rafmacalaba/data-use-mentions-extended huggingface dataset:
**Table 7 – CWI and Expenditure Poverty**

||**CWI Po**|**verty**||**Expend**|**iture Pove**|**rty**|**Differen**|**ce**||
|---|---|---|---|---|---|---|---|---|---|
|**Area**|**FGT0**|**FGT1**|**FGT2**|**FGT0**|**FGT1**|**FGT2**|**FGT0**|**FGT1**|**FGT2**|
|**Urbain**|7.4|1.9|0.8|4.8|0.8|0.2|2.6|1.1|0.6|
|**Rural**|18.3|6.2|3.2|14.4|3.3|1.2|3.9|2.9|2|
|**Total**|12.1|3.8|1.9|8.9|1.9|0.6|3.2|1.9|1.3|

Source: NSLS 2006/07. Totals are simple weighted averages of the urban and rural statistics.

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the market. Female workforce participation rates, rather than property rights, are widely used as the main indicator of women's economic status in India (Agarwal 1995). But while better employment opportunities may complement land-based opportunities, they cannot substitute for land. Efforts to diversify livelihoods of asset-poor rural households through small-scale livestock production and sericulture, for example, generally require some land base, however small.

In India, separate personal laws apply to different religious groups. In most cases, women enjoy rather far-reaching legal rights to inherit and own land. This is especially true for Hindu women following the introduction of the gender-progressive Hindu Succession Act 1956, which provides for the daughters, widow and mother of a Hindu man dying intestate to inherit property _25_ equally with his sons in his separate property . In practice, however, significant and persistent gaps persist between women's legal rights and their actual ownership of land, and between the limited ownership rights women do enjoy and their effective control over land. Women's legal rights in land conflict with deep-seated social norms and customs, and are rarely recognized socially to be legitimate. There are strong pressures on women to forfeit their legal rights in favor

> 25 Significant gender biases persist both in land reform legislation and in personal laws, however. Agricultural land subject to tenancy is exempt from the Hindu Succession Act, and is governed by state-level acts. In states such as Uttar Pradesh where tenancy is officially banned, this precludes most arable land. In the case of land ceilings acts, additional land may be kept in the case of adult sons but not adult daughters. Also, in assessing 'family' holdings, holdings of both spouses are considered, but women's holdings are often arbitrarily declared as surplus land while men's holdings remain untouched (Agarwal 1995).

25
# **How have employment and incomes responded to this strong growth performance?**

Table 4 shows how the labor force has evolved since 1999.

**Table 4: GHS 1999 - 2006 - Sample Population aged 15 - 65 not in Schooling (in percent, weighted)**

|**Labor Force Status**<br>|**1999**|**2004**|**2006**|
|---|---|---|---|
|**Not in the Labor Force**|**25.3**|**23.0**|**25.2**|
|**In the Labor Force**<br>|**74.7**|**77.0**|**74.8**|
|**Unemployment Status**<br>|**1999**|**2004**|**2006**|
|**Employed**<br>|**97.8**|**97.0**|**97.4**|
|**Unemployed**<br>|**2.2**|**3.0**|**2.6**|

_Source: Francis Teal / Luke Haywood NLSS 2003-2004 and GHS 1999-2004_ 14. A key feature of Nigeria’s working-age population is the high share (approximately onefourth) of the population that is not in the labor force. As in other African countries, formal unemployment (measured as job seekers who cannot find a job) is extremely low. The vast majority of people outside the labor force consist of individuals who are either discouraged job seekers or who have not embarked upon a job search, as they do not consider the prospects to be promising. The share of people outside the labor force
Zoellick, at the 2008 High-Level Conference on World Food Security, advocated for an international call to remove export bans and restrictions. These controls encourage hoarding, drive up prices, and hurt the poorest people around the world who are struggling to feed themselves.<sup>2</sup> U.S. Secretary of State Hillary Clinton echoes the same concerns in a 2011 speech on global food security: We also saw how unwise policy also had an impact. Some policies that countries enacted with the hope of mitigating the crisis, such as export bans on rice, only made matters worse. (...) And that sounder approach includes (...) abstaining from export bans no matter how attractive they may appear to be, using export quotas and taxes sparingly if at all (...).<sup>3</sup> This paper revisits these claims and argues that trade policies are not necessarily the fundamental source of the macroeconomic amplication decried above. Rather, we show that an

> 1Though in Ravallion (1987), the analysis of the time series data for famines in British India indicated that the aggregate income eects were not strong enough to undermine the consumption-stabilizing eects of unrestricted trade in that specic period.

> 2http://go.worldbank.org/BUEP7C3NC0

> 3http://www.state.gov/secretary/rm/2011/05/162795.htm

2
commodities important to the poor. Also it may affect the incentives to production of commodities mostly produced by the poor vis-à-vis those produced by the non-poor. These policies also indirectly affect the rural poor if they have an impact on the performance of the agricultural sector. Finally, the rural poor may also be affected by the non-rural sectors of the economy through migration and remittances, and by affecting real wages in the rural areas.

We estimate variants of the following poverty equation, (10) _pov it_ = _β_ 1 _L_ [ _g it_ ] + _β_ 2 _L_ [ _Yit_ ] + _β_ 3 _L_ [ _Eit_ ] + _β_ 4 _L_ [ _S it_ ] + _β_ 5 _L_ [ _Tit_ ] + _ξ i_ + _τ it_ , where<sup>_ξ_</sup> _i_<sup>is a random country effect and</sup> _τ it_ is a random disturbance. We expect the effects of g, E, and Y on poverty to be non-positive while the impact of T to be ambiguous and, according to the discussion in the previous section, the effect of S to be positive. As in the case of the GDP equation, we tried various lag structures to capture for cumulative effects of the explanatory variable E over time as well as other instruments. The most popular measure of poverty is the head count ratio. However, head count measures may be quite heterogeneous as the definition of poverty lines tends to differ quite considerably across countries and over time. We use per capita income of the poorest two quintiles as a proxy for the variable _pov it_ .

# **IV. The Data**

In this section we examine a new data set for rural public expenditures for ten countries in Latin America recently assembled by the FAO regional office for Latin America and the Caribbean with the support of the World Bank and others. The annual data for the ten countries cover the period 1985–2000.<sup>18</sup> An advantage of this data is that it is quite disaggregated
accompanied by a 5-percentage point increase in the rate of informality, and a 13 percent reduction in hourly earnings.<sup>5</sup> The rest of the paper is structured as follows. Section 2 reviews the recent literature on the labor market effects of forced migration. Section 3 describes the events that have led to the Venezuelan crisis and provides some context regarding the economic situation in Ecuador at the time of the arrival of the migrants. Section 4 discusses our main data sources. Section 5 presents the analysis of the location choices of Venezuelan migrants within Ecuador. Section 6 contains the difference-in-difference estimation of the labor market effects of Venezuelan migration along with several robustness checks. Lastly, Section 7 concludes with our final remarks.

# **2 Literature**

Our paper contributes to the recent literature on the effects of forced migration on the host labor markets, which has focused on the exodus of Syrians primarily to Turkey (e.g. Ceritoglu et al. (2017), Tumen (2016), DelCarpio and Wagner (2015) and Loayza et al. (2018)) and Venezuelans to Colombia (Caruso et al. (2019) and Penaloza-Pacheco (2019)), which we review in detail below. Our contribution is twofold. First, we provide the first analysis of the labor-market effects of Venezuelan migration to Ecuador, one of the main receivers of Venezuelans over the last few years. Secondly, we make use of new data based on cell phone contracts and usage that allow us to measure with a high degree of accuracy the density of Venezuelan migrants across Ecuador’s geography, and merge these data with the household labor force survey and administrative records on migrants’ points of entry.<sup>6</sup> Our study contributes to the growing literature on the economic consequences of forced migration for host countries (Becker and Ferrara (2019)). Despite its enormous policy interest, this topic has remained understudied due to the scarcity of high quality data. Another challenge in
supervisor of an international bank may not accept the local currency ratings of corporate or other clients.

Linked to this, if the subsidiary of an international bank lends to a developing country sovereign in own currency and funded in own currency the home supervisor must decide whether that will be treated with a zero risk weight by the consolidated entity. Further, the same issue applies to the more favorable treatment of short-term inter-bank loans in local currency. A set of further questions arise given the long list of items subject to “national discretion”. For example, if the local regulator chooses not to apply the 35% for mortgages (or the 75% for retail etc.) would the home regulator still allow the subsidiary of an international bank to adopt the 35%?

Many developing countries may apply the SA multiplying the risk weight obtained in the Basel II tables relevant to the local rating by the relevant basic requirement. Some developing countries currently have an 8% basic requirement but others have higher requirements. This implies that the SA may not be so Standardized when it comes to cross-country comparisons. First there is an issue as to whether one country’s local AA is the same as another’s and second that rating is then converted into a capital charge using different basic requirements (8%, 10%, 11 % etc). It seems further work is required here to consider the calibration issues involved across different countries where local ratings are employed.

# **_Pillar 1: Where the home country bank adopts IRB_**

A major concern with the advanced approaches of Basel II is that there will be an inappropriate application of the advanced approaches where supervision is not strong enough to be able to monitor the more sophisticated rules on capital appropriately. This fear is also relevant for the subsidiaries of foreign banks, especially where the foreign bank is large for the host country.

In these circumstances it would appear paramount that the host supervisor adopts a system that it can monitor effectively. Only if the foreign bank gives a broad
97%|97%|97%|
|**On track in learning**=1 if on track if one or both of<br>the following are true: child follows simple<br>directions on how to do something correctly; when<br>given something to do, is able to do it<br>independently|86%|88%|82%|82%|83%|81%|
|**On track in social and emotional development:**=1<br>if two of the following are true: the child gets along<br>well with other children; the child doesnotkick,<br>bite or hit other children; and the child doesnot<br>get distracted easily|65%|70%|56%|65%|63%|70%|
|Source: Authors’ estimates based on the 2014-15 MIC|S from the|Rep. of Con|go and São T|omé & Prín|cipe||

# **Methods**

The main question addressed in this paper is an inference question: how does the predicted value of an indicator of early childhood development change if the incidence of stunting (a binary variable) or height-for-age-z score (a continuous variable) or a mother’s years of education are increased by one unit, holding other confounding factors fixed. This question can be answered within the context of a partially linear model, such as 1 1 2 2 , 1 2] = 0 (1) YY= ββ DD + ββ DD + ff(ZZ) + εε EE[εε|ZZ, DD , DD

8
capitalization may be set at levels lower than those for regular commercial banks. It should be noted that many countries' banking laws do not allow for _tiered-banking,_ under which licensed but specialized banks can be established at levels of minimum capital lower than those for "4universal" banks;<sup>31</sup> 89. The experience in Bolivia, Peru and the Philippines with lower minimum capital requirements for specialized institutions licensed to carry out limited banking operations demonstrates the use of a minimum capitalization requirement as a _standard of entry_ rather than a _barrier to entry._ In the recent reforms to its banking laws, Nicaragua will permit the establishment ofnonbank financial entities with a non-profit charter, a specialized microfinance and SME focus and shareholder capital at a level lower than that for regular commercial (multiple) banks,<sup>32</sup> The application of a liability-to-capital ceiling would complement the standard of entry aspect of minimum capitalization, becoming a positive inducement for striving to increase capital (and the resulting capacity to expand microlending) over time.

# **Considerations for governments, donors and MFIs**

90. The worldwide inventory of microfinance institutions undertaken by the World Bank indicates that as of September 1995, some $7 billion in loans to more than 13 million individuals and groups were outstanding in the 206 institutions that responded to the survey These institutions had also mobilized over $19 billion in 45 million active deposit accounts.<sup>33</sup> Supporting the survival and developmrent of the economic activities of the poor has become one of the priorities of the policy agenda of the 1990s.

91. The financial system as a whole continues to evolve and find new ways to service demands for financial services in the emerging markets. The innovative and rapid development of many localized efforts to provide financial services to the poor outside of formal channels has generally overtaken taken policy formulation by governments. The reaction of some governments (e.g., Bosnia, Bangladesh and others) and multilateral agencies (e
# 1. Introduction

Identifying the poor in developing countries is crucial to inform development policies and programs, particularly those related to social assistance. However, governments and the development community are severely constrained by the high cost of collecting household surveys, censuses, or social registries that are typically used to inform targeting decisions. For example, between 2002 and 2011, 57 countries had conducted zero or one nationally representative household budget survey, preventing them from producing timely poverty estimates, and typically four years pass between nationally representative surveys on consumption or asset wealth in most African countries.<sup>1</sup> Even when household data is collected, data collected by household surveys are typically too small to provide reliable estimates of welfare for small geographic areas such as villages. Estimating poverty at the small area level requires alternative sources of data, traditionally census data, and utilizing this type of auxiliary data for small area estimation can provide resources to the poor more efficiently.<sup>2</sup> Due to this lack of timely and adequate information on measures of well-being indicators in small areas, satellite imagery and other types of non-traditional data have great potential to fill these data gaps and complement traditional household surveys to provide more timely and accurate estimates for local areas.<sup>3</sup> This paper investigates the benefits of combining traditional data with publicly available remote sensing indicators to predict welfare across approximately 4,500 villages in 10 districts in Malawi. The 10 districts correspond to the ones selected for phase one of the Unified Beneficiary Registry (UBR), which was conducted in 2017, collecting information on living standards to determine the eligibility of households for social programs.

We evaluate four alternative village targeting methods which are compared to a benchmark welfare measure derived from an extract of the 2018 household census: (1) PMT scores calculated in the 2017 UBR administrative data, (2) the Meta Relative Wealth Index,<sup>4</sup> (3) predictions derived from a village-level model estimated
private rental stock is typically in worse physical condition and has fewer amenities and lower standards than the postwar municipal rental stock, the grading scales result in the lower average private rents.<sup>61</sup> This will be changing, however, with new regulations allowing substantial rent increases in this rental stock.

In the uncontrolled markets of Romania and Russia, in contrast, private rents are both significantly higher than public rents and less affordable. Although distorting factors in the LSMS and HBS is a possibility - for example, strategic behavior of interviewees to conceal true rent levels because they might violate regulations or lead to higher taxation - we believe that these results by and large reflect the low quantities of rental housing supply in those countries determined earlier in the chapter.

- The data for Romania confirm our evidence on the scarcity of rental housing supply - especially in Bucharest. According to our interviews, for example, flats in public rental units in Bucharest in 2004 were let for just one-tenth of the rent level in the private market.

- The data for Russia indicate somewhat lesser relative scarcity of private rental units than in Romania, but certainly still yield a high differential. This is consistent with both the findings of a low base effect concerning sector size reported in this study and the dynamics of new rental supply noted by Kalinina and Klepikova (2002).

The countries of Armenia and Serbia are both in special situations:

- The low mark-up for private rents in Armenia seems to reflect the combined effects of a lack of effective demand and a lack of net emigration, which leaves many units vacant. Low general affordability makes public rents appear very high - which they are not, if compared to costs.

- Serbia has by definition the highest mark-up of private rents, because our survey does not record rent payments made for public rental apartments.

It would be worthwhile to refine the results obtained by the LSMS and HBS by location or available information reflecting housing quality and tenant income. Such a hedonic pricing approach would lead to
extensive/spatial margin of trade where an increase in transport cost can sever the link between OD pairs who were engaged in trading during the pre-pandemic period. We use the trade flow and freight rate data during the pre-pandemic period to estimate elasticity and spatial margin of trade. The shift in freight rate during the post-lockdown period is then used to simulate the effects of this shock on these two margins of trade. The pandemic has affected every facet of the economy, including the way goods are transported, how people migrate across areas and how preferences shift in response to it. The exercise is not intended to predict the overall spatial effects of the pandemic or even trade flows and trucking costs in the long run.

Taking the observed changes in freight rates as given, we limit our analysis in favor of providing a suggestive view of how trade flows and spatial margin of trade may be affected in the short run.

# 4 **Estimating trade gravity regression during the pre-pandemic period**

The first step in analyzing the impacts of the increase in trucking costs on inter-regional trade flows is the estimation of elasticity of trade flow with respect to the freight rate, which to the best of our knowledge is not available from existing literature for developing countries, particularly for India. We start by describing how values of trade flows across districts are constructed.

The volume of goods transported is reported for each transaction in our trucking data set. Using these data, we construct district to district flow of volumes of goods by aggregating over all trips for each OD pair. However, the data set does not provide information on the value of traded goods which is needed for the estimation of trade elasticity. To estimate the value of trade, we web-scrapped daily prices of essential commodities reported by the Reserve Bank of India for 114 cities. As noted in Atkin and Donaldson (2014), it is important to establish the origin of comparable goods to trace out the trading and transport cost over distance. We select two commodities loose tea and palm oil whose
10

# **3. Background**

The total global building volume equals 1,593 billion m<sup>3</sup> ( _∼_ 1.52 million Empire State Buildings), resulting from a total building area of _∼_ 300,000 km<sup>2</sup> and a mean height of _∼_ 5 m. We obtain 1,558 billion m<sup>3</sup> in WSF3Dv1, implying that it missed 2% of global volumes. WSF3Dv2 mostly improves upon WSF3Dv1 for cities, where WSF3Dv1 missed 5% of global volumes (we get 9% for cities above 5 million today). Indeed, WSF3Dv1 disproportionately missed high-rise buildings and skyscrapers typically found in cities. This holds as well in the developing world where the same missing shares are 2%, 4%, and 8%, respectively. Focusing on cities, the volume discrepancy between WSF3Dv2 and WSF3Dv1 is then larger for the developing economies of Latin America & the Caribbean (LAC) (7%) than in developing Asia (3%) or Africa (1%).

Regional statistics from WSF3Dv2 are provided in Table 1. Developing economies account for two-thirds of global volumes. Upper-middle, lower-middle, and low income economies account for 70%, 25%, and 5% of total volumes in the developing world, respectively. Africa accounts for 9% of global volumes despite comprising almost 18% of the world’s population.

Table 1: Selected summary statistics for several groupings of countries, 2012/2019

|Economies|Volume km<sup>3</sup>|Per Cap. m<sup>3</sup>|% Outward|% Upward|% Low-Rise|% High-Rise|
|---|---|---|---|---|---|---|
|World|1593|207|52|48|46|2|
|
spent at residential spaces. These data are available in close to real time and can be used to document compliance with mobility restrictions. Similarly, near real-time data on nitrogen dioxide pollution showed less pollution in some areas in the aftermath of the shock (Masaki et al., 2020). The varied speed of the onset of the crisis and the progression of recovery in different countries, and regions within them, raises the natural question of how well these real-time indicators track the economic indicators collected in the phone surveys, and which real-time indicators are most informative.

> 2 Director-General’s opening remarks at the media briefing on COVID-19, 11 March 2020. <u>https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-atthe-media-briefing-on-COVID-19---11-march-2020.</u>

2