related to poverty status and household income. As a result, we employed an IV regression approach. Following the literature, we used the access to land resources as potential instrument for the adoption of biofortified cassava. The land ownership status a farmer has is a measure of access to land resources that could influence farmer's adoption of biofortified cassava (Afolami et al., 2015). We assume that this variable has no direct effect on productivity and welfare outcomes except through its effect on farmers' decisions to adopt biofortified cassava.
Furthermore, the decision to adopt and intensity of adoption of biofortified cassava depends on a number of socioeconomic and institutional factors. Therefore, the decision to adopt and intensity of adoption of biofortified cassava was captured using Cragg's double hurdle regression.

The Cragg's model two-step estimation procedure
The Cragg's model was chosen for this study because it relaxes the restrictive assumption of the Tobit model that the factors influencing the discrete decision (adoption decision) and the continuous decision (intensity of adoption) as well as their effects are the same. Hence, in the Cragg's model, the coefficients of the dependent variables of the first and second hurdles are different. The first step analyses the factors influencing the decision of farmers to adopt bio-fortified cassava varieties, while the second step deals with the intensity of adoption of bio-fortified cassava varieties.
Step 1: Probit model for the discrete adoption decision For the Probit model, we assume that the decision of the 'i'th farmer to adopt a technology or not depends on an unobservable utility index Y i *, that is determined by the explanatory variables, and that the higher the value of this utility index the higher the probability that the farmer will adopt the technology. The adoption probability (dependent variable) Y i is limited between the values of 1 and 0.
The Probit model is expressed as: Where; F X 0 β ð Þ = cumulative degree of freedom of the standard normal distribution.
Where Y i * is the independent variables (1 =adoption,0 =otherwise) and X 0 β are the set of dependent variables, εiis the error term.
Step 2: Model for the continuous decision (intensity of adoption using uncensored observations) Here, the Cragg's model makes use of uncensored observations i.e. the observations with zero adoption level were not cut out of the observation, thus giving a better representation of the population.
Y i * is the dependent variable (intensity of adoption) and X 0 γ are set of independent variables. εiis the error term

Outcome indicators
The outcome indicators are related to productivity and welfare. Our first productivity outcomerelated indicator is biofortified cassava yield. Our second productivity-related indicator is measured by income from biofortified cassava production. Looking into the distribution of income from biofortified cassava production, income received from cassava sales is higher for the adopters of biofortified cassava (Table 2). However, these differences in biofortified cassava yield and income cannot simply be attributed to the adoption of biofortified cassava by looking at the mean differences between adopters and non-adopters. In particular, these mean differences are only indicative of correlations and cannot be used to make causal inferences regarding the impacts of the adoption of biofortified cassava on yields and income without controlling for other confounding factors. Our welfare-related indicators include food expenditure, non-food expenditure, and total expenditure, all measured on per-capita basis. In addition to expenditure indicators, we also used headcount poverty ratio as an additional welfare indicator. Total expenditure is calculated by summing food and non-food expenditure values. A household's food consumption expenditure is comprised of monetary expenditures on purchased food and the imputed values of consumption from own harvest. Looking into the distribution of consumption expenditures, the average per capita total consumption expenditure is about ₦124,119 per year (Table 2). Like productivity indicators, we found significant differences in per capita food, non-food, and total consumption expenditures for adopters and non-adopters of biofortified cassava (Table 2). However, as mentioned above, these differences between adopters and non-adopters cannot be entirely attributed to production of biofortified cassava only. Our final welfare-related outcome indicator measures the proportion of households below the poverty line, commonly referred to as the headcount ratio. Following Foster et al. (1984), per-capita total expenditure is used to determine households' poverty status. Formally, headcount ratio (P 0 ) is calculated as: Where n is the total number of the people in the group, q is the number of poor, Z is the poverty line, Yi is the value of the per capital consumption expenditure of the ith person and α is the poverty aversion parameter. The classification of the poverty status was as follows; (i) Non-poor: These are respondents whose per capital consumption expenditure is above the poverty line. That is, P >2/3 of the mean per capita consumption expenditure per year. (ii) Poor: These are respondents whose per capita consumption expenditure is below the poverty line. That is, P <2/3 of the mean per capita consumption expenditure per year.

Descriptive statistics
In the household survey, detailed information were collected regarding the awareness and adoption of biofortified cassava. More specifically, households were asked if they were aware of biofortified cassava varieties. Second, those who responded in the affirmative were asked if they had adopted the biofortified cassava. According to the survey, about 71.3% of the households were aware of the biofortified cassava and only 52.6% of them adopted the biofortified cassava. Since our main objective is to evaluate the overall impact of adoption of biofortified cassava on productivity and welfare outcomes, we used adoption status of the farmers as our main treatment variable. In particular, adoption status is measured by a dummy variable which takes a value of one if the farmer adopted the biofortified cassava and zero otherwise. In the robustness section, access to biofortified cassava stem was used as our treatment variables. Table 1 presents the descriptive statistics of the key variables of interest based on the adoption status of households.
We included household characteristics such as age, household size, education, membership in different social groups, risk-aversion, drought shocks as well as farm size. In addition, we have included access to extension services as these variable affect awareness and adoption decision of biofortified cassava. We assume that the above key household characteristics affect farmers' ability to adopt biofortified cassava. For instance, we hypothesize that the education level of the farmer affects the likelihood of adoption of biofortified cassava positively. However, for most of our controls, the direction of expected impacts cannot be determined a priori. The variable riskaversion is measured by farmer's willingness to try new agricultural technology such as biofortified cassava. In particular, data were collected on how willing the farmers are to take risks related to new improved biofortified cassava varieties. We consider farmers as risk-averse if they are unwilling to ever try new improved varieties. However, given the proxy nature of our measurement, its effect should be interpreted with caution. In addition to household characteristics, we also included state dummies to control for state-level fixed effects. Finally, the land ownership status serves as an instrument for the adoption of biofortified cassava. Table 1 further presents the difference in means between adopters and non-adopters of biofortified cassava. From Table 1, adopters of biofortified cassava were found to be literate although there is a considerable proportion of non-adopters that were literate also. It was found that there was a significant mean difference in the educational level of the adopters and non-adopters which shows that the adopters were more educated than the non-adopters. This might have influenced their decision in adopting the technology. Table 1 shows that there was a significant mean difference in access to credit by the adopters (71%) and non-adopters (58%). The adopters of biofortified cassava were found to be majorly male (79%) with the non-adopters being 58%. About 26% of the adopters were found to have experienced drought shock which might be attributed to climate change while 18% of the non-adopters had experienced drought shock in the time past. Extension services was very instrumental in the adoption of agricultural technologies as 84% of the adopters had access to extension services while 47% of the non-adopters had access to extension service in the past. This might have contributed to the decision to adopt biofortified cassava among the adopters. Regarding the membership to credit and saving groups, 88% of the adopters were members while 52% of the non-adopters were member. We found a significant mean difference in access to climate condition between the adopters and non-adopters of biofortified cassava as many of the adopters of biofortified cassava had access to climatic information. On average, about 96% of the adopters were willing to try new things while 51% of the non-adopters were willing. About 82% of the adopters of biofortified cassava had access to land resources while 67% of the non-adopters had access to land. From Table 2, a mean significant difference was found in the yield of biofortified cassava among the adopters (4,013 ton/ha) and non-adopters (3,418 ton/ha). This shows that on average, adopters of biofortified cassava has a mean yield more than the non-adopters. We also found that there is a significant mean difference in the income of the adopters (₦153,582) and non-adopters (₦98,158). On average, a mean significant difference was found between the total, food and nonfood expenditure of the adopters and non-adopters of biofortified cassava.   Robust standard error in bracket, ***,** Significant at 1 and 5%, respectively. Kolapo & Kolapo, Cogent Food & Agriculture (2021)

Matching impact estimator on outcome indicators
The result of the IPWRA estimation on various outcome indicators including biofortified cassava yield; income from biofortified cassava production; per-capita total expenditure; per-capita food expenditure and poverty headcount ratio are presented in Table 3. We find a positive and statistically significant impact of adoption of biofortified cassava on all productivity and welfare outcome indicators. The results presented in Table 3 show that adoption of biofortified cassava increased yields and income by 47 and 54%, respectively. Regarding welfare outcomes, we found positive and statistically significant impacts on consumption and a negative and statistically significant impact on poverty headcount ratio. In essence, the probability of being poor declined by 19% due to the adoption of biofortified cassava. Although, these results need to be interpreted with caution and in fact they may be biased since we did not control for unobserved heterogeneity.

Residual diagnostics tests
The test of residual diagnostics was carried out and presented in Table 4 to ensure appropriateness of our data set. An insignificant coefficient of the squared adoption variable informs us that the relationship between productivity and adoption is approximately linear. In other to test for normality in our model residual, we conducted a Shapiro-Wilk normality test. The estimate of the Shapiro- Wilk normality test obtained is not significant which indicates a normal distribution within our data set. We also tested for non-constant variance (heteroscedasticity) in our model. A non-significant estimate of the result of non-constant variance test shows that we do not encounter heteroscedasticity problem in the model.

Determinants of adoption and intensity of adoption of biofortified cassava (probit and truncated regression)
We used the probit model (first hurdle) to examine the determinants of adoption of biofortified cassava while truncated regression (second hurdle) was used to examine the intensity of adoption of biofortified cassava as stated in the methodology section. Results of the probit model indicate that the included IV (access to land resources) affects the probability of adopting biofortified cassava (Table  5). This implies that the selection bias has been remedied by the IV. Examining the determinants of adoption of biofortified cassava, we found that farmer characteristics such as education, years of experience, gender of the household head, farm size membership to cooperatives, membership to credit and savings group, access to extension services, risk aversion, access to land resources and access to training all influenced positively, the probability of adopting the biofortified cassava. Marginal effects were computed to ascertain thepercentage change that might contribute to the probability of adoption of biofortified cassava. This result is consistent with the findings of Oparinde et al. (2016). In addition, the likelihood estimates of the probit regression indicated that the Chi-square statistics of 43.29185 was highly significant (p < 0.0001) which suggested that the model has a strong explanatory power. Regarding the intensity of adoption (truncated regression) of biofortified cassava presented in Sigma 0.129*** 0.020 6.21 *** = significant at 1%, ** = significant at 5%, * = significant at 10%.
Kolapo & Kolapo, Cogent Food & Agriculture (2021), 7: 1886662 https://doi.org/10.1080/23311932.2021.1886662 Table 6, we found that farmers' characteristics such as education, household size, marital status, years of experience, farm size, access to off-farm income, drought shock, membership to cooperatives, membership to credit and savings group, access to extension services, access to climate information, access to land resources and access to training positively influenced the intensity of adoption of biofortified cassava among the farmers. *** = significant at 1%, ** = significant at 5%, * = significant at 10%. State level fixed effects included

Impact of adoption of biofortified cassava on farm yields and income
The result of the impact of adoption of biofortified cassava on the yields and income of farmers is presented in Tables 7 and Tables 8, respectively. The parameter estimates of "No control" present a parsimonious specification for biofortified cassava yield and income that includes only the *** = significant at 1%, ** = significant at 5%, * = significant at 10%. State level fixed effects included. Per-capita total expenditure are measured in per capita. treatment variable along with state-level fixed effects as indicated in Tables 7 and Tables 8,  respectively. The parameter estimates of "With control", present results where standard controls for biofortified cassava yield and income are included. The parameter estimates of "With IV" present the results of the IV specification where the adoption of biofortified cassava is treated as endogenous. Furthermore, we specify a log-linear functional form for biofortified cassava yield and income from biofortified cassava production is estimated at levels. From Table 7, the results obtained show that adoption of biofortified cassava has a positive and statistically significant impact on farmers' yields and income. Examining the parsimonious model specification for yield, it was found that the impact of adoption of biofortified cassava is similar considering the direction and magnitude of the estimated impacts. In particular, farmers who adopted biofortified cassava increased their farm yields by 31.1% when only state-level fixed effects were controlled, 29.7% when standard controls with state-level fixed effects is included and by 28.5% when potential endogeneity of adoption of biofortified cassava was controlled. In addition, the estimated results presented in Table 8 suggest an increase in income of famers by ₦2.16 to ₦2.21. It should be noted that the values for biofortified cassava income are expressed in ₦12,500. The impact size ₦2.16 implies that adoption of biofortified cassava increases income of the farmers from the production of biofortified cassava by ₦27,000. The results presented in Table 7 show that farm yield has increased by 28.5% due to adoption of biofortified cassava varieties. Similarly, farmers' (adopters) income has increased by ₦22,812. These results obtained implies that the adoption of biofortified cassava has enabled small holder farmers to improve their productivity and income. Furthermore, interaction terms to test if adoption of biofortified cassava has heterogeneous impacts are included in Tables 7 and Tables 8. We introduced an interaction term between adoption of biofortified cassava and the gender of the household head as well as between adoption of biofortified cassava and farm size. A dummy variable was created which was referred to as "land category" and this takes on a value of 1 if a household owns less than 1 ha of farmland and 0 otherwise. The result shows that the interaction term between adoption of biofortified cassava and the gender of the household head is significant for both farmers' yield and income. This result implies that adoption of biofortified cassava benefits the male-headed households more than the female-headed households because more of the male-headed households adopted the biofortified cassava varieties. Similarly, the interaction term between adoption of biofortified cassava and land category is also significant.

Impact of adoption of biofortified cassava on welfare outcome indicators
The results of the welfare impacts of adoption of biofortified cassava are presented in Tables  9 and Tables 10. As indicated in the methodology section, per-capita total expenditure, food expenditure and poverty headcount ratio were used as indicator for welfare. In this analysis, food expenditure and total expenditure were measured on per capita basis which was estimated using a log-linear functional form. The results of the per-capita total expenditure and per-capita food expenditure are reported in Tables 9 and Tables 10, respectively. Just as previous section, parsimonious specifications was done in which we estimated impacts without controls, with controls, and with IV. For this section, discussion is based on the computed IV results presented in Tables 9 and Tables 10. The result shows that adoption of biofortified cassava has a positive and significant impact on per-capita total expenditure and per-capita food expenditure, respectively. The direction of the estimated effect size shows a large improvement in the welfare outcomes of the farmers as a result of adoption of biofortified cassava. From Table 9, per-capita total expenditure increased by 39.1%. In addition, percapita food expenditure increased by 29.7%. These results are in agreement with previous studies on adoption impacts of improved technology in Nigeria. For instance, Afolami et al. (2015) found that adopters of improved cassava technology have a better welfare status than non-adopters as it was found that adoption of improved cassava technology increased per capita consumption expenditure per annum and annual household income and subsequently contributed to overall poverty reduction among the adopters of the improved cassava technology. Like the previous specification, interaction term between the adoption of biofortified cassava and gender and farm size was included. We found a significant impact for both percapita total expenditure and food expenditure. The third welfare indicator, that is, headcount poverty ratio, is a binary variable. However, the estimates for biofortified cassava will only represent changes in the probability of poverty instead of actual poverty reduction rates. Estimating the impact of adoption of biofortified cassava on poverty reduction instead of changes in the probability of poverty reduction will require examining the distribution of observed poverty of adopters of biofortified cassava and the distribution of the counterfactual poverty of adopters of biofortified cassava had they not adopted biofortified cassava. In essence, we are to examine the poverty reduction impacts of the 39.1% per-capita total expenditure reported in Table 9 and also ascertain whether such changes are sufficient to lift the poor smallholder farmers above the poverty line. In doing so, we then, calculated changes in the headcount poverty ratio of the adopters of biofortified cassava as a result of the 39.1% increase in per-capita consumption expenditure. From the computed result, headcount poverty ratio has decreased by 21.3% points as a result of adoption of biofortified cassava.

Conclusions
Improving the welfare and productivity of smallholder farmers through the adoption of improved agricultural technology is of paramount priority in Nigeria to lift these farmers from poverty and ensure that they are food secured. However, adoption of such technology such as biofortified cassava is low in SSA and in particular in Nigeria. With the intents of improving the productivity and welfare of farmers, biofortified staple food crops including biofortified cassava was bred. Using a household-level data from smallholder farmers in Nigeria, the study examined the welfare and productivity impact of adoption of biofortified cassava in Nigeria. The study examined to what extent, adoption of biofortified cassava had improved the farm yield and farmers' and also their welfare outcomes. Instrumental variable regression was in the study to control for endogeneity of adoption of biofortified cassava. The empirical findings of the study include the fact that smallholder farmers who adopted the biofortified cassava increased their farm yield by 28.5%. Also, farmers' income increased by ₦22,812 as a result of adoption of biofortified cassava. These results prove that adoption of biofortified cassava enabled the farmers to improve their income and productivity which justify the reasons why more farmers should adopt the different varieties of biofortified cassava. Regarding the welfare outcomes, the results of the study showed a positive and significant impact on per-capita total and food consumption expenditure with the size of the impact suggesting an improvement in welfare as a result of adoption of biofortified cassava.
In particular, adoption of biofortified cassava increased the per-capita total expenditure of the smallholder farmers by 39.1% and subsequently decease poverty head count ratio by 21.3% points. This further established the fact that adoption of biofortified cassava among the smallholder farmers has improved the welfare of the farmers thereby declining their poverty status. In addition, the impact of the interaction term between adoption of biofortified cassava and gender as well as farm size is statistically significant indicating the presence of heterogeneity impact based on gender and farm size. This implies that adoption of biofortified cassava had benefitted more the male gender. Moreover, in estimating the impacts on welfare, we did not consider the possibility of the farmers cultivating other crops along with biofortified cassava which might lead to crowding-out effect. Therefore, examining the crowding-out effect of the adoption of biofortified cassava for future research will be necessary. In addition, in order to ensure equal benefits among the two genders, the female-headed household should be massively mobilized to adopt the biofortified cassava so as to improve their productivity, income and welfare outcomes. Also, more high yielding varieties of biofortified cassava should be bred and circulated by the government and private agencies so that cassava farmers can further increase their productivity and income. An increased level of awareness about the nutritional content of consuming the biofortified cassava products should be spontaneously considered by the government and private agencies especially among the consumers so that the production of biofortified cassava can increase thereby subsequently increasing the income and welfare of the smallholder farmers in Nigeria.