rafmacalaba/data-use-mentions-extended huggingface dataset:
current policy debate focuses on calculating how much financial support is needed to achieve internationally-agreed development goals for reducing poverty and improving key social indicators, namely, the Millennium Development Goals (MDGs) adopted by the United Nations Assembly in 1999.

The results of this experiment are summarized in Table 5. They indicate that, through the channels highlighted in the previous experiments, a permanent increase of 5 percentage points of the aid-GDP ratio could lead to a reduction in the proportion of poor by about 20 percentage points between 2002 and 2015, if either the household survey linkage is used or the partial growth elasticity is -1.8. One of the main mechanisms, of course, is through an increase in public investment, which rises by about 4.9 percentage points (in terms of GDP) in the long run. The growth rates of real GDP per capita and disposable income follow an inverted U-shape pattern. Despite the sharp increase in aid, there is no evidence of a “Dutch disease” effect; in fact, the real exchange rate depreciates (because the increase in domestic supply puts downward pressure on domestic prices), leading to higher exports (which increase by about 4.4 percentage points of GDP in the long run). Higher income and tax revenue lead to a lower budget deficit (despite the increase in spending), and a large drop in the external debt-GDP and debt service-exports ratio in the long run. With a partial elasticity of -0.5, however, poverty drops by only 6 percentage points during the simulation period. If the actual elasticity is indeed close to -0.5 (and there are indications that this may well be the case), these results suggest that to reduce poverty by 20 percentage points between 2002 and 2015 the increase in aid should amount to almost 17 percentage points of GDP. This estimate is, of course, only a rough order of magnitude, given that it does not account for nonlinearities. But it does show how dramatically different the results can
conjecture that if a lender cannot fully adjust the interest rate of a subsidized loan (e.g., an earmarked loan in the context we study), a bank with market power might increase the pricing of other loans to the same client, weakening the transmission of the government subsidy. We establish a series of hypotheses related to the use of cross-product pricing strategies and test them using granular loan-level data. We evaluate two alternative hypotheses that might explain the average increase in interest rates: the credit reallocation and credit risk channels. Our findings are consistent with the view that banks with market power transfer part of the cost of earmarked lending into other lending products.

We provide novel evidence about the limits of government programs that rely on subsidies to reduce the cost of credit. These programs typically require banks to set interest rates in certain ranges. Our analysis illustrates why, even under such strategy, lenders with market power can prevent the transmission of subsidies to final borrowing costs.

# **References**

<mark>Ayyagari, M., Demirguc-Kunt, A. and Maksimovic, V., 2011. Small vs. young firms across the world: contribution to employment, job creation, and growth. The World Bank.</mark> <mark>Bartik, A., Cullen, Z., Bertrand, M., Glaeser, E.L., Luca, M. and Stanton, C., 2020. How Are Small Businesses Adjusting to COVID-19? Early Evidence from a Survey.</mark> _<mark>(April 6, 2020). Harvard Business School NOM Unit Working Paper</mark>_ <mark>, (20-102), pp.20-102.</mark> <mark>Berger, A.N. and Udell, G.F., 1995. Relationship lending and lines of credit in small firm finance.</mark> _<mark>Journal of Business</mark>_ <mark>, pp.
An unexpected and sudden inflow of refugees might bring both benefits and constraints to the local economy, which might then create or shrink opportunities for livelihood diversification and agricultural commercialization. Hence, it is important to understand how livelihood strategies of people in host communities change in the presence of refugees. The current paper attempts to address whether refugee inflow expands or diminishes opportunities for livelihood diversification and agricultural commercialization.

Our findings show that refugees bring substantial benefits to host communities through creating more jobs that people engage in as a secondary occupation, and raising demand for livestock products. Refugee inflow has a positive impact on diversification of livelihood activities as a secondary occupation and on commercialization of livestock products. Specifically, a 1 percent increase of the refugees’ presence<sup>5</sup> leads to a 2.7 and 15.9 percent increase in the diversification of livelihood activities as a secondary occupation and value of livestock product sale, respectively. It should be noted that this analysis is taking place during a period where refugees in Ethiopia were prohibited by law from seeking work outside designated camps. This has changed after 2019 because of the revised Ethiopian Refugee Law. These effects tend to be heterogeneous across regions and to a limited extent, vary depending on the gender of the household head. The negative effects tend to be concentrated in Gambella, a region that hosts most of the refugee population in Ethiopia and where the refugee population is as large as the population of the region. Overall, compared to women-headed households, households with a male head seem to benefit through increased diversification of activities as a secondary

> 4 Region refers to the administration level 1 from the Database of Global Administrative Areas (GADM). The nearest region to the refugee camp is identified as the one that has the shortest straight distance to the refugee camp among all neighboring regions in the major refugee source countries.

> 5 As explained above, refugee presence is the number of refugees (population) in the nearest refugee camp to the household location weighted by the household’
*|**14.4%**|

<u>Notes: The findings are based on 1,719 parcel observations and the responses that were provided by 931 couples, about</u> 55.5 percent of which had more than one garden. H = Owned by Husband, J = Jointly Owned, W = Owned by Wife; “No” = Reported No Ownership or Rights.

# **4. Results**

# **4.1 (Individual-Level) Ownership of and Rights to Agricultural Land**

Table 4 presents a summary table of the estimates of the coefficient 1 from equation 1 (i.e. the effect of following the business-as-usual approach to respondent selection vis-à-vis conducting ββ individual interviews) – derived from the regressions that are estimated on the whole, and separately for male and female sub-samples, and for a range of ownership and rights constructs as the dependent variables. We show that under the business-as-usual approach, the levels of exclusive reported and economic ownership of agricultural land are higher among men, while the levels of joint reported and economic ownership of agricultural land decline among women. The effect on the joint reported ownership among men is also negative, albeit significant only at the 10 percent level. On the other hand, for the rights to sell and bequeath, the business-as-usual approach to respondent selection leads to an increase for both men and women, driven by a positive effect on reporting of joint rights (as reflected above in Table 2). Given the survey treatment effects on 20
pesticide overuse. Steps could include stricter enforcement of existing regulations, the promotion of integrated pest management programs, and further research on alternative pest control methods.

# **References**

- Antle, J. M. and P. L. Pingali 1994. Pesticides, Productivity, and Farmer Health: A Philippine Case Study. _American Journal of Agricultural Economics_ , **76** : 418-430.

- Bangladesh Bureau of Statistics (BBS) 2001. Statistical Yearbook of Bangladesh, December 2003, Planning Division, Ministry of Planning, Government of the Peoples Republic of Bangladesh.

- Blais, J. M., D. W. Schindler, D. C. G. Muir, L. E. Kimpe, D. B. Donald and B. Rosenberg 1998. Accumulation of Persistent Organochlorine Compounds in Mountains of Western Canada. _Nature_ **395** : 585-588.

- Cropper, M. 1994. Economic and Health Consequences of Pesticide Use in Developing Country Agriculture: Discussion. _American Journal of Agricultural Economics_ **76** : 605-607.

- Davies, V., H. Freed, and F. W. Whittemore 1982. _An Agromedical Approach to Pesticide Management: Some Health and Environmental Considerations_ . Miami, Fla., USA: University of Miami School of Medicine in cooperation with the Agency for International Development (USAID) and Consortium of International Crop Protection.

- Dung, N. H. and T. T. T. Dung 1999. Economic and Health Consequences of Pesticide Use in Paddy Production in the Mekong Delta, Vietnam.  EEPSEA Research Report Series.  Available at: <u>http://www.eepsea.org/en/ev-8427-201-1-DO_TOPIC.html.</u>

- Dung, N. H., T. C. Thien, N. V. Hong, N. T. Loc, D. V. Minh, T. D. Thau, H. T. L. Nguyen, N. T. Phong and T.
Figure 4. The Correlation between the Export Orientation Index and Productivity <!-- Start of picture text --> 11<br>9<br>7<br>0 .2 .4 .6 .8 1<br>Export Orientation Index<br>Log of Productivity<br><!-- End of picture text --> Source: Authors’ calculation using HIES 2016. Note: The line is the fitted line.

We also examine to what extent farmers’ crop mix is diversified. Diversification tends to be associated with risk-coping strategies <mark>(Di Falco and Chavas in Ethiopia, 2009; McCord et al. in Kenya, 2015); r</mark> esilience to climate shocks <mark>(Birthal and Hazrana in India, 2019; Lin, 2011; and M</mark> ulwa and Visser in Namibia, 2020); food security <mark>(Bellon et al. in Ghana, 2020; Waha et al. for 18 African countries, 2018); p</mark> overty reduction <mark>(Michler and Josephson in Ethiopia, 2017), and sustainable agriculture in Sri Lanka (D</mark> harmasiri 2008). On the other hand, some papers recognize the role of crop specialization in raising agricultural productivity <mark>(Huffman and Evenson in the United States, 2001; Latruffe et al. in Poland, 2005; Kurosaki in West Punjab, 2003). How diversification versus specialization would affect agricultural productivity appears to depend on the country and the context.</mark> Following common practice in the literature, we measure a farmer’s level of crop diversification using the Simpson Index of Diversification (SID)<sup>9</sup> : i where SIDi is the Simpson Index of Diversification for farmer _i_ and is the proportionate cultivated area dedicated to the _k_ th crop. A high value indicates that a farmer cultivates many iikk PP crops, in an evenly distributed way
Using administrative data from EF, we examine the rate of program take-up by the treatment and control groups for the 2010, 2011 and 2012 cohorts in Table 6.<sup>44</sup> The table shows a high degree of uptake (65 to 74 percent) among the treatment group, but also a high rate of participation among the control group.<sup>45</sup> Between 26 percent and 36 percent of the individuals in the control group participated in the EF training course that they applied for, even though their scores did not qualify them for admission.<sup>46,47</sup> In the presence of imperfect compliance, standard impact evaluation methods produce intent-to-treat (ITT) estimates, as described in section IV. However, the relatively high degree of noncompliance in our study leads to a likely downward bias in our ITT estimates, which compare a treatment group in which not everyone received treatment to a control group in which some people did receive treatment, hence diluting the impact of the program. We present an alternative set of ATT estimates in Annex 3 (available upon request from the authors) in which we compare those who actually complete training to those who do not, irrespective of treatment assignment.<sup>48</sup> In our view, the ITT results serve as a lower bound for the estimated program impact while the ATT results serve as an upper bound.

# **VI. Short-Run Results of the EF Program**

This section describes the impact of the Employment Fund’s training programs for the combined 2010, 2011 and 2012 samples. We measure outcomes approximately one year after the start of training.<sup>49</sup> We start with a description of our analysis on likelihood of being in the treatment group. We proceed with the shortterm impacts of the EF program on the full sample and on various demographic and socioeconomic subgroups.

## **a. First-Stage Estimation of Propensity Scores**

At the
5 of 21 Shuttle Radar Topography Mission (SRTM) (Farr et al. 2007), at 30-meter spatial resolution were used to define floodplains. Given its focus on agricultural landscapes, urban areas were not directly mapped. Instead, urban pixels were extracted from Landsat’s Global Human Built-up and Settlement Extent (HBASE) Dataset (Wang et al. 2017). The HBASE provides global 30-meter spatial resolution information on settlement extent for 2010.

Using these data, we developed an LCLU mapping framework adapted to the region’s agricultural landscapes to produce a 30-meter resolution map of northern Nigeria for the baseline year 2015. The framework implemented a knowledge-based expert system (KBES) that relied on dense stacks of Landsat 8 images and exploited inter- and intra-annual vegetation dynamics and contextual information to map the main components of the study region’s land surfaces (Srinivasan and Richards 1990). Recent research highlights the role of expert knowledge to advance remote sensing–based agricultural monitoring (Bégué et al. 2018), even if such experts lack remote sensing experience (for example, field extension agents). These systems constitute a useful alternative when the lack of consistent training and validation data limit the use of supervised learning systems. Expert knowledge is commonly stored as a set of rules in a knowledge base. Subsequently, the information is passed to an inference mechanism that interprets and assigns class memberships to pixels. A KBES has been successfully implemented in a number of applications, such as protected areas conservation (Szantoi et al. 2016), crop classification (Choudhury et al. 2012; Cohen and Shoshany 2002; El Hajj et al. 2009; Janssen and Middelkoop 1992), and urban mapping (Amarsaikhan et al. 2013).

We built a knowledge base that established production rules using spectral, temporal, and spatial constraints to identify the main agricultural systems and natural vegetation types in the study area (Cohen and Shoshany 2002). The production rules were not necessarily conclusive, but they provided a degree of evidence in favor of
of the variables of interest to the occurrence of any type of disaster the same year the disaster occurs and in the years following the disaster. We estimate the model using annual data for high and middle-income countries during the period 1975-2008. While low-income countries are also of interest, data availability and the importance of aid flows for government financing makes them

> 1 These types of models use the cross-country dimension of the data to increase the power of the estimation of time series models, and have been routinely used when short time series data is available, as it is the case in this paper.

2
Policy Research Working Paper 8893

# **Abstract**

Cambodia has recorded both rapid economic growth and macroeconomic stability in recent decades despite (or thanks to) high levels of dollarization. Previous studies on dollarization in Cambodia have largely focused on examining its causes and estimating seigniorage losses. As an attempt to further explore the effects of dollarization in Cambodia, this paper examines its impact on the competitiveness of the export sector. The main results, based on a vector autoregression estimation of quarterly data over 1994Q4–2016Q4, indicate that a positive US interest rate shock has a negative impact on Cambodia’s trade balance with the European Union, its main trading partner, as it leads to appreciation of the US dollar. Furthermore, this shock also leads to a significant decrease in Cambodia’s international reserve levels during the first two quarters following the shock. The surrendering of monetary and exchange rate independence seems to affect the competitiveness of the tradable sector negatively as well as exacerbate financial sector vulnerability to solvency and liquidity risks.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at msanchezmartin@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or
- Hillson, R., Alejandre, J. D., Jacobsen, K. H., Ansumana, R., Bockarie, A. S., Bangura, U., Lamin, J. M., Malanoski, A. P., and Stenger, D. A. (2014). Methods for determining the uncertainty of population estimates derived from satellite imagery and limited survey data: a case study of bo city, sierra leone. _PloS one_ , 9(11):e112241.

- Horvitz, D. G. and Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe. _Journal of the American statistical Association_ , 47(260):663–685.

- Jean, N., Burke, M., Xie, M., Davis, W. M., Lobell, D. B., and Ermon, S. (2016). Combining satellite imagery and machine learning to predict poverty. _Science_ , 353(6301):790–794.

- Li, G. and Weng, Q. (2005). Using landsat etm+ imagery to measure population density in indianapolis, indiana, usa. _Photogrammetric Engineering & Remote Sensing_ , 71(8):947–958.

- McBride, L. and Nichols, A. (2016). Retooling poverty targeting using out-of-sample validation and machine learning. _The World Bank Economic Review_ .

- Mullainathan, S. and Spiess, J. (2017). Machine learning: an applied econometric approach. _Journal of Economic Perspectives_ , 31(2):87–106.

- Oakridge National Laboratory (2018). Documentation page of the landscan. Retrieved from https://landscan.ornl.gov/documentation on August 3rd 2018.

- Socioeconomic Data and Applications Center (2018). Gridded Population of the World (GPW). Retrieved from http://sedac.ciesin.columbia.edu/data/collection/
>refers to the mothers’ cohort with</mark> _<mark>s</mark>_ <mark>=1 if the mother was in utero,</mark> _<mark>s</mark>_ <mark>=2 if she was 0 to 2 years old and</mark> _<mark>s</mark>_ <mark>=3 if she was 3 to 5 years old. The analysis is restricted to mothers born after January 1, 1979 (less than 16 years old at the time of the first refugee inflow in 1993) and throughout our analysis our control group consists of mothers born between 1979 and 1988 (more than 5 years of age in 1993).</mark>

# **6.** **<mark>Results</mark>**

## **6.1** **<mark>Means Difference Tests</mark>**

<mark>Before moving forward with the econometric analysis, we provide simple means t-tests on the main outcomes of interest between refugee and non-refugee affected areas before the refugee crisis using the 1991-1992 DHS. Table 1 provides the results splitting the sample into its 1991 and 1992 components to allow for some heterogeneity between the two years covered by the DHS. While it would be plausible to find differences given the different geographical areas considered, we do not find any statistical difference in our main outcomes of interest (HAZ and stunting). This provides a nice benchmark for the econometric analysis.</mark> <mark>Similarly to the geographical comparison, in Table 2 we compare 0-5 and 6-16 y.o. cohorts of children using the 1991-1992 DHS (mothers in 2015/2016). As before, we could expect some differences but the t-tests show no difference in the main outcomes considered (HAZ and stunting). In Table 2, we also</mark> 15
24

# Location of Contraceptive Markets

For firms that lack production facilities vithin a particular country, the decision to market products and make investments in that country depends on the size and potential profitability of sales to both public and private sectors. Because so many couples in much of the developing vorld rely on the public sector for contraceptives, sales to the public sector are quite important to pharmaceutical producers (the public/private sector breakdown is given in Table III.1). Private companies vie to vin contracts from USAID, UNFPA, other international donors or local governments to supply the public sector clinics.

Some firms have argued that they just meet marginal costs when supplying to donors and governments at vell belov vholesale market prices and that they do not cover research and investment costs on these transactions. In part, the economies of scale in production allov them to sell to public entities at a reduced rate. Other firms say that they are able to defray their fixed costs through commercial sales. Further, some firms take a longer run viev and believe that the pay off to investments made in developing country markets over the past fev decades vill occur in the coming years as these markets grow and are committed to long available products. Other firms have stated that it becomes difficult to "break into" a nev market vhen other firms are already vellestablished.

Firms that supply contraceptives to the public sector may have advantages over competitors at gaining a foot-hold in the private sector. There is evidence from the last round of the Contraceptive Prevalence Surveys (CPS) that in some countries, vhile most vomen obtain their initial supply of the pill from a clinic, they are most likely to have obtained their pill resupply from a pharmacy (Tunisia CPS, 1983). Thus the type of oral contraceptives (color, size, brand and hormone mixture) provided in the public sector are likely to be in greater

**al.tp:Vaiy Planlinq** Paper **Iwbol.)**
incentives, and the process might delay the project for several months. “This does not encourage me to apply,” he explained, “for me, time is money.” Officials at local Departments of Commerce seem to be well aware of the circumvention of approvals by private firms. As one official said, “they (the private firms) don’t come to us because, frankly, they want nothing from us,” adding “Nor is there much we can do about it.” Foreign exchange control, which is supposed to be an effective gatekeeper, fails to work in many cases because firms can draw money from their established overseas accounts or swap currencies with other firms with overseas accounts. Unsurprisingly, off-the-record estimates by MOC officials of private overseas projects ran from two to three times that captured by the MOC database.

10