rafmacalaba/data-use-mentions-extended huggingface dataset:
matching grant program in Mauritius, 80 percent of recipients said they would have made the investments in technology transfer even without the matching grants. In many countries the mindset was still very much one of trying to select the “best” firms or the ones most likely to succeed, not necessarily those for whom the grant funding could make a difference between success and failure. We hoped that the process of engagement of World Bank operational staff and governments in the impact evaluation would also help improve project implementation in this respect.

Finally, given that these programs are pervasive throughout Africa, we emphasized that there is a global public good element to the knowledge produced by any impact evaluations – the results would not only influence and inform policy in the country being studied, but also help inform efforts in other countries. For these reasons we were able to raise funding from different sources to help finance the impact evaluations, so that, when approaching these countries to try to implement evaluations, we were coming with some funding in hand to supplement their data collection costs.

# **3.2 Why Use Randomized Experiments as an Evaluation Tool?**

There are a number of private sector development policies in which a randomized evaluation is difficult or near impossible (e.g., changing a national regulation, building new infrastructure). Matching grants on the other hand satisfy a number of conditions that make randomization a possibility: i) they involve selection of individual firms; ii) the numbers of firms involved can be large enough to potentially generate enough statistical power for measuring impacts (provided that appropriate methods are used, see McKenzie, 2011b, 2012); and iii) data on key outcomes may be measured reasonably well through firm surveys.

Furthermore, matching grants are a type of program for which it is hard for non-experimental methods to convincingly deal with selection issues – firms self-select into whether or not to apply for the program, and then government implementation units select which firms receive the grants. An explicit element of both selection stages
sizes are typically too small to yield reliable estimates of poverty at the level of districts or communes. Censuses do not suffer from small sample problems as they cover the entire population. But while censuses also collect valuable information on individual and household characteristics that provide insights into living standards, they rarely include the income or expenditure information needed to measure poverty directly.

Small area estimation techniques have been developed to estimate poverty at the small area level. One popular approach, introduced by Elbers, Lanjouw and Lanjouw (2002, 2003) – henceforth ELL - combines household survey data and census data at the unit record level. The approach exploits the census’s coverage of the entire population and the household survey’s detailed information on income and expenditure. First, an expenditure (or income) model is estimated using the household survey data. The dependent variable is expenditure (or income), and the explanatory variables are a set of household and community characteristics that are comparable and that are available in both the household survey and the census. Subsequently, the parameter estimates from the expenditure model are applied to the census data in order to predict expenditure of all households in the population. From there it is a straightforward procedure to estimate poverty measures in small areas such as communes and districts.

The small area estimation method has been applied in a large number of countries to produce maps of not only poverty measures but also other welfare indicators (see Bedi _et al._ , 2007 for a review of applications). In Vietnam, a number of poverty maps have been developed using the ELL small area estimation method. Minot (2000) combines the 1993 Vietnam Living Standard Survey (VLSS) and the 1994 Agricultural Census to estimate poverty at the local level in rural areas of Vietnam. Minot _et al._ (2003) construct a poverty map using a 1998 VLSS and a 33% sample of the 1999 Population and Housing Census. Nguyen (2009) applies the 2002 VHLSS to the 33% sample of 1999 Population and Housing
businesses. Typically, they capture laws on the books that are only part of the story. Beyond the enforcement issue, macro datasets offer little information on how binding are for example, tax administration procedures on the private agents. A simple count of the number of tax procedures or the time it takes to comply with all tax procedures may not portray the full picture as to the sorts of countries that have more burdensome tax administration – it may depend on for example, the opportunity cost of time to the firms. We believe that our micro measure captures not just laws on the books but also their enforcement and how binding they are on the firms. Fourth, recent firm-level surveys such as the one used in the present paper offer a rich set of information about various economic phenomena that is typically not available in macro data. For example, the firm-level data we use contains detailed information about various firm characteristics such as age, size, ownership structure, gender of the owner, years of managerial experience and the quality of the broader business environment as experienced by the firm. Fifth, by utilizing firmlevel data, we are able to control for cross-country differences in for example, the composition of corporate sector and firm-size, which might cause spurious correlation in aggregate regressions.

Another novelty of the present paper is in exploring the possible non-linear effect of country size on the quality of tax administration. Specifically, we check if the strength of the proposed relationship between country size and tax administration is the same or does it vary across small vs. large countries. While there is little theoretical work on the issue, it is entirely possible that there could be increasing or decreasing returns to country-size. For example, if being large leads to more complicated tax rules and more wieldy tax administration (congestion costs), this effect may kick in only after a critical country size is reached or it may cease to matter at the margin once a country crosses a critical level in size. We treat the possibility of a non-linear effect of country size
traditional building materials and practices erode indigenous knowledge (Rautela 2005, cited in Adger et al. 2014).

The chapter also notes that the large majority of studies on climate change and indigeneity have focused on rural settings while leaving a knowledge gap with respect to urban indigenous communities. Main obstacles that undermine indigenous peoples’ adaptive efforts to maintain cultures, livelihoods, and traditional food sources stem from relocation enforced by governments, obstacles regarding knowledge transmission between generations, dependencies created by disaster relief and ill‐suited policies, and inadequate entitlements and rights as currently provided through the Western judicial system. Additional barriers result from lack of voice and inclusion in formal, governmental decision‐making processes over resources and development opportunities, for instance tourism and industrial activities, which may increase rather than reduce risks.

# **<mark>Short case studies (vignettes)</mark>**

## _3)_ _<u>Indigeneity as a driver of inequality in the highlands of Bolivia</u>_

Studies on the state of glaciers in the tropical Andes (see Rabatel et al. 2013 for a good overview) show unprecedented glacier retreat in this part of the world over the last three decades, at least since the Little Ice Age in the mid‐17th–early 18th century. Mass balance records show declining trends, with a critical threshold possibly crossed in the late 1970s. Measurements indicate that the surface temperature of the Pacific Ocean drives the reduction in mass balance and dramatic shrinkage in glaciers more so than precipitation, coupled with temperature increase and higher frequency of El Niño events. Now, how do these climatic stressors interact with inequality along the axis of indigeneity?

<!-- Start of picture text --> Measurements indicate that the surface temperature of the Pacific Ocean drives the reduction<br>in mass balance and dramatic shrinkage in glaciers more so than precipitation, coupled with<br>temperature increase and higher frequency of El Niño events. Now, how do these climatic<br>stressors
characteristics that it would like to control for in the comparison. The only requirement is that the characteristic be observable and that data exist for the units of analysis of interest.

Figure 7 presents comparisons across different police districts relative to their own CAP distributions. One can note by comparing Figures 8 and 7 that, taking account of the characteristics does make a slight difference to the comparisons of the targets to recent tendencies. In general, the targets appear somewhat less demanding relative to past performance, once one takes into account the particular characteristics of the police districts today.

**Figure 7.   Conditional relative performance on homicide reduction from 2000-2008, by Police Regions**

<!-- Start of picture text --> Trend 2000/2008 Barbacena<br>100<br>Trend 2004/2008 Vespasiano Belo Horizonte<br>90<br>Target 2008/2009 80<br>Unaí Contagem<br>70<br>60<br>50<br>Uberlândia 40 Curvelo<br>30<br>20<br>10<br>Uberaba 0 Divinópolis<br>Teófilo Otoni Governador Valadares<br>Patos de Minas Ipatinga<br>Montes Claros Juiz de Fora<br>Lavras<br><!-- End of picture text --> Source: Author’s calculations using data from Peixoto et al (2010) 17
investment opportunities for adaptation and mitigation.

This contribution is structured as follows. Section 2 underlines the challenges of assessing ESG components and presents a high level literature review on ESG topics. In section 3, we discuss the methodology and in section 4, we show some results for emerging economies with a particular focus on the MENA region, where firms are showing the worst results across emerging markets.

# **2 The challenges of assessing ESG: A review of existing methodologies**

Under increasing regulatory and market pressure, firm-related ESG disclosure developed significantly over the last couple of years. However, while ESG topics require consistent and comparable metrics in order to compare firms’ performances, a consensus has not been reached on the relevant dimensions to assess the performance of firms.

Typically, ESG rating agencies<sup>4</sup> use firm-level quantitative and qualitative information to produce ESG ratings. They engage with firms directly – often using questionnaires to obtain financial and

> 3 Survey information is widely used for assessing ESG/Sustainability ratings. It is normally complementing financial information, hard data and public domain information.

> 4 The main ESG rating agencies are the following: Vigeo Eiris, which is part of Moody's (Moody's acquired a majority stake of Vigeo Eiris in April 2019); ISS-oekom (Institutional Shareholder Services group of companies - “ISS”) which has been integrated

3
|Livestock, 2010, mt|2,014,887|13021.28|<br>73234.23|0|1060007|
|---|---|---|---|---|---|
|_Buffaloes,_|2,008,899|94.980|906.527|0|119607.5|
|_Goats_|2,014,567|475.125|2351.833|0|237936.2|
|_Cattle_|2,014,533|723.358|1943.561|0|328070.9|
|_Sheep_|2,014,215|558.121|1885.496|0|344862.1|
|_Horses_|2,013,909|30.783|153.932|0|105564.2|
|_Pigs_|2,014,572|484.444|2889.772|0|411115.7|
|_Chickens_|2,014,564|9994.698|67859.33|0|10500007|
|_Ducks_|2,012,134|663.042|7095.628|0|1311365|

Note: Data for livestock cover not available. One grid cell has a spatial resolution of 1/12 degree - about 9 to 10 sq km. Urban extent is the percentage of urban area in a grid cell (ranging from 0 to 1). Crop production for each grid cell is defined as the yield multiplied by harvested area in metric tons. Food crops include cereals, fruits, oils, pulses, roots, sugar, vegetables food groups. Livestock production is the global population densities of eight types of livestock: cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 1/12 degree degrees (approximately 10 sq km at the equator). Missing values in the crop production dataset are specifically distinguished
<!-- Start of picture text --> COV; MDG CATA; SDG<br>HBS<br>escs [ass[e_ [rs].||p |<br>eee<br>2p a<br>EJ<br>oF<br>DHS 2<br>az=<br>OUT; MDG<br>WHS<br>-—T TTT} was<br><!-- End of picture text -->
<!-- Start of picture text --> Polsr Paning, and lRcshm<br>Fln ndal Podby and Sytems<br><!-- End of picture text --> Fmancial liberalization was carried out in a period when the nonfimancial corporate sector was in financial distress due to reduced profitability. The consequent emergence of substantial nonperfonming **lo-is** in the banking sector, especially among smaller banks, created fierce competition for financial resources. The result was a rapid expansion of deposits and high real interest rates. Instead of forcing insolvent borrowers into bankniptcy, banks refinanced nonperforming loans as a way to prolong their own survival, and real credit to the private sector increased dramatically. Furthermore, the market mechanism turned out to be il-equipped to induce the exit of insolvent banks and thereby increase the efiTciency of allocating loanable funds.

An analysis of finn-level data reveals that nonfinancial corpor ions were subject to both an earnings shock (increases in costs relative to sales income) and an interest rate shock. Although the debt-to-asset ratios cf profitable firms did not change, those of firms under distress actually increased, despite higher costs of borrowing.

The Turkish experience suggests that financial liberalization may not produce desired results when it occurs in a period of major macroeconomic realignments that adversely affect the profitability of the corporate sector, especially when it is implemented without an adequate regulatory framework.

This paper is a product of the Fmancial Policy and Systems Division, Country Economics DeparEment. Copies are available free from the **World** Bank, 1818 H Street NW, Washington DC 20433. Please contact Wilai Pitayatonakam, room N9-005, extension 60353.

The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planming, **and** Research Complex. An objective of the series is to **get** these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, **and** conclusions in these papers **do**
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019<br><!-- End of picture text --> Note: Trade is global exports of goods and services. GVC share of trade is proxied by foreign value added in exports, based on the UNCTAD-Eora GVC database. The underlying FDI trend is an UNCTAD indicator capturing the long-term dynamics of FDI by netting out fluctuations driven by one-off transactions and volatile financial flows.
,860|
|Adult Tonsillectomy|3,398|17,251|1,931|102,749|1,010|13,588,218|
|<br>Hysterectomy|5,783|640,565|5,420|N/a|1,869|250,704,845|
|<br>Haemorrhoidectomy|4,945|12,787|2,081|137,213|781|23,160,663|
|<br>Rhinoplasty|5,050|7,265|3,417|N/a|1,906|2,284,315|
|<br>Bunionectomy|6,046|3,139|2,392|41,507|1,487|5,186,290|
|<br>Cataract extraction|3,595|2,215|2,325|1,430,785|1,133|171,078,116|
|Varicose vein surgery|7,065|1,957|2,373|148,043|1,393|15,618,521|
|<br>Glaucoma procedures|3,882|-|2,292|75,838|1,017|9,670,440|
|<br>Tympanoplasty|4,993|754|3,347|149,246|1,261|31,408,685|
|Total savings||||||1,415,264,725|

_Sources:_ Health care Cost and Utilization Project (H-CUP) database, 2002, Vanbreda International, and authors’ calculations. An “N/a” denotes that data was not available. Patient volume data pertain to 2002, while the prices pertain to 2004.

20
impact of ICT on productivity than what the standard neoclassical growth model would predict, and it is attributable, at least in part, to investments in complementary intangible capital.

Brynjolfsson, Rock, and Syverson (2021) find that the productivity growth resulting from ICT use was initially underestimated but subsequently overestimated when the benefits of intangible investments were realized with a lag. This “productivity J-curve” can be largely attributed to the poor measurement of intangible capital in national accounts. The authors find that adjusting for intangibles related to computer hardware and software yields a TFP level that is 15.9 percent higher than official measures in the United States by the end of 2017. Analyzing firm-level data across 13 EU countries, Bloom, Sadun, and Van Reenen (2012) find that foreign affiliates of US multinationals obtain higher productivity than non-U.S. multinationals (and domestic firms) from their IT capital owing to better management practices. The advent of AI is likely to spawn a new wave of complementary investments in intangible capital.

There is some evidence from developing economies on the link between digital technologies and productivity growth through investments in ICT and related intangible capital. Analyzing data across 156 countries between 1990 and 2019, Calderon and Cantu (2021) find that broadbandcapable mobile connections have an impact on economic growth through the total factor productivity growth channel, while the number of internet users drive it through the capital accumulation channel. Commander, Harrison, and Menezes-Filho (2011) identify a strong positive link between ICT capital and productivity in manufacturing firms in Brazil and India. Diao et al. (2021) show that capital-intensive technology advancements in the manufacturing sector improve firms' productivity in Ethiopia and Tanzania accordingly, with large firms experiencing stronger productivity gains. Piatkowski and van Ark (2005) show that ICT investment contributed to economic convergence between Central and Eastern European countries with the EU-15 and the United States during the 1990s. Intangible capital is found to be positively correlated with growth in China (Hulten and Hao 2012), export growth and TFP growth in
that 12.8 % of the population of the poorest quintile declared to have gone to a private clinic or hospital when ENDESA survey was conducted (2007). This probably reflects that the fully subsidized national insurance regime still presents wide gaps in coverage that force the poorest to recur in some cases to private clinics and make burdensome disbursements to get treated.

**Figure 11: Form of payment of the medical check up**

<!-- Start of picture text --> 100<br>90<br>80<br>70 Totally paid by<br>the patient<br>60<br>50 Partial/totally<br>paid by the<br>40<br>insurance<br>30 Free<br>20<br>10<br>0<br>Q1 Q2 Q3 Q4 Q5<br>Source: ENDESA survey, 2007<br>Percent of population<br><!-- End of picture text --> By looking at the form of payment of the medical check up, it is possible to observe that population in quintiles 3 and 4 (intermediate strata) are the most propense to totally assume health-care related expenditures, as often they are neither covered by the national insurance (if they work informally) nor enrolled in private insurances. Payments for medicines and for laboratory analysis are a burden for the Dominicans; 66% of the population interviewed in ENDESA was wholly affording their medication, with few variation across income quintiles. Again, this is a barrier in the health system with regressive implications.

ENDESA survey also offer estimations of average expenditure per capita in health checkups during the month preceeding the survey. This may be a good estimate of “out of pocket” spending, since it covers money paid for doctor check up, medicines, and laboratory analysis and it does not consider expenditure related to prolongued/chronical diseases, surgery and prolonged treatment (“internamientos”).

[17]
increase in participation for the recent cohorts is confirmed.<sup>16</sup> Going beyond this graphical examination, we applied the formal econometric Age-Period-Cohort (APC) decompositions discussed in the methods section for two countries where we have a sufficient number of evenly repeated cross section data sets. The results from the models in the APC analysis for Bangladesh and Nepal complement the conclusions from the graphical examination of these effects on female employment. Tables A5 and A6 in the Annex present the parameter estimates and their standard errors

> 14 This inverted “U” shape for the age effect, with a peak around 30-40 years of age and lower participation at the other ages, is typical for countries in South Asia as well as in other regions (see Figure A4 in the Annex).

> 15 Afghanistan is not included because it has only one round of survey in 2015.

> 16 Interestingly, the sharp rise in employment happens at the same time for the two cohorts born most recently, i.e. it seems mainly driven by data from the latest two survey rounds. Thus, what in the figure is labeled as a cohort effect, it may in fact also be a ‘year effect’. As Deaton and Paxson (1994) clearly explain, one has to make some strong assumptions to identify the age, cohort and year effects in these panel data. And clearly the graphical decomposition in Figure 7 and Figure 8 are not fully identifying these three components. For a similar analysis see also Yang, Schulhofer-Wohl and Land (2008); Fosse and Winship (2019); Tunalı, Kırdar and Dayıoğlu (2019).

14
18 (iii) by facilitating the payment of bills (by allowing discriminatory administrative arrangements in favor of the permanently or temporarily poor).<sup>21</sup> For a long time, analysis of these instruments focused on efficiency and was conducted at a fairly theoretical level by public finance specialists. But enormous methodological progress over the past 10–15 years has allowed the academic world to make much better assessments of the performance of these instruments not only in terms of efficiency but also in terms of their effects on the behavior of poor people and service providers. Methodological developments have occurred in three fields: microeconometrics (especially developments in the econometrics of panel data), evaluation techniques, and incentive theory applied to the theory of regulation. The standard reference on microeconometrics is Deaton (1996). A recent book edited by Bourguignon and Pereira (2003) and containing contributions from many of the key researchers in the field provides an exhaustive overview of the status of evaluation techniques. On incentive theory the standard reference is Laffont and Tirole (1993), and for developing countries Laffont’s final book (2004) will likely become the main source.

A look at the empirical evidence generated from these theories is somewhat disappointing for infrastructure policymakers. The top academic economic journals contain relatively few specific articles on targeting, affordability, or regulation for infrastructure services in developing countries (especially relative to health and education services, where there is much more data and data quality lends itself better to academic publications). On targeting—which has received the most attention, and almost invariably raises issues of affordability and regulation--, an unusually large share of the recent output has been generated by a few contributors, including P. Lanjouw, Ravallion, Van de Walle, and Wodon—alone or with coauthors.<sup>22</sup> The main contribution of this literature has been developing techniques that allow the production of poverty maps and of rigorous analysis of the evolution of poverty and its characteristics over time, making