Begin draft Benin script

notes/benin/2208181123_benin-key-notes.md

@@ -0,0 +1,27 @@
+# Research Benin
+
+* focus on:
+    * income inequality, based on bottom 40%, Gini coefficient, other inequality measures
+    * inequality in policy areas of development interventions:
+        * Benin inequalities in access to electricity
+
+## Project
+
+The project in Benin has the objective of provide access to electricity to approximately 182,000 people in 59 rural villages. The programme will also benefit 57,000 households living in the administrative perimeters of the targeted villages, but outside the areas that will be covered by the project. A large part of the beneficiary population is below the 1.90 dollar a day poverty line.
+
+requires data on:
+
+* poverty rates, poverty trends
+    * *rural* poverty rates/trends
+* inequality rural/urban
+    * how does electricity increase/decrease inequality
+* electricity rates, trends
+    * *rural* vs urban
+* extension of pre-payment techniques mimicking urban pre-payment
+    * increase/decrease inequality?
+* dispersion of charging stations
+    * effects?
+* institutional obstacles etc
+
+## Literature
+

notes/benin/2208181200_script.md

@@ -0,0 +1,108 @@
+---
+title: "Drivers of inequality Benin"
+author:
+    - Marty Oehme
+documentclass: report
+papersize: A4
+geometry:
+  - left=2cm
+  - right=2.5cm
+  - top=2.5cm
+  - bottom=2.5cm
+indent: true
+linestretch: 1.25
+fontfamily: lmodern
+fontsize: 12
+lang: en
+bibliography: /home/marty/projects/jobs/afd/inputs/libraries/afd-dev-research.bib
+csl: /home/marty/documents/library/academia/styles/APA-7.csl
+output:
+    pdf_document:
+        latex_engine: xelatex
+header-includes:
+    - \usepackage{fvextra}
+    - \DefineVerbatimEnvironment{Highlighting}{Verbatim}{breaklines,breakanywhere,commandchars=\\\{\}}
+---
+
+# Script
+
+Summary:
+
+-----
+*
+*
+*
+*
+*
+*
+-----
+
+<!-- intro/overall -->
+Benin in recent years has seen fairly stable real GDP growth rates and downward trending poverty levels in absolute terms.
+Its growth rate averaged 6.4% for the years 2017 to 2019 and, with a decrease during the intermittent years due to the Covid-19 pandemic, has recovered to a rate of 6.6% in 2021 [@WorldBank2022b].
+There only exists sporadic and highly fluctuating data on the country's overall inequality, with the World Bank Development Index noting a Gini coefficient of 38.6 for the year (2003) before rising to 43.4 (2011) and up to 47.8 (2015),
+though decreasing below the 2003 level to 37.8 (2018) in its most recent calculation.
+At the same time, the country's poverty rate, even measured based on the international line, only decreased at a very slow rate in its most recent years,
+from a relative rate of households in poverty at 18.8% in 2019, to 18.7% in 2020 and 18.3% at the end of 2021,
+with the reduction threatened to be slowed further through increased prices on food and energy [@WorldBank2022b].
+
+<!-- poverty -->
+Based on its national poverty line, Benin's overall poverty rate is 38.5%,
+though it hides a strong spatial disparity between rural and urban households with 44.2% to 31.4% households in poverty respectively [@WorldBank2022b].
+Looking at the effect of income growth on the time to exit poverty,
+@Alia2017 finds a general negative correlation with stronger growth indeed leading to shorter average exit times (7-10 years for a household at a per capita growth rate of 4.2%),
+though this aggregate also hides a large heterogeneity primarily determined by a households size, its available human capital and whether it is located rurally.
+So while the study does conclude for an overall equitable pro-poor growth in Benin,
+rural households, beside already being relatively more poverty stricken,
+are in danger of being left further behind during periods of overall growth.
+@Djossou2017 find similar pro-poor growth with spatial disparities but surprisingly see urban households potentially benefiting less than rural households from additional growth,
+with efforts to open up communities to harness the benefits of growth often primarily targeted at rural communities.
+
+<!-- drivers: endowment/assets: education, ..? -->
+For the household-level factor of education for this disparity,
+the Learning Poverty index shows that in Benin 56% of children at late primary age are not proficient in reading,
+55% do not achieve minimum proficiency levels at the end of primary school and 3% of primary school-aged children are not enrolled in school at all.
+<!-- TODO These levels are higher than in Uganda, though, since ... gender dimension? -->
+Looking purely at attendance rates, @McNabb2018 finds that the primary household-level determinants of attendance are the wealth of a household, its religion, as well as the education level of its household head.
+Here, gender disparities persist, however,
+with girls continuously less likely to attend and adopted girls being at the greatest disadvantage,
+while boy tend to face higher opportunity costs than girls due to often working in the fields in which case the distance to a school begins to play an important role.
+While the household-level variables do play a role ---
+through the availability of educational resources at home, differences in schooling quality and overall health and well-being ---
+@Gruijters2020 find that most of the disparity stems from the community-level:
+the difference in school quality is large,
+marked by high socio-economic segregation between schools,
+and primarily determined through an unequal distribution of teaching resources including teachers and textbooks.
+
+<!-- electricity access -->
+Thus, while growth is generally pro-poor in Benin, its primary determinants do not cluster only at the household level,
+but are comprised of partly household-level but especially community-level differences.
+One of the foremost examples of the effects of inequal endowments can have is brought by @VanDePoel2009 when they look at the determinants of rural infant death rates in Benin among others and find that environmental factors ---
+such as access to a safe water source, quality housing materials and electricity ---
+are the primary determinants, ahead even of access to a health facility in the community.
+Access to electricity in the country especially underlies a large heterogeneity based on location.
+The overall level of electrification of Benin has been rising slowly ---
+though outpacing population growth ---
+from 22% in 2000 to 26% in 2005, 34% in 2010, a regression to 30% in 2015 and a faster increase to 40% in 2019, however,
+there is a broad difference of electrification levels between urban (65%) and rural (17%) regions remaining [@WorldBank2021].
+In rural areas there are generally three approaches to electrification that work outside of a connection to the main grid,
+individual installation of solar panels or generators for smaller electric appliances,
+collective solutions like kiosks offering electric charging for some cost,
+or autonomous mini-grids powering a portion of a more densely populated rural area
+(though often requiring permits or licenses if above certain sizes) [@Jaglin2019].
+
+@Rateau2022 see one of the primary reasons for off-grid electrification in either physical unavailability in rural areas or a prohibitively high cost for connection to the grid.
+However, these more individualized solutions are often only targeted at credit-worthy customers and can lead to a further increase in inequalities between income percentiles,
+leaving behind households which are already neglected within the field of energy access [@Barry2020].
+The former, physical access, is argued by @Djossou2017 as well, emphasizing the need for continued infrastructure expansion to more households,
+in order to provide access to more durable goods (fridges, mobile phones and internet) which can help decrease the inequality gap.
+The latter, prohibitively high costs, should not be disregarded in such an infrastructure expansion as well, however.
+One of the major obstacles to main grid connection remains the high charge a customer is expected to pay with solutions requiring continued political commitment to identify, examine and implement more low-cost electrification processes as well as financing solutions.
+@Golumbeanu2013 point out the main obstacles that need to be addressed here:
+the lack of incentives to increase electrical affordability,
+a weak utilities commitment toward providing broad electricity access with focus often lying more on high-consumption urban markets,
+often overrated technical specifications for low loads,
+too great distances between households and distribution poles in an area,
+and an overall lack of affordable financing solutions.
+
+<!-- conclusion -->

notes/benin/2208181301_literature-education.md

@@ -0,0 +1,33 @@
+### [x] McNabb2018 - regional and gender inequalities in school attendance
+
+* looks at attendance rates and its determinants
+* results:
+    * high increases in attendance since 1990s
+    * important determinants: richer HHs, Christian religion, educated HHHs more likely to have children enrolled in school
+    * gender disparities persist:
+        * girls less likely to attend, adopted girls at greatest disadvantage
+    * opportunity costs higher for boys working along school than girls
+        * distance mattered more for boys working in field than domestic work
+
+### [x] Gruijters2020 - learning inequality of poor and rich
+
+* looks at correlation of family socioeconomic status and learning outcomes
+    * data from 10 francophone African countries
+    * standardized mathematics and reading competence end of primary school
+* results:
+    * outcomes both poor and highly stratified
+    * 3 determinants within family socioeconomic status, but little effect overall:
+        * educational resources at home
+        * health/well-being
+        * differences in school quality
+    * most effect comes from differing school quality (unequal distribution of resources teachers, textbooks) and high socio-economic segregation between schools
+
+### [x] WorldBank2022a - Learning poverty
+
+* looks at Learning Poverty Indicator formed of 'Schooling Deprived' (out-of-school) children and 'Learning Deprived' (below minimum proficiency) children
+* results:
+    * 56% of children late primary age not proficient in reading
+    * 55% of children do not achieve minimum proficiency level at end of primary school
+    * 3% of primary school-aged children are not enrolled in school
+* does not disaggregate rural/location-based, can not disaggregate gender (missing data in Benin, except learning deprivation 56.1% boys, 52.8% girls) etc.
+

notes/benin/2208181309_literature-poverty.md

@@ -0,0 +1,29 @@
+### [x] Alia2017 - Effect of income growth on poverty exit time
+
+* looks at (negative) correlation between growth and poverty using 'exit time from poverty'
+* results: (for data 2009-2011)
+    * growth rate per capita of 4.2% means average poor household needs 7-10 years to escape poverty
+    * stronger growth does lead to shorter avg time to exit from poverty
+    * large heterogeneity, HHs size, human capital, rural location important determinants
+    * equitable growth requires development of human capital and inclusive/pro-poor growth
+
+### [x] WorldBank2022b - World Bank Poverty outlook
+
+* results:
+    * Gini index: 37.8
+    * robust real GDP growth pre-Covid (avg 6.4% 2017-2019)
+        * real GDP recovered to 6.6% in 2021
+    * fiscal deficit deterioration due to socio-economic measures
+    * poverty rate based on national poverty line: 38.5% in 2019
+        * strong spatial disparities: rural 44.2%, 31.4% urban (12.8% higher for rural)
+    * poverty rate based on international line: 18.8% (2019), 18.7% (2020), 18.3% (end of 2021)
+        * reduction could be slowed by increased food and *energy prices*
+
+
+### [x] World Bank - World Development Index
+
+* Gini coefficients:
+    * 2018: 37.8
+    * 2015: 47.8
+    * 2011: 43.4
+    * 2003: 38.6

notes/benin/2208181310_literature-electricity.md

@@ -0,0 +1,90 @@
+### [x] VanDePoel2009 - HH characteristics determining rural infant death
+
+* looks at determinants of infant deaths in rural regions at HH and community level
+    * at multiple countries (6?) throughout SSA (including Benin)
+* results:
+    * mainly derived from rural disadvantage in HH characteristics (2/3rds of gap)
+        * environmental factors (safe water source, electricity, quality of housing materials) biggest contributors
+    * community characteristics less than 1/3rd:
+        * 2/3rds of this from unobserved heterogeneity
+        * 1/3rd of existence of health facility in community
+    * lack of environmental factors can derive both from lack of community-level infrastructure and inability of some HHs to exploit it when available
+    * effective policy thus needs to operate at both levels to improve it
+
+### [ ] Golumbeanu2013 - electricity access and high connection charges
+
+* looks at reasons for poor access to electricity for poor rural (and urban) HHs
+* results:
+    * major obstacle is high charge for customer to connect to electricity grid (some of highest connection charges in world)
+    * solution requires concurrent political commitment toward identifying, examining, implementing low-cost electrification processes and financing solutions
+    * low-cost technologies need to be put in center of attention
+    * determinants:
+        * lack of incentives to increase affordability
+        * weak utilities commitment to provide broad electricity access,
+        focused more on high-consumption urban markets
+        * overrated technical specifications for low loads
+        * greater distances between HH and distribution pole in rural areas
+        * lack of affordable financing options
+
+### [x] Djossou2017 - growth is pro-poor in Benin
+
+* looks at relation between economic growth and poverty
+    * data from 2006, 2011 Benin Demographic and Health Surveys
+* results:
+    * growth generally pro-poor in Benin
+    * disparities between rural/urban; women and elderly:
+        * women, elderly general livelihood improvement but generally favored non-poor relative to poor
+        * urban poor HHs benefited less than rural from growth
+            * potentially due to numerous efforts to open up rural communities to harness benefits of growth
+            * **rural households access to electricity 17.64% (2006) 25.03% (2011)**
+            * possession of durable goods (fridges, mobile phone, internet, ..) significantly improved in rural households
+            * emphasizes need of infrastructure expansion to HHs (to rural communities)
+
+### [x] Jaglin2019 - electricity autonomy in Africa
+
+* looks at ways of electrification and different approaches
+* results for rural areas:
+    * individual offerings of solar panels/generators or smaller electric appliances (LED dry cell powered torches)
+    * often offering collective solutions (kiosks, autonomous mini-grids)
+    * half-way between individual and grid connection: mini-grid construction for more densely populated rural area, often requiring some sort of permit or license
+
+### [x] Barry2020 - pay-as-you-go system does not bridge last mile problem
+
+* looks at extension and preferred customers for PAYG contracts
+    * PAYG: flexible loans allowing fees payment through mobile banking, to purchase solar kits or panels for lighting and charging services
+    * 'last mile' problem: addressing an area neglected within the field of energy access (scaling challenge)
+* results:
+    * most of PAYG customers live in well electrified areas
+        * esp Cotonou, Porto Novo, Abomey Calavi, coastal zone
+    * most customers in urban/peri-urban areas
+    * PAYG used to substitute unreliable grid electricity services
+    * consumers in periferic/less electrified areas (Savalou) have low probability to default on credit
+        * thus PAYG primarily targets credit-worthy customers
+
+### [x] WorldBank2021 - electrification levels
+
+* electrification level:
+    * 2000: 22%
+    * 2005: 26%
+    * 2010: 34%
+    * 2015: 30%
+    * 2019: 40%
+* location:
+    * urban: 65% (2019)
+    * rural: 17% (2019)
+* electricity growth outpaced population growth (2017-2019)
+
+
+### [x] Rateau2022 - Electrifying urban Africa
+
+* data from 2017-2018 for Cotonou (urban economic capital Benin)
+* Benin depends on Nigeria for power supply
+* difficult to connect grid due to connection costs and long distances
+    * solar energy in Cotonou is used as alternative power source not complementary, until they can connect to main grid
+    * diffusion of solar/generators not systematic or the same
+    * to be connected to conventional grid requires location close to it, while it covers only planned urban areas
+* thus 2 main obstacles of rural and urban unplanned areas:
+    * either electricity physically not available in local area
+    * or high initial costs consumer pays for connection unaffordable
+* generators and solar panels have become material markers of inequalities in access to electricity
+* grid strengthening efforts also make Benin more independent from Nigeria as main supplier (with outages in Nigeria otherwise strongly felt in Benin)