title: Essays on climate-smart agriculture (CSA) technologies, youth involvement in agricultural activities, and agricultural finance

authors: Magembe, Yohane Kitwima

subjects: agricultural finance

abstract: The thesis presents four essays addressing key issues in smallholder agriculture in Tanzania,
such as CSA technologies, youth involvement in farming, and agricultural finance. The thesis
examines the effects of climate-smart agriculture (CSA) adoption on crop productivity and
income. The thesis addresses the impact of climate change to enhance farm performance and
improve farmers’ resilience. Also, the thesis analyzes youth engagement in agriculture. Under
this theme, the thesis seeks to understand how we can attract and keep youths in the agricultural
sector as a response to alarming youth unemployment. Further, the thesis examines agricultural
finance constraints and their impacts on farm performance. Access to agricultural finance by
farmers is ideal for poor farm resource farmers to improve farm input usage and resilience.
Chapter 1 consists of the introductory part.                                                                                                                                                                                                                                                                                                            Chapter 2 investigates the impacts of CSA on crop
productivity and income using nationally representative data that sampled 1862 smallholder
household farmers who cultivate less than 2 hectares. The chapter reports that smallholder
farmers who practice CSA augment crop productivity per acre and income more than nonadopters.
Interestingly, non-adopters, had they adopted, would have remarkably gained in both.
The results survived robust checks and remained consistent. We used the endogenous switching
regression (ESR) model, instrument variables, and other control variables to address the
endogeneity and selection bias issues. The propensity score matching (PSM) is adopted for
comparison and for a consistency check of the results. At least the results are consistent in both
models. The implication of the findings is that plausible programs, promotions, campaigns, or
policy support initiatives for scaling up CSA adoption have a significant contribution to food
security and poverty reduction through increased crop productivity and income augmentation.
Chapter 3 contains two research papers. The first paper investigates youth involvement in
agricultural activities, using a sample of 6419 Tanzanian youths aged 15-35 years old. The paper
highlights the critical problems and challenges faced by youth in the agricultural sector. Further,
the paper elucidates the crucial drivers of youth’s full involvement in agriculture. The
statistically significant drivers include access to and usage of farm machines (e.g., tractors),
irrigation facilities, land ownership, presence of agro-product processing, profits, access to
agricultural credit, youth membership in the farmers’ cooperatives and organizations, access to
and use of extension services, use of information source channels to access agricultural
information, and distance to the nearest market. At the same time, off-farm income, general
education, and age reduce the propensity of youth’s involvement in agriculture. A series of
robust checks were performed to ensure that the assumptions of the ordered logit model are met
to ensure unbiased and consistent results. The second paper examines the impact of youths’
intensive participation in agriculture on farm performance. We used nationally representative
cross-sectional data of 3399 small youth farmers in Tanzania. We employed a doubly robust
IPWRA estimator, and we compared these empirical results with the results from ESR and PSM
models. The results remain statistically and quantitatively consistent in all models: that youth
intensive involvement in agriculture significantly impacts maize yields, net returns, and returns
on investment (ROI). Overall, both papers propose policy actions, academic interventions, and
parental interventions to promote and retain many youths in agriculture.
Finally, chapter 4 contains one paper that used a sample of 1042 smallholder farmers. The paper
examines the significant obstacles to agricultural financing that both the demand and supply
sides of agricultural credit encounter. Further, the paper demonstrates the impact of agricultural
finance on farm performance for credit-constrained smallholder farmers. We applied the ESR
model to address the endogeneity problem and selection bias. Furthermore, PSM was used to
compare the results of the ESR model. The results in both models are consistent that credit
access augments smallholder farmers’ crop productivity. Interestingly, farmers without credit
counterfactual would increase their crop production if they were assumed to be credit
unconstrained. The findings carry important policy implications in favour of smallholder
farmers’ credit access.

text: Essays on climate-smart agriculture (CSA) technologies, youth involvement in agricultural activities, and agricultural finance The thesis presents four essays addressing key issues in smallholder agriculture in Tanzania,
such as CSA technologies, youth involvement in farming, and agricultural finance. The thesis
examines the effects of climate-smart agriculture (CSA) adoption on crop productivity and
income. The thesis addresses the impact of climate change to enhance farm performance and
improve farmers’ resilience. Also, the thesis analyzes youth engagement in agriculture. Under
this theme, the thesis seeks to understand how we can attract and keep youths in the agricultural
sector as a response to alarming youth unemployment. Further, the thesis examines agricultural
finance constraints and their impacts on farm performance. Access to agricultural finance by
farmers is ideal for poor farm resource farmers to improve farm input usage and resilience.
Chapter 1 consists of the introductory part.                                                                                                                                                                                                                                                                                                            Chapter 2 investigates the impacts of CSA on crop
productivity and income using nationally representative data that sampled 1862 smallholder
household farmers who cultivate less than 2 hectares. The chapter reports that smallholder
farmers who practice CSA augment crop productivity per acre and income more than nonadopters.
Interestingly, non-adopters, had they adopted, would have remarkably gained in both.
The results survived robust checks and remained consistent. We used the endogenous switching
regression (ESR) model, instrument variables, and other control variables to address the
endogeneity and selection bias issues. The propensity score matching (PSM) is adopted for
comparison and for a consistency check of the results. At least the results are consistent in both
models. The implication of the findings is that plausible programs, promotions, campaigns, or
policy support initiatives for scaling up CSA adoption have a significant contribution to food
security and poverty reduction through increased crop productivity and income augmentation.
Chapter 3 contains two research papers. The first paper investigates youth involvement in
agricultural activities, using a sample of 6419 Tanzanian youths aged 15-35 years old. The paper
highlights the critical problems and challenges faced by youth in the agricultural sector. Further,
the paper elucidates the crucial drivers of youth’s full involvement in agriculture. The
statistically significant drivers include access to and usage of farm machines (e.g., tractors),
irrigation facilities, land ownership, presence of agro-product processing, profits, access to
agricultural credit, youth membership in the farmers’ cooperatives and organizations, access to
and use of extension services, use of information source channels to access agricultural
information, and distance to the nearest market. At the same time, off-farm income, general
education, and age reduce the propensity of youth’s involvement in agriculture. A series of
robust checks were performed to ensure that the assumptions of the ordered logit model are met
to ensure unbiased and consistent results. The second paper examines the impact of youths’
intensive participation in agriculture on farm performance. We used nationally representative
cross-sectional data of 3399 small youth farmers in Tanzania. We employed a doubly robust
IPWRA estimator, and we compared these empirical results with the results from ESR and PSM
models. The results remain statistically and quantitatively consistent in all models: that youth
intensive involvement in agriculture significantly impacts maize yields, net returns, and returns
on investment (ROI). Overall, both papers propose policy actions, academic interventions, and
parental interventions to promote and retain many youths in agriculture.
Finally, chapter 4 contains one paper that used a sample of 1042 smallholder farmers. The paper
examines the significant obstacles to agricultural financing that both the demand and supply
sides of agricultural credit encounter. Further, the paper demonstrates the impact of agricultural
finance on farm performance for credit-constrained smallholder farmers. We applied the ESR
model to address the endogeneity problem and selection bias. Furthermore, PSM was used to
compare the results of the ESR model. The results in both models are consistent that credit
access augments smallholder farmers’ crop productivity. Interestingly, farmers without credit
counterfactual would increase their crop production if they were assumed to be credit
unconstrained. The findings carry important policy implications in favour of smallholder
farmers’ credit access.

year: 2024

title: Components of regional population growth, 1986-2001

authors: Pool, Ian

subjects: population growth

abstract: The vitality of a region is frequently assessed by looking at its population growth pattern. This is seen as being linked to its economic and social vibrancy. To better understand the dynamics of this growth pattern it is necessary to decompose population growth into the contributions of natural increase (births less deaths) and migration (both domestic and international). This provides a demographic accounting of the factors of population change which we use to analyse the degree to which the levels and impacts of these factors differ between the Regional Council Areas of New Zealand. We find large variations between Regional Council Areas in overall population growth for the three quinquennia between 1986 and 2001. The Auckland region experienced the largest growth, coming both from high natural increase and international migration, while the “sunbelt” regions of Bay of Plenty, Nelson-Tasman and Marlborough had high growth, but driven by internal migration. In other regions, such as Gisborne, West Coast and Southland population growth declined.

text: Components of regional population growth, 1986-2001 The vitality of a region is frequently assessed by looking at its population growth pattern. This is seen as being linked to its economic and social vibrancy. To better understand the dynamics of this growth pattern it is necessary to decompose population growth into the contributions of natural increase (births less deaths) and migration (both domestic and international). This provides a demographic accounting of the factors of population change which we use to analyse the degree to which the levels and impacts of these factors differ between the Regional Council Areas of New Zealand. We find large variations between Regional Council Areas in overall population growth for the three quinquennia between 1986 and 2001. The Auckland region experienced the largest growth, coming both from high natural increase and international migration, while the “sunbelt” regions of Bay of Plenty, Nelson-Tasman and Marlborough had high growth, but driven by internal migration. In other regions, such as Gisborne, West Coast and Southland population growth declined.

year: 2004-05

title: Te kākahu whakataratara o Ngāi Tūhoe: Ko te reo ōkawa, ko te reo o te marae

authors: McFarland, Agnes

subjects: Reo Māori

abstract: Ko te reo ōkawa ara ko te reo o te marae, he reo hōhonu. Ka mutu, he tapu katoa ōna āhuatanga katoa. E rua ngā kōrero whakatau o runga i te marae. Ko te karanga me te whaikōrero. Kai roto i wēneki reo e rua, ka ahu mai te kupu nei te poroporoaki. Ka āta tirohia te poroporoaki i roto i ngā whakaaro e pā ana ki ngā tikanga o te karanga. Whai muri ka titiro ki te wāhanga o te poroporoaki i roto i te whaikōrero. Mā wēneki tikanga e rua, ka whakaputaina ngā whakaaro me te hōhonutanga o te mamae o te ngākau pōuri ka ea hoki te mamae. Ka tiro ake tātau ki ngā take i whakaputaina, ngā tohutohu ā rātau mā me ngā rongo o te wairua o te kupu kōrero. Tae atu hoki ki te tohungatanga ki te whakatakoto i te rerenga kupu mai i ngā whatumanawa o ngā kuia me ngā kaumātua ō Ngāi Tūhoe. Nō reira, ka titiro ake tātau ki ngā momo āhuatanga katoa o te karanga. Whai muri ko ngā tikanga e pā ana ki te whaikōrero. Whai muri, ko wētahi atu tūmomo tauira mō te poroporoaki.

text: Te kākahu whakataratara o Ngāi Tūhoe: Ko te reo ōkawa, ko te reo o te marae Ko te reo ōkawa ara ko te reo o te marae, he reo hōhonu. Ka mutu, he tapu katoa ōna āhuatanga katoa. E rua ngā kōrero whakatau o runga i te marae. Ko te karanga me te whaikōrero. Kai roto i wēneki reo e rua, ka ahu mai te kupu nei te poroporoaki. Ka āta tirohia te poroporoaki i roto i ngā whakaaro e pā ana ki ngā tikanga o te karanga. Whai muri ka titiro ki te wāhanga o te poroporoaki i roto i te whaikōrero. Mā wēneki tikanga e rua, ka whakaputaina ngā whakaaro me te hōhonutanga o te mamae o te ngākau pōuri ka ea hoki te mamae. Ka tiro ake tātau ki ngā take i whakaputaina, ngā tohutohu ā rātau mā me ngā rongo o te wairua o te kupu kōrero. Tae atu hoki ki te tohungatanga ki te whakatakoto i te rerenga kupu mai i ngā whatumanawa o ngā kuia me ngā kaumātua ō Ngāi Tūhoe. Nō reira, ka titiro ake tātau ki ngā momo āhuatanga katoa o te karanga. Whai muri ko ngā tikanga e pā ana ki te whaikōrero. Whai muri, ko wētahi atu tūmomo tauira mō te poroporoaki.

year: 2012-05