rafmacalaba/datause-encoder-data huggingface dataset:
aminations for grades 5 and 7 and grade repetition for all grades. Primary schools in India may have only primary classes (grades 1 through 5), only upper-primary classes (grade 6 through 8), or both (grade 1 through 8). The data provide information about whether the school offers only primary classes, only upper-primary classes, or both. The school management categories in the data include (1) Department of Education, (2) Tribal/Social Welfare Department, (3) Local body, (4) Private Aided, (5) Private U- naided, (6) Others, and (7) Un-recognized. We construct three aggregate categories - government run schools (1 and 2), private schools (4 and 5) and others (3 , 6, and 7). In addition to these features, the data report ongoing incentive schemes in various schools to increase enrollment. Various schemes running in schools before MGNREGA provide free uniforms, textbooks, stationery, and attendance fellowships. One concern with the DISE data is that since schools self-report the data, there is measurement error in the data.<sup>13</sup> We address the implications of measurement error in the data for our results in subsequent sections.

The district level characteristics are from the Census of India 1991 and 2001. These include total population, population growth rate, percentage of female population, literacy rate, female literacy rate, percentage of the Scheduled Castes and Scheduled Tribes population, and percentage of working population. Agricultural wages for 1996-97 and total output per agricultural worker for 1990-93 come from the Planning Commission’s 2003 report.

Table 1 provides the summary statistics of outcome variables by phases of MGNREGA districts. Consistent with the roll-out criterion, the better-off Phase III districts have better educational outcomes. Conditional on being enrolled, 92 percent of the children pass exams in grade 5 in Phase III districts, whereas 88 percent do in Phase I districts.

> 13These data are collected using a district level administrative structure. School principals fill a standardized survey about the school. The data are manually checked at various levels for completeness, accuracy, and inconsistencies. States also implement checks. NEUPA has commissioned an external audit of the school data. These audits check 5 percent of the schools chosen randomly from at least 10 percent of the districts from each state. The auditors also visit the schools. These audits have established that the enrollment data reported by the principals are remarkably accurate.

8
- In the worst case, the boom-bust case, the repayment of debts through fiscal adjustment will reduce spending and the real exchange rate will depreciate during the middle-periods.

# **_Macroeconomic and Other Effects of Alternative Spending Strategy_**

Table 16 shows the effects on Niger’s economy under alternative spending plan. We make the following observations:

- When there is significant investment and productivity, GDP (non-oil) may grow by 6.8 to 7.5 percent a year and consumption may rise by 7 to 7.7 percent a year. Although there are differences across spending plans, the differences are quantitatively minor. This is true also in the two borrowing cases.

- Even so, the “Borrow-Now” strategy has the potential of raising average output growth slightly more if spending raises investment and productivity, despite some adjustment in the middle periods. We discuss this further in the next subsection.

- When resources are consumed rather than invested primarily, GDP growth will not improve relative to the base case in all spending plans.  Aggregate consumption will grow slightly more than the base case, but nowhere near the cases where investment raises output growth.

- Even so, when resources go to the households through lump-sum transfers from the government, there is still a slight increase in real private investment compared to the base case – for example in the PIH scenario, real investment grows annually by 4.63 percent, while in the base scenario it grows annually by 4.47 percent. This is because households will save a small portion of these transfers; the increase in total savings results in a modest increase in the annual growth rate of real private investment. This pattern holds for all simulations in which resources are given to the households, compared to the base case.

- Although equity impact, which is not the focus of this study, is best investigated with more household data and approaches that merge macro and micro modeling (such as Go et al. 2010), some broad distribution effects among the three basic types of households (rural, urban, and capital-owners) are discernible from these two and contrasting avenues of spending. When additional resources are used by the government to increase public infrastructure, there will be higher GDP and household income growth if there is productivity growth arising from the investments. Owners of capital receive 95 percent of their income from capital returns, so they generally benefit from infrastructure spending that improves the returns to capital. The relative distribution of factor income in the infrastructure spending case is similar to the base

29
**<u>Table 5: Factors affecting land parcels’ transferability</u>**

||<br>|<br>**Can bequeat**|<br>**h**||**Can sell**||**Woman**|**has a say**|
|---|---|---|---|---|---|---|---|---|
||**All**|**State**|**Cust.**|**All**|**State**|**Cust.**|**bequest**|**Sale**|
|**Panel A. Baseline regres**|**sion**||||||||
|Has title|0.195***|0.161***||0.190***|0.168***||-0.114**|-0.100*|
||(0.038)|(0.040)||(0.038)|(0.041)||(0.052)|(0.053)|
|Title in process|0.212***<br>(0.039)|0.146***<br>(0.052)|0.250***<br>(0.063)|0.230***<br>(0.043)|0.167***<br>(0.058)|0.302***<br>(0.067)|-0.110**<br>(0.052)|-0.151***<br>(0.052)|
|Has inf. certificate|0.219***|-0.070|0.252***|0.285***|0.017|0.315***|-0.009|-0.110**|
||(0.040)|(0.084)|(0.041)|(0.038)|(0.109)|(0.040)|(0.052)|(0.050)|
|Residential parcel|0.032***|0.136***|0.014|0.039***|0.118***|0.024**|-0.024|-0.014|
||(0.011)|(0.035)|(0.011)|(0.011)|(0.037)|(0.012)|(0.030)|(0.039)|
|Customary tenure|0.084**|||-0.009|||0.014|0.073|
||(0.034)|||(0.026)|||(0.065)|(0.073)|
|R-squared|0.217|0.300|0.179|0.275|0.321|0.170|0.284|0.270|
|**Panel B. Control functio**|**n approach**||||||||
|Has title|0.195***|0.162***||0.190***|0.168***||-0.111**|-0.097*|
||(0.038)|(0.040)||(0.038)|(0.041)||(0.052)|(0.054)|
|Title in process|0.212***|0.146***|0.251***|0.230***|0.167***|0.300***|-0.105**|-0.147***|
||(0.039)|(0.052)|(0.062)|(0.043)|(0.058)|(0.068)|(0.052)|(0.052)|
|Has inf. certificate|0.218***|-0.070|0.252***|0.285***|0.017|0.315***|-0.007|-0.105**|
||(0.040)|(0.084)|(0.041)|(0.038)|(0.109)|(0.040)|(0.052)|(0.051)|
|Residential parcel|0.032***|0.137***|0.015|0.038***|0.117***|0.024**|-0.024|-0.013|
||(0.011)|(0.035)|(0.011)|(0.011)|(0.037)|(0.012)|(0.030)|(0.039)|
|Customary tenure|0.084**|||-0.009|||0.015|0.073|
||(0.034)|||(0.026)|||(0.065)|(0.073)|
|non-response|0.053|-0.070|0.181|-0.058|0.023|-0.141|-0.324|-0.402|
||(0.207)|(0.256)|(0.296)|(0.168)|(0.214)|(0.228)|(0.348)|(0.282)|
|R-squared|0.217|0.300|0.179|0.275|0.321|0.171|0.284|0.272|
|Observations|7,457|1,341|6,116|7,457|1,341|6,116|1,055|811|
|Dep. var. mean|0.365|0.568|0.320|0.283|0.596|0.215|0.237|0.211|
|**Tests (p-value):**|||||||||
|Title = Inf. cert|0.659|0.009||0.052|0.162||||
|Titleprocess = Inf. cert.|0.899|0.016|0.967|0.295|0.177|0.855|||

_Notes_ : Each column reports results from a parcel-level regression. Dependent variables are responses to questions on whether a parcel can be transferred via bequest (col. 1-3) or sale (col. 4-6). Col. 7 and 8 regress “Woman has a say” in the sample of parcels owned by married households who have transfer rights via either bequest or sale, respectively, on which the questions on genderdifferentiated transfer rights are administered only in quarters 3 and 4. Household characteristics, region and survey quarter fixed effects are included. Constant is not reported, and standard errors are clustered at village level. Panel B checks robustness, using a control function approach by controlling for the probability that a sample household not reporting owning land. Significance is denoted by *** for p<0.01, ** for p<0.05, and * for p<0.1.

25
- Profitability requires access to institutional markets to complement the initial low demand through retail or sales channels.

- Complementary foods should be delivered through channels that are close to the target population to facilitate purchase.

- Relevant consumer benefits, including those that are not nutrition- or health-related, can be used as aspirational drivers to create demand.

- In addition to raising awareness and encouraging use of complementary foods and supplements, it is important to promote _effective_ (i.e. regular) use.

- Effective use or coverage of complementary foods and supplements should be monitored regularly.

_Source_ : Adapted from van Liere et al. 2017.

# _Households and communities_

A range of factors influence whether policy, legal, and program interventions by the government, combined with actions by other actors, translate into improved feeding.

First, a mix of interventions needs to reach households to address the context-specific barriers at the level of the household, the community, the workplace, or the health facility that would otherwise prevent caregivers from adopting recommended feeding practices. For example, in low-income households, caregivers may be unable to act upon the information or counseling on complementary feeding that they receive from health workers unless the household also receives support to produce, purchase, or otherwise acquire nutritious food. Conversely, children in high-income households, which are able to afford nutritious food, may have a poor-quality diet if their caregivers are not informed or counseled on how best to feed their children.

Second, interventions must reach caregivers at the right time and with the necessary frequency, intensity, and quality (Menon et al. 2016; Benedict et al. 2018b). Information and counseling should be delivered at age-appropriate points during pregnancy and the first years of life; maternity leave needs to be of adequate duration for working mothers; and actions aimed at improving the availability and affordability of food must ensure that the food is nutritious and safe.

Third, households and communities play a crucial role in supporting caregivers to adopt recommended feeding practices. A study in Bangladesh reported that the adoption of such practices was determined by the mother’s workload and time, family perceptions of child feeding and what is good for the child’s health, and family support (Avula et al. 2013). Breastfeeding and complementary feeding require a substantial commitment of time, and family support to relieve mothers of domestic chores during such periods can make this commitment easier (UNICEF 2016). Social and behavior-change communication interventions need to be based on an understanding of sociocultural factors that influence feeding practices in a specific context. They should target not only caregivers, but also other influential family members, peers, and community members.

14
**Figure 1: EAC exports and intra-regional trade**

<!-- Start of picture text --> 100% 9,000,000<br>90% 8,000,000<br>80% 7,000,000<br>70%<br>6,000,000<br>60%<br>5,000,000<br>50%<br>4,000,000<br>40%<br>3,000,000<br>30%<br>20% 2,000,000<br>10% 1,000,000<br>0% -<br>2000 2001 2002 2003 2004 2005 2006 2007 2008<br>intra-trade extra-eac exports total exports (US$'000)<br><!-- End of picture text --> _Source: UN Comtrade via WITS_ But as most East African countries are relatively small – and even in its larger economies, domestic market size is constrained by low income levels – regional trade has limits in its potential to drive growth. Complementarity of production also restricts the scope of intra-regional trade at the moment. Rather, exploiting the much larger global opportunities will be the key to sustained export and economic growth. Despite the significant growth of exports from the EAC in recent years, the region’s share of the world market for exports remains well below 0.1%, around half the global average on a per capita basis.

In fact, global market integration and regional integration are not alternative strategies, but rather complementary ones. Increasing the global exports of individual member states requires improving the competitiveness of its firms. One of the key mechanisms through which to improve competitiveness is through scaling up regional production – i.e. integrating regional value chains to allow firms to reap the advantages of greater specialization and scale. Successful integration of regional value chains will not only facilitate exports to global markets but, by definition, will result in greater inter-regional trade through increased task or component-based trade. Indeed, this process of regional integration of production is being supported through the EAC Industrialization Strategy<sup>5</sup> . At the moment, however, integration of production networks within the EAC is extremely limited. Figure 2 shows that while intraindustry trade (IIT) – a proxy for integration of manufacturing networks – within the EAC is higher than within other regions in Africa or in South Asia, it remains dramatically lower than through East Asia, Europe, and the Americas. In the case of ASEAN<sup>6</sup> , for example, the removal of formal and informal trade barriers resulted in the spreading of value chains across the regions, with most countries benefitting by specializing in the production of various components of complex goods that were shifted across the region in various stages of production.

> 5 Articles 79 and 80 of the EAC Treaty

> 6 Association of Southeast Asian Nations

3
Because the growth of a city is associated with lower consumer prices, surrounding rural consumers who have access to urban markets may benefit through higher real wages (Jacoby 2000). This effect may be due to increased competition among a larger number of producers in the growing urban area as well as thicker market effects in both factor and goods markets (Fujita et al. 1999). However, the increased demand for agricultural goods may also lead to higher prices for these goods, especially if the supply is fairly inelastic. Therefore, the direction of the net effect of urbanization on consumer prices is a priori ambiguous.

This study predicts that the total net effect of urbanization on rural poverty is poverty reducing. Moreover, the bulk of the effect is expected to be felt in rural areas that are relatively close to the growing urban area. This distance decay effect is consistent with recent research on the welfare impact of the expansion of a gold mine in Peru (Aragόn and Rud 2009) and is important for our identification strategy, as explained below. The next sections will detail the methodology used to test these hypotheses by measuring the total net effect in the case of Indian districts.

# **<<A>>Data**

The data for the empirical analysis come from three main sources. For the district-level measures of poverty, we use data from three “thick” rounds of the National Sample Surveys (NSS: the Indian household survey) spanning the 1980s and the 1990s, the 38th (1983–84), 49th (1993–94) and 55th (1999–2000) rounds of the NSS.<sup>7,8</sup> These measures have been adjusted by Topalova (2010) in two ways. First, she uses the poverty lines (based on the state-level prices computed separately for rural and urban areas) proposed by Deaton ( 2003a, 2003b ) instead of the standard Indian Planning Commission poverty lines, which are based on defective price indices. Second, she adjusts the consumption data from the 55th round to 9
even stronger. In our model, politicized aid is not effective if it is not accompanied by aid delegated to the ML. In equilibrium, politicized bilateral aid can coexist with multilateral aid, while still giving recipients maximal incentives to improve their policies.

Aid delegation has been studied in a game theoretic framework in Svensson (2000) and Hagen (2006). In their models, aid is never policy selective without an exogenous commitment device as policy has no impact on aid effectiveness. In the setup proposed here, policy influences aid effectiveness, which makes policy selective aid possible. However, the strategic interplay between donors can greatly reduce policy selectivity, hence the motive to delegate aid to a multilateral agency. In the models by Svensson (2000) and Hagen (2006), delegation of aid to a multilateral agency occurs in equilibrium because of a difference in poverty aversion between the ML and the donor. In our model, the ML’s equilibrium aid allocation is both more poverty and policy selective as compared to the bilateral donors’ allocations. In Svensson (2000), for example, the ML’s aid allocation is less poverty selective as it is assumed to be less poverty averse than the bilateral donor.

A second noteworthy difference is that our model has two donors whereas the models in Svensson (2000) and Hagen (2006) have only one donor. This is important because maximizing the public good across recipient countries benefits all donors. However, if donors disagree with respect to the distribution of the public good across recipients, then the presence of the other donor reduces or removes policy selectivity in each donor’s aid allocation. Our point is that with one donor aid is always policy selective, but with two and more donors, it may not be. The role of the ML then is to produce that public good for all donors which occurs if it represents the average donor in the game. Thus, our model can explain why it is optimal for donors with very different motives for aid-giving to delegate aid implementation to the same multilateral agency. Svensson (2003) develops a game theoretic model that studies aid conditionality where policy – as in the paper here – affects aid effectiveness. In that setup the optimal aid allocation is policy selective if a donor disburses aid to more than one recipient. However, the previous observation made related to the number of donors also applies to Svensson (2003), as he studies the case with one donor only. Also, note he does not study aid delegation to multilateral agencies in that paper.

The remainder of the paper is organized as follows: Section 2 describes the sectoral composition of aid disbursements of bilateral donors and compares it with some selectively chosen multilateral agencies. Section 3 introduces the game theoretic model explaining why delegation to non-specialized agencies is optimal for bilateral donors. Section 4 presents empirical evidence pertaining to the World Bank’s International Development Administration (IDA) that supports some of the predictions made by our theory. Finally, Section 5 concludes.

4
account at this bank. We find business registration alone does not result in any increase in the likelihood of having a bank account, savings, borrowing, or separation of household and business accounts. However, coupling the business registration assistance with the bank information sessions leads to a higher rate of formalization than with registration assistance alone, as well as resulting in an increase in the proportion of firms with a business bank account, increased separation of business and household finances, and greater access to insurance. These short-term results suggest that complementary efforts to enable firms to access the purported benefits of formalization may be needed for these benefits to actually be realized.

We oversampled female-owned enterprises in order to be able to examine how these interventions differ by gender. Given that female-owned enterprises tend to be smaller and have a lower capital base than male-owned enterprises on average, female-owned enterprises may be further away from the margin of formalizing and less likely to respond to the assistance. We find this to be the case when business registration is offered together with tax registration, but not for business registration alone. Although access to finance is often thought to be particularly difficult for female-owned businesses, the gender gaps in who has a bank account in Africa tend to be small (Demirguc-Kunt and Klapper, 2012), and in fact we find female business owners to be more likely to have a personal bank account than male business owners in our baseline. As a result, we find smaller effect on bank accounts of the bank information and business bank account treatment for women than for men.

A growing literature has shown some positive effects of access to personal bank accounts on microenterprises’ investment and profits (Ashraf et al, 2006; Brune et al, 2011; Dupas and Robinson, 2013; Schaner, 2013). However, many microenterprises do not separate household and business resources (e.g. Drexler et al, 2013). The combination of bank information sessions on separating these expenses and having a separate business bank account may better help owners to separate business and personal expenses. In addition, setting up a business bank account that is only available to registered firms may also enable firm owners to subsequently access additional financial products and business contacts that can help grow the business. Two more rounds of follow-up surveys are planned that will enable us to measure these longer-term 4
In the present analysis, we use the same cross sectional methods used in the above studies of Africa and South America to study farm adaptation in China. We expect that farmers in China have also adapted to the range of climates that they face in China. Analyzing a sample of 8,405 farms sampled across 28 provinces in one year, we estimate logit models of irrigation and multinomial logit regressions of crop choice to detect how these choices vary with long term temperature and precipitation. Matching the location of each farm to climate data and soils, it is possible to examine the effect of climate on these endogenous choices by farmers while controlling for several other factors.

The available data allow us to measure the direct effects of temperature and precipitation on irrigation choice and crop choice. We specifically examine the choice of 9 major crops in China: wheat, rice, maize, soybean, potato, cotton, oil crops, sugar, and vegetables. Unfortunately, the amount of irrigation water a farmer uses is not available in the dataset. We do not know water availability or cost. If future climate scenarios reduce available water supplies, this is likely to affect these choices and the present study does not take this into account. This is an important omission for an agricultural system such as in China that relies heavily on irrigation.

The paper is organized as follows. We briefly review the methodology of adaptation analysis in the next section. Section three discusses the available data and the construction of the variables in the data set. In the fourth section, we present the estimation results for current farmers. The fifth section then forecasts how future farmers would change their irrigation and crop choice for three different climate scenarios in 2050 and 2100. The paper concludes with a summary of the key results and a discussion of policy relevance.

# **II. METHODOLOGY**

We assume that farmers make choices that maximize their income. We define income broadly to include both products they sell and consume. In this analysis, we are interested in modeling how they select from a number of discrete and mutually exclusive choices (McFadden 1981). In order to study irrigation choice, we rely on a dichotomous logit. We test how climate influences the probability of choosing whether to irrigate or 4