rafmacalaba/data-use-mentions-extended huggingface dataset:
fact a near-perfect overlap between these modules that are singled out in the discussion of interviewer effects and those that are identified as the top time-consuming household and individual questionnaire modules. And these modules are central to understanding monetary poverty and inequality in these contexts and to monitoring a range of individual-level indicators for the Sustainable Development Goals.

Overall, our findings reveal important insights from survey paradata on module development and implementation, in otherwise understudied low- and middle-income contexts. The type of analyses conducted in this paper can be considered by NSOs and survey practitioners for high-frequency and disaggregated insights regarding respondent burden and identification of priority modules with elevated interviewer effects in duration analysis such that timely training and field supervision measures that can be deployed to minimize these effects during ongoing surveys – particularly in the context of large-scale household surveys that can span up to 12 months in low- and middleincome contexts. Doing so would be in line with the calls for building NSO technical capacity in the use of paradata for household survey design, management, and quality control (Carletto et al., 2022).

29
|0.837|0.44|

Notes: Robust standard errors in parentheses; *** and * indicate significance at the 1 and 10 percent percent confidence levels, respectively. The dependent variables used in the regressions are measures in the country-year-destination level dataset (file CYD.dta) in the year 2008 for each country. The real GDP variable used is in PPP terms.

Our evidence that significantly more exporters serve larger destination markets is consistent with trade models with heterogeneous firms. These models show that as the size of the export market increases, firms with lower productivity are able to generate sufficient variable profits to cover the fixed costs of exporting and thus the number of exporting firms increases (Bernard, Redding, and Schott, 2011). Distance is typically used in gravity equations to proxy for 36
to Islamic inheritance law after their death - but the gender discrimination in the final wealth allocation is attenuated. Collecting novel survey data, I first provide correlational and descriptive evidence to assess to what extent gifting represents a second-best alternative to legal reform. Second, within a survey experiment I test whether providing information on public support for inheritance law reform and/or the possibility to gift one’s daughter has a causal impact on attitudes regarding women’s inheritance.

The primary data necessary for answering these research questions was collected in Tunisia between February and April 2023 via the phone. The total sample size in the first survey round was N=1,505. Respondents were randomly allocated to control (C), or to two different treatment arms where they received information on gifting (T1) or information on public reform support and gifting (T2). The second treatment T2 included a belief correction: respondents were told whether they underestimated, overestimated or correctly guessed public support for the introduction of gender equal inheritance law. I test the effect of the provided information on a set of inheritance-related gender attitudes, which are measured in a first endline directly following the treatment and in a second endline about four weeks later. I hypothesized that both treatments would increase respondents’ awareness of gender discrimination in inheritance and should thus lead to more gender equal attitudes. Yet, I conjectured that reform support may decrease in the treatment groups if gifting is viewed as a substitute for legal reform. Moreover, assuming that the perceived social norm functions as a constraint on individuals’ gender attitudes, the belief correction in T2 was expected to render the views of respondents who underestimate public reform support more gender progressive.

The observed treatment effects are mixed: T1 significantly increases respondents’ likelihood to favor a gender equal bequest allocation. Treatment effects on the other main outcomes - reform support and willingness to use gifting to achieve a more gender equitable bequest allocation - are positive but shy of statistical significance. Furthermore, these effects largely disappear when the gifting information is paired
# **1. Introduction**

A large body of research has attempted to explore the links between women’s autonomy and their use of reproductive health services in South Asia, but the evidence is inconclusive. Despite the consistent finding that broad socio-demographic characteristics such as education and economic status have a significant impact on reproductive health services uptake, the relationship between women’s decision-making power and their use of reproductive health services is unclear. For example, in India there appears to be no relationship between women’s freedom of movement and decision-making power and their use of reproductive health services (Bhatia and Cleland 1995; Bloom, Wypij, et al. 2001). Similarly in Nepal, Matsumura and Gubhaju ( 2001) report that decision-making power has a mixed impact on maternal health services utilization. Survey data from Pakistan also show a weak or no relationship between women’s reproductive health services uptake and measures of their autonomy (Sathar and Kazi 1997; Fikree, Khan, et al. 2001; Mumtaz and Salway 2005).

In addition to data source and methodology issues, some inconsistencies in the research findings may be due to lack of consistent measures of “autonomy” (Kabeer 1999), which in some South Asian countries is measured as women’s “mobility”. Thus, more recent literature urges the need to rethink the concept of women’s autonomy as the framework for understanding gender and reproductive health in South Asia and elsewhere (Mumtaz and Salway 2009). Although women are typically the primary points of contact for reproductive health programs, often the decisions that lead them to seek services are outside their own control and may occur in the context of families or households (Becker 1996; Beegle, Frankenberg et al. 2001).

This paper contributes to the literature by applying several constructed indices composed of eight women’s decision-making indicators to assess the relationship between women’s decision making and their reproductive health services uptake. This paper also considers the influence of male household members (household heads or husbands
, exploiting policy variation from Uruguay in regression discontinuity and difference-in-difference estimations. The rebate program was introduced in August 2014, at a time when Uruguay lagged behind peer countries in key financial inclusion measures (Figure A.1). There was significant scope to increase the use of electronic payment technology, and the reform program provided large and salient incentives: the rebates reduced the VAT payable on debit card transactions by up to 40 perent. The rebates were immediately granted to customers paying by card, without the need for refund claims or other hassle costs. We evaluate this program using transaction-level data on all electronic transactions and monthly firm-level VAT declarations for 2006-2015.

We document three main results. First, we use the high frequency of our data and a regressions discontinuity design in time to show that the introduction of the rebates lead to an 2
Figure 21: Probability of accessing public support by firm attributes.

<!-- Start of picture text --> (a) By firm size (b) By firm sector<br>50 50<br>40 36 39 40 39<br>33 33 31<br>30 30 30 26 29 28<br>23 24<br>20 17 21 20 19 17 19 17 17<br>13<br>10 10<br>0 0<br>Micro (0-4) Small (5-19) Medium (20-99) Large (100+) Hospitality Knowledgeintensive servicesOther Manufacturing Retail Agriculture<br>Wave 1 Wave 2 services<br>Wave 1 Wave 2<br>(c) By firm productivity<br>40<br>31 31<br>30 29<br>20 15 17 17<br>10<br>0<br>Low Middle High<br>Labor productivity tercile (within country)<br>Wave 1 Wave 2<br>Probability of accessing public support Probability of accessing public support<br>Probability of accessing public support<br><!-- End of picture text -->

# **5. Conclusions**

More than a year into the COVID-19 pandemic, policy makers’ attention has shifted from immediate crisis mitigation to policies that support medium-term adaptation and a longer-term, productivitydriven recovery. Utilizing novel panel data from 38, mostly developing countries, this paper provides new evidence to guide policy makers in this process. This evidence has been grouped into a set of six stylized facts on the shape of the recovery, its heterogeneity across indicators, countries, sectors, and types of firms; its relationship with uncertainty; digital technology adoption; financial development; and the evolution of policy support.

The results show that, some 7-12 months since the onset of the pandemic, business activity is recovering. Three in four firms that had temporarily closed during the early months of the crisis are operating
with all relevant stakeholders to manage the process of data production. (IOM, 2018). These are hard challenges, but non-conventional data sources offer such great potential in complementing (not in substituting) survey data that, at some point, these challenges will have to be faced. Our assessment, therefore, is that while these challenges and drawbacks currently make their potential combination with household surveys challenging in the short-run, these sources appear promising for the future, especially because of their ability to provide a large amount of more timely and granular data.

# **6. Conclusions**

<mark>It is easy to envisage that, as climate change intensifies, the climate change-migration nexus will keep gaining prominence in the international agenda. In parallel, the empirical literature will keep growing. Further refinements to the conceptual framework, as well as developments in econometric techniques, will shed new light on the relationship between these complex, multifaceted phenomena. However, all of this cannot provide concrete benefits for policy making without closing the existing data gaps.</mark> Based on the empirical review, we have identified the main data gaps on the climate-migration nexus. Using a household survey program currently at the forefront of methodological research, the LSMS-ISA project, we then identified the limitations and opportunities for household survey data to enhance our understanding of the causal relationship. A summary of this assessment is reported in Table 1, which provides a list of the most relevant conceptual and empirical issues, with the corresponding data gaps and a set of initial proposals to boost the potential of household surveys such as the LSMS-ISA. <mark>We have stressed that household surveys currently allow limited exploration of the climate-migration nexus. At the same time, we have also documented, in light of the open issues and research gaps in the literature, the great potential that LSMS-type surveys hold to help address some of the most policy-relevant research questions in the field. Our proposals are twofold: conceptual and operational. Conceptually, we call for researchers to make use
Policy Research Working Paper 10112

# **Abstract**

Similar to tariffs, non-tariff measures may induce trade fraud when they are restrictive. This paper examines whether discrepancies observed in the official trade statistics of importing and exporting countries are partly due to trade fraud from evading border non-tariff measures. To capture the restrictiveness of non-tariff measures, the paper estimates the ad valorem equivalent with importer-exporter-product variations. It presents a theoretical model and empirical evidence showing that discrepancies increase with ad valorem equivalents, consistent with the trade fraud due to traders intentionally mis-declaring countries of origin or misclassifying products in order to evade border non-tariff measures. The results are driven by homogeneous products and the trade between developed and developing countries.

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 hlkee@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
empirical evidence and international experiences, this working paper explores the potential role of investment incentives in advancing goals around gender equality, specifically, increasing female labor force participation, growing the number of women in leadership roles, and encouraging female entrepreneurship.

This paper is organized along three key sections. This opening section continues with the identification of supply‐ and demand‐side barriers that can impede progress toward gender equality in the workplace, and then introduces incentive instruments that may be considered to address these barriers. Section two elaborates on when and how different incentive instruments can help promote gender equality, discussing their respective advantages and disadvantages, and providing design considerations for implementation. Finally, the paper concludes with a summary of key findings and suggestions on areas for further research.

# **1.2 Identifying key barriers to gender equality in the workplace**

To understand which types of investment incentives can be effective in supporting gender equality goals, a first step involves discussing the barriers they aim to address. These can be categorized as “demand‐ side” barriers, which are barriers inhibiting firms and investors from hiring or investing in women‐led

> 7 World Bank Group, Enterprise Surveys, Latest available year.

> 8 Elborgh‐Woytek et al.

3
during this period while TFP growth explains about half of that performance. Additionally, demographics also contributed positively as the share of working age population increased.

**Figure 14. Growth decomposition of high performers during the Africa Rising period, 2000-14**

<!-- Start of picture text -->
-1<br>-2<br>Physical Capital  Human Capital  Demographics  TFP  Output per capita<br>SSA Tanzania Ghana Mauritius Zambia Angola Zimbabwe Liberia Nigeria Lesotho Mozambique Rwanda Mali Ethiopia Sierra Leone<br><!-- End of picture text -->

_Source:_ Penn World Tables 10.01 (Feenstra, Inklaar, and Timmer 2015). _Note:_ SSA=Sub-Saharan Africa.

The contribution of total factor productivity (TFP) growth is positive and large for all high-growth performers in Sub-Saharan Africa. TFP contributes over half of growth in nine of the 14 fastest growing economies in Figure 14 and is positive in the remaining five. It should be noted though that the high share of TFP contribution, the residual not explained by physical and human capital growth, in resource abundant countries might result from an intensive use of natural capital. Of the six resource abundant countries, two are oil abundant (Angola and Nigeria) while the remaining four are abundant in metals and minerals (Liberia, Mali, Sierra Leone, and Uganda). More specifically, accounting for the accumulation of natural capital reduces the contribution of TFP to growth per worker by almost 1 percentage point per year (Calderon 2021). On the other hand, factor accumulation accounts for more than half of growth per capita in five of the 14 fastest growing countries in the region, namely, Ethiopia, Mauritius, Mozambique, Rwanda, and Tanzania.

# **4. Growth Miracles: What Could We Learn from Successful Growth Stories?**

This section identifies “growth miracles”— as defined by episodes of sustained growth for a prolonged period—around the globe from 1960 to 2019. Once identified, we compare
Economic development involves specialization and movement of labor out of agriculture. An inability to formally trade or lease land will impede structural change, land market imperfections have been identified as key contributors to factor misallocation in agriculture (Restuccia and Santaeulalia-Llopis 2015). Limited tradability of untitled land across farmers results in land misallocation and distorts individuals’ occupational choice between farming and working outside agriculture, with potentially far-reaching impact (Chen 2017).

The importance of land rights documentation to facilitate long-term land transfers and occupational shifts out of agriculture is supported by the migration-enhancing impact of community land rights certification in Mexico, an effect that was particularly pronounced for households with weaker initial rights (de Janvry _et al._ 2015) and possibly mediated via inheritance (Valsecchi 2014). Reforms affecting transferability of land had large impacts on migration historically (Chernina _et al._ 2014) and on female labor force participation and wages (Emran and Shilpi 2017). Broad distribution of property rights in the US is seen as fundamental to participation in capital markets, use of land as collateral, and access to opportunity (Libecap 2018).

Documented land rights allow realizing the full potential from trade in land and its use as collateral in financial markets if authoritative information on the assignment of property rights is available at low cost, normally from public registries (Arrunada 2009). Credit impacts from land titling can be expected if land markets are sufficiently fluid and third parties such as mortgage lenders can easily access registries to get reliable land ownership information. If these conditions do not hold, credit effects of land titling may be absent or limited to the better off (Carter and Olinto 2003). Simple measures to reduce transaction costs and improve the quality of information, such as computerization can affect credit volume and the number of mortgages, as documented in India (Deininger and Goyal 2012) and, by enhancing access to digital savings and loan products, the rapid spread of digital handsets opens up opportunities in this space (Bharadwaj _et al._ 2019).

# **
|
|Unemployment rate|7.2|8.7|5.6|
|**(B) Only youth**||||
|Employed|23.8|23.0|24.4|
|Unemployed|3.7|5.2|2.4|
|Not active|72.5|71.8|73.2|
|Labor force participation rate|27.5|28.2|26.8|
|Unemployment rate|13.5|18.4|8.9|
|**(C) Poor**||||
|Employed|53.2|55.3|51.2|
|Unemployed|5.0|7.3|2.7|
|Not active|41.8|37.4|46.1|
|Labor force participation rate|58.2|62.6|53.9|
|Unemployment rate|8.5|11.8|5.0|

_Source_ : Kinshasa Survey 2018.

The female (particularly young) working-age population with higher education faces a particularly high rate of unemployment. A simple look at unemployment rates and workers’ educational attainment does not show any clear correlation (Panel A in Figure 3). The unemployment rate is 5–8 percent among those with primary education, secondary education, and higher education. Breaking down the relationship by gender, however, shows a contrasting pattern. The

> 3 Labor force is defined in this report as active if an individual either (a) worked during the last 7 days, (b) did not work during the last 7 days but had a job (that is, absent), or (c) did not work but looked for a job. The labor force participation rate is calculated as the share of active working-age population. Unemployment rate is calculated as the ratio of working-age population with no job to the total number of active
(2) _YhdJ = a, + Xhd!p + 5Fd + ehdl,_ where 6 is the (margyinal) impact of program expenditure on the outcome. These two equations can be more compac.tly written as follows: (3) _Yhd, a, + Xhdp +_<sup>_6_</sup> _Fd l(tl ) + ehd,,_ where I(t-l) is a indicator function equal to 1 in year 1, and 0 otherwise.

The "naive" approach is to estimate equation (2) by ordinary least squares, using only data from time period 1. This will produce a consistent estimate of 6 only under the assump Lion that the expectation of ehdl conditional on _Xhd,_ is zero. This assumption is suspect, however, both because FONCODES is targeted to poor areas, and because it is demand-driven. If poorer districts, with worse educational outcomes, receive larger levels of _Fd,_ and if poverty is n(:t adequately controlled for in _Xhd,,_ then it is likely that the estimate of 6 will be biased down. The estimate could be negative even if the program actually improves outcomes (see, for exan, pie, the results in Pitt, Rosenzweig and Gibbons for Indonesia). To some extent, this problem can be countered by including district-level measures in _Xhdt,_ in particular the composite index of unmet basic needs which FONCODES uses to make allocations. It is still possible, however, that decisions to fund projects are based on more accurate information about local conditions, informnation that we do not possess. It is also possible that households in districts that care. more about education, or have greater local institutional capacity, are those that organize to apply for FONCODES funding. If institutional capacity and "tastes" for education are unobserved and positively correlated with better educational outcomes, the naive estimate of 6 may be bias,-d up.

If two cross-sections of data are available, one from time 0 and
sense of not being a commercial bank.<sup>25</sup> Upwards of 750 million clients<sup>26</sup> of an economic level “not typically served by commercial banks” are estimated for this broad category – only one in four with loans. Commercial banks also offer such services in many countries, but these are not considered “alternative” and as such are not included in the CGAP inventory.<sup>27</sup> Despite its extensive coverage, it needs to be noted that the information on each intermediary stored in the CGAP database is rather limited: name, organizational type, number of deposit accounts, no of loan accounts, no. of members and sometimes the total value of loans and deposits outstanding. Also, it is not free of the multiple banking relationships problem alluded to above.

Shifting from their outreach to the operations of MFIs a large number of assessment reports and ratings are available for specific institutions. No attempt will be made here to summarize those. The largest cross-country database which does include a considerable amount of financial and operating information, is that assembled by the Microfinance Information Exchange (The Mix) with a summary published in _MicroBanking Bulletin_ . This is based on a 12-page questionnaire, covering balance sheet and income statement, infrastructure (staffing, offices etc), products and clients, portfolio performance, liabilities, subsidies received. The response rate has been quite variable from year to year. More than 200 firms reported in the most recent year, but a time series is available only for a fraction of that.

_Seeking information from the regulator and from providers_ In an attempt to obtain further detail on a cross-country comparable basis, the World Bank has recently prepared a questionnaire for developing country bank regulatory authorities (Beck et al., 2004). In addition to regulatory matters, this covers information on branch numbers and on the number and size of different types of deposit and loan accounts broken down by type of intermediary and by class of customer