rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 8882

# **Abstract**

Individual-level employment data have a wide range of applications. They are used to monitor labor markets and the Sustainable Development Goals, contribute to understanding and explaining socioeconomic conditions, and may help to design and inform labor market policies. This paper is relevant for academics and policy makers who want to understand the main survey design issues behind the collection of individual-level employment data in nationally representative household surveys and the implications for data quality, particularly for women and young people. The paper reviews four survey programs (Living Standards Measurement Study, Living Standards Measurement Study– Integrated Surveys on Agriculture, Labor Force Surveys, and Demographic and Health Surveys) in 14 developing countries. First, the paper reviews the Sustainable Development Goals to identify a core set of labor market indicators and briefly discusses the International Labour Organization’s definitions of key concepts that shape these indicators. Second, it assesses whether the Sustainable Development Goals labor market indicators are captured in the reviewed surveys. Third, it takes stock of current approaches to collect employment data and discusses critical survey design features, such as the structure of the labor module and the wording of the questions. Fourth, the paper examines whether these survey design features are gender and age neutral. Data from the Living Standards Measurement Study–Integrated Surveys on Agriculture are used to illustrate these issues. The paper concludes by proposing short- and medium-term objectives to improve the data quality in the Living Standards Measurement Study–Integrated Surveys on Agriculture.

This paper is a product of the Development Data 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 sam.desiere@kuleuven.be and vcosta@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 the World Bank or the governments they represent._ Produced by the Research Support Team
Table 10: Oaxaca-Blinder decomposition

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||GBF-EXT|GBF-INT|SBF-EXT|SBF-INT|
|FTM|-0.026|-0.028*|-0.038|-0.032|
||(0.023)|(0.017)|(0.035)|(0.023)|
|MTM|0.005|-0.001|-0.006|-0.008|
||(0.013)|(0.009)|(0.019)|(0.013)|
|Diference|-0.031|-0.027|-0.032|-0.023|
||(0.027)|(0.019)|(0.040)|(0.027)|
|Explained|-0.015|-0.016*|0.039*|0.019|
||(0.014)|(0.008)|(0.022)|(0.013)|
|Unexplained|-0.016|-0.011|-0.071**|-0.043*|
||(0.023)|(0.018)|(0.035)|(0.025)|
|**Explained**|||||
|Managerial quality index|-0.008*|-0.005*|-0.003|-0.002|
||(0.004)|(0.003)|(0.007)|(0.004)|
|Management human capital index|-0.004|-0.002|0.000|0.000|
||(0.005)|(0.003)|(0.004)|(0.003)|
|Innovation and skills index|-0.002|-0.001|-0.000|-0.000|
||(0.003)|(0.002)|(0.005)|(0.002)|
|Size|0.000|0.000|0.009|0.005|
||(0.005)|(0.003)|(0.006)|(0.003)|
|Multinational|0.001|0.000|0.003|0.003|
||(0.001)|(0.001)|(0.002)|(0.002)|
|Exporter|-0.004|-0.002|-0.002|-0.001|
||(0.003)|(0.002)|(0.004)|(0.002)|
|Government Support|-0.007***<br>|-0.004**<br>|-0.004<br>|-0.004*<br>|
||(0.003)|(0.002)|(0.003)|(0.002)|
|Interaction MNEs|0.004*|-0.001|0.006*|0.001|
||(0.002)|(0.001)|(0.003)|(0.001)|
|Sector|0.005|-0.000|0.030***|0.017**|
||(0.004)|(0.003)|(0.011)|(0.008)|
|**Unexplained**|||||
|Managerial quality index|-0.045|-0.028|-0.071|-0.024|
||(0.034)|(0.026)|(0.058)|(0.042)|
|Management human capital index|0.054<br>|0.035<br>|-0.040<br>|0.002<br>|
||(0.038)|(0.028)|(0.060)|(0.042)|
|Innovation and skills index|-0.016|-0.016|0.004|0.002|
||(0.020)|(0.017)|(0.027)|(0.019)|
|Size|0.005|-0.014|-0.004|0.045|
||(0.030)|(0.024)|(0.042)|(0.036)|
|Multinational|0.041|-0.002|0.109**|0.026|
||(0.033)|(0.028)|(0.045)|(0.033)|
|Exporter|-0.006|0.009|-0.026|-0.018|
||(0.025)|(0.022)|(0.035)|(0.029)|
|Government Support|-0.015|-0.005|-0.055**|-0.026|
||(0.018)|(0.013)|(0.023)|(0.017)|
|Interaction MNEs|0.011|-0.012|-0.000|-0.032|
||(0.026)|(0.021)|(0.038)|(0.029)|
|Sector|-0.056|-0.049*|-0.057|-0.038|
||(0.040)|(0.028)|(0.045)|(0.036)|
|Observations|11830|11831|7466|7428|

Note: This table presents the Oaxaca-Blinder decomposition results. MTF = Male Top Manager and FTM = Female Top Manager. All estimates employ sampling weights. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

Altogether, these results highlight some crucial aspects in which public policies can improve technology adoption by FTM and, in turn, reduce the productivity gap. Much attention has been given to policies tackling the gender digital divide, mainly focusing on increasing women’s participation in STEM and high technology sectors, fostering digital lit26
# **4 Online Experiment Methodology and Results**

## **4.1 Methodology**

The design of the online experiment was based on prior surveys about COVID-19 vaccine acceptance conducted by the World Bank in 2021 (Kovacevic et al., 2022; Bidani et al., 2022). It took place via Facebook from March 4 to April 6, 2022. Participants were recruited using Facebook advertisements (see example in Appendix A3) and were taken to a chatbot in Facebook messenger to complete the survey (see example of how the questions appeared in Appendix A3). Advertisements to recruit people to this study reached approximately 825,000 Facebook users and 10,837 people clicked on an advertisement to begin the survey. The sample was drawn from all Facebook accounts in Zambia over the age of 18 and quotas were applied based on demographic characteristics (age, gender, and region) to ensure adequate representation in the sample. At the time of the online survey, it was estimated that almost one-third of adults in Zambia have a Facebook account (Napoleon Cat, 2022), but these individuals were more likely to be younger, male and in urban areas compared to the general population. To address this issue, survey data was weighted using inverse probability weights based on age, gender, and region calculated using the most recent Zambian census from 2010 (see Appendix A3 for details). As a robustness check, the main experimental findings are calculated without survey weights and the results (i.e., the sample average treatment effects) are qualitatively similar to those presented in the body of the paper.

The treatments in the online experiment were informed by the findings of the in-person survey, existing studies on vaccine acceptance, and were also tailored to suit the Zambian context based on consultation with local stakeholders. Two similar, but distinct treatments were included to explore whether any differences existed between messages emphasizing benefits at an individual versus household level from getting a vaccine. Efforts were made to ensure that the treatments were as comparable as possible and potential differences between treatment groups would be attributable to the content, as opposed to the format. The 19
to determine the distribution of food assistance in Sahelian countries. As Figure 11 shows, the share of the population that is classified as food insecure by this methodology – specifically those in the ‘crisis’, ‘emergency’, or ‘disaster/famine’ phase of the Cadre Harmonisé – typically rises in the period from June to August, which corresponds directly with the agricultural lean season in Sahelian countries. Thus, seasonality is also captured by the tools that development practitioners use to monitor welfare and food security in the Sahel.

**Figure 11. Seasonal variation in food insecurity according to the Cadre Harmonisé**

<!-- Start of picture text --> 16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>Burkina Faso Mali Niger Senegal Chad<br>insecure (percent)<br>Share of the population that are food<br><!-- End of picture text --> Note: Food insecure corresponds to any populations in Phases 3 (‘Crisis’), 4 (‘Emergency’), and 5 (‘Disaster/Famine’) of the Cadre Harmonisé. Population numbers used to calculate share of the food insecure population taken from the Cadre Harmonisé itself. Source: Cadre Harmonisé and World Bank estimates.

The 2018 rainy season, which would determine the extent of the 2019 lean season on which this paper focuses, was regarded as relatively benign, enabling high agricultural productivity across the Sahel. For many areas in Burkina Faso, Mali, Niger, and Chad, biomass production during the 2018 rainy season was well above the 1998-2018 average, although in the Western Sahel – including in Senegal – rainfall was lower, leaving biomass somewhat depleted (Action Contre La Faim, 2018; FEWS NET, 2019). The reduced scarcity of agricultural output across most Sahelian countries is corroborated by the relative stability or even slight decline in the prices of key staple crops, which at least partially emerges in Figure 9 above (RPCA, 2019). As such, this paper covers a period of relative ‘normality’, which enables the analysis to try and isolate the effects of seasonality per se, rather than the compounding effects of large covariate shocks.

33
that _p_<sup>_′_</sup> _k_<sup>_≡dpk,d/dpk,i_isapositivefunctionof</sup><sup>_ρ_</sup> _k_<sup>.</sup>

# **3.1 Lobbying Game**

We model the lobbying game along the lines of Grossman and Helpman familiar protection for sale model, assuming for simplicity that all sectors are organized.<sup>17</sup> In the first stage, owners of sector specific capital in the home country lobby the government for advantageous trade policies on imported substitutes. In particular, they offer contribution schedules _Ck_ ( **t** ) that depend on the full vector of import tariffs. Each individual enjoys a consumer surplus _CS_ ( **t** ) =<sup>�</sup> _k_<sup>[</sup><sup>_Uk_(</sup><sup>_Xk_(</sup><sup>_pk,d, pk,i_))</sup><sup>_−pk,d_(</sup><sup>_p_</sup> _k_<sup>_∗_+</sup><sup>_tk_)</sup><sup>_xk,d −_(</sup><sup>_p∗_</sup> _k_<sup>+</sup><sup>_tk_)</sup><sup>_xk,i_]andreceivesalsoalump</sup> sum transfer from the government representing a share of the total tariff revenues _TR_ ( **t** ) = � _k_<sup>_tkxk,i_(</sup><sup>_pk,d_(</sup><sup>_p_</sup> _k_<sup>_∗_+</sup><sup>_tk_)</sup><sup>_, p∗_</sup> _k_<sup>+</sup><sup>_tk_),thatarerebatedtothepubliconanequal,percapitabasis.</sup> Note that both these components depend on the price of the domestic variety and we have made use of expression (6) to express them in terms of tariffs.

Assuming that the ownership of the specific factor is highly concentrated in the population, and in particular that the factor owners represent a negligible fraction of the total population, the objective function of each organized group can be approximated by where _lk_ is the total labor supply (and also labor income) of the owners of the specific input used in industry _k_ . In the second stage, each government chooses trade policy and collects the contributions that were offered. Formally, it seeks to maximize the following objective function: where **t** is the vector of tariffs applied by the Home country and _a_ is the weight the government puts on social welfare in its objective function. _W_ ( **t** ) denotes the aggregate social 17For a similar approach, see Grossman and Helpman (1995) and Mitra et al. (2006).

13
this analysis will be a useful template by which projects can better manage uncertainty in their investment decisions.

# **2 Review of World Bank Projects**

The typical approach to economic analysis is to conduct a cost-benefit analysis of the preferred investment option under best estimate predictions of the relevant future conditions. Consistent with the World Bank’s manual on economic analyses, analysts sometimes conduct a sensitivity analysis around the best estimate projection to address uncertainty (Belli, 2001). Occasionally they may replace a single projection with a probabilistic projection, assigning likelihoods to a variety of future outcomes.

These approaches have a common underpinning. Often termed Predict-then-Act (Dessai and Wilby, 2010), they seek to characterize the future (i.e. make predictions) and then measure policy options against the characterizations to determine the best near-term course of action. Predict-then-Act forms the basis of several analytic methods commonly used to evaluate investments (Lempert and Kalra, 2011; Hallegatte et al., 2012) – including traditional risk analysis, cost-benefit analysis (Arrow and Fisher, 1974), and real options analysis (Henry, 1974).

Yet the World Bank increasingly recognizes that such approaches may not help manage deep uncertainties that arise in many lending decisions (Hallegatte et al., 2012; IEG, 2010; Independent Evaluation Group (IEG), 2012). In this study, we sought to understand the World Bank’s economic analyses in greater detail by reviewing the Project Appraisal Documents (PADs)<sup>3</sup> of ten projects that were approved between 2002 and 2011. PADs are compulsory documents that projects must to submit to the World Bank’s Executive Board for lending approval. They contain basic information on the proposed projects, such as Country Ministries involved, project length and its objectives, a section on key risks and plausible mitigation measures, and the economic and financial analyses. The economic analysis should quantify the benefits and the costs of the proposed project and of the other options examined.

In our review of ten PADs we asked several questions:

- How many and which alternative options did the project originally evaluate?

- What uncertainties did analysts identify in the project narrative?

- Which of these were carried into the economic analysis of projects?

- How did the projects manage uncertainty?

While our small sample size lends no statistical weight to the answers, it enriches the observations made by the Independent Evaluation Group and others at the World Bank. We randomly selected investment projects in two sectors – energy and transportation – that were characterized by the World Bank’s project database as addressing climate change, a deep uncertainty.

> 3 PADs summarize the project team’s assessment of a lending project and are the basis for the World Bank's review and approval of lending projects. PADs include a project rationale, key components of the loan, potential areas of risk, and an assessment of the economic merits of the project.

4
contraception gained from watching TV (IEG 2008; Peters and Vance 2010). By the same argument, other health related behaviors may alter and lead to better family nutrition, reduce child morbidity and result in overall health improvements. Television shows, such as popular soap operas, may also have a role in altering the bargaining power and possibly the preferences of women within a traditional rural household.

Any improved productivity for one member is likely to have implications for other members through re-allocations within the household. Schultz (1993), for example, discusses how changes in home-based technology such as electricity can reduce household dependence on girls' labor. This will reduce the opportunity cost to the parents of sending their girls to school.<sup>9</sup> A number of studies also examine whether lighting in the home increases time spent studying and affects student performance, with mixed findings (for example, Aturapane et. al. 2011; Amin and Chandrasehkar 2009; Bensch et al. 2012). On the other hand, increased time spent watching television may well reduce the time on these activities.

Past claims about the household-level impacts of electrification on employment are hard to reconcile with the classic characterization of an under-developed rural economy as having a large labor surplus—as in the famous Lewis (1954) model. In a setting with a large excess supply of labor one would not normally expect a purely supply-side change such as a household’s electrification to directly increase employment. If the Lewis model is right, then the channel would have to involve relaxing the external quantity constraints on labor supply at the household level. However, it is important in this setting to distinguish formal (regular or casual) wage work from self-employment. The quantity constraints may well apply to the former but not the latter. For example, Dinkelman (2011) conjectures that the female employment effects she obtains (in a setting with unusually high unemployment rates<sup>10</sup> ) are through self-employment, although her data (from census employment questions) do not allow this type of work to be identified.

Externalities appear to be pervasive in this context. It appears to be common that when one family in a village acquires electricity and a TV, other friends and family without a TV come

> 9 For example, if schooling displaces child labor one-for-one then parents face a price of schooling equal to the child labor wage rate. While, there is evidence that one-for-one displacement is unlikely in a similar setting (Ravallion and Wodon, 2000), some displacement of activities within the household is plausible.

> 10 Around the time period of Dinkelman’s (2011) data (1996-2001), the female unemployment rate in South Africa was 40-50% and even higher in the region (KwaZulu-Natal) for which her data pertain (Bhorat and Oosthuizen, 2006). However, these are unusually high unemployment rates compared to other developing countries.

7
Policy Research Working Paper 7475

# **Abstract**

This paper identifies the low-elevation coastal zone populations and developing regions most vulnerable to sea-level rise and other coastal hazards, such as storm surges, coastal erosion, and salt-water intrusion. The focus is on the rural poor in the low-elevation coastal zone, as their economic livelihoods are especially endangered directly by coastal hazards and indirectly through the impacts of climate change on key coastal and near-shore ecosystems. Using geo-spatially referenced malnutrition and infant mortality data for 2000 as a proxy for poverty, this study finds that just 15 developing countries contain over 90 percent of the world’s low-elevation coastal zone rural poor. Low-income countries as a group have the highest incidence of poverty, which declines somewhat for lower-middle-income countries, and then is much lower for upper-middle-income economies. South Asia, East Asia and the Pacific, and Sub-Saharan Africa account for most of the world’s low-elevation coastal zone rural poor, and have a high incidence of poverty among their rural low-elevation coastal zone populations. Although fostering growth, especially in coastal areas, may reduce rural poverty in the low-elevation coastal zone, additional policy actions will be required to protect vulnerable communities from disasters, to conserve and restore key coastal and near-shore ecosystems, and to promote key infrastructure investments and coastal community response capability.

This paper was commissioned by the World Bank Group’s Climate Change Cross-Cutting Solutions Area and is a background paper for the World Bank Group’s flagship report: “Shock Waves: Managing the Impacts of Climate Change on Poverty.” It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The author may be contacted at EBarbier@uwyo.edu.

_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 the World Bank or the governments they represent._ Produced by the Research Support Team
25 Table 19: Ease of Obtaining Bank Credit Table 20: Involvement of Banks

||1990|11991|1992]||1990|1991|1992|
|---|---|---|---|---|---|---|---|
|AAA<br>AA|3.0<br>3.1|2.8<br>2.4|3.2<br>1.3|AAA<br>AA|2.5<br>3.1|3.0<br>3.6|3.2<br>3.7|
|A|3.2|2.0|1.2|A|2.4|2.6|2.8|
|Total||||Total||||
|Sample|3.1|2.3|2.2|Sample|2.6|2.9|3.1|

An improvement in the credit assessment of banks can also be inferred from the fact that of 25 enterprises denied credit in the last two years, 21 were A and only 4 were AAA. But the reason typically given was the general condition of the firm rather than the unviability of the project for which funds were sought. This points to a continuing weakness in project evaluation.

When asked why they believed bank behavior was changing, two replies prevailed: (a) banks have no option but to change owing to their vanishing net worth and deteriorating portfolios (most frequent reply); (b) banks, like enterprises, are learning. Although managers never alluded to it, there is a remarkable coincidence between perceptions regardino tighter bank behavior and the change in the governance in late 1991 of the 9 commercial banks spun off from NBP (commercialization, supervisory board control, strict monitoring by MOF, including a freeze in lending to some 2000 suspect firms - not all SOEs). At the same time, banks have been benefiting from the skills transference flowing from twinning with foreign banks.

Summing up, three positive developments are under way: (a) obviously good firms are actively wooed by banks to borrow; (b) banks were considered to have increased their involvement in enterprise operations and assessment of prospects even in cases where firms were no longer receiving loans; (c) good firms are now switching banks to bargain for lower interest rates.

## II.11. B Internal Financial Mana ement

The budget constraint is also hardening internally. More and more, firms have installed cash management and reporting systems. Profit centers have been created in some cases to pinpoint responsibility and ease performance measurement. There are unmistakable signs that financial management is strengthening.

# m. .c Inter firm Credit

There has been a remarkable change here. Good firms are no longer interested in supporting weaker ones. Firms frequently create their own ranking lists of buyers, specifying which will be dealt with only on cash terms, which will receive two weeks' credit, and which will not be supplied at all. Some make use of published lists of firms in conciliatory proceedings published in newspapers such as Rzeczpospolita.

## HIl.1.D Tax Arrears

This is the area where least change is visible, as Table 9 amply showed. Not only has the