rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 6: ICT firms do not import or export significantly more than other firms Average share of input and output exchanged domestically:

||||Inputs||||
|---|---|---|---|---|---|---|
||ICT|ICT<sup>_∗_</sup>|non-ICT|Manufacturing|Retail|Other<br>Industries|
|% inputs from West|66%|61%|65%|54%|64%|68%|
|Bank and Gaza|||||||
|Observations|126|60|407|87|202|118|
|_H_0 : ICT = non-ICT|(0.86)|(0.64)|||||
||||Output||||
||ICT|ICT<sup>_∗_</sup>|non-ICT|Manufacturing|Retail|Other<br>Industries|
|%<br>output<br>to<br>West|76%|70%|77%|59%|79%|80%|
|Bank and Gaza|||||||
|Observations|126|60|407|87|202|118|
|_H_0 : ICT = non-ICT|(0.75)|(0.29)|||||

_Notes:_ ICT<sup>_<u>∗</u>_</sup> excludes retailers and repairers. P-values for Wald tests reported in parentheses. _Sources:_ Authors’ survey.

as fundamentally oriented inwards. This is consistent with the conjecture that difficulties to import and export affect all firms, regardless of the industry. Given the lack of differentiation in the exposure to international markets between ICT and the rest of the economy, we abstract from these considerations in the model.<sup>28</
1.5 million website views in the first four months after the launch of the _Doing Business_ 2018 report. Overall, from 2004 to 2018, _Doing Business_ has been highlighted by countries’ local press more than 17,400 times.<sup>3</sup> Moreover, _Doing Business_ findings are widely discussed by international newspapers, including The Economist, The Wall Street Journal and The New York Times.

Media research presented in this paper demonstrates that to date, the OECD high-income group has the highest media coverage of _Doing Business_ , followed by the East Asia and the Pacific region. Conversely, in the Middle East and North Africa and Sub-Saharan Africa media give _Doing Business_ the least attention compared to the rest of the world. However, as demonstrated by our research, this tendency correlates with the media presence in the regions as well as with reform implementation efforts in the subsequent two years. At the same time, among all income groups, media across lower-middle income countries has the highest number of _Doing Business_ citations.

This paper aims to investigate to what extent (if at all) media impacts political decisions. A practical approach to test the relationship between mass media and political actions is through

> 3 Primary data collection on media coverage of _Doing Business_ has been done through the use of the Factiva database. Factiva is an online comprehensive database primarily designed to provide data to business communities, researchers and specialists, aggregating content from both private and public sources. It pulls data from more than 32,000 information sources, including newspapers, journals, magazines, television and radio transcripts. Factiva has an almost universal reach, allowing to filter data by local and international sources.

2
Policy Research Working Paper 8982

# **Abstract**

Turkey has moved rapidly from a current account that was relatively in balance up to the turn of the millennia, to sustaining relatively large current account deficits over the past 15 years. Using annual data from 1986 to 2017 and a jackknife model-averaging estimator, the paper estimates the relationship between the current account balance and a set of determinants that are broadly consistent with the cross-country literature. These determinants include private sector credit, public expenditure, real exchange rate changes, gross domestic product growth relative to the rest of the world, trade openness, international oil prices, foreign direct investment levels, past net foreign assets, inflation volatility, and global levels of uncertainty. The analysis then decomposes the predicted current account balance for five-year periods to illustrate the factors that have driven the current account over time. Over 2003–07, a large current account deficit became established in Turkey, driven by an expansion of credit to households and rapid gross domestic product growth, coupled with improved macroeconomic stability that supported higher spending and therefore imports. Since then, the negative effect of household credit has abated, but was replaced in 2008–17 by an expansion of credit to the corporate sector as a driver of the current account deficit. The current account balance in Turkey is also found to be less persistent than.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. 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 aportugalperez@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
br>§>> 1.500 zgogo<br>zs<br>8<br>z 522<br>g 1000 g 4 4<br>3 2<br>= &<br>R500 R 20<br>0 0<br>Urban Rural Urban Rural<br>HE WorldPop EEE Census | WorldPop MEE Census<br><!-- End of picture text -->

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. If we assume that access to finance is harder for women entrepreneurs than male entrepreneurs, then mobile money may provide female-owned businesses access to financing that was already available to male entrepreneurs. Therefore, through the financing channel we can expect mobile money to have a positive effect on investment by female-owned businesses but not male-owned businesses. Similarly, the collection of transaction, savings, and financial operations data from digital financial service platforms may generate credit scores and evaluate and price credit risk. This can help to overcome the so-called collateral technology hurdle, which has hindered the development of credit markets in Africa (Ndung’u, Morales, and Ndirangu. 2016). Mobile money can provide female-owned firms a way to develop 7
Our findings demonstrated the value of data for targeting users and tracking them to measure ad effectiveness, contributing to the ongoing debate on privacy and the use of third-party data in digital marketing. We proposed a series of micro-targeting techniques to maximize impacts in subpopulations of interest. By integrating privacy considerations into our experimental methodology, our approach highlighted how first-party data, directly collected from users on social media, can inform targeting and help reach the most valuable segments of the population—in our context, those most at risk of malaria. The methodology used in this paper is sector-agnostic and can be applied to both social and commercial campaigns.

## **Funding and Competing Interests**

This research has received funds from the World Bank’s Development Impact Department (DIME) and the Facebook’s Campaigns for a Healthier World initiative. Three authors do not have any competing interests to this work. One author has ownership interests in Virtual Lab LLC, a company that uses the open-source methodology described in the paper.

# **References**

- Acquisti, A., Taylor, C. and Wagman, L. (2016), ‘The economics of privacy’, _Journal of economic Literature_ **54** (2), 442–492.

- Ajzen, I. (1991), ‘The theory of planned behavior’, _Organizational behavior and human decision processes_ **50** (2), 179–211.

- Anderson, S. J., Chandy, R. and Zia, B. (2018), ‘Pathways to profits: The impact of marketing vs. finance skills on business performance’, _Management Science_ **64** (12), 5559–5583.

- Andreasen, A. R. (1994), ‘Social marketing: Its definition and domain’, _Journal of Public Policy and Marketing_ **13** (1), 108–114.

- **URL:** _http://www.jstor
9 months) because of the supply disruption.

# **(8) Concluding Comments**

There is a widely held view that the presence of marketing intermediaries in commodity markets ends up raising consumer prices; the effects of their market power in the supply chain exceed the value of the cost-reducing distribution services they provide. The Bangladesh 2011 policy experiment provides a rare opportunity to test this view, as it attempted to eliminate an entire layer of such intermediaries. Using high frequency data for the prices of imported crude palm oil besides wholesale and retail prices of refined oil relative to wheat, which is also imported in bulk and incurs similar storage and transport costs, we showed that the reform increased the average margin between the crude import and the wholesale price. In particular, the data firmly rejects the predictions of the standard double marginalization model which formalizes 34
|
|<br>Wouldstore:Sorghum|0.282|0.230|0.326|0.014|0.317|0.335|0.663|0.266|0.302|0.405|
|<br>Would store: Maize|0.565|0.514|0.657|0.001|0.660|0.654|0.882|0.598|0.603|0.907|
|Wouldstore:Millet|0.209|0.208|0.222|0.694|0.218|0.226|0.825|0.172|0.270|0.013|
|<br>#ofbagstostoreiftakingpartinwarrantage,|«6.745|5.175|8.063|0.001|7.172|8.940|0.069|5.898|6.963|0.221|

Notes: In sample refers to all households who were interviewed in the baseline survey. Participants and non-participants refer to those households who did and those who did not take part in the warrantage lottery respectively. Each row presents the proportion or means of the respective variable for the designated group. Column (4), (7), and (10) present p-values to test whether the means between the identified groups are the same.
no explanatory power in the decision to enroll, the R<sup>2</sup> would be close to zero.

As presented in Table 5, clearly, Central America is still far from reaching equal opportunity for all individuals, although the picture is mixed. Guatemala has the most unequal access to tertiary as household characteristics explain an important part of the probability of reaching tertiary education.

**Table 5: Explaining Access to Tertiary Education**<sup>**1 /2**</sup>

|**Country**|**Circa 2001**|**Circa 2009**|
|---|---|---|
|**Costa Rica**|0.18|0.19|
|**Panama**|0.17|0.18|
|**Guatemala**|0.35|0.43|
|**El Salvador**|0.30|0.23|
|**Honduras**|0.26|0.34|
|**Nicaragua**<br>Source: Authors’ c|0.28<br>alculations based on|0.18<br>several household|

<mark>Source: Authors’ calculations based on several household surveys circa 2001 and circa 2009</mark>

> 1 <mark>Pseudo R</mark> 2 <mark>from probit regressions. Dependent variable is starting post secondary education, independent variables are income and education of head of household and urban location.</mark>

> 2 <mark>Population group 21 to 25 years old.</mark>

Guatemala is followed by Honduras, and in both cases, the inequity in access has increased since 2000. On the other hand, El Salvador and Nicaragua have improved the equity in access to tertiary education. This evolution has allowed Nicaragua to join Costa Rica and Panama, which constitute the
to revisit our full baseline sample in each of these waves; we reached between 81% and 89% of households across treatment arms during these two survey waves, and find no evidence of differential attrition across treatment arms (Appendix Tables A7 and A8).

**Demonstration monitoring** In addition to the household survey, we gathered operational data during the demonstration year (November 2012 – March 2013) through detailed communication with each of the extension agents. For each village, we identified the full set of crops for which demonstration packages were distributed, and

18
In contrast, Honduras and Nicaragua, show constant correlations since the year 2000, suggesting no progress in mobility.

The last set of marginal effects in Figure 17 focuses on the location of households in rural versus urban areas. The estimates show that in all countries, living in a rural area is significantly correlated with the probability of being enrolled during secondary age, and notably, this is the marginal effect with the greatest magnitude in El Salvador, Guatemala, Honduras, and Nicaragua, where living in a rural area is associated with a reduced probability of enrolment of 13, 15, 16, and 14 percent, respectively. There are several channels through which geographic location can influence school attendance, and given that this effect results from an estimation that controls for personal and household characteristics, it is possible that this is capturing the effect of access to services, especially at the US levels. For example, in Honduras, analysis finds that over 1,000 additional secondary schools in rural areas would be needed to provide access for all secondary-age youth who are currently out of school, compared to the fewer than 200 that are currently operating today (World Bank 2014b).

The correlation of service supply with enrollment can be directly examined in the case of El Salvador, where we have access to detailed information at the municipality level on the number of schools of each level from the 2011 National School Census, which we merge with the household survey. Table 5 presents our results and compares them with the base estimation from which the coefficients in Figures 15-17 are derived. Two additional estimations are presented. The first includes only the number of schools for each level in the municipality of reference, and its effect is not statistically significant. However, in the second estimation (third column of the table) we

> 20 The lack of significance is not entirely surprising given how many other variables related to household head’s education are being controlled for, including household poverty and single-parent status

16
is easier to tie aid. Nevertheless we attempt to correct for any possible endogeneity bias empirically using instrumental variables estimation.

In table 5 we treat aid share as endogenous in estimating its effects on tied aid using 2SLS. Exogenous instruments for aid share include (1) geographic distance between the capital cities of the donor and recipients, (2) a dummy for whether or not the recipient is a former colony of the donor country, and (3) share of aid from multilateral donors, including the EC. Data on distance were obtained for 1946 observations from Gleditsch (2011), and supplemented with our own research for 13 other observations belonging to Tonga and Kiribati. The colonial ties variable was the product of our own research, and is defined with respect to the final colonial power for recipients where there was more than one. Data on multilateral aid shares are from AidData.

Colonial ties have been shown in various studies to be associated with higher aid from a donor (e.g. Alesina and Dollar, 2000). Donors also tend to focus more of their aid on countries within their geographic region, for example Japan and Australia in the East Asia and Pacific region. This likely reflects enhanced geo-political interests, as well as lower costs in providing aid (such as shorter flights for donor missions). Colonial ties and distance vary across observations both by donors and by recipients. The third instrument, share of aid from multilaterals, is a recipient-level variable. In recipients with higher shares of multilateral aid, aid shares for each bilateral donors should be lower (unless there are fewer of them present). The share of aid from multilaterals should have no direct effect on tying status of bilateral aid, although we cannot rule out the possibility that the decisions of some bilaterals may be influenced one way or the other by greater multilateral involvement in a country. For colonial ties and geographic distance, it is conceivable they could affect aid tying directly. If donors have more of a stake in development outcomes in recipients that
WPS3425

# **Can Student Loans Improve Accessibility to Higher Education and Student Performance?**

**An Impact Study of the Case of SOFES, Mexico**

Erik Canton<sup>a,b</sup> and Andreas Blom<sup>b</sup> a CPB Netherlands Bureau for Economic Policy Analysis b World Bank JEL: I2; J24

## **Abstract**

_Financial aid to students in tertiary education can contribute to human capital accumulation through two channels: increased enrollment and improved student performance. We analyze the quantitative importance of both channels in the context of a student loan program (SOFES) implemented at private universities in Mexico. With regard to the first channel, enrollment, results from the Mexican household survey indicate that financial support has a strong positive effect on university enrollment. Given completion of upper secondary education, the probability of entering higher education rises 24 percent. Two data sources are used to investigate the second channel, student performance. Administrative data provided by SOFES are analyzed using a regression-discontinuity design, and survey data enable us to perform a similar analysis using a different control group. Empirical results suggest that SOFES recipients show better academic performance than students without a credit from SOFES. However, the results cannot be interpreted as a purely causal impact of the student loan program, since the impacts also could reflect (self-) selection of students._

## World Bank Policy Research Working Paper 3425, October 2004

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available
on the data.

# 3.1 Demand and technology parameters

Our main parameters of interest are the capital adjustment cost and labor mobility cost parameters. We denote them with the vector Γ = ( _γ_ 1 _, γ_ 2 _, γ_ 3; _Ce, Cu_ ) . We estimate Γ by simulated method of moments (SMM, McFadden, 1989; Pakes and Pollard, 1989). Prior to the estimation of Γ we dene or estimate values for the other model parameters.

Table 1 provides a list of the parameters that are predened or estimated prior to the SMM. We set the discount factor _β_ to 0.95. The depreciation rate _δ_ is 0.0991. Due to lack of data for Argentina, we compute it as a weighted average of sectoral depreciation rates for the U.S. reported by the Bureau of Economic Analysis, using number of rms as weights. From National Accounts, we recover the consumption weights for each sector _φj_ in order to compute sector demand. Because demand is assumed to be Cobb-Douglas, a constant fraction given by the CPI weights is spent on each product. Argentine families spend on average 31.3 percent of the budget on food and beverages, 37.4 percent on non-tradables and 21.1 percent on other manufactures; textiles and apparel account of 5.2 percent, and minerals and metals for about 2.5 percent each.

The technology parameters, including coecients of the production function and the stochastic processes for the sector-level and rm-level shocks, are estimated with the rm panel and reported in Table 1 as well. We estimate the Cobb-Douglas output elasticities using the regression method of Ackerberg, Caves and Frazer (2015) with data on revenue, employment and capital stock. The estimates for _αL_ and _αK_ are 0.619 and 0.283, both statistically signicant. The input requirement for materials _vm_ is computed as a weighted average of the share of expenditure in materials on total value of production. The estimate is 0.41
2011). The Bank’s approach has evolved considerably over time. Initially the allocation of IDA funds was needs-based—with needs proxied by income per capita and population in 1960. To counter the politicization of aid during the Cold War, IDA first introduced selectivity to intercountry allocations in its allocation system. At the end of the Cold War, during its 12<sup>th</sup> replenishment negotiations, IDA took the conscious political decision to give more prominence to governance ratings.

Today the performance-based allocation system uses Country Performance Ratings (CPR) based on the Country Policy and Institutional Assessment (CPIA)—which is an annual assessment of policies and institutions by IDA and IBRD country teams along 16 criteria grouped into four clusters. The cluster that measure governance accounts for 68 percent of the weight and the other three clusters—macro management, structural policies, and social policies—have a weight of 24 percent of the total; and an assessment of portfolio performance also enters into the formula with a weight of 8 percent.<sup>9</sup> IDA attempts to balance needs and performance with a complex formula.<sup>10</sup> However there are also exceptional allocations for post-conflict countries, debt sustainability, regional projects, arrears clearance, and re-engaging countries. In conclusion,

> 8 There is a vast empirical literature on this topic, with no clear conclusions (for reviews, see Dethier 2008b or Arndt, Jones and Tarp 2009).  Some researchers have challenged the robustness of these results (Hansen and Tarp 2001, Easterly and Levine 2003, and Rajan and Subramanian 2008).  Some studies tend to find a beneficial effect of aid, differing primarily on how much the beneficial results depend on the environment, especially over a longer period (Minoiu and Reddy, 2009). Case-study evidence seems more consistent with the _Assessing Aid_ argument. Empirical work based on cross-country data remains work in progress (Temple 2010; Arndt, Jones and Tarp 2011). 9  The weight of
(Massey, 1986; Munshi, 2003, McKenzie and Rapoport, 2010). These datasets include different measures of individual economic, demographic and social characteristics, such as age, income, occupation and education. This contrasts with more approaches the employ aggregate international migration data. Both approaches have their advantages and drawbacks and should be seen as complementary strategies to address the key issues at stake here.

By focusing on individuals or households, micro data directly accounts for the role of individual characteristics of the migrants. For example, McKenzie and Rapoport (2010) confirm that the networks are more important for uneducated migrants than for educated ones in the case of Mexican migration to the United States. Another appealing feature of the micro datasets is that they can distinguish between different types of networks such as networks defined at the community (city or region) level or at the household (family) level. If such data were available, then we can identify what kind of assistance (such as financial 7