rafmacalaba/data-use-mentions-extended huggingface dataset:
||Jawand<br>Muqur<br>Qadis|700<br>1686<br>763|0<br>0<br>0|
|---|---|---|---|
||Qala-e-Naw|4615|1790|
|July-Dec 2020|Ab Kamari|909|0|
||Bala Murghab|11480|0|
||Ghormach|264|0|
||Jawand|1461|0|
||Muqur|2002|0|
||Qadis|1029|0|
||Qala-e-Naw|7674|6072|

# Changes in the numbers of Arrival IDPs (stock of IDPs) in 2018-2020

In 2020, the number of IDPs (protracted IDPs) in the Badghis province decreased by 24,327 compared to 2018 (Table A8). In particular, this effect was achieved due to IDPs leaving Qala-e-Naw (-67,888) and Ab Kamari (-693) districts. In other districts, the numbers of IDPs increased as compared with those in 2018. These numbers should be interpreted with caution as the government of Afghanistan disputes IOM’s numbers of protracted IDPs.

Table A8. Changes in the numbers of IDPs in 2020 vs. 2018 according to IOM data

|Districts|2018|2020|Absolute change|Percentage change|
|---|---|---|---|---|
|Ab Kamari|7,806|7,113|-693|-8.9|
|Bala Murghab|9,985|44,118|34,133|341.8|
|Ghormach||1,146|1,146|-|
|Jawand|3,319|6,138|2,819|84.9|
|Muqur|7,203|12,319|5,116|71.0|
|Qadis|8,069|9,109|1,040|12
# **Table 1: IPC Acute Food Insecurity Phase Descriptions**

For more details we refer to IPC 3.0 Area Phase Classification (IPC Global Partners, 2019). The left-most column describes the classification used in this article. The rationale being that IPC3+ phases are identified as requiring “urgent action” (IPC Global Partners, 2019) and individual high IPC stages lacking sufficient historical observations.

|IPC1|Phase 1|Minimal|Households are able to meet essential food and non-food needs without engaging in atypical<br>and unsustainable strategies to access food and income.|
|---|---|---|---|
|IPC2|Phase 2|Stressed|Households have minimally adequate food consumption but are unable to aford some essential<br>non-food expenditures without engaging in stress-coping strategies.|
||Phase 3|Crisis|Households either have food consumption gaps that are refected by high or above-usual acute<br>malnutrition, OR, are marginally able to meet minimum food needs but only by depleting<br>essential livelihood assets or through crisis-coping strategies.|
||||Households either have large food consumption gaps which are refected in very high acute|
|IPC3+|Phase 4|Emergency|malnutrition and excess mortality, OR, are able to mitigate large food consumption gaps but<br>only by employing emergency livelihood strategies and asset liquidation.|
||Phase 5|Famine|Households have an extreme lack of food and/or other basic needs even after full employment<br>of coping strategies. Starvation, death, destitution, and extremely critical acute malnutrition<br>levels are evident.|

# **Table 2: Exogenous variables and transformations**

This table shows the collected exogenous variables in different categories and the transformations we apply (feature engineering). The order of transformations and aggregations follow the vertical structure of the table. Spatial aggregations are applied to the district-level data to compute country-level values. Temporal aggregations
active people who reported domestic work but resides in agricultural households where similarly aged people of their gender report agriculture work, and detailed adjustment makes adjustments using information from other questions and modules of the questionnaire (secondary activities, and time use and household enterprise module)._

When the information content differs across surveys, a trade-off between comparability and adequately capturing the concept of economic participation is implicitly involved. As an example, the UNHS 2005/06 and UNHS 2009/10 both have screening questions that form a better base for measuring economic participation (LFPR), but indicators constructed from these will not be comparable with previous surveys. If the trend is to stretch back to 1992/93, it will be even more difficult to create comparable indicators, even if we use both primary and secondary employment status responses for all three years. The suggestions above are simply ways to approach data comparability and minimize non-sampling bias, but obviously user discretion is advised where questionnaires are simply too different.

# **5. Conclusions:  A framework for capturing activities, not dreams**

While much has been made of the poor quality of national accounts or poverty data in Sub-Saharan Africa, less has been written on the quality of labor force and employment outcome data. Yet the shortcomings in employment data are at least as important, not only because they inform the national accounts data. The main problem has been the use of poorly worded questionnaires. These questionnaires – the “bed” in the title of the paper – are applied without first clarifying the reality they seek to measure. So they end up measuring what is in people’s heads as they hear the words of the interviewer - their “dreams”. This makes the data difficult to interpret or to use in cross-country or trend analysis.

The analysis in this paper showed the sensitivity of labor outcome estimates to type of questions, their framing, recall periods and computation methods. Using multiple Ugandan cross section household survey data sets and exploiting the variations across surveys, and sometimes within
in the private sector compared to the public sector.

We find that 28% of working women in the sample are working in the private sector, compared to 42% of men.<sup>10</sup> The nature of private sector work continues to be largely informal, with nearly 75% of women in the private sector reporting to be “self-employed” or an “unpaid worker in the family business.”<sup>11</sup> We also observe formal private sector participation for women in the Rwanga sample. For example, nearly 75% of female job seekers who found a job in the preceding 2 months (i.e. in June and July 2018) were employed in the private sector. We

> 9 Income was recorded for the last 60 days since some workers are not paid every month. This is just lower but not very different than the median income range reported in the demographic survey in 2017, where the median fell in the range of 500,000-750,000 IQD.

> 10 While we oversampled working women, we did not stratify based on public or private sector. However, our sample is small, and we advise caution in over-interpreting this statistic. There are several other factors that may affect this statistic, such as seasonality.

> 11 Over 98% of women in public sector work report being a paid employee.
3 3.1<br>HE-SE 7.3 15.3 58.4 19.1 HE-SE 16.7 61.9 21.4<br>Paid Form 1.7 19.8 50.1 28.4 Paid Form 14.0 49.5 36.5<br>0 20 40 60 80 100 0 20 40 60 80 100<br>Agricultu re Industr y Servic e Other Low-skille d Medium-skille d High-skilled<br><!-- End of picture text --> Source: Own elaboration based on GMD. Notes: Cross-country averages using population weights. Countries included in the sectoral averages: Angola, Burundi, Benin, Burkina Faso, Chad, Cote d’Ivoire, Cameroon, Gabon, Ghana, Guinea, Guinea Bissau, Mali, Niger, Senegal, Sierra Leone, Sao Tomé and Principe, South Africa, Eswatini, Togo, Uganda, Zambia and Zimbabwe. Countries included in the occupation averages: Angola, Benin, Burkina Faso, Chad, Cote d’Ivoire, Cameroon, Ghana, Guinea, Guinea Bissau, Liberia, Mali, Niger, Senegal, Sao Tomé and Principe, South Africa, Togo, Zambia and Zimbabwe.

> 55 Low-skilled occupations include <mark>agricultural, forestry and fishery workers and elementary workers; medium-skilled occupations include clerical and support workers, service and sales workers, craft and related trades workers, and plant and machine operators and assemblers; high-skilled occupations comprise managers, professional and technicians and associate professionals.</mark>

25
percent of the foreign-born who got married in the year before the survey opted for a “marriage migrant”, and men do so to a much larger extent than women.

# **3.3 Migration may affect the stability of marriages and lead to (or prevent) family dissolution**

This is often raised as a policy concern with temporary migration programs that result in one spouse moving and another remaining behind. For example, a Samoan NGO notes that infidelity is an issue among some Samoan seasonal workers, resulting in family separations.<sup>13</sup> Using migration event histories, Davis and Jennings (2018) document that Nicaraguan migration is associated with an increased rate of marriage dissolution. Boyle et al. (2008) 13SeeSee

> 13SeeSee `https://www.rnz.co.nz/international/pacific-news/469161/ infidelity-is-an-issue-among-samoa-rse-workers-says-ngo` (last accessed on November 5, 2023).

13
Personal Initiative|0.0136|0.0147|0.0120|-0.0314|-0.0688|-0.000793|
|(PI)_after 1.5 years|(0.0192)|(0.0224)|(0.0261)|(0.0224)|(0.0595)|(0.0323)|
|Basic Skills (BSED)_after|0.0336*|-0.00230|-0.000625|-0.0327|-0.0839|0.0365|
|1.5 years|(0.0192)|(0.0225)|(0.0261)|(0.0225)|(0.0591)|(0.0325)|
|Observations|1,492|1,485|1,482|1,485|1,729|1,421|
|Control Group Mean at|0.374|0.632|0.691|0.758|4.975|0.653|
|Follow-up|(0.0161)|(0.0172)|(0.0201)|(0.0172)|(0.0481)|(0.0253)|

_Notes:_

* significant at 10% level ** significant at 5% level *** significant at 1% level

(1) Controls include: received WEDP loan at baseline, age of owner, marital status, education, household size, number of children and digitspan score at baseline.

(2) Record Keeping Index = Has a written business plan; Has a written annual budget; Keeps financial records (3) Marketing Practices Index = Visited at least one of its competitor’s businesses to see what prices they are charging; Visited at least one of its competitor’s businesses to see what products he or she offers; Asked existing customers whether there are products they would like
them in each site and also contributed to inform the designing of survey questionnaires based on local contexts. Second, we shifted to semi-structured individual interviews and focus group discussions with more specific questions on themes which had emerged during the initial interviews with key informants. This allowed us to deepen our understanding of refugee-host relationships in each of the research sites. The main purpose of our qualitative research is not to make generalizations of findings. However, to minimise the influence of specific groups in findings, we endeavoured to include various groups of refugees (and hosts to some degree), notably those from different genders, ethnicities, and age groups (the qualitative methods used and a breakdown of participants is detailed in Table A.6 in the Appendix). The analytical procedure of qualitative data is as follows. First, all of the conducted interviews were transcribed by the interviewer, who is in charge of qualitative research of the project, from the field notes. Next, each interview data was reviewed and explored by the researcher to identify repeated ideas or topics which are broadly related to the interactions/contacts/perceptions between refugees and hosts. Then, based on the initial identification of ideas and topics,

> 9Higher values of the index indicate more interaction with the outgroup. A one standard deviation change in the index corresponds to about 10-15 more direct interactions in the past month (the number varies slightly depending on the sample considered, as shown in Tables A.3-A.4 in the Appendix).

14
Our finding that even modest reductions in the cost of accessing the registry increase mortgage market activity and women’s credit access suggests that the extent to which registration costs determine financial sector deepening and female empowerment may have been underappreciated, at least in urban contexts. It implies that, without a well-functioning property registry that has reasonably complete urban coverage, the benefits from expanding into informal and rural areas that have traditionally been the focus of land titling may be few and difficult to sustain (Galiani & Schargrodsky 2016). Policy and institutional reforms to reduce the cost of gender-sensitive urban property registration may thus not only constitute a precondition for expanding registry coverage into peri-urban and rural areas but also generate significant direct benefits. If improving how land and financial markets function can translate into higher property values, part of which can be captured through property taxation to finance local public goods, in principle such reforms could be self-sustaining and strengthen accountability and the social contract (Weigel 2020).

A final area on which we provide insight relates to the contribution of land rights to women’s social and economic empowerment. Registering land in women’s names, as sole or joint owners, has proved to increase their ownership of assets and enhance their bargaining power, thus affecting consumption choices, investment, productivity, and participation in local land or labor markets in countries as diverse as China (Wang 2014), Vietnam (Menon et al. 2017), India (Agarwal 1994), Ethiopia (Deininger et al _._ 2008), Rwanda (Ali et al. 2014), Malawi (Deininger et al. 2021), and Peru (Field 2007). Though analyses of the economic impacts of U.S. legal reforms in the 1850s that allowed women to own property, such as Hazan et al. (2019), have found far-reaching long term impacts, they do not discuss the mechanisms underpinning such changes.

In the context examined here, similarly far-reaching legal provisions had no independent impact in the short term but did increase
in the Latin American sample relative to the developed countries. This evidence on the quantitative e¤ect of HtM arguments, coupled with the strong evidence supporting a larger share of HtM agents in emerging markets, suggests that a bigger STM may be expected for emerging market economies in general.

The rest of the paper proceeds as follows. Section 2 shows the empirical estimates of STMs for both the developed and the Latin American samples. Section 3 presents the TANK model. Section 4 provides evidence that the share of HtM agents and the share of social transfers actually reaching them in emerging markets are much larger than in developed economies. Section 5 shows that a

> 5 As discussed in Kaplan et al. (2014), while the identi...cation of HtM agents is di¤erent from those studies based on the agents’liquid wealth, the empirical evidence is notably similar in terms of the shares of population living HtM. This robust ...nding is also present in our study when relying on Global Findex. For example, for the United States, Kaplan et al. (2014) ...nd a share of HtM ranging between 25 and 40, with their preferred estimate being one-third. Ours, using Global Findex, is 27 percent. Section 4 provides extensive evidence of these similarities.

> 6 In light of the heated debate in developed countries about the so-called wealthy HtM individuals (i.e., those with signi...cant amounts of illiquid assets like real estate properties, yet high marginal propensity to consume out of transitory changes in income), we ...nd evidence that wealthy HtM individuals also exist in emerging markets. Yet, the HtM phenomenon in emerging markets is largely driven by poor HtM individuals.

> 7 This evidence is also in line with well-established, more macro/aggregate, evidence that emerging market economies have less ...nancial depth, intermediation, and development than their developed counterparts (e.g., King and Levine, 1993;
World Bank (1995), Appendix Table 5.5.

As shown in table 2, interest and dividends accounted for 4.7% of total household income, on average, between 1989 and 1994. At the same time, taxes on interest and dividends raised 10.2% of total personal income taxes, thus contributing more than proportionally to tax revenues. More importantly, a comparison with total dividend and interest payments unveils that tax revenues equal 20% of the tax base -- in other words, APEH, the tax office, was able to completely exploit the tax base of capital income.<sup>14</sup> This is a very significant result given that rates of tax evasion are very high. According to recent estimates, evasion in Hungary varies between 7% of the tax amount due (corporate income tax) and 25% - 30% (value-added tax, personal income tax).

In 1995, interest received by individuals and interest on government bonds was tax exempt. Accordingly, the Government has foregone potential revenues from taxing this source. These revenue losses can be estimated on the basis of financial savings of households (see table 3). At the end of 1995, financial savings of Hungarian households totalled HUF 2,182 billion. Assuming average interest rates of 20% on forint deposits and bank securities and 3.5 % on foreign exchange deposits, potential tax revenues would add up to HUF 20.7 billion, given a tax rate of 10%. Note that government bonds and bills remain tax exempt. The additional revenue foregone would thus

> 14 This experience is common to other countries operating withholding schemes (see below). Ministry of Finance figures do not match National Accounts data. According to the latter, interest income in 1991 - 1994 amounted to HUF

> 48.9; 70.7; 100.6 and 130.2 billion, respectively. During the same period, corporate dividends totalled HUF 12.6; _15.5;_
. R. Kerr, and S. D. O’Connell (2014): “Political reservations and women’s entrepreneurship in India,” _Journal of Development Economics_ , 108, 138–153.

- IIPS (2017): “National family health survey (NFHS-4), 2015-16: India. Mumbai: IIPS,” .

- Iyer, L., A. Mani, P. Mishra, and P. Topalova (2012): “The power of political voice: women’s political representation and crime in India,” _American Economic Journal: Applied Economics_ , 4, 165–93.

17
We can further assess the extent of elite capture and mistargeting of NAIVS over time in our study villages in Arusha compared to those in Kilimanjaro by running the main specification in Alatas et al. (2019): where Yij is a dummy that indicates whether household i in village j reported being a NAIVS beneficiary, Relatedij is a dummy that takes the value of 1 if the head of household i in village j reports holding the position or being related to the DALDO, WEO, VEO, VVC member, Village Chair or Hamlet chair, and Eligibleij is a dummy that indicates whether household i in village j is eligible in the 2008/09 season for the NAIVS program (i.e. had not used improved inputs prior to the start of NAIVS and had cultivated less than 1 Ha of land). We use baseline and follow-up data from the Villager survey and report the OLS estimates of Equation 3 in Table 6. We run separate regressions for the 2008/09 and 2010/11 seasons in Arusha (columns 1 and 2, respectively) and Kilimanjaro (columns 3 and 4, respectively).

In Arusha villages, being related to government officials or influentials is not correlated with being a NAIVS beneficiary in either 2008/09 season (column 1) or 2010/11 season (column 2). In both columns, the coefficient β1 is small and not statistically different from zero at conventional levels. In contrast, political connections played a role in voucher distribution in the 2008/09 season in Kilimanjaro (column 3), consistent with the findings of Pan and Christiansen (2012), Kilic et al. (2015) from Malawi and Mason et al. (2017) from Zambia. Column 3 reports that being related to government officials or influentials increased the probability of receiving vouchers by 3.2 percentage points, an increase of 60 percent over the mean of 5.4 percent among non-eligible individuals that were not related to government officials or influentials. By 2010/11, however, the elite
5 hospitals that had already been autonomized, and others that had not. Were the experiment a pure natural experiment we could compare simply the two groups at any moment in time. However, we cannot be sure that the timing of a hospital‘s autonomization is entirely uncorrelated with unobservables that may influence the outcomes of interest. To get round this we employ a generalized version of differences-in-differences (DID) where, instead of having two periods (―before‖ and ―after‖) and a ―control‖ group and a ―treatment‖ group, we have in each of several periods some ―treated‖ (autonomous) hospitals and some ―untreated‖ (not yet autonomized). In addition to using hospital data to get at the impacts of autonomization on hospital outcomes, we employ household data for the years 2004, 2006 and 2008 to look at the effects on household-level outcomes – use of services and out-ofpocket payments – of changes in the autonomy status of the local hospital.

We find that autonomization probably led to more hospital admissions and outpatient department visits, though the effects are not large. It did not, however, appear to affect bed stocks or bed-occupancy rates. Using a multi-product cost function specification for our differences-in-differences regression, we find no evidence that autonomization shifted the cost structure; autonomization did not apparently therefore increase hospital efficiency. Oddly, despite the volume effects and the unchanged cost structure, we do not find any evidence of autonomization leading to higher total costs. However, we do find some evidence that autonomization led to higher out-of-pocket spending on hospital care, and higher spending per treatment episode; the effects vary in size depending on the data source and hospital type, but some of our estimates are quite large. We find no evidence that autonomy affected in-hospital death rates or complications, but our results suggest that in provincial and district hospitals autonomization did lead to more intensive style of care, with more lab tests and imaging per case.
standard calibrated TANK model is able to match key empirical regularities shown in Section 2 in terms of the size, main macroeconomic variables involved, and temporal pro...le of the STM for both the developed and Latin American samples. Section 6 o¤ers some ...nal thoughts.

# 2 Empirical evidence on the Social Transfer Multipliers

Social transfers comprise both ongoing social protection programs and emergency policy responses.<sup>8</sup> Ongoing social protection programs refer to the disbursement of government funds to individuals who meet certain eligibility criteria. The main categories include unemployment bene...ts (transfers to unemployed individuals), family programs (transfers essentially to the poor and most vulnerable households), and pensions (mainly transfers to individuals after retirement). Social transfers represent a large component of government spending comprising more than 50 percent of primary government spending in developed countries and about 40 percent in emerging markets. By and large, the largest category of social transfers spending is pensions (accounting, on average, for more than 75 percent of social transfers), followed by family programs (about 20 percent, on average). Interestingly, in contrast to the emerging world’s long history of social protection in terms of social security and the most recent wave of family programs, unemployment insurance programs are rare in emerging countries (they simply do not exist or, if they do, they have negligible coverage). In terms of their short-term ‡uctuating nature, unemployment insurance spending is, by design, countercyclical (even at the quarterly frequency!).<sup>9</sup> On the other hand, pensions and family programs spending tend to be more rigid and slow-moving in nature and are mainly driven by demographic and structural deep-rooted social problems, respectively.<sup>10</sup> This section estimates STMs using unbalanced quarterly data for the period 1960:Q1 through 2019:Q4 for six Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico,