rafmacalaba/data-use-mentions-extended huggingface dataset:
|Rural Poor – Chriqui|105.6|3.5%|132|1.1%|1,250|
|---|---|---|---|---|---|
|Rural Non-Poor Chiriqui|120.0|3.9%|359|3.1%|2,993|
|Rural Poor – Other Panama|513.9|16.8%|520|4.5%|1,012|
|Rural Non-Poor Other Panama|236.8|7.7%|584|5.1%|2,468|
|Urban Poor|370.9|12.1%|575|5.0%|1,550|
|Urban Non-Poor|1,483.9|48.5%|8,941|77.5%|6,025|
|Rural Poor|757.5|24.8%|800|6.9%|1,055|
|Rural Non-Poor|447.3|14.6%|1,220|10.6%|2,728|
|**All Panama**|**3,059.6**|**100.0%**|**11,536**|**100.0%**|**3,770**|

_Source:_ Authors’ calculations from 2003 Panama SAM.

Table 6 shows the effects of a 1 dollar exogenous increase in value added from the various tradable goods sectors. For example, on average, a US$1 increase in the output of goods and services from the Zone Colon leads to an additional US$0.42 increase in value added from non-traded goods and services (national economy simulation).<sup>17</sup> This gain is due mainly to consumer spending effects as incomes earned in various activities
labor force can foster the idea that girls are equally capable of being economically productive. This in turn can change young girls’ aspirations and perceptions,<sup>19</sup> and encourage parents to invest in their daughters (similar to the role model effect described above). Schooling and employment opportunities can also bring about ideational change by exposing young individuals to gender egalitarian ideas (see Thornton’s (2001) literature review/commentary on developmental idealism).

Note that women with higher education and/or employment status do not always display a lower tendency to sex select. In fact, there are various studies that suggest that they are more likely to sex select (DasGupta 1987; Amin 1990). The results from the studies cited in this paragraph and the one above are not necessarily contradictory if one accounts for the non-linearity between maternal education (or other markers of socioeconomic development) and son preference (this argument is expanded upon in Section 5).

**Table 4: Overview of studies that illustrate the link between female education/employment/access to financial resources, and female child wellbeing**

|**Author(s)**<br>**(Date)**|**Research question**<br>|**Data**|**Empirical strategy**|**Key findings**|
|---|---|---|---|---|
|Murthi et. al<br>(1995)|What covariates are<br>associated with<br>gender-specific<br>child mortality<br>rates?|District-level data<br>from 1981 Census|Multi-variate<br>regression<br>(associative study)|Higher female<br>literacy in a district<br>is associated with<br>lower odds of a<br>gender gap in child<br>mortality. These<br>results hold across<
unweighted, and clustered standard errors are reported in parentheses.

# **Reduced Coping Strategy Index (RCSI)**

|**Statement**|**Share of r**<br>**choosing**<br>**that indi**<br>**severe ou**<br>_PPCS_|**espondents**<br>**responses**<br>**cate more**<br>**tcomes (%)**<br>_Facebook_|**Difference**<br>**(Percentage**<br>**point)**|**N**<br>**(combined)**|
|---|---|---|---|---|
|Reduced the number of meals for all|27.64|63.59|35.95|6450|
|household members per day|(1.31)|(2.01)|(2.40)||
|Reduced the quantity of meals eaten by adults|25.09|56.45|31.37|6434|
|in favor of children|(1.24)|(2.10)|(2.44)||
|Purchased low quality markets "Leftover"|35.99|46.21|10.22|6430|

24
Figure A11: Heterogeneity in poverty gradient across countries, DB <!-- Start of picture text --> MWI<br>LSO<br>AGO<br>UGA<br>GHA<br>GNB<br>BFA<br>NER<br>SEN<br>GIN<br>TCD<br>CIV<br>ETH<br>TZA Core<br>MRT Suburb<br>Towns<br>GAB<br>−.5 −.4 −.3 −.2 −.1 0 .1 .2<br>Regression coefficients and confidence intervals<br><!-- End of picture text --> Source: International Urban Poverty Database. Each dot represents the regression coefficients _DBj_ ( _i_ ) of regression 6 for each country _c_ , excluding control variables. Confidence intervals are represented with a line. The dependent variable _POVi_ is a dummy variable taking the value 1 if a household’s per capita expenditure expressed in PPP and spatially deflated falls below the poverty line. _DOUj_ ( _i_ ) is a vector of dummy variables: "Core", "Suburb", "Town" respectively take the value 1 if household _i_ lives in an "Core", "Suburb" or "Town" as defined by the DB method. The baseline category is "Other rural". WorldPop 250m is used.

35
using the World Bank classification. We interact our main robot measure with a developed and developing country dummy, in order to report the estimated effect for each country group against zero. We do this in preference to sample splitting in order to maximize the power in our IV estimations.

> 17 We also examine including product-year fixed effects, thereby fully saturating the model with dummies.  This clearly works the data extremely hard and first-stage F statistics fall to around 5.  We find broadly similar results, with similar signs and size of coefficients, but these are identified more noisily, with some evidence of statistical significance.  Results are available upon request.

18
lost some of its previous attraction to donors but can be expected to have a major revival as part of various carbon sequestration initiatives (Paquette and Messier 2010). This can be instrumental since the underlying problem in the mismanagement of most commons is under-investment (Swanson, 1992). Despite the academic leaps in understanding the functioning of CPR management, spearheaded by Ostrom, there is still much to learn about how external actors, such as governments and donors, can support a process that both leads to sustainable resource management and equitable distributions. Section 2.3.3. noted the importance to give particular emphasis to the representation of disadvantaged women in such management committees if their interests are to be taken into consideration.

Charcoal projects have the potential to reach also urban beneficiaries. The charcoal trade also gives rise to a large number of jobs. Charcoal is, however, not a very sustainable source of energy to invest in from a climate change perspective, as long as traditional kilns are used.

# **5.3 Increased access to improved cooking technologies**

**The Bank Group should facilitate tapping into carbon finance and technical assistance to promote improved cooking options. It should also consider a program of rigorous impact evaluations and participatory monitoring of household cooking and energy projects, as well as analytical work on the gender dimensions of political economy.**

> 53 For the book ―Rising Global interest in farmland‖ the World Bank made an in-depth inventory of large-scale land acquisitions in 19 countries. One of the findings was that ―[m]any of the projects studied had strong negative gender effects, either by directly affecting women‘s land-based livelihoods or, where common property resources were involved, by increasing the time required of women to gather water or firewood and take care of household food security. In many cases, it was presumed that land rights were in the name of men only, and consultations were limited to males in the community, leaving women without a voice. Bargaining power within the household was affected
2,422|2,422|2,422|2,422|2,422|2,422|

Note: This table estimates how households were impacted by the complete air and sea blockade that began during November 2017. The post blockade indicator is an indicator equaling one if the household was interviewed after November 6, 2017, which was the day the blockade began. All specifications include governorate fixed effects. Standard errors are clustered by governorate and reported in parentheses. The data used in these specifications is the household-level data from the November 2017 mobile Vulnerability and Analysis Mapping Survey. * denotes significance at the 1 percent level; ** denotes significance at the 5 percent <u>level; and *** denotes significance at the 1 percent level.</u> 24
more gains there are from their removal. The larger distortions in the CASE study partly reflect the fact that our study was based on estimates of distortions in 2010, while the CASE study uses estimates of distortions from 2006 or 2007. Since Armenia has implemented substantial reforms in the interim, the initial distortions in the CASE study are significantly higher. This is the case with border costs. But it is also due, in some cases, to the fact that we had greater data available to us that allowed a more accurate estimate, for example in the services survey and estimates that we conducted. Further, there is a key modeling assumption difference in the assumption of which countries benefit from preferential liberalization of services that results in larger estimated gains in the CASE study, and a further modeling assumption difference in the comparative steady state scenario.

# **I. Comparative Static Estimates**

# (i) **Barriers in Services.**

The estimated gains of the CASE team from services commitments as part of a DCFTA should be substantially greater than the estimates in the present study for two reasons. First, the CASE team assumed that the barriers to foreign direct investors in services are much higher than we have estimated. Second, while our study assumed that commitments to foreign services suppliers under the DCFTA will be limited to EU suppliers, the CASE team assumed that the commitments under the DCFTA will be provided to all foreign suppliers (Maliszewska et al., 2008, p.154). We elaborate on each of these two aspects.

> 44 The latter estimates is for our ―unilateral‖ scenario.

115
- Masyn, Katherine. 2013. Latent class analysis and finite mixture modeling. In T. D. Little (Ed.) _The Oxford handbook of quantitative methods in psychology. Volume 2_ . pp. 551-611. New York, NY: Oxford University Press.

- <mark>McMillan, J. and Woodruff, C., 1999. Interfirm relationships and informal credit in Vietnam.</mark> _<mark>The Quarterly Journal of Economics</mark>_ <mark>, 114(4), pp.1285-1320.</mark>

- <mark>Medina, L. and Schneider, F., 2019. Shedding light on the shadow economy: A global database and the interaction with the official one.</mark>

- <mark>Mike, Károly, and Gábor Kiss. "Combining formal and informal contract enforcement in a developed legal system: a latent class approach."</mark> _<mark>Journal of Institutional Economics</mark>_ <mark>15, no. 3 (2019): 521-537.</mark>

- <mark>Moran, Peter, and Sumantra Ghoshal. "Markets, firms, and the process of economic development."</mark> _<mark>Academy of Management Review</mark>_ <mark>24, no. 3 (1999): 390-412.</mark>

- Noordewier, T. G., G. John and J. R. Nevin. 1990. “Performance Outcomes of Purchasing Arrangement in Industrial Buy-Vendor Relationships.” _Journal of Marketing_ 54: 80-93.

- North, Douglass C. 1990. _Institutions, Institutional Change, and Economic Development_ , Cambridge: Cambridge University Press.

- Nylund-Gibson, Karen, Katherine E. Masyn 2016 Covariates and Mixture Modeling: Results of a Simulation Study Exploring the Impact of Mis-specified Effects on Class Enumeration, _Structural Equation Modeling: A Multidisciplinary Journal_ , 23:6, 782-797.

- Oberski, Daniel.
<mark>Aterido et al. (2011) examine the impact of access to finance, the regulatory environment, corruption, and access to electricity on the employment growth of small and large firms in 85 countries. They observe that market failures or policy-induced distortions can create fixed costs in business operations, resulting in cost advantages for larger firms; large firms may also wield more political power, influencing regulations and policies in their favor; however, lax enforcement of laws may benefit small businesses. Aterido et al. (2011) do f</mark> ind that micro and small firms have less access to formal finance, face significantly greater interruptions in infrastructure services, and pay more in bribes—as a percentage of sales—than do larger firms. In turn, larger firms spend significantly more time dealing with officials and red tape. In general, the evidence suggests that smaller firms may be more vulnerable to lower-quality institutions and public goods provision because of greater ethnic fractionalization.

# **<mark>3. Data and Main Variables</mark>**

# 3.1 _Data description_

The main data source we use is firm-level surveys conducted by the World Bank's Enterprise Surveys (ES) between 2007 and 2019. The ES are nationally representative surveys of formal (registered) private firms with five or more employees. The surveys cover manufacturing and service firms but exclude some industries such as banking and finance, health care, extractive industries, and agriculture. The sampling methodology used is stratified random sampling with the region (sub-national), sector, and size as the strata. The use of a standardized survey instrument and methodology allows for comparisons across economies. Sampling weights are provided to correct for oversampling and are used throughout. We complement the ES with country-level data obtained from World Development Indicators (WDI, World Bank), Worldwide Governance 13
Policy Research Working Paper 8033

# **Abstract**

Absent actual panel household survey data, this paper constructs, for the first time, synthetic panel data for more than 20 countries accounting for two-thirds of the population in Sub-Saharan Africa. In this process, the analysis employs repeated cross sections that span, on average, a six-year period for each country. The analysis suggests that all these countries as a whole have had pro-poor growth. One-third of the poor population escaped poverty during the studied period, which is larger than the proportion of the population that fell into poverty in the same period.

The region also saw a 9 percent reduction in poverty and a 28 percent increase in the size of the middle class. However, chronic poverty remains high, and a considerable proportion of the population is vulnerable to falling into poverty. There is some limited evidence that most resource-rich and middle-income countries have more upward mobility than downward mobility. Post-secondary education is especially strongly associated with higher upward mobility and less downward mobility, which holds to some extent for female-headed and urban households.

This paper is a product of the Poverty and Equity Global Practice Group and the Development Data Group. 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 authors may be contacted at hdang@worldbank.org and adabalen@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/
_yc,t_ = _αc_ + _λt_ + _Postt ×_ ( _β_ 1 _T_ 1 _c_ + _β_ 2 _T_ 2 _c_ ) + _uc,t,_ (2) where the dependent variable will be one of the labor market outcomes. The right-hand side of the model includes canton and year dummies. The latter account for aggregate economic fluctuations, such as the downturn affecting Ecuador in 2014 and the years that followed, which clearly impacted labor market outcomes at the national level.

_Postt_ is an indicator taking a value of one for years 2016-2019 and zero prior to that (2013-2015). The key explanatory variables are _T_ 1 _c_ and _T_ 2 _c_ . These indicator variables identify _cantons_ with, respectively, a medium (2 _._ 5% _−_ 5 _._ 0%) and high ( _>_ 5%) density of Venezuelan migrants in the canton’s population in year 2019. The omitted category are _cantons_ with the lowest density of Venezuelans ( _<_ 2 _._ 5%).

Table 4 presents the estimates. The top panel estimates the models using the labor market indicators constructed using the whole working-age population. The estimates do not indicate any effects of Venezuelan migration on participation or employment rates, that is, we do not detect deviations in these labor market indicators of the highVenezuelan-density regions in the post-2016 period relative to the low-density regions. However, the estimates do suggest a worsening in employment conditions, measured by the adequate employment and informality rates, along with reductions in monthly earnings and employment, in the regions receiving Venezuelan migrants. The magnitudes are relatively small but with a clear pattern of larger effects (in absolute value) in the regions with the highest density of Venezuelan migrants (identified by indicator _T_ 2). Next, we turn to the labor-market indicators for the female population, which the literature has often shown to be adversely affected by inflows of refugees (e.g. Ceritoglu et al. (2017), Tumen (2016),
ception of fairness of the tax system. In addition, the new information generated through rms' self reports and third-party reports give the government a broader view of the economy and hence a better basis for policy design.

# 5 Conclusion

This paper has argued that non-ling among tax registered rms constitutes an important and under-researched compliance gap in low income countries, that can be addressed cost-eectively. In Costa Rica, approximately 25% of tax registered rms do not le their income tax declaration in a given year, and this share is similar in other countries in the Latin America region. We evaluate a nation-wide communication campaign in which the tax authority in Costa Rica requested non-ling rms by email to le their income tax declaration. The emails featured strong but credible deterrence messages, integrated behavioral insights and leveraged third-party reports about taxpayers' business activities. We nd that the emails tripled the ling rate and doubled the payment rate among previous non-lerstreatment eects that are substantially larger than those found in much of the existing literature, and that further increase when emails specically mention examples of third-party reported sales. The return on an email was US$ 19 for rms covered by third-party information, but only US$ .39 for rms not covered by third-party information.

We extend the literature on communication interventions to reduce compliance gaps by considering a large variety of outcomes, all measured through rm-level administrative tax records. We show that the emails generated no negative spillovers on sales tax compliance. They slightly increased the deregistration rate, but they also increased the likelihood of ling third-party reports about clients or suppliers, and income tax ling in the year prior to and following the year of the intervention. This nding of a persistent treatment eect, which applies to income tax ling and payment and the ling of third-party reports, suggests that the intervention permanently raised rms' perceived enforcement probability and hence their compliance level.

Although the intervention increased total tax revenue by less than a fraction of a percent,
# 6 Conclusion

This paper reviews the existing literature on the impact of migrant networks (diasporas) on the international migration patterns. In addition to size of the migration flows, we include the skill composition and concentration among these patterns we analyze and show that diasporas strongly influence all three. We first present a simple theoretical model that identifies the channels through which diasporas would influence migration patterns. These channels mainly operate through lowering of bilateral migration barriers via assimilation effects and family reunification programs. It identifies the key issues, namely the impact on size, selection and concentration of the migration flows. The paper also reviews the data and econometric hurdles that the researchers face in assessing the importance of networks. Among the key issues are the choice of individual micro vs aggregate macro approach, the definition of a network, the access to suitable data, and the adoption of econometric methods accounting for the main features of those data, such as wide prevalence of zeros.

The main results are illustrated with estimation results obtained using the Docquier-Lowell-Marfouk (DLM, 2009) data. Larger networks are shown to exert strong positive influence on the size of the international flows and lead to lower skill composition for a given corridor. We also show that diasporas also favour the concentration of the unskilled migrants with respect to the skilled ones. Destination and origin country specific factors are captured via fixed effects. All other bilateral variables, such as linguistic overlap, distance, colonial linkages have the expected signs and economically significant effects.

Naturally, there are many questions remain unanswered. One venue to consider is whether if these results hold for non-OECD destination countries and south-south migration. They require higher quality data that covers larger number of destination countries outside the OECD. Another key issue is separating the assimilation effect of diasporas from the visa effect which operates mainly through the family reunification programs. Such questions will require different types of dataset that combine aggregate data with household level data. In closing, diasporas are among the key determinants of migration patterns and we have only scratched the surface in
employers do not hire mothers of young children because of the pervasive doubt about the latter’s “attachment to the labor market”? The Pew Research surveys find that 84 percent of Indians agree with the statement: “when jobs are scarce, men should have more right to a job than women” (Pew Research Center 2010). Such attitudes are found to be negatively correlated with women’s labor force participation across many countries and are a reflection of social norms that reinforce the traditional role of women and also mediate the way institutions treat women and perpetuate gender inequality in the labor market (Das et al. 2015; World Bank 2013). Norms are often selfperpetuating, in that employers and investors look for what they expect to find. Unless they make a concerted effort to question the conventional wisdom, norms will remain largely stubborn to change.

The state can signal a more enabling vision for women and mothers in different ways. Publicly funded information campaigns that value women as workers and project child care as a shared responsibility in the home, are likely to remove some of the guilt that women often experience when they leave children behind to go out to work. Such campaigns have been effectively used in India and elsewhere to achieve health outcomes such as family planning, immunization, or for literacy and to enroll participants in social programs such as conditional cash transfers schemes. Both the state and the private sector in India are beginning to gingerly experiment with options to attract larger numbers of female workers into the labor market. We need a better understanding of what these initiatives are, how well they work and how they can scale up.

Finally, there is the issue of data and the analysis of the complexity of Indian women’s decision to stay out of the labor market. We need data that better capture norms, perceptions and aspirations, in addition to conditions of work, transport, housing, and infrastructure. Better analysis is also required about the mediating factors for women’s employment such as the extent to