rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 8912

# **Abstract**

Adding a module designed to measure land tenure-related Sustainable Development Goals indicators to the 2018 round of Zambia’s labor force survey shows low transferability and high levels of tenure insecurity. Having a title is associated with greater transferability and reduced insecurity. Although demand for titles, including willingness to pay, is high, current policies limit the scope for tenure regularization and reinforce rather than reduce gender discrimination. Efforts in this direction need to be preceded by (i) procedural reform to reduce costs, streamline procedures, and make them gender-sensitive; (ii) institutional change to increase the efficiency of service delivery and ensure record maintenance; and (iii) legal change to recognize customary tenure and improve land management and transferability. Adding the Sustainable Development Goals land tenure module to ongoing surveys has the potential to provide the evidence base needed to design results-based approaches for the land sector and reliably track progress.

This paper is a product of the Development Research Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at dali1@worldbank.org, kdeininger@worldbank.org, thilhorst@worldbank.org, and yyi@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of
prevalence across all industries and are thus transversal skills for this segment of the labor market. Some industries such as the IT sector express high demand for particular software skills, thereby signaling specific industry needs with which curricula could be better aligned. Firms are more likely to express education or diploma requirements rather than work experience when searching for potential workers through job ads. On job platforms, employers require on average 2.5 years of work experience and tertiary education, suggesting that platforms are of limited use to labor market entrants. Employers who require several years of work experience are also those who express demand for a higher number of skills. Finally, we establish that job platforms in Kosovo represent a specific segment of the labor market. They mostly require a minimum level of experience and are used almost exclusively for high-skill occupations in Pristina, the capital city and are concentrated on permanent contracts and full-time jobs, whereas low- and medium-skill jobs are more likely to be filled through informal channels.

Information from job platforms has great potential as it provides useful real-time data complementing traditional sources on labor and skill demand across occupations and sectors.<sup>3</sup> Our paper relates to the literature analyzing job descriptions to better understand labor demand. Recently, Hershbein and Kahn (2019) have used job descriptions from US posted vacancies collected by Burning Glass Technologies to identify “upskilling” by looking at changes in firms’ skills requirement in job postings during recession times. Kureková et al. (2016) analyze the text of vacancies in the Slovak Republic to compare the profiles in student-targeted vacancies with other flexible jobs. Similarly, we use job descriptions to shed light on the skills demanded by employers in Kosovo. Muller and Safir (2019) have also documented the skills in demand for Ukraine, using data from one private portal. Our paper adds to this by offering a rigorous methodology on the aggregation of data across four portals. We also use a highly detailed skills taxonomy so that our findings lead to very clear policy recommendations on
gender disadvantage: Constrained and unconstrained models_**

Using the pooled sample of men and women in all countries to estimate the log-earnings functions, with gender as a dummy variable, we find that women’s log earnings are 31 percent lower than men’s in the basic model (only schooling, without skills), with selection bias correction, and 28 percent lower in the full model (with skills) (Table 4). Turning to individual countries, we also estimate a constrained model in which gender enters as a dummy variable, first with just schooling and then with both schooling and skills (columns 1 and 2, Table 10). Except in Serbia and Kenya, women are paid significantly less than men, whether or not we control for skills, with 51
A further employment-related issue concerns the overall welfare impact of any regulation-induced job loss. As Masur and Posner (2011) note, the standard RIA assumption is that in a full employment world there are few transitional impacts associated with any individual job loss, as displaced workers can readily find comparable work elsewhere. Yet, as they note, especially in times of high unemployment, there are likely to be some lost wages, as well as the potential for depreciation in workers’ human capital and increased family instability. If properly monetized, such impacts could be substantial. Importantly, if the results were actually included in a formal BCA, it could influence the desired degree of stringency of a rule. Although the quantification and monetization of these effects is limited, further analysis may reveal this to be a nontrivial effect.

# **IV. The Mexican Regulatory System**

Mexico is a particularly interesting case to examine regulatory issues in the context of green growth in a developing nation. A recent World Bank study reviewed the Worldwide Governance Indicators for 212 countries and territories, measuring six dimensions of governance, 1996-2007 (Kaufman et al., 2008): Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Efficiency, Regulatory Quality, Rule of Law, and Control of Corruption. The aggregate indicators are based on 35 data sources provided by 32 different organizations, reflecting the views of experts, as well as citizen and firm survey respondents worldwide. Despite its relatively low scores in the areas of Political Stability and Absence of Violence/Terrorism, Rule of Law, and Control of Corruption, Mexico scores reasonably well in the area of Regulatory Quality, ranking above the median among all 212 countries for this category (OECD). Mexico also shows modest improvements in Regulatory Quality for the three most recent years in the study. Interestingly, Mexico’s scores for Regulatory Quality are significantly higher than for other large, industrial countries in Latin America (with the exception of Chile, which scores higher than all other countries in
# **6. Consistency of monetary international poverty rates with non-monetary welfare dimensions**

This section considers whether the international extreme poverty rate rankings are consistent with non-monetary dimensions of welfare. Thus far, we have examined monetary metrics of individual well-being, including the national and standardized consumption aggregates. This section assesses how the ranking of monetary welfare related to other non-monetary dimensions of well-being. A country with high levels of (monetary) international poverty may perform badly in other nonmonetary welfare dimensions. Table 13 lists some indicators of non-monetary well-being for the subpopulation of poor people identified using the national consumption aggregates.

**Table 13. Summary statistics of indicators of non-monetary well-being for the extreme poor**

|**identified**|**using the na**|**tional cons**|**umption**|**aggregates**||||
|---|---|---|---|---|---|---|---|
|**Variable**|**Bangladesh**|**Bhutan**|**India**|**Maldives**|**Nepal**|**Pakistan**|**Sri Lanka**|
|_Household Composition_||||||||
|Household size|5.73|8.40|6.43|7.53|7.16|10.01|5.60|
|Dependency Ratio|0.97|0.73|0.78|0.67|1.16|1.42|0.70|
|_Education Attainment in Household_||||||||
|Household head Knows How to<br>Read/Write|0.29|0.19|0.50|1.00|0.37|0.28||
|Proportion of Household Member<br
countries to estimate that the proportion of adult migrants with tertiary education increased fourfold over 1975-2000. The increasing amount of South-North migration coupled with the increasing skill level of this migrant flow means that brain drain is increasing in absolute terms.

However, educational levels in developing countries have also been rising dramatically over the past decades. As a result, de Foort (2008) finds that the _rate_ of high-skilled emigration (relative to the base of all tertiary-educated individuals) has been very stable at the global level over the period 1975-2000, with the educational level of the home workforce increasing at a similar rate to the increase in tertiary educated migrants. However, sub-Saharan Africa is an exception to this pattern – a region in which tertiary education growth remained low and did not offset the rise in skilled migration.

Analysis of migration flows faces severe data constraints, and a full picture of brain drain trends during the 2000s will not emerge until after data are released from the 2010-11 round of global population Censuses. However, brain drain appears likely to have fallen in relative terms during this time. Tertiary enrolment rates have continued to grow dramatically, with gross tertiary enrolment rates for sub-Saharan Africa increasing from 3.9 percent in 1999 to 6.0 percent in 2009, those in South Asia increasing from 8.0 percent in 2000 to 11.4 percent in 2008, and those in Latin America and the Caribbean increasing from 20.9 percent in 1999 to 35.2 percent in 2007 (World Bank WDI and GDF global database [accessed November 22, 2010]). At the same time as stocks of tertiary-educated individuals have been rising in many developing countries, the intake of skilled workers has been quite flat over the first part of the decade in many OECD destination countries, and fallen in 2008-2010. For example, the United States H1-B visa program (the main temporary residence category for admitting skilled workers<sup>3</sup> ) issued visas to an average of 130,000 workers a year over the 2000s,
procedure used to estimate how much of a given expenditure (or taxation) category is received (imposed) by (on) a particular socioeconomic group or geographical area. Incidence analysis aims not only at identifying how much people in the lowest income groups receive or pay (that is, how ―pro-poor‖ spending or revenue collection is), but also how ―progressively‖ it does so—that is, how the cost or benefit correlates with a given welfare measure, such as income, consumption or wealth. Incidence analysis consists of several steps (see van de Walle [1998],):

- (i) Approximate the value to consumers of a public service—typically by equating it to the cost of providing the service;

- (ii) Identify all beneficiaries of the service;

- (iii) Obtain _gross_ unitary benefits by dividing total benefits (from step i) among total beneficiaries (from step ii);

- (iv) Rank the identified beneficiaries in the household dataset according to some agreed measure of welfare (such as, for example, deciles or quintiles of household per capita consumption); and

- (v) Assign the gross unitary benefit (as obtained in step iii) across the distribution of beneficiaries identified in the household dataset and compute the shares of the services that are allocated to different portions of the population. The unit of analysis is, typically, the representative household by quintile or decile of the income or consumption distribution on a per capita basis.

In order to calculate _net_ benefits two additional steps are needed:

- (i) Calculate the out-of-pocket household per capita spending from the household dataset; and

- (ii) Subtract the out-of-pocket household per capita spending to the expenditure assigned as the benefit. The resulting figure is the net unitary benefit per individual or household after receiving a public service. .

As for data requirements, the first three steps rely on information about public spending in the relevant sectors and the beneficiaries or users of those services, which is typically available
and re-timing provisions (Column 6) also play a role: each accounts for about 15% of the ETR difference on average. Finally, Column 9 controls for all our explanatory variables at once: 83% of the coefficient on the top 1% dummy is explained but 17% remains unexplained with our method.

This is because we only control for tax incentives with dummy variables, instead of actual amounts. Taking into account the amounts, i.e. fully decomposing the STR-ETR difference into the different drivers, is not possible with our methodology and with the requirement that tax expenditure concepts are harmonized across countries. This is because some tax expenditures are deducted from the tax base while others are deducted from the tax liability, and these concepts interact. For instance, the importance of losses in explaining low ETRs depends on the extent to which a firm used special deductions to lower its tax base. We do not engage in a full accounting decomposition of the ETR, as this would require a country-specific exercise, and distract from our focus on the general ETR-firm-size pattern and its comparison across countries.

**Discussion** We would ideally like to categorize and study tax expenditures by their intended rationale, but doing this transparently with tax return data is challenging: some provisions have generic names, while others have precise names but refer to laws stating multiple objectives. Frequently, line items on tax returns concern several tax provisions and objectives. To try to specify the intent and importance of specific tax provisions, we draw, in addition to the tax return forms, on each country’s tax expenditure reports. Table A.7 lists for each country the availability of each type of provision (based on the tax form): claims for tax credits (the most important tax provision in explaining the ETR drop at the top) and exempt income are available in 8 of the 13 sample countries. The countries where neither is available are the ones with flatter ETR-firm-size profiles: the low tax rate Balkan countries (Albania and Montenegro
Third, the magnitude of discrepancies between different methods varies by crop, with larger difference for continuous crops like cassava and bananas. Moreover, econometric analysis of the difference between different methods to estimate output allows identification of household characteristics that tend to be associated with systematically larger differences. We find that smaller household size, higher levels of productivity (yields), larger cultivated areas, and to some extent higher levels of education and wealth are all associated with lower differences between methods. As these characteristics are also associated with higher levels of drop-out or non-response for diaries, there may be scope to exploit complementarities between different methods, with diaries producing particularly good estimates of output for continuously harvested crops obtained by households with limited amount of formal education at the tail end of the distribution.

The paper is structured as follows: Section two highlights challenges and our approach by reviewing pros and cons of different ways of collecting agricultural production data. This is used to describe why diaries were introduced, how they were implemented, on a trial basis, in Uganda, the challenges they need to respond to.. Section three provides empirical evidence regarding diary coverage and respondent fatigue. Section four compares results obtained by different types of survey both at a descriptive and an econometric level. Section five concludes by pointing towards implications for policy and research.

# **2. Approach and challenges**

To motivate the diary approach, this section briefly reviews pros and cons of different methods used to collect information on agricultural production in situations such as the Ugandan one where large part of crop output is made up of continuously harvested crops. In fact, crops like cassava and banana are generally harvested in small quantities over long periods of time, thus making recall over several months rather difficult. We then describe the methodology used to administer the diary approach in parallel to the 2005/06 National Household survey and the potential biases it was expected to reduce.

# **2.1 The challenge of collecting reliable information on continuously harvested crops**

Data on agricultural
**4**

Our results have implications for future policy making and research. First, our results show that the impact of noncognitive skills can be underestimated when looking at only one individual in the household, particularly in informal sectors where the household is the relevant unit of production. This insight has important implications for evaluating the growing number of training programs aimed at increasing individual noncognitive skills. Second, our results show that what matters for predicting income-earning is the relative level of noncognitive skills within the household. Looking at equilibrium effects through impacts on other individuals is crucial to fully understand the poverty-reduction potential of noncognitive skills. Lastly, our results imply that positive impacts of noncognitive skills could be enhanced by an accompanying alleviation of inputs scarcity.

The remainder of the paper proceeds as follows. Section 2 introduces the data and presents summary statistics. The conceptual framework is outlined in Section 3, while Section 4 presents our main results on the link between spouses’ self-esteem and income-earning and its mechanisms. Section 5 presents evidence on the direction of causality, while Section 6 provides additional results with an alternative outcome specification. Section 7 concludes with policy implications and suggestions for further research.

# **2 Context**

This paper uses data on farmer couples collected by the authors in June-July 2016. The survey formed the baseline of a randomized controlled trial to assess the impact of improving farmers’ access to technologies and markets. The survey elicited information on the self-esteem, agricultural self-efficacy and time and risk preferences of the farmers that applied to the program, as well as of their spouses. The spouses were asked these modules separately and privately. The household survey also collected information on couples’ socio-demographic characteristics and income generating activities, along with modules on expenditures, saving, credit, transfers and social networks, shocks and coping strategies, assets and food security. Table 1 shows descriptive statistics for our sample.

Our primary outcome of interest is income-earning in agriculture. For the rural households in Côte d’Ivoire we surveyed, the scope for engaging
sup> Tribes often play a very practical role in daily life, with many Iraqis relying on their tribe for physical protection, economic resources, and dispute mediation on a day-to-day basis,<sup>31</sup> not only in rural areas (where adherence to tribal customs, traditions and hierarchies is typically strongest) but also in urban areas, particularly where rural-to-urban migration is common.<sup>32</sup> Tribal justice and formal justice often work in a complementary manner in Iraq, and coordination occurs regularly between tribal leaders and security forces to address criminal behaviour;<sup>33</sup> in some cases, law enforcement officials and courts choose to refer cases to the tribal system for settlement.<sup>34</sup> Conversely, in controversial or

> 23 Genat, M. 2020. _Tribal Justice Mechanisms and Durable Solutions for Families with a Perceived Affiliation to ISIS_ . IOM Iraq.

> 24 Blocked returns are commonly enforced by security actors on the ground, usually on the grounds of the IDPs families not possessing the required documentation (mostly a security clearance) to leave the area if displacement or re-enter the area of origin (IOM Iraq, 2021).

> 25 Genat, M. (2020) and IOM Iraq (2018).

> 26 See for example Human Rights Watch (2017). _Iraq: Looting, Destruction by Forces Fighting ISIS._ Available at: https://www.refworld.org/docid/58a5b4344.html

> 27 Oxfam (2021). _Community perceptions of Sexual and Gender Based Violence._

> 28 Aymerich, O., 2020. Community Resilience and the Return of Iraqi IDPs with Perceived Affiliation to the Islamic State. Refugee Survey Quarterly, 39(4), pp.552-563.

> 29 Hussein H. (2007) _Iraq: Tribal structure, social, and political activities._ Otterman, S. (2005). _Iraq: The Role of Tribes_ . Available at: https:/
growth of world trade in the second half of the twentieth century. Conversely, Rubin and Tal (2008) and Rubin (2009) have built on this theory to conjecture that rising oil prices will lead to a major slowdown in the growth of world trade, and especially intra-GPN trade. In this section, we will attempt to gain insights into this latter conjecture, by using the panel data structure of the processing trade data to analyze the sensibility of intraGPN trade to changes in oil prices.

# **5.1. Trends in oil prices and transportation costs**

Oil prices have risen dramatically in the last decade. As it is shown in Figure 10, while crude oil prices were relatively stable and even declined over the period 1980-1999, they have rapidly increased over the period 1999-2008, growing at an annualized rate of 20.6%. During the Great Recession of 2008-2009, the oil prices have retreated (see Figure 10), but this is likely a temporary phenomenon. As the global economy comes out of the recession and as peak oil is reached, oil prices are expected to return to and even exceed its pre-crisis levels. Peak oil refers to the attainment of the maximum conventional oil output (i.e. excluding heavy oil from tar sands, oil shale etc.), expressed in terms of millions of barrels of crude oil extracted per day (Deffeyes, 2001). There is a general consensus among oil experts that peak oil will be reached prior to 2015 (De Almeida and Silva, 2009). When this occurs, the gap between oil production and demand is expected to increase. As a consequence, the price of oil is expected to both rise significantly and become more volatile.

# **[Figure 10 about here]**

Rubin and Tal (2008) have argued that the rise of oil prices is likely to lead to significant hikes in international transportation and thus will lead to a major slowdown in the growth of world trade. As supporting evidence, they