Collected farm level data will be edited, summarized, tabulated and analyzed to fulfill the objectives of the study. In most cases, tabular method of analysis supported with appropriate statistical parameters will be used to present the results of the study. The adoptions of improved technologies will be measured through three ways: variety adoption, acreage covered, and use of crop management technology (i.e. agronomic practices, time of operation, input use). For assessing the adoption of crop management technology, respondent farmers will be grouped into three categories such as high adopter, medium adopter, and low adopter based on the mean index of the farmer with respect to each technology. A higher index will indicate a higher level of adoption, while a lower index will indicate a lower level of adoption of a technology. Adoption level will be categorized for mean index >100 as over use; (70-100) as high, (50-69) as medium, and <50 as low. Pearson’s Correlation Coefficient will be used to estimate the degree of relationship between the adoption and different socioeconomic factors of the adopters. On the other hand, Probit/Logit model will be used for analyzing farmer’s adoption and for identifying factors influencing the adoption of improved technologies. The theoretical and empirical Probit/Logit model is discussed below. Theoretical probit model: Qualitative Response Models (i.e. Probit or Logit model) will be used extensively by agricultural production and farming systems economists for studying and analyzing farmer adoption and diffusion of agricultural interventions. Probit/Logit model is based on a cumulative normal distribution function which is symmetric around zero with variance equal to 1. The following Probit model will be used to identify the factors responsible for the adoption of improved technologies of the selected crops. Log P = α + βiXi (1) Where, P = Adoption (1 for adoption, 0 for non-adoption), Xi = Explanatory variables (i = 1, 2, 3.........n); α = Constant term; and βi = Coefficients (i = 1, 2, 3.........n). Relative change in P with a constant increase in Xi can be measured by the above model. When P approaches 1, a relative change in P can be obtained with a constant increase in Xi by equation (2); here 1-P is used. Log (1-P) = α + βiXi (2) When Equations (1) and (2) are combined, we get Equation (3) that can be transformed into Equation (4). Log P-Log (1-P) = α + βiXi (3) Log {P/(1-P)} = α + βiXi (4) The ratio of P/(1-P) is called the odd ratio and log {P/(1-P)} is called the log odds or Logit/Probit. Equation (4) can be rearranged and solved for P; P = [1/(1 + e- (α + βiXi) )] (5) The probability function used in Equation (5) is called the logistic distribution function and ensures that the predicted value (P) of the relative frequency of the independent variable is always between 0 and 1. The Equation (5) will be used to analyze the determinants of farmer adoption of an intervention. Equation (5) is expanded to use more variables as depicted in Equation (6). P = [1/(1 + e- (α + β1X1 + β2X2 + ..…... + βnXn )] (6) Empirical probit model: In order to ascertain the relationship between the adoption of improved technology and socio-economic factors, the following empirical Probit model (equation 7) will be carried out. The dependent variable of this model will be adoption of improved varieties. Since the dependent variable is dichotomous, OLS cannot be used. The model will be as follows- Ai = α + βiXi + ……..+ Ui ........................................................ (7) Where, Ai = Farmers adopting improved pulse variety If, Yes = 1; Otherwise = 0 α = Intercept Xi = Explanatory variables (Socio-economic characteristics) Ui = Error term The adoption of improved technology is likely to be influenced by different explanatory variables given below; X1 = Topography (Medium high = 1, Otherwise = 0) X2 = Soil type (Sandy loam =1, Otherwise = 0) X3 = Age/experience of the respondent (year) X4 = Education (Year of schooling) X5 = Training received on agriculture (No./lifetime) X6 = Farm size (in ha) X7 = Organizational participation (Score) X8 = Cosmopolites of the farmer (Score) X9 = Involvement in innovative activities (Score) X10 = Extension contact (Score) X11 = Influence of family members (Score) X12 = Influence of neighbouring farmers (Score) X13 = Influence of DAE personnel (Score) X14 = Net profit (Tk/ha) Xn = Other influencing variables Comparative profitability analysis: The comparative profitability of improved pulses over their traditional varieties will be calculated using simple accounting procedures. Hence, data relating to input use for the production of selected improved and traditional crops and their market prices will be collected. On the other hand, data on outputs and their prices will also be gathered for the study. Finally, the costs and returns of selected crop cultivation will be compared. Measurement of comparative advantage: Domestic resource cost (DRC) will be estimated for evaluating the efficiency of production of pulses in relation to comparative advantage. DRC is the ratio of cost of domestic resources and non-traded inputs (valued at their shadow prices) of producing a commodity to the net foreign exchange earned or saved by producing the good domestically. Mathematically DRC is defined as (equation 8): ............................................................ (8) (j = 1-------------m; k = 1-----------n) Where, = Quantity of domestic resources and non-traded inputs used for producing i crop per metric ton = Price of domestic resources and non-traded inputs (Tk/mt) = Border price of i crop (Tk/mt = Quantity of tradable inputs for producing i crop per metric ton = Border price of tradable inputs k per metric ton. If DRC1, the economy will save foreign exchange by producing the i crop domestically either for export or for imports substitution. This is because the opportunity cost of domestic resources and non-traded inputs used in producing i crop is less than the foreign exchange earned or saved. In contrast, if DRC1, domestic costs will be in excess of foreign costs or savings indicating that the i crop should not be produced domestically and should be imported instead. 19. Benefit-cost and Ex-ante Analysis (if applicable) The ex-post evaluation with the help of economic surplus model will be adopted in this study to estimate the benefit-cost ratio, IRR and NPV of investment on research and development of selected technologies in Bangladesh. The analysis will be done under closed economy situation. The theoretical discussion of economic surplus model is given below. Theoretical framework of the model: The concept of economic surplus has been used to measure economic welfare and the changes in economic welfare from policy and other interventions (Alston et al., 1995 and Currie et al., 1971). The social benefits to the research and extension of improved technology in Bangladesh are measured in terms of producers’ and consumers’ surpluses resulting from a shift in the supply curve, caused by an increase in productivity. This outward shift in the supply function results from an upward shift in the aggregate production function resulting from the adoption of improved technologies. This relation is shown in Figure-1 in which D1 and So represent the actual market demand and pre-research supply curve, whereas Sn represents the post-research supply curve that would have existed due to the adoption of improved technology. Assuming market equilibrium and closed-economy commodity market, the shift in the supply curve from So to Sn would increase consumers’ surplus by Area ABC+Area PoBAPn, the producers’ surplus by Area AOC-Area PoBAPn, and the total social benefit or economic surplus by Area ABC + Area AOC (Fig 1). The shift in the supply curve has decreased the price that made consumers better off. The change in consumers’ surplus (benefits) can be measured as a monetary value. Besides, area AOC represents the benefits to the farmers from adopting improved technology and can also be measured and quantified in monetary terms. Farmers will be benefited from the adoption of improved technology intervention if Area AOC is greater than Area PoBAPn. In the present case, the Area AOC is less than the Area PoBAPn. The size of the two areas depends on the elasticities of the supply and demand curves and the size of the supply curve shift. The total social benefit from the adoption of improved technology is the summation of the change in consumers’ surplus plus the change in producers’ surplus for adopting the technology. Figure 1. Closed-economy Economic Surplus Model Quantity (Q) Distribution of Economic Benefits: Change in consumer surplus/benefit = Area ABC + Area PoBAPn Change in Producer surplus/benefit = Area AOC - Area PoBAPn Change in total economic surplus/benefit = Area ABC + Area AOC Empirical economic surplus model: The Akino and Hayami (1975) approximation formula for calculating changes to producer and consumer economic surplus will be used in the proposed study. The approximation formula for calculating the change in economic surplus for a closed-economy situation (Fig 1) is as follows: Area ABC = ((½ PnQn) ((k ( ))2 /( ))) ------------------------------------------------------- (9) Area AOC = (kPnQn) ------------------------------------------------------------------------------------- (10) Area PoBAPn = ((PnQnk( ))/( ))x((1- (½ k (( ) ))/( )) - (½ k ( ))) ---- (11) Where, Po = Output price that would exist in absence of research
Qo = Quantity of output (ton) produced that would exist in absence of research Pn = Actual output price (existing market price) Qn = Actual quantity of output (existing production) k = Horizontal supply shifter = Price elasticity of output supply = Absolute price elasticity of the demand for the output. (For a closed-economy model, the estimated is used in the above formulas. For a small open-economy model where the is perfectly elastic, use a sufficiently large number for .) Supply shifter (k) estimation: The overall yield advantage of improved technology over the traditional varieties weighted by the proportion of the total production saved due to improved technology adoption is called the supply shifter (k). In estimating yield advantage, the yield of selected crops (both improved and traditional variety) will be collected through HH survey. The supply shifter k is calculated as follows: Where, Yit = Yield of improved variety in year t Yt = Yield of traditional variety in year t Ait = Proportion of the total production saved due to improved variety adoption in year t n = Number of farms (Sample respondent). Rate of return calculation: The IRR is calculated relating the total social benefit (TSB) minus an input cost change, if any, in each year to the research expenditure (C) in each year and is the discount rate that results in a zero net present value of the benefits. The IRR will be calculated as: 20. Environmental impact, social safeguard and gender matter (One para statement on each of these issues. If negative impacts, add mitigation plan. Environmental matrix to be filled and attached, check the website of BARC) The quality of soil is deteriorating day by day due to repeated crop cultivation, practicing injudicious cropping patterns, use of excessive chemical fertilizers & pesticides, and unable to keep land fallow for a certain period. All these activities are appeared to be threatening to the environment and whole agricultural system. For various reasons, to increase agricultural land is quite impossible in the country. In this tricky situation, introducing pulses in the existing cropping patterns is the only means of rejuvenation of soil as well as environment. If the expected impacts of pulses research and extension are positive and significant for the nation, the investment decision will be extended for more years in the new areas of the country. Thus, the project activity will be appeared to be beneficial to the environment as well as whole agriculture system. The successful adoption of improved pulses technologies so far developed by the BARI and other concerned institutes will obviously improve crop productivity as well as household income of the farmers. Increased production and income will also improve farmers’ livelihood pattern. Furthermore, due to adoption of improved technologies of the selected crops will reduce the imports of pulses and edible and save costly foreign exchange for the country. Attaining self-sufficiency in pulses and edible oils through local production will obviously be safeguard for the country. The unused and under-used family member, especially women and children can easily be utilized through adoption of improved varieties of the selected crops, especially pulse technologies (i.e., mungbean). The higher production of these crops and its backward and forward linkages will generate more jobs for the women in the rural economy of the Bangladesh.