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@ -2603,14 +2603,12 @@ vertical-align: -.125em;
-->
<!-- environmental inequality -->
<p>While the effect of agriculture on inequality outcomes is an equalizing one, its future growth, and that of agricultural livelihoods, is threatened by vulnerability to risks such as natural disasters and environmental degradation, exacerbated through climate change <span class="citation" data-cites="Kozel2014">(<a href="#ref-Kozel2014" role="doc-biblioref">Kozel, 2014</a>)</span>. Kozel <span class="citation" data-cites="Kozel2014">(<a href="#ref-Kozel2014" role="doc-biblioref">2014</a>)</span> goes on to argue the continuous precarity of poor households against economy-wide shocks (such as the effect of climate change on rainfall and temperatures) but also highlights the danger of vulnerable households <em>falling</em> into poverty through generated inequalities. Looking at the particularities of flood risk management in the Ninh Binh province, Mottet and Roche <span class="citation" data-cites="Mottet2009">(<a href="#ref-Mottet2009" role="doc-biblioref">2009</a>)</span> find that most areas within the region are vulnerable. They find the strengths of current management lying in prevention with existing dykes designed to channel high waters, effective monitoring of weather conditions (rainfall or typhoons) and consolidation or elevation of existing residences, while the weaknesses are mainly centered around insufficient information given to inhabitants over flood risks, few compensation systems for flood victims and construction policies continuing to allow building in flood-endangered zones. Sen et al. <span class="citation" data-cites="Sen2021">(<a href="#ref-Sen2021" role="doc-biblioref">2021</a>)</span> estimate that the main barriers to better information are farmers’ lack of trust toward formal climate-related services, their lack of perceived risk from climate change itself and difficulties in balancing both climate adaptation and economic benefits of interventions. They argue that, while ethnicity itself is not a barrier to information access with all farmers receiving information through informal channels — friends neighbors and market actors instead of agricultural departments or mass media — cultural issues such as language do come into play and act as a barrier. Reactionary economic mitigation efforts by households, such as reduced healthcare spending, selling of land or livestock assets, taking children out of school due to needing assistance at home can in turn lead to longer-term adverse consequences (thus, <em>mal-adaptation</em>) <span class="citation" data-cites="Kozel2014">(<a href="#ref-Kozel2014" role="doc-biblioref">Kozel, 2014</a>)</span>.</p>
<ul>
<li>estimated Gini coeff: Ninh Binh province <span class="citation" data-cites="Kozel2014">(<a href="#ref-Kozel2014" role="doc-biblioref">Kozel, 2014</a>)</span>
<ul>
<li>0.283 (2013)</li>
<li>top 90th percentile 3.57 times income 10th percentile</li>
<li>13.63 percent in richest quintile</li>
</ul></li>
</ul>
<!--
* estimated Gini coeff: Ninh Binh province [@Kozel2014]
* 0.283 (2013)
* top 90th percentile 3.57 times income 10th percentile
* 13.63 percent in richest quintile
-->
<!-- extreme events / climate change -->
<p>The results are further intensification of inequality along existing social lines during extreme events such as flooding: The effects of inequalities mainly affecting ethnic minorities are illustrated by Son and Kingsbury <span class="citation" data-cites="Son2020">(<a href="#ref-Son2020" role="doc-biblioref">2020</a>)</span>, with droughts impacting yield losses between 50% and 100%, cold snaps leading to loss of livestock and floods damaging residential structures but even more importantly disrupting livelihoods through landslides, crop destruction and overflowing fish ponds. Locally employed coping strategies, they argue, are always conditional on the strength and foresight of institutions and implemented preventative policies along local but also regional and central levels. Similarly, Ylipaa et al. <span class="citation" data-cites="Ylipaa2019">(<a href="#ref-Ylipaa2019" role="doc-biblioref">2019</a>)</span> analyze impacts mainly across the gender dimension to find that, resulting inequalities may be exacerbated with differentiated rights and responsibilities leading to unequal opportunities and, especially, decreased female mobility in turn increasing their vulnerability to climate impacts with a reduced capacity to adapt. Hudson et al. <span class="citation" data-cites="Hudson2021">(<a href="#ref-Hudson2021" role="doc-biblioref">2021</a>)</span> along the same dimension find that, while the set of relevant variables is largely similar with age, social capital, internal and external support after the flood and the perceived severity of previous flood impacts having major impacts, women tend to show longer recovery times and psychological variables can influence recovery rates more than some adverse flood impacts.</p>
<p>While the quantitative evidence for impacts of such shock events are relatively sparse, Jafino et al. <span class="citation" data-cites="Jafino2021">(<a href="#ref-Jafino2021" role="doc-biblioref">2021</a>)</span> lament the overuse of aggregate perspectives, instead disaggregating the local and inter-sectoral effects to find out that flood protection efforts in the Mekong Delta often predominantly support large-scale farming while small-scale farmers can be harmed through them. They find that measures decrease the aggregate total output and equity indicators by disaggregating profitability indicators into inundation, sedimentation, soil fertility, nutrient dynamics, behavioral land-use in an assessment which sees within-sector policy responses often having an effect on adjacent sectors, increasing the inter-district Gini coefficient. Adaptation during these catastrophic events reinforces the asset and endowment drivers of non-shock event times, with impacts levels often depending on access to non-farm income sources, access to further arable land, knowledge of adaptive farming practices and mitigation of possible health risks such as water contamination <span class="citation" data-cites="Son2020">(<a href="#ref-Son2020" role="doc-biblioref">Son &amp; Kingsbury, 2020</a>)</span>. Karpouzoglou et al. <span class="citation" data-cites="Karpouzoglou2019">(<a href="#ref-Karpouzoglou2019" role="doc-biblioref">2019</a>)</span> make the point that, ultimately, the pure coupling of flood resilience into infrastructural or institutional interventions needs to take care not to amplify existing inequalities through unforeseen consequences (‘ripple effects’) which can’t be escaped by vulnerable people due to their existing immobility.</p>
@ -2705,7 +2703,7 @@ vertical-align: -.125em;
<div id="quarto-appendix" class="default"><section class="quarto-appendix-contents" role="doc-bibliography"><h2 class="anchored quarto-appendix-heading">References</h2><div id="refs" class="references csl-bib-body hanging-indent" data-line-spacing="2" role="doc-bibliography">
<div id="ref-Alia2017" class="csl-entry" role="doc-biblioentry">
Alia, D. Y. (2017). Progress <span>Toward The Sustainable Development Goal</span> on <span>Poverty</span>: <span>Assessing The Effect</span> of <span>Income Growth</span> on <span>The Exit Time</span> from <span>Poverty</span> in <span>Benin</span>: <span>Exit Time Out</span> of <span>Poverty</span> in <span>Benin</span>. <em>Sustainable Development</em>, <em>25</em>(6), 495–503. <a href="https://doi.org/10.1002/sd.1674">https://doi.org/10.1002/sd.1674</a>
Alia, D. Y. (2017). Progress <span>Toward The Sustainable Development Goal</span> on <span>Poverty</span> : <span>Assessing The Effect</span> of <span>Income Growth</span> on <span>The Exit Time</span> from <span>Poverty</span> in <span>Benin</span>: <span>Exit Time Out</span> of <span>Poverty</span> in <span>Benin</span>. <em>Sustainable Development</em>, <em>25</em>(6), 495–503. <a href="https://doi.org/10.1002/sd.1674">https://doi.org/10.1002/sd.1674</a>
</div>
<div id="ref-Barry2020" class="csl-entry" role="doc-biblioentry">
Barry, M. S., &amp; Creti, A. (2020). Pay-as-you-go contracts for electricity access: <span>Bridging</span> the <span>“last mile”</span> gap? <span>A</span> case study in <span>Benin</span>. <em>Energy Economics</em>, <em>90</em>, 104843. <a href="https://doi.org/10.1016/j.eneco.2020.104843">https://doi.org/10.1016/j.eneco.2020.104843</a>
@ -2723,7 +2721,7 @@ Benjamin, D., Brandt, L., &amp; McCaig, B. (2017). Growth with equity: Income in
Brass, J. N. (2008). Djibouti’s unusual resource curse. <em>The Journal of Modern African Studies</em>, <em>46</em>(4), 523–545. <a href="https://doi.org/10.1017/S0022278X08003479">https://doi.org/10.1017/S0022278X08003479</a>
</div>
<div id="ref-Bui2019" class="csl-entry" role="doc-biblioentry">
Bui, T. P., &amp; Imai, K. S. (2019). Determinants of <span>Rural-Urban Inequality</span> in <span>Vietnam</span>: <span>Detailed Decomposition Analyses Based</span> on <span>Unconditional Quantile Regressions</span>. <em>The Journal of Development Studies</em>, <em>55</em>(12), 2610–2625. <a href="https://doi.org/10.1080/00220388.2018.1536265">https://doi.org/10.1080/00220388.2018.1536265</a>
Bui, T. P., &amp; Imai, K. S. (2019). Determinants of <span>Rural-Urban Inequality</span> in <span>Vietnam</span>: <span> Detailed Decomposition Analyses Based</span> on <span>Unconditional Quantile Regressions</span>. <em>The Journal of Development Studies</em>, <em>55</em>(12), 2610–2625. <a href="https://doi.org/10.1080/00220388.2018.1536265">https://doi.org/10.1080/00220388.2018.1536265</a>
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<div id="ref-Cali2014" class="csl-entry" role="doc-biblioentry">
Cali, M. (2014). Trade boom and wage inequality: Evidence from <span>Ugandan</span> districts. <em>Journal of Economic Geography</em>, <em>14</em>(6), 1141–1174. <a href="https://doi.org/10.1093/jeg/lbu001">https://doi.org/10.1093/jeg/lbu001</a>
@ -2738,7 +2736,7 @@ Cooper, S. J., &amp; Wheeler, T. (2016). Rural household vulnerability to climat
Datzberger, S. (2018). Why education is not helping the poor. <span>Findings</span> from <span>Uganda</span>. <em>World Development</em>, <em>110</em>, 124–139. <a href="https://doi.org/10.1016/j.worlddev.2018.05.022">https://doi.org/10.1016/j.worlddev.2018.05.022</a>
</div>
<div id="ref-Djossou2017" class="csl-entry" role="doc-biblioentry">
Djossou, G. N., Kane, G. Q., &amp; Novignon, J. (2017). Is <span>Growth Pro-Poor</span> in <span>Benin</span>? <span>Evidence Using</span> a <span>Multidimensional Measure</span> of <span>Poverty</span>: <span>Is Growth Pro-Poor</span> in <span>Benin</span>? <em>Poverty &amp; Public Policy</em>, <em>9</em>(4), 426–443. <a href="https://doi.org/10.1002/pop4.199">https://doi.org/10.1002/pop4.199</a>
Djossou, G. N., Kane, G. Q., &amp; Novignon, J. (2017). Is <span>Growth Pro-Poor</span> in <span>Benin</span>? <span>Evidence Using</span> a <span> Multidimensional Measure</span> of <span>Poverty</span>: <span>Is Growth Pro-Poor</span> in <span>Benin</span>? <em>Poverty &amp; Public Policy</em>, <em>9</em>(4), 426–443. <a href="https://doi.org/10.1002/pop4.199">https://doi.org/10.1002/pop4.199</a>
</div>
<div id="ref-Ebrahim2021" class="csl-entry" role="doc-biblioentry">
Ebrahim, C., Jack, A., &amp; Jones, L. (2021). Women’s economic empowerment and <span>COVID-19</span>: The case of vulnerable women with intersectional identities in <span>Indonesia</span> and <span>Vietnam</span>. <em>Enterprise Development and Microfinance</em>, <em>32</em>(1), 44–56. <a href="https://doi.org/10.3362/1755-1986.21-00007">https://doi.org/10.3362/1755-1986.21-00007</a>
@ -2765,7 +2763,7 @@ Fritzen, S., Brassard, C., &amp; Bui, T. M. T. (2005). <em>Vietnam inequality re
Golumbeanu, R., &amp; Barnes, D. (2013). <em>Connection <span>Charges</span> and <span>Electricity Access</span> in <span>Sub-Saharan Africa</span></em> (No. 6511; Policy <span>Research Working Paper</span>). <span>World Bank</span>. <a href="https://openknowledge.worldbank.org/handle/10986/15871">https://openknowledge.worldbank.org/handle/10986/15871</a>
</div>
<div id="ref-Gruijters2020" class="csl-entry" role="doc-biblioentry">
Gruijters, R. J., &amp; Behrman, J. A. (2020). Learning <span>Inequality</span> in <span>Francophone Africa</span>: <span>School Quality</span> and the <span>Educational Achievement</span> of <span>Rich</span> and <span>Poor Children</span>. <em>Sociology of Education</em>, <em>93</em>(3), 256–276. <a href="https://doi.org/10.1177/0038040720919379">https://doi.org/10.1177/0038040720919379</a>
Gruijters, R. J., &amp; Behrman, J. A. (2020). Learning <span>Inequality</span> in <span>Francophone Africa</span>: <span>School Quality </span> and the <span>Educational Achievement</span> of <span>Rich</span> and <span>Poor Children</span>. <em>Sociology of Education</em>, <em>93</em>(3), 256–276. <a href="https://doi.org/10.1177/0038040720919379">https://doi.org/10.1177/0038040720919379</a>
</div>
<div id="ref-Hudson2021" class="csl-entry" role="doc-biblioentry">
Hudson, P., Pham, M., Hagedoorn, L., Thieken, A. H., Lasage, R., &amp; Bubeck, P. (2021). Self-stated recovery from flooding: <span>Empirical</span> results from a survey in <span>Central Vietnam</span>. <em>Journal of Flood Risk Management</em>, <em>14</em>(1), 1–15.
@ -2810,10 +2808,10 @@ Nagasha, J. I., Mugisha, L., Kaase-Bwanga, E., Onyuth, H., &amp; Ocaido, M. (201
Naiga, R. (2018). Conditions for successful community-based water management: Perspectives from rural <span>Uganda</span>. <em>International Journal of Rural Management</em>, <em>14</em>(2), 110–135.
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Naiga, R., Penker, M., &amp; Hogl, K. (2015). Challenging pathways to safe water access in rural <span>Uganda</span>: <span> From</span> supply to demand-driven water governance. <em>International Journal of the Commons</em>, <em>9</em>(1).
</div>
<div id="ref-Nguyen2007" class="csl-entry" role="doc-biblioentry">
Nguyen, B. T., Albrecht, J. W., Vroman, S. B., &amp; Westbrook, M. D. (2007). A quantile regression decomposition of urban–rural inequality in <span>Vietnam</span>. <em>Journal of Development Economics</em>, <em>83</em>(2), 466–490. <a href="https://doi.org/10.1016/j.jdeveco.2006.04.006">https://doi.org/10.1016/j.jdeveco.2006.04.006</a>
Nguyen, B. T., Albrecht, J. W., Vroman, S. B., &amp; Westbrook, M. D. (2007). A quantile regression decomposition of urban–rural inequality in <span> Vietnam</span>. <em>Journal of Development Economics</em>, <em>83</em>(2), 466–490. <a href="https://doi.org/10.1016/j.jdeveco.2006.04.006">https://doi.org/10.1016/j.jdeveco.2006.04.006</a>
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<div id="ref-Rateau2022" class="csl-entry" role="doc-biblioentry">
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@ -2837,10 +2835,10 @@ Ssewanyana, S., &amp; Kasirye, I. (2012). <em>Poverty and inequality dynamics in
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Twongyirwe, R., Mfitumukiza, D., Barasa, B., Naggayi, B. R., Odongo, H., Nyakato, V., &amp; Mutoni, G. (2019). Perceived effects of drought on household food security in <span class="nocase"> South-western Uganda</span>: <span>Coping</span> responses and determinants. <em>Weather and Climate Extremes</em>, <em>24</em>, 100201. <a href="https://doi.org/10.1016/j.wace.2019.100201">https://doi.org/10.1016/j.wace.2019.100201</a>
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@ -2852,34 +2850,50 @@ van de Walle, D., &amp; Gunewardena, D. (2001). Sources of ethnic inequality in
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http://documents.worldbank.org/curated/en/449741576097502078/Challenges-to-Inclusive-Growth-A-Poverty-and-Equity-Assessment-of-Djibouti
"> http://documents.worldbank.org/curated/en/449741576097502078/Challenges-to-Inclusive-Growth-A-Poverty-and-Equity-Assessment-of-Djibouti </a>
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"> http://documents.worldbank.org/curated/en/563561468329654096/2012-Vietnam-poverty-assessment-well-begun-not-yet-done-Vietnams-remarkable-progress-on-poverty-reduction-and-the-emerging-challenges </a>
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http://documents.worldbank.org/curated/en/203361579888116251/Location-Matters-Welfare-Among-Urban-and-Rural-Poor-in-Djibouti
"> http://documents.worldbank.org/curated/en/203361579888116251/Location-Matters-Welfare-Among-Urban-and-Rural-Poor-in-Djibouti </a>
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http://documents.worldbank.org/curated/en/099929206302212659/IDU068dce0c7003280435b099f8040232925d37f
"> http://documents.worldbank.org/curated/en/099929206302212659/IDU068dce0c7003280435b099f8040232925d37f </a>
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