rafmacalaba/data-use-mentions-extended huggingface dataset:
## **Template 4  ODA in infrastructure service delivery**

|**US$ millions**|**t-4**|**t-3**|**t-2**|**t-1**|**t**|
|---|---|---|---|---|---|
|Total infrastructure||||||
|140: I.4. Water supply and sanitation||||||
|210: II.1. Transport and storage||||||
|220: II.2. Communications||||||
|230: II.3. Energy||||||

Table 1.4 provides another example of how to leverage the SPI exercise using secondary sources. In this case, the table shows data from the OECD Credit Reporting Database for Sierra Leone.

**Table 1.4 Sierra Leone 2007, ODA in Infrastructure**

|**US$ millions**|**2002**|**2003**|**2004**|**2005**|**2006**|**2007**|
|---|---|---|---|---|---|---|
|Total infrastructure|2.79190057|66.48603636|39.50414176|94.27007312|3.33610499|55.43493961|
|140: I.4. Water supply and sanitation|0.97405642|8.82893883|18.16274457|5.58331844|10.6412804|11.78243788|
|210: II.1. Transport and storage|0.16644811|66.45760378|0|56.27007312|2.94492878|27.37850787|
|220: II.2. Communications|0.67516879|0|
**Figure 8. Incidence of main components of tax benefit system by types of households, share of final income, percent.**

<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>-20<br>-40<br>-60<br>two adults (or two adults (or two adults (or one adult and only working only pensioners mixed adults,<br>more) and 1 more) and 2 more) and 3+ child(ren) age adults no children<br>child children children<br>SSC Direct Taxes Pensions Direct Transfers<br>Indirect Taxes In-kind Health In-kind Education Total<br>Source: authors’ calculations using HBS-2017 data.<br><!-- End of picture text --> Geographically, the main beneficiaries are concentrated in rural areas and small towns, while those who live in big cities are net payers on average (Table 11, Figure 9). The rural and small town residents receive 12 and 5 percent of their final income as net benefits. It comes mainly in the form of pensions (23 percent). Other three components of benefit system (direct transfers, in-kind health and education services) have similar shares between 3 and 7 percent of the final income. While residents of big cities, including Chisinau, are net payers to the system on average, mainly because they benefit less from in-kind transfers and pensions, while pay much more through direct taxes and especially social contributions.

**Table 11. Incidence of main components of tax benefit system by types of location, share of final income,** **<u>percent.</u>**

||SSC|Direct Taxes|Pensions|Direct<br>Transfers|Indirect<br>Taxes|In-kind<br>Health|In-kind<br>Education|<sup>
# 2. Existing evidence

When safe spaces are already occupied, new developments can disproportionately occur in previously avoided areas such as riverbeds, flood plains, or wetlands. When making locational decisions, households and businesses often trade off job accessibility and market potential with disaster risks, and settling in flood-prone areas can become a rational choice<sup>12,13</sup> . Behavioral biases, market failures, and information constraints can also exacerbate excessive risk taking<sup>14,15,16</sup> , while inefficient land markets<sup>17</sup> can allow safe land to sit idle while risky areas are developed. Risk levels in urban development depend on geography, socioeconomic trends, and institutional and regulatory factors, such as planning restrictions.

Case study evidence illustrates these mechanisms. For example, in India, low-income households move to Mumbai from rural peripheral regions, searching for economic opportunities. The high density of settlements and land price differentials in the city force new arrivals into previously avoided areas, such as high-risk flood zones near riverbeds, and informal settlements grow without planning or public infrastructure<sup>18</sup> . Similarly, in Vietnam, a flood risk assessment for Ho Chi Minh City finds that informal poor settlements are systematically exposed to higher flood risks than the rest of the city<sup>19</sup> , while evidence from the United States documents how, in recent decades, new construction on the Atlantic coast avoided flood-prone areas in sparse locations but took place in the ‘least-bad’ flood-prone areas in dense locations<sup>20</sup> . New Orleans, first established on higher lands, expanded into lower-lying flood plains as the port’s growing role spurred economic activity<sup>21</sup> .

The case of Vietnam illustrates the scale and dynamics of evolving flood exposure. Almost one-third of Vietnam’s coastline is occupied by towns and built-up settlements, and its 28 coastal provinces are home to 46.6 million
(4) of the theoretical framework.

Following Duma (2011), the fluctuation of the crude oil price represented by its change rate ( _goilp_ ) is exogenously included in the VAR system as a control for external shocks. Furthermore, we add another exogenous dummy variable ( _dummy_ ) to the estimation to capture the macroeconomic effects resulting from: political instability during the violent conflicts and political unrest in 1997; the 1997-98 Asian financial crisis; election periods in 1998, 2003, 2008, and 2013; and the 2008-09 global financial crisis.

As an extension to the VAR system, another variable added is international reserves. Cambodian authorities may use the international reserve adjustment as a policy tool to,

> 4 In this study, the cointegration methodology based on the vector error correction model (VECM) proposed by Johansen and Juselius (1990) that requires that all variables are I(1) is not adopted. This is because the integration order of the variables under consideration in our estimation are mixed. We have both I(0) and I(1) variables in the VAR system, as discussed later.

> 5 z illustrates the depreciation of KHR if it increases and the appreciation of KHR if it decreases.

> 6 Broad money is incorporated as a share of GDP to take into account the scale effect.

> 7 Trade balances are incorporated as GDP shares, taking into account scale effect.

> 8 The VAR estimation by using deposit interest rate as domestic interest rate is also conducted. We obtain very similar results of impulse responses and variance decompositions. Data on the deposit interest rate is obtained from International Financial Statistics (IFS) published by the International Monetary Fund (IMF). The results can be provided upon request.

9
of countries) out of the potential of over 11 million observations.

In the more granular analysis, we rely on the World Bank’s Exporter Dynamics Database (EDD), which is based on firm-level customs data covering the universe of export transactions provided by customs agencies from 69 countries.<sup>4</sup> The description of the database is provided in Fernandes et al. (2016). EDD contains aggregated measures on export sector characteristics and dynamics at different levels of aggregation. For our analysis, we are mainly interested in two indicators of the dataset: the number of exporting firms and average export per firm, which is constructed at the country-year-industry level.

**Country-level Measures** Data on institutional quality indicators are obtained from two sources: the Worldwide Governance Indicators (WGI) database of the World Bank and the Economic Freedom of the World (EFW) of the Fraser Institute. While various indicators from these sources have been used in some robustness checks, the main indicators used are the _rule of law_ from the former and the _contract enforcement_ variable from the latter source. These are chosen because they correspond to the theoretical channels proposed to link institutions to the pattern of trade, better than the other indicators.

Natural resource endowment figures – total natural resource rent as percentage share of GDP – are extracted from the World Development Indicators (WDI) database of the World Bank. Exporter and importer GDP (both in constant 2010 US dollars) are also extracted from WDI. Human capital

> 3 The conversion table is available at _http_ : _//wits.worldbank.org/product concordance.html_

> 4 The aggregate measures are publicly available at _http_ : _//www.worldbank.org/en/research/brief/exporter − dynamics − database_

8
and to look at the evolution over time of trust in institutions, with the same degree of disaggregation. Also, future data collection could provide data on subnational institutions, including at the municipality levels. Other surveys on trust in Morocco (MIPA trust index, Arab barometer) show stronger trust in local elected governments than central government. Additional research could try to tease out the causes of such variation.

The paper’s findings have important policy implications. In particular, by highlighting the relation between transparency and institutional trust, the results echo ongoing debates about the need for critical (rather than blind) trust to generate positive spillovers for development (Zmerli and Van der Meer 2017, Norris et al. 2019). It is only when citizens have the information to critically evaluate policies, and the institutional channels to contest them and hold officeholders accountable, that they can place their trust - and resources - at the disposal of state institutions. When such space is limited, mistrust can turn into distrust, challenging stability and development opportunities.

25
Although the IHS data provide extensive detail about the vehicles, unfortunately, the data are incomplete for vehicle prices and certain other attributes. We use El Motor Magazine<sup>3</sup> to impute vehicle prices. We use Carfolio.com to impute fuel economy, GHG emissions rates, and other attributes.

To assess the quality of the imputation, we compare imputed values with non-missing data. For vehicle attributes with continuous values, such as horsepower and price, the absolute mean difference between the observed and the imputed data was 5%, with a standard deviation of 0.8%. We obtain gasoline and electricity prices from Colombia’s Ministry of Energy.

Data for charging stations come from different sources, including OpenChargeMap,<sup>4</sup> Electromaps,<sup>5</sup> and PlugShare.<sup>6</sup> Because our registration data are at the national level, we compute the total number of public charging stations by quarter.

# 2.2 Characteristics of Colombia’s New Vehicle Market

Colombia is Latin America’s fourth largest market for both automobiles sales and production (after Brazil, Mexico, and Argentina).<sup>7</sup> There are two large light-duty vehicle manufacturers in Colombia (Colmotores/GM and Sofasa/Renault).<sup>8</sup> These two firms assemble cars from imported materials that represent around 70 percent of a fully assembled car.<sup>9</sup> These imported materials are subject to import tariffs of a similar magnitude (currently 35 percent) as imported cars. Since Colombia liberalized trade in light-duty vehicles in 1991, the incumbent advantage of the domestic assembly plants has gradually dissipated, and previously nonexistent imports of other cars have grown significantly (Tovar 2012). Currently, two-thirds of new vehicle sales are imports.<sup>10</sup>

> 3 <u>https://www.motor.com.co/
14.420|14.070|0.350|
|Hindu|0.888|0.882|0.894|-0.012|
|SC/ST|0.419|0.404|0.438|-0.034|
|Owns agricultural land|0.579|0.599|0.555|0.044*|
|Has pucca house|0.476|0.483|0.467|0.016|
|# observations|23,350|12,678|10,672||
|**Panel B: Individual characteristics**|||||
|Female|0.490|0.491|0.489|0.002|
|Age|39.8|39.9|39.7|0.200|
|Educ. primary.|0.213|0.208|0.218|-0.010|
|Educ. up to high school|0.291|0.291|0.292|-0.001|
|...up to graduate|0.110|0.116|0.102|0.014|
|Others|0.015|0.015|0.014|0.001|
|Married|0.748|0.742|0.754|-0.012|
|Unmarried|0.174|0.176|0.172|0.004|
|No. of obs.|66,362|34,707|31,655||

_Note:_ Author’s own calculation from 2014/15 REDS follow-up survey. To test difference in means, p values from regressions with district fixed effects and standard errors clustered by village panchayat are reported in the last column.

17
used in the literature have usually been the firm revenue deflated by the the industry-level prices. Thus, within-industry price differences (e.g. due to different markups) have been part of the output and productivity estimates of such studies, potentially biasing their results.

# 5.3 Estimation Results

Before moving on to the results, let us first observe the simple correlations of total factor productivity and tariffs. The overall correlation coefficient for log Ait and log τ it in the whole sample of 920 observations is -0.222. This is significant at the 1% level and can be observed graphically in Figure 5 as well. In Table 3, I present the correlation matrix for all the combinations of log Ait and log τ it across years. The two variables again have a relatively small negative correlation for the most part which is insignificant for certain years such as 1992 through 1994. These relationships also appear in Figure 6 which includes plots of TFP versus tariffs by year. In Table 3, it is interesting to note that the two variables can be concurrently and also intertemporally correlated. This is one reason why using lagged tariff rates may not get around the endogeneity problem of tariffs with respect to productivity. Topalova (2004) notes a similar pattern in the Indian data for the 1997-2001 period and excludes this period from her analysis due to her concern about endogeneity.

However, we cannot establish a causal relationship between tariff protection and productivity with these crude observations alone. We need to control for the other important variables as required by the theory and tackle the endogeneity issues. In this section, I show how productivity influences tariffs after I control for the endogeneity of productivity. Later in Section 6, I estimate a system of equations related to this setup and show that accounting for the effect of productivity on tariffs may strengthen the positive impact of trade reform on productivity.

As noted in Section 5.1, the two right-hand-side variables—the inverse import penetration to import demand elasticity ratio, and total factor produtivity—in
- Allen, Franklin, Asli Demirguc-Kunt, Leora Klapper, and Maria Soledad Martinez Peria. 2016. “The Foundations of Financial Inclusion: Understanding Ownership and Use of Formal Accounts.” _Journal of Financial Intermediation_ 27(XX): 1-30.

- Anginer, Deniz, Ata Can Bertay, Robert Cull, Asli Demirgüç-Kunt, and Davide S. Mare. 2022. “Bank Capital Regulation and Risk after the Global Financial Crisis.” _Journal of Financial Stability_ , forthcoming.

- Ardizzi, Guerino, Andrea Nobili, and Giorgia Rocco. 2020. “A Game Changer in Payment Habits: Evidence from Daily Data during a Pandemic.” Bank of Italy Occasional Paper, 591.

- Ashraf, Nava, Dean Karlan, and Wesley Yin. 2010. “Female Empowerment: Further Evidence from a Commitment Savings Product in the Philippines.” _World Development_ 38(3): 333344.

- Banerjee, Abhijit, Esther Duflo, Clement Imbert, Santhosh Mathew, and Rohini Pande. 2015. “Can E-Governance Reduce Capture of Public Programmes? Experimental Evidence from India’s Employment Guarantee Scheme in Bihar.” Harvard Kennedy School Impact Evaluation Report 31. Cambridge, MA.

- Banerjee, Abhijit, Dean Karlan, and Jonathan Zinman. 2015. “Six Randomized Evaluations of Microcredit: Introduction and Further Steps.” _American Economic Journal: Applied Economics_ 7(1): 1-21.

- Barth, James R., Gerard Caprio, and Ross Levine. 2013. “Bank regulation and supervision in 180 countries from 1999 to 2011.” _Journal of Financial Economic Policy_ 5(2): 111-219. <u>https://doi.org/10.1108/17576381311329661</u>

- Beaman, Lori, Dean Karlan, and Bram Thuysbaert. 2014. “Saving for a (Not So) Rainy Day: A Randomized Evaluation of Savings Groups in Mali.” National Bureau of Economic Research Working Paper N. 20600.

- Blumenstock, Joshua, Michael Callen, and Tarek Ghani. 2018. “
Egypt region experienced the largest gains and jumped one place in the inter-regional ranking, and Lower Egypt reached levels of opportunity in education and nutrition more comparable to the Metropolitan region.

- The five most unequalizing circumstances are parents’ education, income per capita, urbanrural location, number of siblings, and regional location. These are at least twice as important as gender, presence of elderly family members, and presence of both parents in the household.

- The most unequalizing set of circumstances differs across sectors; therefore, policy makers should adjust targeting mechanisms accordingly.

- For nearly all opportunities (14 of 16), demographic circumstances considered jointly lead to greater inequality than location circumstances.

Four policy recommendations follow from these findings:

- The fact that the most unequal set of circumstances varies across sectors must be disseminated and discussed with government officials as a key reference to revise targeting designs _within each sector,_ in order to remove the barriers to access for children in the most unfavorable circumstances and improve equality of opportunity. Special attention should be paid to children with more than two or three unfavorable circumstances because the cumulative effects multiply the barriers to access.

- An agenda for reforming expensive and inequitable subsidies for food and fuel is clearly justified in order to promote equality of opportunity among Egyptian children. The relatively poor performance of the HOI nutrition indicators (non-stunting, 2-17, and nonwasting, 0-4), and the poor targeting of food subsidies are good reasons to reform those programs.

- Moreover, the substantial resources that could be saved in the fuel and food subsidy programs might be devoted to conditional cash transfer nutrition programs, which would compensate for the most unfavorable circumstances (income per capita and number of siblings) that have been found to prevent access to nutrition opportunities.

- Finally, to increase awareness of inequality of opportunities among stakeholders and policy makers, the computation of opportunity indicators should be updated and disaggregated. HOIs available by sub-region and municipality -using census data– would provide relevant information to sub-national governments to implement more equitable policies for
# **1. Introduction**

This paper uses a unique and rich micro dataset on pension funds to shed new light on how incentives might affect institutional investors in their portfolio allocation decisions. In particular, we study two aspects discussed in the literature but still relatively unexplored: (i) how institutional investors trade in different types of assets and (ii) what incentives managers at various layers of the financial industry face when implementing their investment strategies. Because of the interest of the literature in herding behavior, we focus on herding statistics. This kind of analysis helps understand more broadly the role of institutional investors on capital market activity and the services they effectively provide as financial intermediaries. Furthermore, it offers new evidence on the importance of several factors often discussed in the literature on the behavior of institutional investors, including information, liquidity, incentives related to organizational aspects of the financial industry, and the regulatory framework in which managers operate.

Institutional investors are interesting to analyze not only because they have become very large, but also because detailed asset-level portfolios over time (unavailable at the household or retail-investor level) are sometimes accessible. In particular, institutional investors are increasingly relevant for both asset management and the development of financial systems. In fact, institutional investors are likely to be among the most important conduits of private and public savings, intermediating funds and supplying capital for firms and countries to grow. As institutional investors became prevalent, research flourished trying to understand how they invest. Many papers in the literature focus on equity mutual funds, for which portfolio data are mostly publicly available, and study their investment patterns (Grinblatt et al., 1995; Wermers, 1999; and Kacperczyk et al., 2005). Others analyze general data on institutional investors (Sias 2
public effects (Table 3, columns 4-7). We cannot conclusively rule out this interpretation but we view it as unlikely. The private reports do not have the candidate’s name and identity number, so they cannot be linked to a particular candidate. They have no branding, from Harambee or the World Bank. They do not explain that Harambee has used these assessments widely to place candidates with companies or that assessments predict workplace productivity and do not link to a website. None of the 15 hiring managers interviewed during piloting reported that they would view the private reports as credible.

Second, the public certification effects on employment and earnings may be larger than the private effects because workseekers incorrectly believe that firms face information frictions. Under this explanation, workseekers in the public certification group believe that firms are more likely to respond to job application submitted with certificates, hence they search more or search differently

> it more credible to workseekers) or because the information is more likely to be retained (e.g. workseekers are more likely to keep copies of the public report or discuss it in recent job interviews). To separate these hypotheses, we measure workseekers’ beliefs about their skills using a text message survey 2-3 days after treatment. The public and private effects in this survey are not different to each other, suggesting that workseekers’ beliefs update in the same way straight after receiving the reports and that the difference in the endline survey 3-4 months later is due to differential retention. See Appendix D and Table D.8 for details.

22
Mekong delta region (Cassou, Jaffee, and Ru 2018; Chea, Grenouillet, and Lek 2016). To measure the consequences of nitrogen pollution, the analysis focuses on children aged four to twelve years surveyed in the latest Living Standards Survey of 1997–98. Table 7 shows that repeated exposure to nitrate pollution for the first three years of life substantially lowers height‐for‐age scores in childhood, with full exposure decreasing height‐for‐age scores by 0.7 standard deviation. These effects occur despite nitrate‐nitrogen concentrations being below the recommended safety thresholds of 10 mg/L and emerge even after accounting for exposures from other contaminants.

In Africa, although present‐day fertilizer usage is lower than in Asia, it is growing. Other sources of nitrate exposure include expanding urban centers that lack wastewater treatment facilities and increased livestock farming. The analysis is based on the entire universe of child records up to age 5 years across 33 countries in Africa from DHS records. The results in Table 8 show that 12