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Since 2014, the Agricultural Sector Support Program (PASA) has been assisting smallholder farmers in Togo with the adoption of Improved Traditional Poultry Farming Technique (ITPFT) in rural areas in order to create wealth and reduce poverty. This paper focuses on comparing the socioeconomic characteristics of beneficiaries and non-beneficiaries of government subsidies (PASA). Both random and purposive sampling techniques were used to select 400 farmers. The sample included 86 farmers who were program beneficiaries and 314 farmers who were not. A structured questionnaire was used to collect data. Results of analysis indicated that there is a significant difference in socioeconomic variables such as self-financing capacity, level of education, membership in cooperative societies, household size, farm size, and annual sale of poultry between program beneficiaries and non-beneficiaries prior to program implementation. Descriptive statistics show that five years after the program's implementation, annual poultry sales per farmer ranged from 0 to 1700 birds for beneficiaries and from 9 to 200 birds for non-beneficiaries. The turnover per farmer ranged from US $ 0 to US $ 42409 and from US$ 33 to US $ 996 for beneficiaries and non-beneficiaries, respectively. The profit per farmer ranged from US $ 0 to US $ 25446 for beneficiaries and from US $ 26 to US $ 797 for non-beneficiaries. The magnitude of the standard deviations of the potential outcome variables among beneficiaries and non-beneficiaries suggests that adoption rates of ITPFT may vary from one farmer to another. As a result, compared to non-beneficiaries, beneficiaries experienced a greater increase in potential outcomes five years after the program's implementation. Failure to comply with improved production technique on certain farms, despite receiving subsidies, is a factor that could negatively impact the effective, efficient, and optimal achievement of the program’s expected results. Further research will concentrate on determining the added value of this program through the use of appropriate and thorough econometric adoption and impact assessment methods.

Most applications of input-output (I-O) analysis to date have been to highlight inter-industry flows and to estimate the main aggregate national accounts, such as GDP, gross output and final demand categories. However, multiplier coefficients relating to output and income multipliers have hardly been explored especially in the Nigerian context. Sectors like agriculture, fishing, food & beverages as well as mining/quarrying have particularly significant roles and their economic impacts can be quantified using Nigeria's I-O table. The study adopted a longitudinal design and utilized the 2015 I-O table comprising of twenty-six (26) sectors obtained from Eurostat database. This table was used to compile an inter-industry transaction table and Leontief matrix, which was then used to derive industry-wise Type I and Type II multipliers for the aforementioned sectors. Type I multiplier takes into account the direct and indirect effects while the Type II multiplier captured the induced effects in addition to the direct and indirect effects. Mining/quarrying as a single sector had a Type I multiplier of 1.80 and 2.17 for both output and income respectively and a Type II multiplier of 2.41 and 3.12 for both output and income respectively. Similarly, the fishing sectors were identified to have the highest contributions (2.11 and 2.89 as well as 2.22 and 3.19) in both Types I and II multipliers for both output and income respectively when compared with other sectors.

This study provided empirical information on determinants of climate change adaptation among farming households in Southwest Nigeria using Heckman's double stage selection approach. Three states were randomly selected across southwest Nigeria: Ekiti, Ogun and Oyo States. Data were collected in two phases. The first phase was rapid rural appraisal of the selected states while the second phase was detailed survey using a structured questionnaire administered to 360 randomly sampled farm units. Data collected were analysed using descriptive statistics and Heckman's double stage selection model. The result of the analysis showed that there was relatively high level of awareness of climate change among the farmers. Major sources of information about climate change among the farmers include personal observation and extension agents. From the result of the Heckman double stage selection model, variables that significantly influenced the first decision of whether or not to adapt to climate change include: gender, experience, extension visits, farm size, income, credit access, number of farm labourers and dependency ratio. On the other hand, variables that significantly influenced extent of adaptation to climate change include: gender, experience, education, extension visits, farm size, income, credit access, number of farm labourers and dependency ratio. Based on the findings, the study therefore recommends farmers' sensitization programmes on indicators of climate most especially those indicators with low indices. Effort should be made by government at all levels towards capacity building of the farmers through improved education, extension visits, increased farm size, increase in income and improved access to credit.

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