rafmacalaba/datause-encoder-data huggingface dataset:
-8 -

What has happened to the access to education by provinces in other years? Similar household surveys are not available, but enrollment rates by provinces, ranked by per capita income from poor to rich, indicate that the importance of income as a correlate of school enrollment has not changed, the richer the province the higher the enrollment rate in post-primary education.

**(d) Social selectivity.** Chinese educational system suffers from social selectivity. Disparities in drop-out rates at the secondary education level are quite pronounced . Male-female differences in primary education are modest but very significant in secondary education. Drop-out rates also widely vary according to geographic location and level of education: high in poor provinces and secondary education, and vice versa. In secondary education, in rural areas, more females tend to drop out of school than do males (Table 3). The reason is that due to obvious economic difficulties, females from poor families leave the schools earlier to start working at home or to help their families. Inadequate learning environment in poorer provinces is another reason for early exit from school system.

(e) **Affordablity and** Quality. Private costs incurred by the poor are high enough to prevent them from attending schools. The main components of out-of-pocket educational expenditure are tuition, textbooks, stationaries and contribution to schools (Table 9, Annex 1). The figure 6 shows that as a percentage of non-food household expenditure, the poorest quintile spend three times more on education (14.2%) than those in the top quintile (5.5%). The full private cost of school attendance would raise the cost-nonfood expenditure ratio--a measure of affordability--further if the opportunity cost of time in school is considered. For rural area, total private educational expenditures are examined by provinces, ranked by per capita income from poor to rich (Fig 7), and similar conclusion holds--that the prices faced by families in poorest rural provinces are high enough to create an obstacle to raising enrollment rates than those in the wealthy provinces. Infact, figure 8 shows that economic conditions prevent nearly 40 percent of children among the 7-14 age group, corresponding to primary and junior secondary education, from attending schools in the poorest province (quintile I) compared to 14 percent in the wealthiest province (quintile V). Moreover, regarding quality of schooling, one direct measure of the quality gap is the availability of textbooks and teaching materials in schools. The same data confirm that more than 35 percent of the children living in the poorest provinces reported either inadequate supplies of textbooks or other teaching materials as the main reason for not attending schools; corresponding figure for children in the richest province is 21 percent. In higher education, a simple regression with province-level data show that graduation rates are influenced by the
the developing world (Belhaj et al., 2022). From a climatic point of view, Morocco and most of the MENA region countries are largely prone to recurrent arid conditions and drought events are dramatically increasing. The recent Sixth IPCC Assessment Report points to an average GDP loss of about 11 percent in a scenario with the temperature increase of 4.8 that has been projected for 2100, while in Morocco GDP projected impacts range from -3 to +0.4 percent by 2050 relative to 2003 (Pörtner et al., 2022). Recently, Morocco’s Ministry of Equipment and Water has declared that the country experienced the fourth consecutive year of low rainfall and climatic disruptions and is currently facing the worst drought in 30 years.<sup>2</sup> Therefore, the agriculture sector will be continuously exposed to climate shocks that will make production outcomes highly uncertain (Moriondo et al., 2016). Moreover, individuals living in rural areas face a large socioeconomic and cultural divide with respect to those living in urban areas, a situation that can strongly sharpen the climate impacts (Burgess et al., 2014). The literature has largely documented how in developing economies international migration represents an important margin of adjustment for workers to cope with different types of climatic shocks (Gray and Mueller, 2012; Mueller et al., 2014; Dillon et al., 2011; Marchiori et al., 2012; Kaczan and Orgill-Meyer, 2020). Nevertheless, the cost-opportunity offered by migration is largely heterogeneous (Cattaneo and Peri, 2016), and is more likely to take place with moderate but persistent shocks (Di Falco et al., 2022). Crop and local labor diversification also constitute two well-known adaptation strategies in rural areas. However, while crop diversification is often adopted as an _ex ante_ practice (Asfaw et al., 2018; Alfani et al., 2021; Aragón et al., 2021), labor diversification represents an _ex post_ coping strategy used to face unexpected and severe climatic events such as droughts or floods. By and large, a negative shock in agricultural productivity is expected to drive farmers to allocate more time to economic sectors that are less climate-sensitive, generating an agricultural job displacement

> 2 Source: Morocco’s Ministry of Equipment and Water. For further details, see https://www.reuters.com/ business/environment/catastrophic-moroccan-drought-boost-import-subsidycosts-2022-02-18/ and https://joint-research-centre.ec.europa.eu/jrc-news/agricultural-productionthreatened-combination-drought-an.

4
-90-

(14) Birdsall, N. (1988) "Economic Approaches to Por.ulation Growth," in Handbook of Development Economics, Vol. I, H. Chen.ry and T.N. Sriniva&an, eds., North-Holland: Amsterdam.

(15) Birdsall, N. and Griffin, C. (1988) "Fertility and Poverty in Developing Countries," Journal of Policy Modelling, Vol 10, No. 1, pp. 29-55.

(16) Comision Economica para America Latina (1990) "Magnitud de la Pobreza en America Latina en los Anos Ochenta," United Nations, Document LC/L.533.

(17) Coplamar (1983) Macrceconomia de las Necesidades Esenciales en Mexico: Situacion Actual v PersRectivas al Ano 2000, Siglo XXI: Mexico City.

(18) Coplamar (1985&) Las Necesidades Esenciales en Mexico: Situacion Actual v PersRectivas al-Ano 2Q00. Vol. I. Alimentacion, Siglo XXI: Mexico City.

(19) Coplamar (1985b) Las Necesidades Esenciales en Mexico: Situacion Aetual y Perspectivas al Ano 2000. Vo1. I1. Vivienfa, Siglo XXI: Mexico City.

(20) Coplamar (1985c) Las Necesidades Esenciales en Mexico: Situacion Actuai y Perspectivas al Ano 2000. Vol. ". Geografia de la Marginacion, Siglo XXI: Mexico City.

(21) Deaton, A. (19893 "Looking for Boy-Girl Discrimination in Household Expenditure Data," The World Bank Economic Review, Vol. 3, No. 1, pp. 1-15.

(22) Deolalikar, A. (1988) "Do Health and Nutrition Influence Labor Productivity in Agriculture? Econometric Estimates for Rural South India," Review of Economics and Statistics, Vol. 70, No. 2.

(23) Edmunson, W.C. and Sukhatme, P.V. <1990) "Food and Work: Poverty and Hunger?" Economic Develo2ment and Cultural Chan&e, Vol. 38, No. 2, pp. 263-80.

(24) Finkler, K. (1978) "From Sharecroppers to Entrepreneurs: Peasant Household Production Strategies under the Ejido System of Mexico," Econo fc Development and Cultural Change, Vol. 27, No. 1, pp. 103-20.

(25) Foster, J., Greer, J. and Thorbecke, E. (1984) "A Class of Decomposable Poverty Measures," Econometrica, Vol. 52, No. 3, pp. 761-66.

(26) Garcia A., Szretter, H., Duran H and Soza, S. (1986) "Satisfaccion de las Necesidades Basicas: Diagnostico y Propuestas de Politicas Directas," in Buscando la Equidad, Prealc, Organizacion Internacional del Trabajo: Chile.

(27) Garcia Alba, P. (1986) "Especificacion de un Sistema de Demanda y su Aplicacion a Mexico," Estudios Economicos de El Cole io de Merif&, Vol. 1, No. 2, pp. 305-36.

(28) Gil Diaz, F. (1985) "Investment and Debt," in Mexico and the UnitaStates: Studies in Economic Interaction, P.B. Musgrave, ed., Wastview Press: Boulder.
**Table H6: Relationship between food security measures and height-for-age z-scores (Tanzania): Expanded Controls Version**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|VARIABLES|||Height-for-a|ge z-scores|||
|Per capita kcal|0.001<br>(0.058)||||||
|1-SSR||-0.028<br>(0.048)|||||
|1-SSEXR|||-0.001<br>(0.048)||||
|DDS||||0.067<br>(0.051)|||
|PC expenditure|||||-0.027<br>(0.059)||
|Food share||||||-0.070|
|||||||(0.047)|
|Child is female|0.174**|0.172**|0.174**|0.175**|0.173**|0.171**|
||(0.085)|(0.085)|(0.085)|(0.085)|(0.085)<br>-|(0.085)<br>-|
|Age (in months)|-0.060***|-0.060***|-0.060***|-0.060***|0.060***|0.060***|
||(0.010)|(0.010)|(0.010)|(0.010)|(0.010)|(0.011)|
|Age squared|0.001***|0.001***|0.001***|0.001***|0.001***|0.001***|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Household size|0.012|0.013|0.011|0.012|0.009|0.006|
||(0.015)|(0.015)|(0.014)|(0.014)|(0.015)|(0.014)|
|Share of kids under 5|-0.193|-0.199|-0.190|-0.173|-0.168|-0.231|
||(0.372)|(0.372)|(0.374)|(0.372)|(0.372)|(0.374)|
|Femal- headed HH|-0.186|-0.187|-0.188|-0.181|-0.190|-0.175|
||(0.119)|(0.119)|(0.119)|(0.119)|(0.119)|(0.119)|
|_HH Head's Education_|||||||
|Did not finish Primary School|-0.065|-0.062|-0.063|-0.077|-0.060|-0.062|
||(0.130)|(0.131)|(0.131)|(0.131)|(0.131)|(0.130)|
|Finished Primary School|-0.702**|-0.706**|-0.698**|-0.698**|-0.698**|-0.669**|
||(0.313)|(0.311)|(0.314)|(0.324)|(0.311)|(0.311)|
|Did not finish Secondary|||||||
|<br>School|0.076|0.078|0.076|0.056|0.082|0.083|
||(0.237)|(0.235)|(0.235)|(0.236)|(0.236)|(0.235)|
|Finished Secondary School|-0.344|-0.344|-0.346|-0.370|-0.326|-0.363|
||(0.305)|(0.304)|(0.305)|(0.306)|(0.309)|(0.304)|
|Higher than Secondary School|0.287|0.281|0.284|0.277|0.296|0.257|
||(0.353)|(0.352)|(0.350)|(0.348)|(0.350)|(0.355)|

94
FAO, 1996. _Disposal of bulk quantities of obsolete pesticide in developing countries_ . Provisional technical guidelines No. 4., Food and Agriculture Organisation, Rome, Italy. Available at: <u>www.fao.org/WAICENT/FAOINFO/AGRICULT/AGP/AGPP/Pesticid/Disposal/default. htm.</u> OECD, FAO, UNEP, 2000. Report of the OECD-FAO-UNEP Workshop on Obsolete Pesticides, Alexandria, Virginia, 13-15 September.

World Bank, 2002. “Toxics and Poverty: The Impact of Toxic Substances on the Poor in Developing Countries”, World Bank: Washington: DC.

15
recipients to a group that receives no transfers. Specifically, in the systematic review we consider the effects on consumption of all those goods which studies themselves identify as “temptation”, “demerit”, or “anti-social” goods, or those which reflect “misuse” or “waste”. In conducting the review we focus on the effects on alcohol and tobacco consumption, for comparability purposes.

Consumption of temptation goods is measured in a number of ways across studies: notably, expenditure, share of expenditure, and share of individuals consuming the temptation good in the reference period. We include studies using all of these measures, although we focus on expenditure as our primary outcome of interest.

We classify this universe of eligible studies into the following three categories:

- i. Impact Estimates: Randomized-control trials or quasi-experimental studies that estimate the impact of cash transfers on the consumption of temptation goods;

- ii. Level Estimates: Studies that use surveys or focus groups to characterize the number of beneficiaries or amount of transfers used to purchase temptation goods; and

- iii. Qualitative Reports: Studies that discuss reports of the use of transfers to purchase temptation goods, not necessarily by the interviewed household.

# **Search methods for the identification of studies**

The remainder of this section describes how the literature was searched. The various phases of the search process are also summarized in chronological order in Table 2, together with the number of results they yielded. We restricted all searches to papers published since 1997. Our primary electronic search was conducted using Google Scholar.<sup>3</sup> The initial search was completed on January 20<sup>th</sup> , 2014; thus papers that were not yet available at that time are not included in this review. We searched for papers that included both the term "cash transfers", and any one of the terms “alcohol”, “tobacco”, “cigarettes”, "temptation goods", or "demerit goods". This search yielded a total of 4,290 articles. The titles and sources of these papers were reviewed and the majority of papers discarded due to irrelevant subject areas, leaving 434 papers. These were then checked for duplicates and 23 were removed, leaving 411 papers. These 411 papers were reviewed by reading their abstracts and conducting a word search within each article for appearances of the key search terms listed above, so as to identify the context within which they are referenced by the article. 179 papers were deemed irrelevant and removed on the basis of this review process – typically because the terms of interest

> 3 The search produced results drawn from databases including Science Direct, the Social Science Research Network, and the Wiley Online Library, as well as the databases of a number of international organizations – notably the Overseas Development Institute, United Nations Development Programme, the United Nations Children's Fund, the World Bank, the International Initiative for Impact Evaluation (3ie), the World Food Program – and universities.

6
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Policy Research Working Paper 5778

# **Abstract**

Between 2000 and 2002, the authors followed 1621 individuals in Delhi, India using a combination of weekly and monthly-recall health questionnaires. In 2008, they augmented these data with another 8 weeks of surveys during which households were experimentally allocated to surveys with different recall periods in the second half of the survey. This paper shows that the length of the recall period had a large impact on reported morbidity, doctor visits, time spent sick, whether at least one day of work/school was lost due to sickness, and the reported use of self-medication. The effects are more pronounced among the poor than the rich. In one example, differential recall effects across income groups reverse the sign of the gradient between doctor visits and per-capita expenditures such that the poor use health care providers more than the rich in the weekly recall surveys but less in monthly recall surveys. The authors hypothesize that illnesses—especially among the poor—are no longer perceived as “extraordinary events” but have become part of “normal” life. They discuss the implications of these results for health survey methodology, and the economic interpretation of sickness in poor populations.

This paper is a product of the Human Development and Public Services Team, Development Research Group. 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://econ.worldbank.org. The authors may be contacted at jdas1@worldbank.org, jhammer@princeton.edu, and csanchezparamo@worldbank.org.

_The Impact Evaluation Series has been established in recognition of the importance of impact evaluation studies for World Bank operations and for development in general. The series serves as a vehicle for the dissemination of findings of those studies. Papers in this series are part of the Bank’s Policy Research Working Paper Series. 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 the governments they represent._ Produced by the Research Support Team
**Figure 15. Services are growing fast ...**

<!-- Start of picture text --> Contributions to GDP growth (%)<br>7<br>Services<br>Industry<br>6 A Overall GDP griculture<br><!-- End of picture text --> <!-- Start of picture text --> 4<br>3<br>2<br><!-- End of picture text --> <!-- Start of picture text --> 1<br><!-- End of picture text --> <!-- Start of picture text --> 2002<br>Source:<br><!-- End of picture text --> <!-- Start of picture text --> 2003<br><!-- End of picture text --> <!-- Start of picture text --> 2004<br><!-- End of picture text --> <!-- Start of picture text --> 2006<br><!-- End of picture text --> _Source:_ National Statistical Coordination Board, 2007.

**Figure 16. ... and are less capital-intensive**

<!-- Start of picture text --> 25<br>20<br>Industry Investment<br>15<br>10<br>Agriculture Investment<br>Services Investment<br>5<br>0<br>1980 1983 1986 1989 1992 1995 1998 2001 2004<br>% GDP<br><!-- End of picture text --> _Source:_ Author’s elaboration on National Statistical Coordination Board, 2007.

**FDI are also flowing to less capital-intensive activities.** In 2006, net FDI - growing but still small - reached $2.35 billion, compared with $1.85 billion in 2005.<sup>33</sup> The inflows were sustained by the country’s macroeconomic gains, including the fiscal and external position, and the declining inflation. Net FDI went mainly to non-capital-intensive niches in manufacturing and services. In manufacturing, the investments went to chemicals, electronics and air-conditioning system. In services, the inflows were in BPO, shipping crew training and medical research.

> 33 However, 43 percent of the FDI was in the form of inter-company loans rather than new equity.

23
incorrectly attribute a much larger variation in the dependent variables to the variables we include as regressors than is true. Similarly, in (22), it is possible that the unobservable climate, soil and other topographical conditions that render a village unsuitable for forest growth also make it unsuitable for agriculture which would in turn limit human settlement and give rise to low population densities. On the other hand, villages endowed with a more benign geography in the form of fertile soil, adequate rainfall and easier access to local markets are likely to have higher population densities, higher levels of agricultural technology and thus, ceteris paribus, higher incomes and higher land prices.

In order to control for these time invariant village characteristics that could bias our estimates, we exploit the fact that we have panel data which allow us to observe villages at two points in time. Particularly, by differencing both equations across the two time periods, we can sweep out the fixed effects and end up with, and where _D_ is the operator.

Although the fixed-effect specification eliminates time-invariant characteristics of villages that may bias our coefficients, it is still imaginable that the _change_ in village unobservables between the years of our analysis are correlated with the change in the regressors during the same period. For example in (23), if we interpret _D￿zt_ as an adverse weather shock then this shock could be negatively correlated with village population as households may send out more migrants. By the same token, households that already have migrants working abroad may receive a larger remittance in response to this shock. This is in fact one of the major endogeneities that we have to contend with even after controlling for fixed effects. Similarly a positive weather shock in the first period could independently increase forest area while at the same time increasing village income by triggering adoption of better agricultural technology.

In order to control for contemporaneous effects of weather shocks, we include a village level rainfall variable in all of our specifications. Additionally, to account for the possibility that these first period shocks could have an effect on future realizations of the control variables (good rainfall in the first period leading to better agricultural technology, higher fertility and higher incomes in the subsequent periods), we need instruments that are correlated with the change in income, wages, land prices and population, but are uncorrelated with the shocks. Village population density in 1991 and road density in 1975 provide us with a valid set of instruments for the equilibrium equation.<sup>15</sup> For the reduced form equation, we use population density in 1991, road density in 1975 and an artificial

> 15The equilibrium equation is under-identified right now as I don’t have enough pre-period variables I can use as instruments.

22