rafmacalaba/data-use-mentions-extended huggingface dataset:
/ budget/ Integrated Survey, Agriculture survey, Labor Force Survey,<br>Health/Demographic survey, Business/establishment survey. Source: NSO websites,<br>World Bank microdata library, ILO microdata library, IHSN microdata library|
||Availability of Civil Registration and Vital Statistics (CRVS) indicator. An ideal<br>indicator would include a score based on the density of administrative data available in<br>sectors of social protection, education, labor, and health. However, social protection,|
|Dimension 4.2:<br>administrative data|<br>education, health, and labor admin data indicators not included because of lack of<br>established methodology. While several promising sources for administrative data from<br>the World Bank’s ASPIRE team, WHO, UNESCO, and ILO have been identified, the<br>were not included due to incomplete coverage across countries. Further research and<br>data collection effort would be needed to fill in this information, so that a more<br>comprehensive picture of administrative data availability can be produced.|
||Geospatial data available at 1st Admin Level. This data source from Open Data Watch<br>|
||focusing on data availability at the sub-national level provides a partial understanding|
|Dimension 4.3:<br>geospatial data|<br>of a country’s ability to produce geospatial data. A research and data collection effort is<br>needed to develop an more comprehensive global database of the availability of key<br>geospatial indicators.|
|Dimension 4.4:<br>Private/citizen<br>generated data|Not included because of lack of established methodology. Currently no comprehensive<br>source exists to measure the use of private and citizen generated data in national<br>statistical systems, and this should be another area where more data collection is<br>needed by the international community.|
||
The community social capital index is constructed as an average of binary variables pertaining to the presence of a town hall, a community hall, a church, or a park in the barangay. The commercial capital index is constructed by adding barangay-level variables on the number of financial institutions, industrial establishments and stores and dividing by 30 (the highest number attained'<sup>4</sup> ).

Summary statistics on the model variables can be found in Annex Table 1.

In order to capture any omitted (observable as well as unobservable) provincial/sectoral level determinants of consumption, we also allow for strata fixed effects where 168 strata are identified by the rural and urban sectors of individual provinces.

In the simple construct of model (1), the y-parameters yield measures of the impact of the crisis on household living standards. For instance, an estimated value of -0.05 for J implies that the exposure to labor market shock alone reduces per capita consumption by _5%._ However, model (1) also carries the implication that a given shock has the same proportional impact on consumption for all households affected by that shock. This seems an overly strong assumption. Presumably, a shock may hit some households more severely than others, and similarly, some households may be better able to protect their living standards than others when hit by a particular shock. For instance, the impact of a wage shock may depend on the education level of the workers and the effect of drought may depend on the ownership of land. In general, the impact of the shock would be expected to be a function of the characteristics and circumstances faced by the household. This consideration leads us to an augmented version of model (1) where we interact shock variables with a set of household and community characteristics (Zj):

> 14 For each of these three indicators, the APIS questionnaire records the actual number if less than 10, and records 10 if there are 10 or more of them in the _barangay.
1|
|**Specific grants and compensatory transfers**|**2.2**|**0.9**|**1.2**|
|Health care|0.5|0.2|0.2|
|FUNDEF|0.7|0.2|0.5|
|Other current transfers|0.7|0.4|0.3|
|Capital grants|0.3|0.1|0.2|
|Other Revenues|1.0|0.6|0.4|

Source: Rezende and Garson (2004).

# **Box 3. Municipal revenue**

# **Municipal taxes**

The main municipal taxes are those on services (ISS) and urban property (IPTU). In particular:

- ISS rates are set by the municipalities subject to the ceilings introduced by the federal government. Rates can vary considerably across sectors. Tax legislation is designed to avoid overlap with federal corporate income and state value-added taxes. In the banking sector, for example, ISS is levied on non-lending services such credit card and ATM fees but not on the interest charged on loans, which is taxed by the federal government. In the case of land transportation, ISS is levied on intra-municipal transport but not on intercity or interstate transport, which are subject to the state value added tax.

- IPTU is levied on the capital value of land and buildings in legally-designated urban areas. Property valuations are based on the physical characteristics of each property converted to an estimate of market value using construction cost parameters and surveys of land prices. These valuations are adjusted each year on the basis of an inflation index.

# **Revenue sharing**

Based on constitutionally-mandated revenue sharing (Box Table 1), the municipalities are entitled to: _i)_ 25 percent of revenue from the state value-added tax (ICMS), _ii)_ 50 percent of revenue from the state tax on
A simulation of COVID-19 impact on learning loss considering three, five and seven months of school closures was recently published using data on 157 countries at the primary and secondary level.<sup>32</sup> The authors found COVID-19 could result in a loss of between 0.3 and 0.9 years of schooling adjusted for quality, bringing down the effective years of basic schooling that students achieve during their lifetime from 7.9 years to between 7.0 and 7.6 years. Their findings suggest that students from the current cohort could, on average, face a reduction of up to $1,400 in annual earnings. In present value terms, this amounts to up to $25,000 in lost earnings over the typical working lifetime. Globally, a school shutdown of 5 months could generate learning losses that have a present value of $10 trillion. Similarly, another global study found that if learning in grade three is reduced by one-third, roughly the amount of time many children are likely to be out of school, learning levels in grade 10 would be a full year lower than would have been the case in the absence of COVID-19.<sup>33</sup> We build on these studies by adding higher education students into the calculation. The 224 million young people globally who are studying at the tertiary education level account for around 15 percent of the world’s learners. Meanwhile, just-in-time analysis from the United States using Bureau of Labor Statistics employment and wage shows how quickly COVID-19 had an impact on wages by mid-April 2020. The weekly wages of workers at the bottom quintile decreased by 6 percent on average between mid-February and mid-March and by 26 percent between mid-March and mid-April.<sup>34</sup> In Canada, data from the Labor Force Survey show that COVID-19 induced a 32 percent decline in aggregate weekly work hours among workers aged 20-64, alongside a 15 percent decline in employment.<sup>35</sup> In the United Kingdom
model with capital markets providing more financing (Figure 1, Panel C). For instance, equity and bond markets in China represented 53 percent of financial systems on average in the second half of the 2000s, up from a mere 11 percent observed in the first half of the 1990s. In India, capital markets grew from 57 to 65 percent of the size of the financial system. This trend is less striking than in China partly because capital markets already represented a significant share of financial systems in the early 1990s. Note that price effects might explain part of these trends in financial systems.

Financial systems have also become more complex from the saver’s perspective. In particular, non-bank institutional investors play a more central role in intermediating savings. While both insurance companies and pension funds expanded, mutual funds have shown a remarkable growth in the 2000s. For example, between 2000-2004 and 2005-2009, the size of mutual funds increased almost five times in China relative to GDP and almost doubled in India. Such an expansion suggests that non-bank intermediaries, in particular mutual funds, seem to have played an important role in the development of equity and bond markets by providing a stable demand for financial assets.

These trends for China and India are consistent with the evidence in the growing literature on the overall patterns of financial development. As economies develop, they increase their demand for the services provided by securities markets relative to those provided by banks. In this context, securities markets become increasingly important for economic development.

# **3.2. How widespread is the use of capital markets?**

Given the expansion of financial systems in China and India, we now analyze to what extent the developments documented above have implied a greater use of equity and bond financing by the private sector. We focus the analysis on our data set on capital raising activity (IPOs, SEOs, and 12
# **1 Introduction**

Transport and communication costs fell precipitously during the last century, leading many observers to posit that the world has ‘become flat’, that locational differences no longer matter. With the help of cheap transport and communication, business can be done almost anywhere, or so the story goes, leaving policy makers with the impression that we have entered a ‘brave new frictionless’ world. But, if this were true, the costs of trading and transporting goods should no longer influence firms’ location choices and, thereby, the spatial structure of economic is then the for economic to cluster in still activity. Why tendency activity space strong? Why do many industries nowadays still exhibit strong geographic patterns, including new entrants that should face little locational constraints?

We address this seeming contradiction head-on by identifying the causal effect of transport costs on the geographic concentration of industries. Using micro-level commodity flow data and micro-geographic plant-level data, we construct industry-specific ad valorem trucking rates and continuous measures of geographic concentration. We find that, controlling for international trade exposure and input-output links, increasing trucking rates are significantly associated with declining geographic concentration. The effect is large: had trucking rates not fallen between 1992 and 2008, the observed decline in geographic concentration of Canadian manufacturing industries would have been about 20% greater. Our results hold up to a large variety of robustness checks and to instrumental variables estimations that deal with potential endogeneity concerns of our key variables.

Assessing empirically the impact of transport costs on the geographic concentration of industries is important for several reasons. First, it is fair to say that, despite their fundamental theoretical role in spatial modeling, little is still known empirically on how transport costs drive the geographic structure of industries. Second, among the forces that drive the clustering of industries, transport costs have been less studied, much less than the ‘Marshallian’ determinants such as input-output links, labor market pooling, and knowledge spillovers (see Rosenthal and Strange, 2004; Combes and Gobillon, 2015).
survey as non-Russians- are more likely to be informal.<sup>19</sup> 18 For instance, according to RLMS data -on average and after controlling for other personal characteristics- people with higher education are 15.7 percentage points less likely to be informal than those with basic education in 2010. By 2016 those with some tertiary education are 24.2 percentage points less likely to be informal than those with basic education. Other surveys show qualitatively similar results regarding education. These are “conditional” probabilities, in other words, the probability to have an informal job, keeping all the other observable characteristics (e.g., sex, age and location) constant. Given that these personal characteristics are correlated with education, the “unconditional” probabilities can be different. In fact, according to RLMS data, the rate of informal employment has increased for all education levels between 2001 and 2016. However, the rates of growth have differed. For those with less than secondary education, the rates of informality went from 6.9 to 13.6 percent between 2001 and 2016: an 87% increase. Those with secondary went from 12 percent to 21.2 percent: a 77% increase. On the other hand, those with some tertiary went from 10.9 to 15.3 percent, and those with college, from 6.6 to 8.0 percent, that is, 40% and 21.2% growth respectively. Having post-secondary education has prevented workers from becoming informal.

19 It should be noted that this is the most expansive definition of migrants we can think of using RLMS. It refers to non-Russians in general, independently of birthplace or citizenship. If using a much more fine-tuned definition of migrants (i.e., living in a place that is not where one was born, having been born outside Russia, and having lived there less than 10 years), the proportion of migrants ranges between just 1% and 1.6%
will have to ensure the redeployment of labor both from the public to the private sector and from protected sectors into sectors in which it has a comparative advantage. In addition, it will have to create the conditions for a rapid development of the private sector. Thus, this section looks at whether Vietnam's new Labor Code implemented in 1995 and related Decrees are consistent with these objectives. Three types of labor regulations are looked at: minimum wages, non-wage compensation, and laws regulating employment termination. The analysis is mainly based on new VLSS data and on two case studies, one in export-oriented companies in Haiphong and another at ABB Transformers, a joint venture located in Hanoi.

### **_III.L Minimum wages_**

How do minimum wages affect labor costs and private sector employment growth? This depends on the degree of enforcement and on the extent to which the minimum wage is binding. In developing countries, enforcement is often possible only in very visible companies, including medium and large export-oriented firms (see Agrawal, 1996). In exportoriented sectors, effective minimum wages tend to increase production costs, hurt exports and therefore reduce employment. They may also deter foreign investment; in principle, since many developing countries compete to attract export-oriented foreign investors, a small difference in labor costs can have a large impact on the location of investmnent. In theory, a high minimum wage may also reduce employment -although to a lesser extent- in the inward oriented formal sector, where higher prices can be passed on to consumers but where employers tend to adopt less labor-intensive production. Thus, a high minimum wage may

**_18_**
structural approach also using a Cobb‐Douglas estimate, but with commonly used labor shares so as to explicitly take into account policy distortions that would otherwise affect traditional TFP measures in their revenue as opposed to physical TFP. Hence, their TFPQ is estimated which is put in relative terms compared to each 2‐digit NACE classification sector code. As said, for this approach one needs to have common labor shares from one country which is most likely to serve as a reference point. We use Germany as it represents the EU’s most important economy across all its members. Labor market shares are defined as the wages and salaries for each 2‐digit NACE sector divided by each of their sectoral value‐added. Furthermore, we also take the EU as an average benchmark against which the TFPQ measure is made firm‐specific for each 2‐digit code. Although one could criticize this approach since we include multiple countries, the results obtained from employing the EU‐wide benchmark are much more meaningful. Besides, this approach is also justified on the grounds that actually the EU as a whole is by now a fairly integrated market.<sup>12</sup> Of note, all the appropriate proxy variables are first deflated and then put in Euros using constant exchange rate. Price data come from Eurostat’s National Accounts database and are mostly available at 2‐digit NACE industries. In case these data was missing we used either higher level of aggregation, or otherwise simple GDP deflators were used. For value‐added we used the value‐added in gross price index (i.e. implicit deflator) in constant prices with 2010 as reference year for all countries. For materials we used the deflator for intermediate consumption and finally for capital stock we used the consumption of fixed capital price index.

11 Note that subscripts for country and industry are supressed for now as they are estimated for each of them. Moreover, Amadeus does in fact report the firm’s total wage bill but has worse
Policy Research Working Paper 10965

# **Abstract**

This paper investigates the determinants of mining projects, with a focus on green minerals. The research question is the effect of political risk on investment decisions, the size of projects, the volume of ore mined, and the ensuing resource rents captured by the host country. The paper shows the challenges of measuring and capturing resource rents, using a mathematical model of resource rent maximization for the host country under the constraint of a positive after-tax cash flow for investors. The analysis finds that the optimal approach for taxing extraction is a progressive profit tax on mining revenues that generates revenues for the country while minimally deterring investment. Alternatively, taxing cash flow, which can be non-distortionary, can be implemented. Using the S&P Capital IQ database, the analysis finds that the low-quality of governance, institutions, infrastructure, skills, and services dampens the exploration and exploitation of copper, a key mineral for green energy. The opportunity cost in terms of unexplored or underexploited deposits translates into suboptimal global copper production and forgone revenues for the poorest host countries. To unlock exploration, the paper proposes measures to mitigate political risk, including investing in geological surveys and institutions and designing stable tax systems. For underexploited projects, it proposes that countries not only invest in infrastructure, skills, and services, but also improve governance and institutions. This would lower the metal grade at which investors would be willing to commit, ultimately producing more metal from identified mineral deposits. Interventions from international financial institutions can help to alleviate all country risks, including political risks, that hinder credible intertemporal commitments between investors and countries.

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
For the argument that within-city inequality is egregiously large in metropolitan areas and large cities to hold (in Morocco), it would be necessary (but not sufficient) for the between-group shares reported in the last two columns of Table 5 to be substantial. In the event, it appears that most inequality in the five largest cities in Morocco is not due to some great divide between slum areas and

> 16 Casablanca is the biggest agglomeration of Morocco (2.9 million inhabitants), Figuig is a small town in L’Oriental (49,000). 17 Bertolinia is a small town in the Brazilian state of Piauí, with fewer than 40,000 inhabitants.

> 18 A district (smallest level of disaggregation after the census track) was considered as a slum if less than 10% of the population had access to water and less than 10% of the population had access to electricity. 19 GE(0), or mean log deviation, is the Theil-L index. GE(1) is the Theil-T index. Both are perfectly decomposable into within- and between-group components, in the sense that the decomposition has no residual. GE(0) weighs within-group inequalities by population shares, while GE(1) weighs them by incomes shares.
>63|10||28|
|25% sales, 50% input to/from formal<br>59|9||32|

The above table documents the share of overall firm-to-firm links which have a supplier based in Nairobi, Mombasa or the remaining 45 counties. We present the spatial dispersion of outlinks in the data, the predicted (formal sector) network as well as our default scenario for the revised network and four alternative scenarios to assess sensitivity.

If counties are selling less to Nairobi and Mombasa, where do their inter-county trade links shift? We find that the number of bilateral trade links is now more sensitive to social ties between counties. In Table C2, we regress the number of links between two counties on both travel distance and social connectedness (Bailey et al., 2021), and compare the results for the baseline and the revised network.<sup>26</sup> The findings indicate that, in the revised network, inter-county trade links are more strongly associated with the strength of social ties between counties.

The increased importance of within-county trade and trade between socially connected counties gives rise to a network with a more pronounced group structure. We quantify the extent to which the network is partitioned by measuring the network’s modularity (Newman, 2006). The modularity of a network is higher when groups of nodes have more links among each other

> 25While inter-county trade rises for the median county, 18 out of 47 counties actually have fewer links with other counties in the revised network.

> 26Social connectedness is measured using friendship network data provided by a popular social media platform, see Bailey et al. (2021).

27
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