rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 10. Percentage Rates of Backward and Forward Integration to Manufacturing GVCs by Sources and Destination of Imports and Exports of Intermediate Inputs: Group of Benchmark Countries (1995 vs. 2015**

<!-- Start of picture text --> 100<br>90<br>85.3<br>80<br>76<br>70 67.6<br>60<br>50 52.5<br>40 43.1<br>30 32.6<br>20<br>10<br>0<br>-10 West Europe East Asia China India USA Germany<br>-20<br>Backward Integration (2015) Forward Integration (2015)<br>Δ GVC (2015/1995) Δ Backward Integration (2015/1995)<br>Δ Forward Integration (2015/1995) GVC (2015)<br><!-- End of picture text --> _Source_ : Authors computation using data from EORA database.

**Figure 11. Percentage Rates of Backward and Forward Integration to Manufacturing GVCs by Sources and Destination of Imports and Exports of Intermediate Inputs: Africa, Non-Resource Rich Group of Countries (1995 vs. 2015)**

<!-- Start of picture text --> 100<br>90<br>80<br>70 72<br>60<br>50<br>40 41.7<br>34.2<br>30 30.5<br>20 18.1<br>10<br>0 2.6<br>-10 West Europe East Asia China India USA Germany<br>-20<br>Backward Integration (2015) Forward Integration (2015)<br>Δ GVC (2015/1995) Δ Backward Integration (2015/1995)<br>Δ Forward Integration (2015/1995) GVC (2015)<br><!-- End of picture text --> _Source_ : Authors computation using data from EORA database.

31
Hoff, Karla and Joseph E. Stigliz (1993) “Imperfect Information and Rural Credit Markets: Puzzles and Policy Perspectives” In K. Hoff, A. Braverman, and J. E. Stiglitz, eds., _The Economics of Rural Organization: Theory, Practice, and Policy_ . New York: Oxford University Press.

Hoff, Karla and Joseph E. Stiglitz (1998) “Moneylenders and Bankers: Price-Increasing Subsidies in a Monopolistically Competitive Markets” Journal of Development Economics 55: 485-518.

Kanbur, S M, (1979). "Impatience, Information and Risk Taking in a General Equilibrium Model of Occupational Choice," _Review of Economic Studies_ , Wiley Blackwell, vol. 46(4), pages 707-18, October.

Karlan, D and J. Morduch (2010), “Access to Finance”, Chapter in _Handbook of Development Economics,_ Vol. 5, Edited by Dani Rodrik and Mark Rosenzweig.

Klein, Roger and Francis Vella (2010) “Estimating a Class of Triangular Simultaneous Equations Models Without Exclusion Restrictions” _Journal of Econometrics,_ 154, 154-164 Klein, Roger and Francis Vella (2009a) “A Semiparametric Model for Binary Response and Continuous Outcomes under Index Heterocedasticity” _Journal of Applied Econometrics_ , 24: 735-762 Klein, Roger and Francis Vella (2009b) “Estimating the Returns to Endogenous Schooling Decisions via Conditional Second Moments” _Journal of Human Resources_ , 44(4), pp. 1047-1065 Lewbel, Arthur (2012) “Using Heteroskedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models”, _Journal of Business and Economic Statistics_ , 30, 67-80.

Mallick, Debdulal, 2012. "Microfinance and Moneylender Interest Rate: Evidence from Bangladesh," _World Development_ , Elsevier, vol. 40(6), pages 1181-1189.

Mallick, Debdulal and Nabin, Munirul, ( 2010). "Where NGOs Go and Do Not Go?," MPRA Paper 27185, University Library of Munich, Germany.

Matin, Imran, et al. (2008), “Crafting a Graduation Pathway for the ultra-poor: Lessons and Evidence from a BRAC Programme”, _RED Working Paper, BRAC_ .

Matin, Imran (1998), “Mis-Targeting by the Grameen Bank: A Possible Explanation”, _IDS Bulletin_ , Volume 29 Issue 4, Pages 51 – 58.

Millimet, Daniel L. and Rusty Tchernis (forthcoming) “Estimation of Treatment Effects without an Exclusion Restriction: with an Application to the Analysis of the School Breakfast Program”, _Journal of Applied Econometrics._ Maurer, J, Roger Klein and Francis Vella, (2011). "Subjective Health Assessments and Active Labor Market Participation of Older Men: Evidence from a Semiparametric Binary Choice Model with Nonadditive Correlated Individual-specific Effects _," The Review of Economics and Statistics_ , MIT Press, vol. 93(3), pages 764-774, August.

Rabbani, Mehnaz, Vivek A. Prakash, and Munshi Sulaiman, (2006) “Impact Assessment of CFPR/TUP: A Descriptive Analysis Based on 2002-2005 Panel Data”, BRAC TUP Working Paper No. 12, July 2006.

29
could give rise to omitted variable bias. As long as the omitted variables in question are constant over time, the inclusion of district fixed effects will suffice to remove any bias. If there are timevarying omitted variables correlated with both conflict intensity and the explained variables of interest, the inclusion of district fixed effects will not remove all potential biases, and additional steps must be taken to shed light on the causal impact of the insurgency. In section IV, I test for the presence of such time-varying omitted variables and discuss how I address potential threats to identification.

Despite the civil conflict, Nepal has experienced steady growth in real gross GDP (5 percent per year between 1995/96 and 2003/04), an additional increase in disposable income due to substantial flows of remittances from abroad (representing 12.4 percent of the GDP), a steady decrease in poverty over the period (from 42 percent in 1995/96 to 31 percent in 2003/04), and an improvement in human development indicators, such as primary school enrollment (up from 57 percent to 73 percent) and child mortality, which decreased by 5 percent per year (World Bank 2005; Macours 2011).

However, the positive outlook for Nepal as a whole may mask unequal progress due to heterogeneous conflict intensity across districts. Indeed, national trends may hide a slower decrease in poverty, or even an increase in poverty, in more conflict-affected areas. In this paper, I exploit variation in the intensity of exposure to violent conflict by birth cohort, survey year, and district to investigate differential changes in primary educational attainment and completed years of education across districts that experienced varying degrees of violence.

# III. **<<A>>** Data

DHS have been conducted in a number of developing countries as part of the Measure DHS project, a reputable USAID-funded project. The second and third DHS in Nepal were conducted in 2001 and 2006, respectively, and are nationally representative repeated cross-sections. The timing 8
Self-help groups (SHGs) are the most common form of microfinance in India. By March 2012, about 103 million households had a member in a SHG (NABARD, 2013). Their primary aim is to help the poor to save and borrow. At the outset, SHG members pool their savings to create a common fund and give out small loans to one another. At a later stage, SHGs are able to open savings accounts with commercial banks and apply for loans. Because of some features of their functioning, such as the high frequency of meetings and the mutual trust necessary for their stability, SHGs can impact the lives of their members beyond the mere financial sphere.

We study the long-term, non-financial impact of a SHG program that focuses on women only. Using first-hand data collected in the Indian state of Odisha, we document how collective actions undertaken by SHGs impact the variety of public goods that the Gram Panchayat - which is the lowest official authority - deals with. In our research area, each Gram Panchayat is divided into several wards. A representative, known as _ward member_ is elected in each of those wards. He is the official spokesperson of the villagers: his main responsibility is communicating the ward’s problems and needs to the officials in charge at a higher administrative level, i.e. to officials who are senior to him. The ward member is the only official appointment for these duties. Yet, we find evidence that SHG members undertake collective actions that de facto overtake or complement the work of the ward member. They visit higher officials as well, or intervene directly to solicit a solution for a variety of problems affecting their ward. We show that these collective actions impact the ward member’s choices: it becomes more likely that he starts tackling public goods that SHGs consider important.

We believe the contribution of our findings is twofold. First, to the best of our knowledge, ours is the first paper assessing the long-term effect of microfinance groups on social outcomes (up to 13 years after their creation). Our data suggest that considering such a long time span is crucial since, in our sample, an average SHG undertakes collective actions for the first time after 3 years of weekly meetings only. Second, our results put forward how microfinance can also be used as a political economy mechanism to improve the lives of the poor.

In September 2010, we interviewed all SHGs created by the NGO PRADAN (Professional 1
**<u>Table 2.2. Water Potential and Land Distribution by Basins</u>**

|No|NAME|Area<br>(km2)|Annual Basin<br>Efficiency<br>(l/s/km2)|Average<br>Annual Flow<br>(km<sup>3</sup>)|Farming<br>Land<br>(1,000<br>ha)|Irrigable<br>Land (1,000<br>ha)|
|---|---|---|---|---|---|---|
|1|Maritza-Ergene|14,560|2.9|1.33|1,095.3|1,078.0|
|2|Marmara|24,100|11.0|8.33|865.7|730.0|
|3|Susurluk|22,399|7.2|5.43|850.0|755.9|
|4|North Aegean|10,003|7.4|2.09|367.6|316.3|
|5|Gediz|18,000|3.6|1.95|667.2|623.4|
|6|K.Menderes|6,907|5.3|1.19|222.4|194.8|
|7|B.Menderes|24,976|3.9|3.03|1,044.3|907.4|
|8|West<br>Mediterranean|20,953|12.4|8.93|437.4|406.6|
|9|Antalya|19,577|24.2|11.06|451.2|448.1|
|10|Burdur Lakes|6,374|1.8|0.50|251.4|249.5|
|11|Akarcay|7,605|1.9|0.49|364.4|359.9|
|12|Sakarya|58,160|3.6|6.40|2,814.3|2,681.1|
|13|West Black Sea|29,598|10.6|9.93|855.0|640.8|
|14|Yeşilırmak|36,114|5.1|5.80|1,617.2|1,401.2|
|15|Kızılırmak|78,180|2.6|6.48|4,049.8|3,761.1|
|16|Konya inland|53,850|2.5|4.52|2,182.8|2,134.9|
|17|East<br>Mediterranean|22,048|15.6|11.07|438.3|327.8|
|18|Seyhan|20,450|12.3|8.01|764.7|714.0|
|19|Orontes|7,796|3.4|1.17|376.2|331.7|
|20|Ceyhan|21,982|10.7|7.18|779.8|713.7|
|21|Euphrates|127,304|8.3|31.61|4,293.8|4,111.3|
|22|East Black Sea|24,077|19.5|14.90|712.6|350.7|
|23|Çoruh|19,872|10.1|6.30|326.2|<br>303.4|
|<br>24|<br>Aras|27,548|5.3|4.63|642.0|641.1|
|25|Lake Van|19,405|5.0|2.39|436.5|433.3|
|26|Tigris|57,614|13.1|21.33|1,148.2|1,137.6|
||TOTAL|779,452|209.3|186.05|28,054.3|25,753.6|

_Source: DSI, 2007._ Sectoral consumption of water is presented in Table 2.3. Total human and utility water consumption is increasing steadily with population and income growth, totaling 6.2 km<sup>3</sup> per annum in 2004. The share of the population served by adequate water from the network connected at home or standpipes, reached 85 percent in rural areas, and 98 percent in urban areas. Annual water allocated to industry is about 4.1 billion m<sup>3</sup> supplied mainly from groundwater resources.

11
<!-- Start of picture text --> 100 100<br>90 90<br>80 80<br>70 Urban 70 IDPs in settlements<br>60 60<br>Nomads<br>50 50<br>Rural<br>40 40<br>30 30<br>Poverty line (US$ 1.9 PPP)<br>20 Poverty line (US$ 1.9 PPP) 20<br>10 10<br>0 0<br>0 2 4 6 8 0 2 4 6 8<br>Daily consumption expenditure per capita (US$) Daily consumption expenditure per capita (US$)<br>Source: Authors' calculations. Source: Authors' calculations.<br>% of population % of population<br><!-- End of picture text -->

# 7. Conclusions

The lack of data in Somalia poses a risk to evidence‐based interventions aimed at alleviating poverty and inequality. To mitigate this risk, the World Bank implemented Wave 2 of the Somali High Frequency Survey to better understand the welfare conditions of the population and to estimate the incidence of poverty. An analysis of the data set has been published as the Somali Poverty and Vulnerability Assessment (World Bank, 2018b).

This paper contributes to several themes in the literature on poverty measurement and data collection in the context of conflict and fragility, involving hard‐to‐survey populations. It outlines how challenges associated to the context of insecurity and lack of statistical infrastructure in Somalia were overcome through four methodological and technological adaptations: i) building a probability‐based population sampling frame; ii) minimizing the time spent in the field using the Rapid Consumption Methodology; iii) estimating poverty in completely inaccessible areas with correlates derived from satellite imagery and other geo‐spatial data; and iv) employing a special sampling strategy for the nomadic population.

Further improvements in terms of human resource capacity should be considered to minimize disruptions to the quality of the data, besides field team training and stringent security protocols. Also, future applications should consider refining the model to predict poverty from satellite imagery by incorporating predictors with higher spatial frequencies, as well as data on building footprints, which are likely to improve the estimates. Other alternatives are thresholding some of the distance variables or applying a sigmoid transformation to capture variations in small areas. Furthermore, the accuracy of satellite‐based imputations should be assessed based on a reference data set, ideally in a more stable environment.

36
- Grantham, H. S., Duncan, A., Evans, T. D., Jones, K. R., Beyer, H. L., Schuster, R., Walston,

- J., Ray, J. C., Robinson, J. G., Callow, M., Clements, T., Costa, H. M., DeGemmis,

- A., Elsen, P. R., Ervin, J., Franco, P., Goldman, E., Goetz, S., Hansen, A., ... Watson, J. E. M. (2020). Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity. _Nature Communications_ , _11_ , 5978.

- Ingram, D. J. (2020). Wild Meat in Changing Times. _Journal of Ethnobiology_ , _40_ (2), 117–130. Ingram, D. J., Coad, L., Milner-Gulland, E., Parry, L., Wilkie, D., Bakarr, M. I., Ben ́ıtez-L ́opez,

- A., Bennett, E. L., Bodmer, R., Cowlishaw, G., et al. (2021). Wild meat is still on the menu: Progress in wild meat research, policy, and practice from 2002 to 2020. _Annual Review of Environment and Resources_ , _46_ , 221–254.

- IPBES. (2019). _Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the intergovernmental science-policy platform on biodiversity and ecosystem services_ (tech. rep.). IPBES Secretariat. Bonn, Germany.

- Klain, S. C., Olmsted, P., Chan, K. M., & Satterfield, T. (2017). Relational values resonate broadly and differently than intrinsic or instrumental values, or the New Ecological Paradigm. _PLoS ONE_ , _12_ (8), e0183962.

- LaCerva, G. (2016). Untamed and rare: access and power in DRC’s emerging luxury bushmeat trade. In C. J. P. Colfer, B. B. Basnett, & M. Elias (Eds.), _Gender and Forests: Climate change, tenure, value chains and emerging issues_ (pp. 243–260). Earthscan from Routledge.

- Lucas, A., Kumakamba, C., Saylors, K., Obel, E., Kamenga, R., Makuwa, M., Clary, C., Miningue, G., McIver, D. J., Lange, C. E., Mbala Kingebeni, P., & Muyembe-Tamfun, J. J. (2022). Risk perceptions and behaviors of actors in the wild animal value chain in Kinshasa, Democratic Republic of Congo. _PLoS ONE_ , _17_ (2), e0261601.

35
Td is the handling and transport charges from the border to the domestic market; Cd is the transport, processing and marketing charges from farm gate to the domestic market.

# _Demand_

The national demand for rice in Sierra Leone is a function of the growth in population, the increase in income and the income elasticity of demand. The rate of increase in national demand can be given by the following formula: ND = pr + ie*pc Where: ND is the rate of increase in demand; pr is the rate of population growth; ie. is the income elasticity of demand for rice and pc is the rate of increase in real per capita income.

Based on the United Nations projections, Sierra Leone population will grow at about 2.3 percent per annum over the next five years, assuming constant fertility.<sup>14</sup> The real per capita GDP is also projected to be relatively flat to declining over the same period.<sup>15</sup> Assuming income elasticity of demand between 0.5 and 1, Sierra Leone’s national rice demand would grow in line with its projected population growth of 2.3 percent or marginally below.

Since rice is a normal and staple food for Sierra Leoneans, a priori, it is expected that the price elasticity of demand would be negative and low (inelastic). That is, an increase in the price of rice would lead to only a small decrease in the quantity of rice demanded. Kargbo (1979) used OLS technique and linear, semi-log and log-log model specifications to estimate demand elasticities for rice in Sierra Leone. His estimations yielded elasticities of -0.294, -0.309 and -0.309 for the linear, semi-log and log-log specifications respectively. This was the only study that could be found in a very thorough, but nonexhaustive search of the Literature on Sierra Leone. A review of the broader literature across several countries showed very variable own price elasticity of demand for rice ranging from as low as -0.10 for South Africa to as high as -0.77 for Tanzania (Table 9).

**Table 9: Own price elasticity of demand for rice in selected countries**

|**Country**|**Elasticity**|**Date**|**Methodology**|**Author(s)**|
|---|---|---|---|---|
|Indonesia|-0.13|1985|OLS|Koo et al|
|**Sierra Leone**|**-0.294**|**1979**|**OLS**|**Kargbo**|
|Thailand|-0.42|1978|OLS|Wong|
||-0.392|2008|AIDS|Isvilanonda and Kongrith|
|Taiwan|-0.61|1996|AIDS|Huang and Bouis|
|Bangladesh|-0.45|1994|AIDS|Ahmed and Shams|
|Philippines|-0.50|2013|LA/AIDS|Lantican et al.|
|Tanzania|-0.77|2014|LA/AIDs|Lazaro Edith Ezra|
|South Africa|-0.10|2002|AIDs|Agbola et al.|

Note: OLS =Ordinary Least Squares; AIDS = Almost Ideal Demand System; LA/AIDs= Linear Approximate Almost Ideal System

> 14 United Nations, World Population Prospects, 2019.

> 15 See IMF Country Report No. 18/371. December 2018.

18
# **10 References**

Armitage, Sir Arthur (1980), _Report of the Inquiry into Lorries, People and the Environment,_ presented to the Minister of Transport the Rt. Hon. Norman Fowler, Her Majesty's Stationery Office, London, December.

Averech, H. and J.J. Johnson (1962), 'Behaviour of the Firm under Regulatory Constraint", _American Economic Review,_ vol. 52, pp. 1053-1069.

Coordinaci6n General de Concesiones (1996), _Concession General Program,_ Ministry of Public Works, Santiago, July.

_----------------------------------------------- (1998), Infraestructura Publica y Programa General ae Concesiones,_ Ministerio de Obras Publicas, Santiago.

Engel, E., R. Fisher y A. Galetovic (1996), 'Highway Franchising in Chile', _Estudios Publicos,_ N.61, 5-37, Santiago, [in Spanish].

------------------------------------------- (1997a), 'How to auction an urban road franchise', _Estudios Publicos,_ N.67, 177-214, Santiago tin Spanish].

------------------------------------------- (1997b), 'Highway Franchising: Pitfalls and Opportunities', _American Economic Review Papers and Proceedings,_ 87:2, 68-72.

------------------------------------------(1997c), 'Infrastructure Franchising and Government Guarantees', Chapter 4 in T. Irwin, M. Klein, G. Perry and M. Thobani (eds), _Dealing with Public Risk in Private Infrastructure,_ The World Bank, Washington, D.C.

------------------------------------------(1 997d), 'Privatizing Roads: A New Method for Auctioning Highways', Viewpoint Note, N.1 12, The World Bank, Washington D.C. Reprinted in S. Smith (ed.), _The private Sector in Infrastructure,_ 109-112, The World Bank, Washington D.C.

------------------------------------------- (1998), 'Least-Present-Value-of Revenue Auctions and Highway Franchising', NBER Working Paper 6689, Cambridge.

Fishbein, G. and S. Babbar (1996), 'Private Financing of Toll Roads', RMC Discussion Paper' Series, N' 117, The World Bank.

G6mez-Ibafiez, J.A. (1999), 'Las Autopistas Privadas de Peaje de Mexico', Caso practico N' _5._ Curso Sobre Privatizaci6n y Regulaci6n de Servicios de Transporte, Las Palmas de Gran Canaria. 5-10 April.

_50_
where _αik,t_ , _βijk,t_ , and _γjk,t_ are parameters capturing sales/supply-potential factors of _k_ in _i_ , the trade freedom of _k_ between _i_ and _j_ , and the demand/consumption potential of _k_ in _j_ , all in logs and at time/month _t_ . When only trade but no domestic sales data are available, the unilateral frictions on _k_ enter _γjk,t_ only.

We proceed in two steps to identify the parameters _ηk_ and _ξk_ of interest: (i) estimate _γjk,t_ as importer-product-month fixed effects from monthly bilateral product-level export data _xijk,t_ on 180 sensitive products; (ii) estimate the impact of unilateral trade frictions on product _k_ from where _gjk,t_ is defined as in (2), and _γ_ ̃ _jk_ , _λ_<sup>_γ_</sup> _t_<sup>and</sup><sup>_uγ_</sup> _ik,t_<sup>areimporter-product-fixed,month-fixed,and</sup> importer-product-month residual effects, respectively.

As all ∆ _jk,t_ are binary indicators, all parameters _η_ measure (direct) semi-elasticities of imports. Note that under the assumption of a constant-elasticity-of-substitution model with (direct) trade � elasticity (1 _− σk_ ),<sup>3</sup> one can scale _γjk,t_ by (1 _− σk_ ) to obtain the iceberg-trade-cost increment associated with pandemic-related policies alone by product, importer, and month. E.g., _τjk,t_ = 0 _._ 02 then means that trade costs are (directly plus indirectly) raised by pandemic-related policies for product _k_ and country _j_ in month _t_ by about two percentage points. Apart from reporting on _τjk,t_ , we (trade-weighted) aggregate these trade costs effects for each of the 247 countries and each month _t_ to obtain _τj,t_ . Finally, we aggregate the same trade-cost effects across countries _j_ to obtain _τt_ for the average country and sensitive product.

# **4 Results**

In the following, we first display the evolution of _τk,t_ for selected sensitive products – namely, garments, ventilators, vaccines and tests. The results are summarized in Figure 1.

> 3The values of _σk_ are obtained from Fontagn ́e et al. (2022).

4