東華大學圖書館 |

Essays on Agricultural Productivity, Youth Employment, and Human Capital Investment in Sub-Saharan Africa.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Essays on Agricultural Productivity, Youth Employment, and Human Capital Investment in Sub-Saharan Africa./
作者:	Koima, Josephat.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	201 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Contained By:	Dissertations Abstracts International82-11B.
標題:	Sub Saharan Africa studies. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28492341
ISBN:	9798738619885

Essays on Agricultural Productivity, Youth Employment, and Human Capital Investment in Sub-Saharan Africa.
Koima, Josephat.

Essays on Agricultural Productivity, Youth Employment, and Human Capital Investment in Sub-Saharan Africa. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 201 p.

Source: Dissertations Abstracts International, Volume: 82-11, Section: B.

Thesis (Ph.D.)--Michigan State University, 2021.

This item must not be sold to any third party vendors.

This dissertation focuses on the intersection of agricultural productivity, youth employment, and investments in human capital development in Sub-Saharan Africa (SSA). Agriculture is a dominant employer and source of income in SSA, and plays an important role in youth employment and educational attainments.In Chapter 1, we study the role of structural transformation in the labor reallocation between the farm and the non-farm sector and the consequential impact on worker demographics. Specifically, we investigate whether agricultural productivity differentially reallocates labor by age and gender. We develop a theoretical model where increased land productivity leads to younger individuals sorting into the non-farm sector while older individuals sort into agriculture. We then use data from Zambia in our empirical analysis. Our main results show some evidence of productivity affecting labor reallocation within recent productivity lags (last 2 years) but not when longer productivity lags (4 or 6) are considered. Specifically, consistent with our model prediction, a 10% increase in a 2-year lagged moving average of productivity decreases the probability of farming by 0.3 percentage points among youth (15-24) and older youth (25-34). We also show that youth (15-24) also exit farming following increased productivity. Increased productivity tends to reduce the intensity of farming across all age groups but the reduction is relatively larger among the youth. In addition, young men are more likely to exit business activity as productivity increases relative to young women - across all productivity lags. In the short term (2-lags), while youth exit farming, there is no differential outcome between genders. However, among older youth, males are more likely to exit farming compared to women. Finally, males mainly drive the reduction in intensity of farming. Overall, while we find some evidence in favor of our hypotheses, the evidence is generally limited to the short term and the marginal effects are quantitatively small.Chapter 2 investigates the impact of agricultural productivity on human capital investments in Tanzania. Agriculture remains a major source of employment and income in Tanzania. Therefore, any agricultural productivity shocks are likely to affect educational investment decisions. Our results provide evidence that increased agricultural productivity boosts spending on uniform, contributions and total academic expenses. We find positive but statistically non-significant effects of productivity on study times. In addition, we find no evidence of heterogeneous effects by student gender. We show evidence that productivity effects are smaller in female-headed households. Finally, we find some evidence that post-primary students experience larger impacts compared to primary school students.In Chapter 3, I investigate the impact of primary school electrification on academic outcomes in Kenya. Between 2014 and 2016, the number of primary schools with electricity rose from 56% to 94%. Schools near the grid network were connected to grid electricity while those further received solar photovoltaics. Using this rapid electrification expansion as a source of identifying variation in a panel fixed effects model, the paper estimates the impact on school test scores, enrollment, and completion. The paper also attempts to quantify the effects of lighting on education performance by relying on the off-grid (solar) electricity coefficients. Using a universe of 8th grade students in public schools in Kenya, the paper finds no evidence that electricity affects test scores or enrollment in the short run. However, off-grid electrification increases completion by 1%. Using off-grid estimates, the paper concludes that lighting has a small positive impact on completion but not on test scores or enrollment.

ISBN: 9798738619885Subjects--Topical Terms:

3172272
Sub Saharan Africa studies.
Subjects--Index Terms:

Agricultural development

Essays on Agricultural Productivity, Youth Employment, and Human Capital Investment in Sub-Saharan Africa.
LDR:05142nmm a2200409 4500 001 2284425
005 20211123073018.5
008 220723s2021 ||||||||||||||||| ||eng d
020 $a 9798738619885
035 $a (MiAaPQ)AAI28492341
035 $a AAI28492341
040 $a MiAaPQ $c MiAaPQ
100 1 $a Koima, Josephat. $3 3563591
245 1 0 $a Essays on Agricultural Productivity, Youth Employment, and Human Capital Investment in Sub-Saharan Africa.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 201 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
500 $a Advisor: Muyanga, Milu;Jayne, Thomas.
502 $a Thesis (Ph.D.)--Michigan State University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a This dissertation focuses on the intersection of agricultural productivity, youth employment, and investments in human capital development in Sub-Saharan Africa (SSA). Agriculture is a dominant employer and source of income in SSA, and plays an important role in youth employment and educational attainments.In Chapter 1, we study the role of structural transformation in the labor reallocation between the farm and the non-farm sector and the consequential impact on worker demographics. Specifically, we investigate whether agricultural productivity differentially reallocates labor by age and gender. We develop a theoretical model where increased land productivity leads to younger individuals sorting into the non-farm sector while older individuals sort into agriculture. We then use data from Zambia in our empirical analysis. Our main results show some evidence of productivity affecting labor reallocation within recent productivity lags (last 2 years) but not when longer productivity lags (4 or 6) are considered. Specifically, consistent with our model prediction, a 10% increase in a 2-year lagged moving average of productivity decreases the probability of farming by 0.3 percentage points among youth (15-24) and older youth (25-34). We also show that youth (15-24) also exit farming following increased productivity. Increased productivity tends to reduce the intensity of farming across all age groups but the reduction is relatively larger among the youth. In addition, young men are more likely to exit business activity as productivity increases relative to young women - across all productivity lags. In the short term (2-lags), while youth exit farming, there is no differential outcome between genders. However, among older youth, males are more likely to exit farming compared to women. Finally, males mainly drive the reduction in intensity of farming. Overall, while we find some evidence in favor of our hypotheses, the evidence is generally limited to the short term and the marginal effects are quantitatively small.Chapter 2 investigates the impact of agricultural productivity on human capital investments in Tanzania. Agriculture remains a major source of employment and income in Tanzania. Therefore, any agricultural productivity shocks are likely to affect educational investment decisions. Our results provide evidence that increased agricultural productivity boosts spending on uniform, contributions and total academic expenses. We find positive but statistically non-significant effects of productivity on study times. In addition, we find no evidence of heterogeneous effects by student gender. We show evidence that productivity effects are smaller in female-headed households. Finally, we find some evidence that post-primary students experience larger impacts compared to primary school students.In Chapter 3, I investigate the impact of primary school electrification on academic outcomes in Kenya. Between 2014 and 2016, the number of primary schools with electricity rose from 56% to 94%. Schools near the grid network were connected to grid electricity while those further received solar photovoltaics. Using this rapid electrification expansion as a source of identifying variation in a panel fixed effects model, the paper estimates the impact on school test scores, enrollment, and completion. The paper also attempts to quantify the effects of lighting on education performance by relying on the off-grid (solar) electricity coefficients. Using a universe of 8th grade students in public schools in Kenya, the paper finds no evidence that electricity affects test scores or enrollment in the short run. However, off-grid electrification increases completion by 1%. Using off-grid estimates, the paper concludes that lighting has a small positive impact on completion but not on test scores or enrollment.
590 $a School code: 0128.
650 4 $a Sub Saharan Africa studies. $3 3172272
650 4 $a Agriculture. $3 518588
650 4 $a Education. $3 516579
653 $a Agricultural development
653 $a Electricity
653 $a Gender
653 $a Youth employment
653 $a Human capital investment
653 $a Sub-Saharan Africa
690 $a 0503
690 $a 0501
690 $a 0515
690 $a 0639
690 $a 0473
710 2 $a Michigan State University. $b Agricultural, Food and Resource Economics - Doctor of Philosophy. $3 3177932
773 0 $t Dissertations Abstracts International $g 82-11B.
790 $a 0128
791 $a Ph.D.
792 $a 2021
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28492341