rafmacalaba/data-use-mentions-extended huggingface dataset:
. _et al._ High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. _Nat Sustain_ **3,** 564–570 (2020). 25 DLR(2021) https://geoservice.dlr.de/web/maps/eoc:wsfevolution

> 26 Liu, X., Huang, Y., Xu, X. _et al._ High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. _Nat Sustain_ **3,** 564–570 (2020).

> 27 <mark>Peduzzi, P., Dao, H., Herold, C. & Mouton, F. Assessing global exposure and vulnerability towards natural hazards: the Disaster Risk Index.</mark> _<mark>Nat. Hazards Earth Syst. Sci.</mark>_ **<mark>9</mark>** <mark>, 1149–1159 (2009).</mark>

> 28 de Bruijn, J. A. et al. A global database of historic and real-time flood events based on social media. _Sci. Data_ **6,** 311 (2019).

> 29 Tellman, B. et al. Satellite imaging reveals increased proportion of population exposed to floods. _Nature_ **596** , 80– 86 (2021).

> 30 <mark>Arnell, N. W. & Gosling, S. N. The impacts of climate change on river flood risk at the global scale.</mark> _<mark>Clim. Chang.</mark>_ **<mark>134</mark>** <mark>(3), 387–401 (2016).</mark>

> 31 <mark>Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C. & Ward, P. J. A global reanalysis of storm surges and extreme sea levels.
, J. and Trannoy, A. (2016). Equality of Opportunity: Theory and Measurement. Journal of Economic Literature, 54(4):12881332.

- Roemer, J. E. (1998). Equality of Opportunity. Harvard University Press.

- Solon, G. (1999). Intergenerational mobility in the labor market. In Ashenfelter, O. and Card, D., editors, Handbook of Labor Economics, volume 3 of Handbook of Labor Economics, pages 17611800. Elsevier.

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- Solon, G., Corcoran, M., Gordon, R., and Laren, D. (1991). A Longitudinal Analysis of Sibling

29
or multiple existing indirect sources add to the complexity of this environment .<sup>21</sup> In parallel to this structured data collection, indirect reporting may occur as a response to _ad-hoc_ requests coming from the same IFIs; this could be for IMF Article IV missions or IMF/WB lending operations, or from other key stakeholders such as credit rating agencies (CRAs).

The same direct/indirect reporting dichotomy applies to official lenders (bilateral and multilateral). The IMF and the WB publish comprehensive and timely data on their financing;<sup>2223</sup> however, the level of transparency of other multilateral/plurilateral creditors is mixed and largely depends on the degree of accountability imposed by their internal policies and procedures.<sup>24</sup> As for bilateral creditors, some ParisClub members disclose lending operation information on their website or in publications, although these efforts tend to be isolated and mostly driven by good-will.<sup>25</sup> Creditors also feed into international

> 18 The only IDA countries without recent DSA are Eritrea and the Syrian Arab Republic.

> 19 In the case of the WB’s IDS, “data accuracy and comprehensiveness is ensured by validation with other sources such as market data, creditor data, other external statistics such as BOP/IIP, QEDS—including data used in debt analytical exercises led by the World Bank and IMF, such as the medium-term debt strategy (MTDS) or DSA—and rigorous follow-up with government authorities” (IMF/WB, 2020).

> 20 In June 2020, the WB published detailed external debt stock and service data for 68 IDA eligible countries in the IDS database, including a previously unavailable breakdown by creditor. http://datatopics.worldbank.org/debt/ids/ 21For example, WB World Development Indicators (WDI) accesses its debt data from the IMF Government Finance Statistics Yearbook (GFSY).

22 www.imf.org/en/Data/IMF-Finances

>
# **3.2 Mechanisms**

There are two main channels through which an increase in tradable activity can generate growth in non-tradable services. First, the effect could come from sectoral linkages. The growth in tradable services may lead to growth in input-supplying non-tradable services, or conversely, growth in tradable services could make tradable service inputs into non-tradable services cheaper or of higher quality. This in turn could spur non-tradable service growth in input-receiving sectors. Alternately, on the demand-side, tradable service growth may increase local income, which in turn increases consumer demand for non-traded services. Whether the sectoral linkages or demand-side mechanisms explain our main results is ultimately an empirical question.

We consider the sectoral linkages channel first. To explore this, we use the Indian inputoutput tables from 2006-07, which show the linkages of non-tradable service sectors to and from tradable services, as a share of inputs to/from all the sectors in the economy. We use this to categorize non-tradable service sectors into four categories: (i) sectors that provide a below median (low) share of inputs _to_ tradable services, (ii) sectors that provide an above median (high) share of inputs _to_ tradable services, (iii) sectors that receive a below median (low) share of inputs _from_ tradable services, and (iv) sectors that receive an above median (high) share of inputs _from_ tradable services.

To test for the sectoral linkages channel, in Table 4, we estimate separate regressions for district-level employment in each of these 4 categories in response to an increase in tradable services employment. In column 1, we find that district-level employment increased in nontradable services sectors that provide a low share of inputs to tradable sectors, but there is no statistically significant change in the employment in non-tradable sectors that provide a high share of inputs to tradable sectors (column 2). Similarly, in columns 3 and 4, we find that district-level employment increases in non-tradable services sectors that receive a low share of inputs from tradable sectors, but there
43,806|617,032|
|Middle East and<br>|Number of projects|16 (1)|110 (0)|40 (3)|28 (1)|194 (5)|
|North Africa|Investment|281|45,606|10,213|5,262|61,362|
|South Asia|Number of projects|16 (3)|669 (3)|580 (30)|23 (0)|1,288 (36)|
||Investment|1,816|211,739|130,414|1,764|345,732|
|Sub-Saharan Africa|Number of projects|24 (3)|264 (11)|113 (7)|33 (4)|434 (25)|
||Investment|742|51,619|24,050|1,151|77,562|
|Total|Number of projects|133 (19)|3,658 (59)|1,926 (109)|1,098 (56)|6,815 (243)|
||Investment|23,649|966,164|680,195|109,058|1,779,067|

_Source_ : PPI database.

_Note_ : The number of canceled projects is in parentheses. Investment totals are in millions of 2020 US dollars. ICT = Information and communications technology More than half of all PPP projects in the developing world are in the energy sector (3,658 out of 6,815). Other important sectors are transport (1,926 projects) and water and sewerage (1,098 projects). The remaining 133 projects are in the information and communications technology (ICT) sector.

Almost 3.6 percent of the infrastructure PPPs initiated in the developing world were canceled. The transport sector saw the largest number of cancelations (109), and the ICT sector saw the largest share
# **6. Summary**

By combining information from the 2002 Household Budget Survey and the 1999 Census it is possible to produce spatially disaggregated estimates of welfare based on consumption at the sub-oblast level. The key findings are:

- In general, there is a higher incidence of relative poverty in urban areas as compared to rural areas.

- However, there is a high degree of variation in poverty across urban areas, with the proportion of the population living below the relative poverty line varying between 20 and 60 per cent.

- The picture in rural areas is more homogeneous, with relative poverty rates in most rayons varying between 30 and 40 percent.

- There is also a significant degree of variation _within_ rayons, with some pockets of deprivation   within more affluent areas.

- Comparing the spatial estimates of welfare derived using consumption with those derived using an asset index highlights that the two measures are capturing different dimensions of welfare.

- The asset index largely reflects patterns of ownership of household assets and access to services laid down during Soviet era and is not a good proxy for current levels of welfare in Azerbaijan.

It is important to note that the spatially disaggregated estimates of welfare presented here should be interpreted with caution. There remain problems in the HBS in Azerbaijan that are currently the focus of on-going collaborative work. However this paper presents a positive step forward in the analysis of poverty in Azerbaijan both by demonstrating that it is possible to produce statistically reliable estimates of poverty at the sub-rayon level and through the production of a digit map that will allow the visual representation of census results at the administrative level.

29
"A New Data Set of Educational Attainment in the World, 1950‐2010." Journal of Development Economics, vol 104, pp.184‐198. Version 2.0. Available at <u>www.barrolee.com</u> CEPII, GeoDist database. Available at <u>www.cepii.fr/CEPII/en/bdd_modele/presentation.asp?id=6</u> Kauffman, Kraay and Mastruzzi (2014), Worldwide Governance Indicators. Available at <u>www.govindicators.org</u>

- Kee, H.L, A. Nicita and M. Olarreaga (2009). "Estimating Trade Restrictiveness Indices", Economic Journal (119). Available at go.worldbank.org/FG1KHXSP30

UN Comtrade (2014), International Trade Statistics.

World Bank (2014), Wealth of Nations. Downloaded from data.worldbank.org World Bank (2014), Doing Business. Available at <u>www.doingbusiness.org</u> 23
# **4 Data**

This section presents the description of the variables and the main data sources used in the paper.

**Trade Data** Trade data are obtained from two sources: BACI database and the World Bank Exporter Dynamics Database (EDD). We obtain trade flows (in thousands of US dollars) at the 6-digit HS2007 level from the BACI database, constructed by CEPII based on the UN-Comtrade data (Gaulier & Zignago 2010). Since the data on an important component of our main independent variable (contractintensity of industries) are available only at ISIC Revision-2 3-digit level, conversions are needed. To this end, we used the World Integrated Trade Solution (WITS) product concordance table<sup>3</sup> to convert data from HS2007 to ISIC-Revision 2. This is used as the dependent variable in the base model. Other models employ the number of product varieties – the count of HS2007 6-digit products within an ISIC Revision 2 3-digit product group – and average exports per variety. In models that estimate the effect of institutions on the volume of exports to the whole world, the number of export destinations, or average exports per destination – instead of bilateral trade flows – the trade data are further aggregated over all importers, thereby changing the observation identifier from exporter-importer-industry-year to exporter-industry-year.

Despite the large proportion of zero-trade entries, we have data for 215 exporters, 222 destinations, 29 industries and 8 years. An industry (ISIC 312) is dropped due to missing values on factor-intensity, and a large number of observations are automatically dropped due to missing values in one or the other variable. Depending on the model estimated, this leaves us with 632,363 - 1,662,720 observations (in the full set 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
protect more capital or skill-intensive products. It arises from the conclusions in the numerical literature on trade and poverty that the poor would benefit from trade reforms because the structure of protection is biased against goods they consume/produce—for example, the contributions in Hertel and Winters (2005). Clearly the need for a relatively comprehensive dataset is pressing.

- **Actual/potential impact of trade liberalization on wages** . The high levels of aggregation used in household surveys (2- or 3-digit ISIC) may not be fine enough to detect worker reallocation across firms within the same industry in response to trade liberalization. This leads Goldberg and Pavcnik to call for empirical firm/plant level studies that explore the income distributional effects of trade reforms by analyzing the impacts of reform on firms belonging to the same 3- or 4-digit ISIC sector, as reflected for example in the compositional changes of their output (quality upgrading or other forms of greater differentiation of their production). Information on relative (productivity-adjusted) labor costs would help identify sectors/firms that may be confronted with more serious adjustment costs post reforms. These exercises could also be augmented with information on additional operating costs related to the “quality” of the business environment, of the sort generated by the World Bank’s Investment Climate Research (World Bank 2005a) and _Doing Business_ (World Bank 2005b).

- **Inter-sectoral mobility, entry/exit across sectors** . Borjas and Ramey (1995) found that the effect of trade on the labor market depended on market structure of industries. Barriers to entry and exit will clearly have a bearing on labor market responses to further trade and investment liberalization. Capital/financial market distortions or inefficiencies will affect the ability of firms to expand/enter. These variables may be more important than the labor market. To a large extent such factors have already been studied, but perhaps not from a labor market adjustment perspective.

- **Beyond manufacturing** . The manufacturing sectors are the focus of
**Table 4. Civil Wars, 1960-2006**

_These figures show the percentage of countries that had a new civil war in a given year._

||**Non oil**<br>**producers**|**Oil**<br>**producers**|**Difference**|
|---|---|---|---|
|_Overall:_||||
|**AllStates and Periods**|2.8|3.9|1.0**|
|_By Income:_||||
|**Low Income (below $5000)**|3.8|6.8|3.0***|
|**High Income (above $5000)**|1.2|1.4|0.2|
|_By Period:_||||
|**1960-1989**|2.4|2.7|0.3|
|**1990-2006**|3.6|5.3|1.7**|

*** significant at 1%, ** significant at 5%, * significant at 10%, in a one-tailed t-test.

_Source:_ calculated from data in Gleditsch et al. (2002).

_Notes:_ Oil producers are here defined as countries with over USD 100 dollars per capita in oil income for 2008 (using 2000 general prices). Data are drawn from US Energy Information Administration (EIA). Price data from BP statistical yearbooks.

**Figure 5. Annual Conflict Rates in Oil and Non-Oil Producers**

<!-- Start of picture text --> 10<br>9.1<br>9<br>8<br>7 6.8<br>6<br>5.3<br>5<br>4.2<
decision-making power to subnational governments and their legal ability to raise revenues from different instruments in a country (Vincent, 2020).

With these combined datasets, we estimated how individuals living within a 50 km radius from an active or an inactive mine assess government performance in several public policy areas, including improving living standards, job creation, health and education services, as well as a composite indicator of public services as a whole. We also investigated how the geographical closeness to a mine affects the individual expectation of their living standards in the future (referred to as optimism).

The results from the baseline suggested that residents living within a 50 km radius to an active mine are less likely to approve government performance in improving living standards, jobs creation, health services, and public services delivery. In addition, they are also less likely to be optimistic about their future living standards. While the results are more mitigated for the distance to an inactive mine, they point to the dissatisfaction of nearby with the government handling water and sanitation and a decrease in optimism about the future.

In comparison to non-active mine, active mining statistically reduces the probability of approving government performance in the afore-mentioned policy areas and public services as a whole. In addition, the ‘ _active_ ’ status of a nearby mine also decreases the optimism of the respondents in the Afrobarometer surveys.

We then moved onto exploring the effects of local governance. The results confirm our hypothesis on the confoundedness of the quality of local institutions. We found that effective corruption, measured by the incidence of bribe payment at the local level and the sentiment of distrust in local government councillors, amplifies the negative effects of the geographical closeness to an active mine. The higher the incidence of bribe payment or level of distrust in local governments in a community located within a 50km radius from an active mine, the higher the likelihood of citizens being dissatisfied with government performance. Both variables also render the respondents even more pessimistic about the future.

Finally, we examined the interplay between decentralization and effective
# **1. Introduction**

Recent research by Imbs and Wacziarg (2003) showed that economic development is associated with increasing diversification rather than specialization in lower- and middle-income countries. This paper studies one aspect of economic diversification, namely the introduction of new export products during the process of development. In this context, diversification is related to the market failure hypothesis of Hausmann and Rodrik (2003a), which suggests that discovering that a product can be profitably produced in a particular country, where it has never been produced before, creates valuable social knowledge. Production costs and foreign demand are not knowable _ex ante_ , making such a discovery an ‘inside-the-frontier innovation’. Firms that imitate the first mover derive benefits from such discoveries, yet they pay nothing for it. That is, imitation raises the social returns relative to the private returns. While imitation is clearly desirable from a social viewpoint, the first mover can not appropriate all the value created by their investments in discovery as, as this type of innovation can not be protected by the intellectual property rights regimes used to spur on-the-frontier innovation. As entrepreneurs can not appropriate all of the value they create, they underinvest in the experimentation necessary to discover new export opportunities, and consequently the process of productive diversification and private sector development stagnates.

However interesting this theory is, the market failure hypothesis has not been tested empirically. In fact, we know very little about the relationship between the emergence of new export products and economic development in general. This paper attempts to fill this void.

We develop an identification strategy for the existence of market failures affecting inside-the-frontier innovation, or discovery, using disaggregated product-level export data available for a large sample of countries. In addition, we develop a metric for discovery activity and establish empirical regularities that serve to deepen our understanding of the discovery process and its relationship to productive diversification and economic development.

The rest of the paper is organized as follows. Section 2 proposes a minimalist model of discovery and imitation by focusing on potential interactions between
in their home country before fleeing, and were thus more likely to have been victims of violence, are more likely to return. In the Syrian context, refugees who are single and male are more likely to return since family ties often play a large role in these decisions (Bank (2019)).

## **3.1 Return Considerations**

Knowledge of the factors which initiate displacement is key to understanding when refugees may return. Individuals are more likely to return once there are economic opportunities, services, and social networks in place to support their transition, the same features which may have prompted movement away from a region when they became unavailable (Aymerich and Zeyneloglu (2019), Hoogeveen et al. (2017), Arias et al. (2014)). In a survey study conducted on 6
# **1 Introduction**

Will continuation of economic development increase pressure on the earth’s finite resources, or does the increase in income provide the basis for environmental improvement? This question asked by (Grossman and Krueger, 1995) and highlighted earlier in (World Bank, 1992) is critical to the design of sustainable development strategies but continues to remain at the center of debate. Evidence from past development suggests that increases in wealth and income occur simultaneously with a structural transformation process in which the composition of inputs and methods of production used in the economy gradually shift in favor of less destructive production. We revisit the empirical issue using panel data on environmental output and economic development for a large set of countries using a flexible kernel model that allows dependencies to vary smoothly throughout the data.

Interactions between the economic and natural systems are dominated by complex pathways, and the processes that produce the levels of environmental output are high dimensional. This is because environmental output is determined not only by the efficiency of production, which may improve nonlinearly across GDP, but also by the total production size, which varies across panels of countries (Stern et al., 1996; Stern, 2004). If the scale of the economy is large, minute changes in the efficiency of production can result in large differences in output levels. Therefore, if a panel is constructed that includes economies of widely different scales, the variance in environmental output levels can be expected to vary with the GDP levels of the countries. To cope with this, one should acknowledge in the model design that environmental output is de facto a result of both a _scale_ component, and a _technology_ component.

Many empirical approaches have tried to model degradation levels directly, not distinguishing between the role of _scale_ and a _technology_ separately, and therefore assume an unrealistic degree of homogeneity of the samples. Vollebergh et al. (2005) pay particular focus to homogeneity assumptions in their environmental output regressions, and conclude that correctly modeling heterogeneity is essential to prevent spurious correlation in
and misinformation, particularly if people lack knowledge about who refugees are. Local government officials in Kampala highlighted that most locals do not fully understand why refugees come to Uganda, sometimes regarding them to be ‘economic migrants’ who compete for opportunities (John, Ugandan, Kampala). Similar perspectives were expressed by host nationals in Kenya, often with an emphasis on a terrorist-related security threat, even in the absence of being able to provide clear evidence to support such claims. According to several Kenyan host community members, whenever Al-Shabaab perpetrated terrorist attacks occur, securitisation by the national government has exacerbated intolerance and hostility towards Somali communities at a local level (see also ReDSS 2015). However, it is possible that the impact of national government campaigns on host community perceptions may be short-term.

> 19 On a related note, all regression specifications controls for physical and mental health, the latter using the widely employed depression measure PHQ9. Interestingly, there is an association between depression and holding more negative attitudes towards refugees. The association is less robust for hosts in Uganda (Table 3) than for the full sample (Table 4). This association also applies to depression among refugees and their opinions of hosts, in line with findings on Posttraumatic Stress Disorder (PTSD)-related symptoms and trust in hosts in the recent Kakuma Socioeconomic Survey (Fix et al. 2019).

22