rafmacalaba/datause-encoder-data huggingface dataset:
|System|mated using the<br> across products<br>ple of countries<br>gal index “Legal<br>lts for countries<br> standard errors<br>(6)<br>Lib<br>legal index<br>bove median|0.275***<br>(0.033)<br>-1.847***<br>(0.080)<br>-0.162***<br>(0.032)<br>Yes<br>Yes<br>Yes<br>Yes<br>16,250|
|---|---|---|
|Median of Legal|ll regressions are esti<br> baseline hazard rate <br>(4)-(6) for the subsam<br>ilable data on the le<br>) and (6) report resu<br>azard ratios. Robust <br>% levels, respectively.<br>(5)<br>Lib<br>legal index<br>below median<br>a|0.022<br>(0.039)<br>-1.602***<br>(0.071)<br>0.065***<br>(0.021)<br>Yes<br>Yes<br>Yes<br>Yes<br>26,126|
|bove of the|ted at time _t_0. A<br>allow for diferent <br>ple and columns <br>ountries with ava<br>ndex. Columns (3<br>fcients and not h<br>e 10%, 5%, and 1<br>(4)<br>Lib<br>legal index<br>available|0.138***<br>(0.027)<br>-1.694***<br>(0.055)<br>0.007<br>(0.016)<br>Yes<br>Yes<br>Yes<br>Yes<br>42,376|
|Below and A|d market that star<br> Estimations also <br> for the whole sam<br>rt results for all c<br>ue for this legal i<br>3. We report coe<br> signifcance at th<br>(3)<br>All<br>legal index<br>above median|0.246***<br>(0.035)<br>-1.446***<br>(0.072)<br>-0.028<br>(0.028)<br>Yes<br>Yes<br>Yes<br>Yes<br>23,011|
|ort Survival,|try _c_ to the worl<br>ime fxed efects. <br>)-(3) show results<br> (1) and (4) repo<br> below-median val<br>umn (4) of Table <br> denote statistical <br>(2)<br>All<br>legal index<br>below median|0.070*<br>(0.036)<br>-1.058***<br>(0.064)<br>0.095***<br>(0.015)<br>Yes<br>Yes<br>Yes<br>Yes<br>54,154|
|ng-Term Exp|oduct _k_ from coun<br>ing-country and t<br>ble 3. Columns (1<br> period. Columns <br>for countries with <br>orresponds to col<br>es. *, **, and *** <br>(1)<br>All<br>legal index<br>available<br>|0.149***<br>(0.025)<br>-1.187***<br>(0.049)<br>0.074***<br>(0.013)<br>Yes<br>Yes<br>Yes<br>Yes<br>77,165|
|able 8: Stock Market Liberalization and Lo|pendent variable is the hazard rate for an export spell of pr<br>oportional Hazard Model (Cox, 1972) and control for export<br>ing product _k_ as strata variable. Variables are defned in Ta<br>perienced stock market liberalization during the 1980-1997 <br> and Property Rights”. Columns (2) and (5) report results <br>ove-median value for this legal index. Full set of controls c<br>d at (exporting country)*time (_c ∗t_0) level are in parenthes|beralization x Distance to comparative advantage<br>beralization<br>ce to comparative advantage<br>t of controls<br>ting country FE<br>FE<br>ct stratifcation<br>vations|
|T|The de<br>Cox Pr<br>by defn<br>that ex<br>System <br>with ab<br>clustere|StM li<br>StM li<br>Distan<br>Full se<br>Expor<br>Time <br>Produ<br>Obser|

44
|Refuses Sex<br>Burns Food|(5)<br>(6)|-0.089<br>-0.087<br>(0.048)<br>(0.045)<br>[0.106]<br>[0.051]|0.485<br>0.574|7.92<br>6.85<br>17,873<br>18,072||bles in columns 2–6 are indicators|A 2SLS model is estimated where|o mother tongue instruction (MTI)|teractions for regions in which two|timate is from a unique regression.||
|---|---|---|---|---|---|---|---|---|---|---|---|
|Argues with<br>Husband|(4)|-0.117<br>(0.055)<br>[0.033]|0.553|6.31<br>18,027|16).|e dependent varia|en 1970 and 1988.|measure _I_FPE<br>_zy_<br>, tw|ctively, and the in|for age. Each es||
|Neglects<br>Children|(3)|-0.020<br>(0.052)<br>[0.698]|0.617|6.82<br>18,065|, 2011, and 20|olence, and th|en born betwe|E) intensity|change, respe|s, and a cubic|kets.|
|Beating justifed if wife:<br>Goes Out<br>w/out Permission|(2)|-0.080<br>(0.044)<br>[0.071]|0.582|6.64<br>18,067|ian Demographic and Health Survey (in years 2005|from 0 to 5 of acceptable reasons for domestic vi|0 otherwise. The sample includes all married wom|instrumented with the free primary education (FP|measures for MTI regions without and with script|r and zone fxed efects, zone-specifc linear trend|n in parentheses; _p_-values are shown in square brac|
|s for<br>(of 5)|||||he Ethiop|he count|rue and|chooling,|note the|birth yea|nd show|
|ptable Reason<br>stic Violence|(1)|-0.399<br>(0.171)<br>[0.020]|2.80|7.94<br>17,658|n data from t|column 1 is t|elieved to be t|cted level of s|MTI<br>_y_<br>, which de|ssions include|he zone level a|
|Acce<br>Dome|||||based o|able in|nt is b|e predi|and _I_<br>_z_|l regre|ed at t|
|||�<br>f Schoolingizy|of Dependent<br>orm Cohorts)|ge F-Statistic<br>N|thor’s analysis|dependent vari|1 if the stateme<br>|chooling_izy_ is th|easures _I_MTI-T<br>_zy_|ns occurred. Al|rrors are cluster|
|||Years o|Mean <br>(Pre-Ref|First Sta|_Source_: Au|_Note_: The|that equal <br>|�<br>Years of S|intensity m|interventio|Standard e|

A.30
**Table 5** . Distribution of gender norm index and personality <u>groups, by men and women (</u> _weighted_ <u>)</u>

||**Pooled S**<br>**_Mean_**|**ample**<br>**_SD_**|**Women**<br>**_Mean_**|<br>**_SD_**|**Men**<br>**_Mean_**|**_SD_**|**_T-tests_**|
|---|---|---|---|---|---|---|---|
|**_Main explanatory variables_**||||||||
|<br>Gender role attitudes index|41.38|11.12|40.31|10.06|42.75|12.22|-2.504***|
|Personality Groups||||||||
|<br>Impulsiveness|2.47|0.56|2.46|0.55|2.47|0.57|0.0095|
|<br>Work centrality|4.14|0.75|4.1|0.78|4.2|0.7|-0.0951***|
|<br>Tenacity|3.91|0.72|3.87|0.74|3.96|0.7|-0.0961***|
|<br>Polychronicity|2.13|0.67|2.15|0.69|2.09|0.64|0.0541**|
|<br>Locus of control|2.88|0.7|2.93|0.7|2.81|0.71|0.104***|
|Achievement|3.75|0.58|3.73|0.59|3.78|0.56|-0.0755***|
|Power motivation|3.35|0.81|3.28|0.83|3.44|0.79|-0.174***|
|Organized person|4.08|0.76|4.11|0.77|4.05|0.75|0.0779**|
|<br>Optimism|3.57|0.52|3.56|0.52|3.59|0.53|-0.0355|
|Observations|2,478||1375||1103|2478||

28
|**Table A4: Asian Development Bank Country Policy**<br>**Data Provider**<br>Asian Development Bank<br> <br>|**and I**<br>|**nstit**<br>|**ution**<br>|**al As**<br>|**sess**<br>|**ment**<br>|**s (ASD)**<br>|
|---|---|---|---|---|---|---|---|
|**Description**<br>Multilateral development bank he<br> <br>|adquar|tered|in Ma|nila,|the Ph|ilippi|nes|
|**Website**<br>www.adb.org<br> <br>||||||||
|**Data Source**<br>Country Policy and Institutional A<br> <br>|ssess|ments||||||
|**Type**<br>Expert Assessment<br> <br>||||||||
|**Respondents**<br>Asian Development Bank count<br>comparability<br> <br>|ry eco|nomi|sts, s|ubject|to c|entral|ized review for|
|**Frequency**<br>Annual since 2000<br>||||||||
|**Coverage**<br>Asian Development Bank client c|ountrie|s||||||
|**Public Access**<br>Since 2005, only for countries<br>Development Bank.|eligib|le fo|r con|cessio|nal le|ndin|g by the Asian|
|**Description**<br>Indicators on 16 dimensions of po<br>coded on a 6-point scale. CPIA in<br>the Asian Development Bank.|licy a<br>dicato|nd in<br>rs ar|stitutio<br>e used|nal p<br>to all|erform<br>ocate|ance<br>conce|. Responses are<br>ssional loans by|
|2008|2007|2006|2005|2004|2003|2002|2000<br>1998<br>1996|
|**Voice and Accountability**<br>NA||||||||
|**Political Stability and Absence of Violence**<br>NA||||||||
|**Government Effectiveness**<br>||||||||
|Quality of Public Administration<br>X<br>|X|X|X|X|X|X|X|
|Efficiency of Revenue Mobilization<br>X<br>|X|X|X|X|X|X|X|
|Quality of Budgetary & Financial Management<br>X|X|X|X|X|X|X|X|
|**Regulatory Quality**<br>||||||||
|Trade policy<br>X<br>|X|X|X|X|X|X|X|
|Competitive environment<br>X|X|X|X|X|X|X|X|
|**Rule of Law**<br>||||||||
|Property rights<br>X|X|X|X|X|X|X|X|
|**Control of Corruption**<br>||||||||
|Anticorruption and Accounting Institutions<br>X|X|X|X|X|X|X|X|
|**Country Coverage**<br>**28**<br> <br>|**29**<br>|**26**<br>|**25**<br>|**26**<br>|**26**<br>|**25**<br>|**25**<br>**..**<br>**..**<br>|
|**Year of Publication**<br>**2008**|**2007**|**2006**|**2005**|**2004**|**2003**|**2002**|**2000**<br>**..**<br>**..**|

43
## **Box 5: The role of community responses**

The **Commission on AIDS in Asia** (2008) noted that community participation is critical to successful HIV prevention for people engaged in risk behaviors—studies show that more than 80 percent of drug users could be reached within six months with condoms and cleaning kits through peer outreach workers, whereas interventions relying on local leaders, social workers, and medical staff reached only 25 percent. It also highlighted the importance of community involvement in influencing norms, for example, sex‐worker‐led safe sex efforts such as in the 100 percent condom use program in Thailand and the Sonagachi project in India.

A study **in South Africa** (M’Zamani et al. 2007) found that 90 percent of community organizations were involved in prevention and 70 percent in care and support. Involvement with treatment was more limited, with a focus on treatment literacy. The emphasis of nonstate actors was on general rather than technical services. Community organizations were more active in care and support—more than 70 percent work with OVC—while government institutions were more active in the delivery of such services as voluntary counseling and testing (HCT) and PMTCT.

The **role of communities in the transport sector** deserves mentioning, in particular the role of unions, which often are involved in the provision of preventive services, both for workers in the transportation business but also for those involved in the construction of roads and other infrastructure projects (International Transport Workers’ Federation 2005 and Altaf 2006).

# **_3.3. Actors_**

The typology of community responses can also be defined in terms of the actors that initiate or drive responses. Actors can be categorized as including:

- Individuals within communities, including those living with HIV

- Community initiatives, structures, and organizations

- Local, national, sub‐regional and regional NGOs, FBOs, and networks

- International NGOs, FBOs, and networks (funding and supporting implementation)

- Multilateral, bilateral, and UN agencies (providing funds)

- National and local governments

A review of World Bank documents and published literature suggests that community responses are initiated by individuals or existing structures either in response to the needs of others in the community or in response to their own needs.

With respect to the needs of others, Foster (2005) describes small‐scale, informal actions by groups of individuals motivated to care for those in need, such as PLHIV and OVC. UNAIDS 14
# **1 Introduction**

Low- and middle-income countries spend an average of 1.5% of GDP on social assistance [World Bank, 2022]. These public programmes aim to protect the poor and vulnerable from shocks, help them cope with crises, support investment in human capital and enjoy a decent standard of living throughout the lifecycle [ILO, 2021]. Policymakers design a social protection programme with a specific target population in mind. A crucial aspect of policy implementation, commonly referred to as the targeting problem, is how to identify households or individuals who are members of the target population and therefore eligible for the programme. Due to limited fiscal resources, social assistance tends to be limited to the most economically disadvantaged segment of society. Consequently, socio-economic criteria are a prevalent eligibility category [Grosh et al., 2022], whether applied in isolation – such as in a food subsidy programme for the poor – or in combination with another eligibility category, such as conditional cash transfer programmes that support poor families with school-age children.

In settings where nearly all households’ income is reported to the tax authority, means testing via income tax records can determine socio-economic eligibility. However, countries’ average informal employment share is above 50% in Asia Pacific, South Asia and Sub-Saharan Africa, while the poverty rate of the informally employed is around six times higher than that of those in formal employment [Ohnsorge and Yu, 2021]. This paper is concerned with such settings, where means testing is unviable due to a lack of tax records among poorer households. There, proxy means testing (PMT) has become a widespread targeting approach since its description by Grosh and Baker [1995].

PMT is a statistical approach that relies on two large-scale surveys. The first, conducted at regular intervals in most countries, is a socio-economic population sample survey that serves as training data for the PMT predictive model. The second is a targeting survey that collects current data to determine household eligibility. Due to the large population coverage of many social protection programmes, targeting surveys typically need to be administered to a significant share of the population<sup>1</sup> . Given the high cost of such extensive, country-wide data collection efforts, targeting surveys are typically conducted on a multiannual basis when carried out as a national survey sweep [Lindert et al., 2020]. Infrequent surveys delay assessment of new programme applicants and re-assessment of existing beneficiaries, resulting in programmes’ irresponsiveness to changing household circumstances.

If budgets were not limited, the most accurate PMT approach would be

> 1For example, the social registries that store targeting data covered 87%, 75% and 40% of Pakistan’s, Brazil’s and Indonesia’s populations respectively in 2015-17 [Leite et al., 2017], amounting to total records of ca. 360 million people.

2
5 Shifts in t-he relative importance of FDI in the total flow of financial resources to the developing countries are appa'rent in table 2-2. Although FDI flows were only 12.8 percent of the total net flow of financial resources in 1980, they had increased to 20.9 percent in 1986, and according to preliminary figures, to 33.4 percent in 1987. This reflects the slowdo~'n in bank lending co developing countries. In table 2-2 it is also apparent that FDI flows<sup>to</sup> developing countries have declined considerably as a percentage of total world FDI --from 29.5 percen±t in 1975, to 23.8 percent in 1980 and to 13.7 peicent in 1988. The counterpart to this decline was a large increase in FLI in the industrial countries, especially the United States. The amoun; of FDI in relation to the recipient developing countries' economies declineJ uncil 1986 after peaking in 1981-82.

Table 2-2. Relative Magnitudes of -D; Flows to All Developing Countries, 1975-1988 (percentage)

|Year|Total World<br>FDI flows|<br>Net_f.ow_of<br>Finan-ial<br>resources<br>to developing<br>countries|GDP of<br>developing<br>countries<br>|Gross domestic<br>investment in<br>developiong<br>countrles|
|---|---|---|---|---|
|1975|29.5|15.0|0.8|3.0|
|1976|27.3|10.8|0.5|2.1|
|1977|25.7|12.2|0.5|1.8|
|1978|24.0|12.2|0.5|1.8|
|1979|24.8|13.6|0.5|2.0|
|1980|23.8|12.8|0.5|1.8|
|1981|24.6|14.6|0.6|2.3|
|1982|25.5|14.7|0.6|2.2|
|1983|21.7|13.7|0.4|1.8|
|1984|20.0|15.3|0.5|1.8|
|1985|24.9|20.2|0.5|2.2|
|1986|14.6|20.9|0.5|2.1|
|1987|14.3|33.4|0.7|2.9|
|19888|13.7|--|0.7|2.7|

-- Not available

a. Estimated figures.

Source: IMF
WPS3904

# Farm Productivity and Market Structure: Evidence from Cotton Reforms in Zambia*

Irene Brambilla† Guido G. Porto‡

### Abstract

This paper investigates the impacts of cotton marketing reforms on farm productivity in rural Zambia. The reforms comprised the elimination of the Zambian cotton marketing board that was in place since 1977. Following liberalization, the sector adopted an outgrower scheme, whereby firms provided extension services to farmers and sold inputs on loans that were repaid at the time of harvest. There are two distinctive phases of the reforms: a failure of the outgrower scheme, and a subsequent period of success of the scheme. Our findings indicate that the reforms led to interesting dynamics in cotton farming. During the phase of failure, farmers were pushed back into subsistence and productivity in cotton declined. With the improvement of the outgrower scheme of later years, farmers devoted larger shares of land to cash crops, and farm productivity significantly increased.

JEL CODES: O12 O13 Q12 Key Words: state monopoly, privatization, marketing board

## World Bank Policy Research Working Paper 3904, May 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

*We wish to thank A. Khandelwal for excellent research assistance. T. Jayne, J. Nijhoff, and B. Nsemukila allowed us access to the Post Harvest Survey data collected by the Central Statistical Office in Lusaka, Zambia. We thank J. Altonji, R. Betancourt, M. Duggan, P. Goldberg, C. Udry, and seminar participants at Di Tella, Lausanne, Maryland, Virginia and Yale for useful comments and discussion. Financial Assistance from the World Bank is greatly appreciated.

†Yale University and NBER. Department of Economics, Yale University, P. O.Box 208264, New Haven, CT 06520. Email: irene.brambilla@yale.edu.

‡ World Bank. Development Research Group, Mailstop MC3-303, 1818 H Street, Washington, D.C. 20433. Email: gporto@worldbank.org.
prevalence of intercropping across most of the study countries suggest substantial opportunities for more holistic, landscape-level approaches in policy and other practical efforts seeking to reconcile biodiversity conservation, climate change mitigation, and poverty reduction goals. Given the geographic and socioeconomic diversity encompassed in our study countries, our results also suggest that such approaches may also be applicable in other countries across Africa as does a growing case study literature (e.g. Milder et al., 2014).

# 3.3 Contribution of Trees on Farms to Rural Livelihoods was Non‐negligible

Products harvested from trees on farms in the study countries were used mainly for self-consumption or sale (Figure 2). The relative mix of these uses varied among the study countries. In Uganda, fruit tree products were used primarily for self-consumption, whereas in Malawi such trees served solely as a source of cash income. That fruit trees were used significantly for self-consumption in countries like Uganda (and also Ethiopia) suggests that such trees may play an important role in household food security, as shown in a variety of contexts across Africa (Garrity et al., 2010). In the case of tree cash crops, production was mainly used for sale, as expected, though in Ethiopia a non-negligible share was also used for own consumption (linked to coffee consumption) and in Nigeria to other uses.

Turning to the contribution to total income, income from trees on farms contributed on average 6% of overall annual gross household income (i.e. among tree and non-tree growers alike). The income share averaged 7% in Nigeria, Tanzania and Uganda, and only 3% in Malawi (Table 4). We note that estimates for Malawi may be low because information on tree cash crops was not provided in LSMS-ISA survey data. For those households with trees on their farms the average contribution across the study countries was almost three times as much, i.e. 17% and about 32% as a share of agricultural gross income.<sup>12</sup> Surprisingly, the contribution of trees on farms to gross income among tree growers was highest in Nigeria, even though tree growing occurred least frequently there, suggesting a high degree of specialization among tree growing households. At 18.7% income from trees among tree growing households is also more important in Uganda. Clearly, income from tree growing can be quite important, with the larger share typically coming from tree cash crops (14% of gross income among tree growers). Nonetheless, even though much less commented upon, income among fruit trees still contributes 5% of

> 12 By comparison, a recent cross national study of households living in or near forests found that natural forests in Africa contributed 21% to household incomes and plantation forests less than 1% (Angelsen et al., 2014).

12
⎯ political clout, and governance ability in determining which states are able to attract funds and use them effectively. This needs to be studied carefully in further research.

There is little evidence of ICDS program impact on overall child nutrition status. However, these results need to be interpreted with caution. As we indicated above, using cross-sectional data can lead to various kinds of biases in estimations of the effectiveness of the program. A conclusive evaluation of program impact will have to wait until panel data are available. Yet many studies have highlighted problems with the implementation of the ICDS program, which would limit its impact and are consistent with our result.

In sum, we find limited evidence that the ICDS program is meeting its goals of reducing child malnutrition in India. Some modifications are needed towards this end. Firstly, program coverage and fund allocation needs to be shifted towards states with the highest prevalence of child malnutrition. Secondly, efforts have to be made to ensure that funds are fully utilized in the few states where this is not the case. Thirdly, the impact of the program on recipients can be enhanced by changing some aspects of program design and implementation. With such changes, the substantial resources allocated to the ICDS can be used more effectively for raising future generations of healthy children.

# **Bibliography**

- Alderman, Harold, Jesko Hentschel, and Ricardo Sabates. 2003. With the help of one’s neighbors: externalities in the production of nutrition in Peru, _Social Science and Medicine_ , 56: 2019-2031.

- Allen, Lindsay H. and Stuart R. Gillespie. 2001. What Works? A review of the efficacy and effectiveness of nutrition interventions, Manila: UN Administrative Committee on Coordination Subcommittee on Nutrition, in collaboration with the Asian Development Bank.

- Anderson, Mary Ann, James E. Austin, Joe D.Wray, and Marian F. Zeitlin. 1981. _Nutrition Interventions in Developing Countries, Study 1: Supplementary Feeding_ . Cambridge MA: Oelgeschlager, Gunn and Hain.

- Beaton, George, and Hossein Ghassemi. 1982. Supplementary feeding programs for young children in developing countries, _American Journal of Clinical Nutrition_ 34 (supplement):864-916.

- Behrman, Jere R. and John Hoddinott. 2001. Program Evaluation with Unobserved Heterogeneity, Selective Implementation and Imperfectly Targeted Beneficiaries: the Mexican _Progresa_ impact on child nutrition. Paper presented at the Northeast Universities Development Consortium (NEUDC) Conference, September 28-30, 2001, Boston.

- Behrman, Jere R., Harold Alderman, and John Hoddinott. 2004. Hunger and Malnutrition, Copenhagen Consensus Challenge Paper.

- (http://www.copenhagenconsensus.com/Files/Filer/CC/Papers/Hunger_and_Malnutrition_07 0504.pdf)

- Berggren G. Hebert J. Waternaux C. 1985. “Comparison of Haitian children in a nutrition intervention program with children in the Haitian National Nutrition Survey. “ _Bulletin of the World Health Organization_ 63:1141- 1150.

15