rafmacalaba/datause-encoder-data huggingface dataset:
Table 8 presents these results. We find that market concentration is not related to any of the three market growth variables for the global sample. The coefficients of the stock market total value traded to GDP and equity market capitalization to GDP variables are positive, albeit not significant. Conversely, the coefficients of stock market turnover ratio are negative, but also not statistically significant. For LMICs, however, it is significant, implying that greater share turnover in the market is related to lower concentration in less developed markets. Note, though, that the magnitude of the association is marginal in economic terms. Results are similar when we use an alternative control for the macroenvironment in a country as a robustness check (Table A-6 in the Annex).

# **6. Concluding remarks**

The paper examines how issuer composition changes as stock markets grow, focusing on low- and middle-income countries. Specifically, we study whether such growth is associated with new firms listing in the stock market, the sectoral diversity of issuers and the market concentration among issuers. To investigate these relationships, we use a novel IFC dataset that includes data on various measures of stock market growth (size and activity) and issuer composition (number, concentration, and sectoral diversity) for over 150 countries for the period 2015-2020.

Our results show that stock markets may not necessarily become more inclusive as they grow. Specifically, we find that stock market capitalization, often the most popular headline indicator for market development, tends not to be associated with new equity issuances. Instead, a growing stock market is related to an increase in the number and size of seasoned equity offerings, indicating growth at the intensive margin. Greater trading activity, however, is associated with a higher number of issuances both by existing and new issuers.

These findings hold for low- and middle-income countries. The paper additionally finds that higher stock turnover is related to lower market concentration in these countries. This result is of particular relevance given that less developed markets are more likely to be dominated by a few firms. These markets are also more likely to have a high concentration of listed firms in a few industries. Moreover, the paper does not find any evidence that sectoral diversity of equity issues improves as equity markets increase in size and liquidity.

Our findings have important implications for policy makers seeking to improve access to financing for firms. Participation of a broad and diverse set of issuers reflects a well-functioning stock market, which is able to meet various financing needs in the underlying economy. As our results show, however, this may not naturally follow capital market growth. Our findings therefore highlight the need to go beyond headline growth indicators to ensure stock markets are more 22
INTROoUCTION LXIX of Populatlo Data

|Infant<br>mortality<br>1985-90|**Age*seax**structure,<br>1985|Most recent<br>contraceptive<br>**prevalence**|_Cciuntry,_<br>econom<br>or<br>territory|
|---|---|---|---|
|U.N.1990 revision|ank est.|Ross et**al.**<br>1988|Afghanistan|
|UUPVSR 10/89 (official<br>eat.)|U.N. 1988revision|-|Albania|
|U.N.1990 revision|U.N.1988 revision|Mauldinand Segal 1988|Algeria|
|USEOC 1968|Bank est.|--|American Samoa|
||||Andorra|
|U.N. 1990 revision|U.N.1988 revision|Ross etal.1988|AngoLa<br>Angui l**la**|
|**Based**on officlal<br>est.|UNDY 1978|U.N. 1988|Antigua and<br>Barbuda|
|U.N.1990 revision|U.N.1988 revision|-m|Argentina|
||||Aruba|
|_UNPVSS_4/87 (official<br>**est.)**|U.N.1988 revision|Pop. Ref. Bureau 1990|Australia|
|UIPV.I<br>10/88(official<br>est.)|U.N.1988 revision|U.N.1988|Austria|
|UhPVSR 10/89 (official<br>**set.)**|**Easedon**1980 census||Bahams,The|
|Official<br>**est.,**Central<br>Stat.|U.N.1988 revision||Bahrain|
|Organization||||
|U.N.1990 revision<br>|U.N.1988 revision<br>|Fertility<br>Survey 1989<br>|Banr'adesh<br>|
|**lased**onUNPVSR<br>10/89,<br>(off'ciatast.)|U.N.1988 revision|U.N.1988|Barbados|
|Euroi tat 1989|Eurostat<br>1989|U. N.1988|BeLgium|
|**Base**on USB8C 1985|**Based**on UNDY 1978|Pop.Ref.Bureau 1990|BeLize|
|Babedon**UFS**|Based**on**1979 census|Ross etal.1988|Benin<br>|
||||Bermuda|
|U.N.1990 revision|U.N.1988 revision||Bhutan|
|U.N.1990 revision|U.N. 1988revision|DHS 1989|Bolivia|
|**lased**onDNS 1988|U.N.1988 revision|DHS1988|Botswana<br>|
|U.N.1990 revision|U.N. 1988revision|DHS 1986|Brazil|
||||British<br>Virgin<br>IsLands|
|Bank est.|Based on 1981 censusand<br> <br>||Brunei|
||official<br>projection|||
|UNPVSR 10/89 (official<br>est.)|U.N. 1988revision|U.N.1988|Bulgaria|
|U.N.1990 revision|Bank st.|--|Burkina faso|
|BasedonDHS 1987|U.N.1988 revision|DHS 1987|Burundi|
|U.N. 199revision|**Based**on 1976 census|iFS 1978|Cameroon|
|UlPVSR 10/89 (official<br>est.)|Official<br>ast.,Population<br>Projections<br>for Canada,1984-2006|Mauldin<br>and 3egal1988|**Canada**|
|U.N.1990 revIsion|<br>**lased**on 1980 censu|--|Cape Verde|
||||Cayman IsLands|
|U.N.1990revision|**Based**on 1975 cenwus|-|Central<br>African<br>Rep.|
<!-- Start of picture text --> =0.42, 0.5, =2, n=20<br>140<br>—— Pooled Treatment<br>130 — — Pooled Within-ClusterControl<br>vo Average<br>120 ;<br>110 f<br>- 100 f<br>3 !<br>“| ool i,<br>oa=>coa 80 .: :a fo?Po:io::<br>70 ‘ . 4:fo::<br>. foe<br>60 1 eeeuf -<br>rl<br>40<br>0 0.1 0.2 03 O04 05 O68 of 08 O89 1<br>Saturation P<br><!-- End of picture text -->

<!-- Start of picture text --> P=1/2, n=20<br>100 250<br>——Pooled Effect: #=0,0%=2<br>—— Pooled Effect: 2=0.5,07=0<br>_ “ j<br>80 \ = 4200<br>}l\<br>!any \ |<br>@ 60 l f 150<br>1 \ |<br>= \ {<br>8c@ 40 \\ \ f }i 100<br>& \ 4 4<br>\ Z<br>20 Se se ees “7% 50<br>0 0<br>0 0.1 02. 03 O04 05 08 OF 08 09 1<br>Controly<br><!-- End of picture text -->
# **1. Introduction**

Although Bolivia is located entirely within the tropics, the large altitude variations within the country imply that it has almost every conceivable type of climate ranging from Andean glaciers, via salt deserts, to steaming rainforest. This variation makes Bolivia ideally suited for an empirical analysis of the social impacts of climate change because the limited variation in the time dimension can be complemented by ample variation in the spatial dimension.

A simple way to gauge how climate affects human development is to compare human development across regions with different climates. This has, for example, been done by Horowitz (2006), which uses a cross-section of 156 countries to estimate the relationship between temperature and income level. The overall relationship found is very strongly negative, with a 2  F increase in global temperatures implying a 13 percent drop in income. This is very dramatic, but the relationship is thought to be mostly historical and thus not very relevant for the prediction of the contemporary effects of climate change in the recent past or near future. In order to control for historical factors, the paper includes colonial mortality rates as an explanatory variable, and finds a much more limited, but still highly significant, contemporaneous effect of temperature on incomes. The contemporaneous relationship estimated implies that a 2  F increase in global temperatures would cause approximately a 3.5 percent drop in World GDP.

In order to further control for historical differences, Horowitz (2006) uses more homogeneous sub-samples, such as one with only OECD countries or only countries from the Former Soviet Union, and the negative relationship still holds. However, as directions for further research, he recommends empirical studies of income and temperature variations within large, heterogeneous countries, which would provide much more thorough control for historical differences. This is exactly what we do in this paper.

Using data from the 311 municipalities in Bolivia, we estimate contemporary relationships between temperature and consumption levels (a proxy for income), as well as between temperature and life expectancy. These relationships are then used to gauge the likely direction and magnitude of effects of climate change in Bolivia.

The rest of the paper is organized as follows. Section 2 describes the data and the sources. Section 3 estimates municipal level econometric models of the relationships between climate variables, life expectancy, and consumption levels. Section 4 analyzes climate change in Bolivia from 1948 to 2008. Section 5 uses the estimated models from Section 3 to simulate the effect of recent climate change (from Section 4) on consumption levels, poverty and inequality. Finally, Section 6 concludes.

# **2. The data**

The data used for this paper consist of both cross-section and time series data. The municipal level cross-section data base used to estimate the relationships between climate, 2
# **1. Introduction**

Peers can have important effects on individuals’ economic decisions. During adolescence in particular, young people are exposed to different groups of peers; this exposure can influence subsequent human capital accumulation and behavior.<sup>1</sup> Specifically, the exposure to violent peers can affect not only adolescents’ academic achievement in the short-run (Lavy and Schlosser, 2011; Carrell and Hoekstra, 2010) but also their earnings in the long-run (Carrell et al., 2018). From the existing literature on group composition, there are three important evidence gaps. First, most existing papers only identify the intensive margin: the effect of exposing an individual to a group of peers with certain average characteristic; yet, with some notable exceptions (Garlick, 2018; Duflo et al., 2011; Lafortune et al., 2016), they do not directly compare average effects of different policies to one another.

Second, there is little consensus about what type of group composition—integration or segregation— is more effective in improving relevant economic outcomes. Some studies find that integrated groups are preferable because the interactions with diverse peers have the potential to enhance the learning experience (Lafortune et al., 2016) or that exposure to high-performing peers improves outcomes for more disadvantaged individuals (Lavy et al., 2012; Rao, 2019; Griffith and Rask, 2014; Oreopoulos et al., 2017). However, another strand of the literature finds that grouping individuals with similar peers can generate better results, since that segregation allows teachers to match instruction to a particular group’s needs (Duflo et al., 2011), or because individuals prefer to interact with peers with whom they share particular characteristics (Carrell et al., 2013; Girard et al., 2015; Goethals, 2001).<sup>2</sup>

> 1Evidence from Bursztyn et al. (2019) and Bursztyn and Jensen (2015) show that peers pressure are important determinants of educational investment and academic performance in schools.

> 2This preference for interacting with individuals of the same gender or race has been extensively studied in the role model literature. This evidence has consistently shown that being assigned to mentors or supervisors of the same gender (Athey et al., 2000; Bettinger and Long, 2005) or race (Dee, 2004) improves student’s and worker’s performance.

2
# **Appendix 3: US Goods Imports by Product Category, Ranked by Q4:2009 YTY Growth**

<!-- Start of picture text --> 12.0%<br>5.0%<br>‐18.8% Finished metals assoc with durable<br>‐40.4%<br>‐45.5%<br>‐32.6%<br>32.2%<br>13.6%<br>‐38.3%‐25.0% Chemicals, excl medicinals<br>‐39.0%<br>‐25.9%<br>1.3%<br>‐4.7%<br>‐34.6%‐26.5% Paper & paper base stocks<br>‐33.0%<br>‐23.9%<br>25.6%<br>9.6%<br>‐23.5% Materials assoc with nondurable<br>‐36.5%<br>‐36.7%<br>‐23.4%<br>16.8%<br>‐8.9%<br>‐49.8% Unfinished metals assoc with durable<br>‐60.2%<br>‐54.6%<br>‐18.8%<br>‐20.5%<br>‐25.2%<br>‐34.4%‐34.1% Selected building materials<br>‐29.8%<br>‐17.4%<br>9.2%<br>0.1%<br>‐23.0% Nonmetals assoc with durable<br>‐27.4%<br>‐25.9%<br>‐15.0%<br>54.9%<br>‐15.1%<br>‐52.1% Fuels & lubricants<br>‐54.6%<br>‐48.7%<br>‐13.8%<br>‐3.3%<br>‐12.8%<br>‐31.9%‐27.4% Textile supplies & related matls<br>‐27.4%<br>‐10.9%<br>2.1%<br>‐3.1%<br>‐28.5%‐20.6% Electric generating, & electric eq & parts<br>‐24.7%<br>‐10.8%<br>‐2.2%<br>‐2.3%<br>‐14.4%‐9.4% Apparel, footwear & household goods<br>‐13.8%<br>‐8.6%<br>13.1%<br>‐9.1%<br>‐30.1% Grand Total<br>‐34.8%<br>‐29.2%<br>‐7.9%<br>10.3%<br>5.7%<br>‐9.2%‐5.3% Foods, feeds & beverages<br>‐11.5%<br>‐6.7%<br>3.1%<br>‐6.3%<br>‐26.3%‐20.4% Capital goods, except automotive<br>‐21.1%<br>‐6.3%<br>4.0%<br>‐6.3%<br>‐26.6%‐20.4% Nonelectrical machinery<br>‐20.8%<br>‐5.4%<br>‐12.4%<br>‐24.4%<br>‐49.2%‐48.9% Automotive veh, parts & engines<br>‐23.7%<br>4.0%<br>Q3‐08 Q4‐08 Q1‐09 Q2‐09 Q3‐09 Q4‐09<br><!-- End of picture text --> Source: Own illustration. Data: Bureau of Economic Analysis, International Accounts Product, monthly and quarterly imports of goods, balance of payments-based data, seasonally adjusted.

35
The commission cost has added about 30 basis points to the annuity rate, as shown by the adjusted annuity rate line in Figure 9, reducing the intermediation spread commensurately.<sup>37</sup> In addition, providers also need to cover their operating costs, which in 2008 amounted to about 2.2 percent of assets, implying a negative spread overall. As shown in Figure 11, while the largest life insurance companies have reduced their operating costs and may continue reducing them further, the overall market has increased them. However, if cost ratios decline to 0.6 percent, which is the lowest cost ratio among OECD countries, prospective profit margins would appear to remain unattractive even for the five largest life insurance companies.

The analysis of money’s worth ratios and intermediation spreads suggests that at least some annuity providers may have experienced losses from the annuities issued between 2002 and 2005. These losses have not resulted in immediate financial problems for the companies because of the strong capital and reserve buffer accumulated from previous years which was due to strict capital regulations implemented in the early 1990s. However, the analysis also suggests that the high MWRs offered in 2002-2005 probably cannot be sustained, as they would imply further erosion of capital, at least for some companies.

**Figure 11: Administrative Cost of Life Insurance Companies, 1991-2008 (as a percentage of Total Assets)**

<!-- Start of picture text --> 2.8%<br>2.6%<br>2.4%<br>2.2%<br>2.0%<br>1.8%<br>1.6%<br>1.4%<br>1.2%<br>1.0%<br>1991 1993 1995 1997 1999 2001 2003 2005 2007<br>All Companies Five Largest Companies<br><!-- End of picture text --> Source: SVS The question arises as to why profit-maximizing companies have issued annuities with such thin financial margins. It is unlikely that insurance companies have underpriced their annuities due to outdated mortality tables, because most companies seem to have sufficient technical capacity, including well-trained actuaries. It is more likely that companies have priced their annuities counting on a future increase in interest rates from the low recent levels. The intermediation spreads shown in Figure 8 do not capture the spread earned over the entire life of the annuity contract because assets have a shorter duration than liabilities. If interest rates increase (above the levels implicit in the current yield curve) margins earned on currently issued contracts would increase as well.

> 37The commission rate is transformed into an interest rate (i.e. capitalized) by calculating the difference between the internal rates of return of an annuity with the gross and the net premiums.

30
The results largely hold in the regressions with neighborhood-area fixed effects. Child’s age, child illness, mother’s age at child’s birth, mother’s education attainment, mother’s birth location (specifically, mother’s birth in another urban area), mother’s membership in an NGO, and household wealth continue to have significant effects on HAZ scores. For factors that are similar between our analysis and that of Ahsan et al. (2017), inference results from our regressions with division fixed effects for slum and nonslum samples match those from their final stunting regression specifications. Our findings are also largely consistent with those from studies of the determinants of child undernutrition in selected slum settlements in various urban centers in Bangladesh (Fakir and Khan 2015; Zaman et al. 2015; Alam et al. 2011), as well as with international evidence on the determinants of child undernutrition in slum areas (Goudet et al. 2017; Abuya, Ciera, and Kimani-Murage 2012).

# D. _Effects of the use of maternal and child health services on child HAZ scores_

Here, we examine the effects of antenatal care, delivery, and newborn exam at health facilities on HAZ scores. The information on antenatal care, delivery, and newborn exam were gathered in the 2013 BUHS only for the youngest child born in the three years before the survey (61% of our full analysis sample).

_Mean levels_ : Table 4 reports the rates of use of health services by provider type. In the pooled sample, mothers of 70% of children obtained antenatal care in a health facility, 49% of children were delivered in a health facility, and 40% of children received an exam when newborn in a health facility. While cases exist of qualified health professionals providing antenatal care and conducting newborn exams at home, the shares fall in the low single digits, and these cases are categorized under “no service”.

The use of private providers and facilities dominates. Mothers of 31% of children obtained antenatal care at a private health facility, 23% at an NGO health facility, and 16% at a public health facility. Similarly, 21% of children were delivered at a private health facility, and 14% each at an NGO or public health facility. Eighteen percent of children had a newborn exam at a private health facility, and 11% each at an NGO or public health facility.

Slum children recorded lower rates of use of health services than nonslum children. The rates of maternal antenatal care, delivery, and newborn exam in a health facility were 22–25 pp. lower for slum children. Slum children had higher rates of use of NGO health facilities for 23
Another study that attempts to shed some light on the implications of privatization for welfare is Ugaz and Waddams Price (2003). In contrast to Galal et al. (1994), this study focuses only on consumer welfare, using household surveys before and after privatization. The seven cases analyzed correspond to utilities in Latin America, Spain, and the United Kingdom and present a mixed picture. They show that prices have often risen as a result of the rebalancing of tariffs after privatization, and this has affected low-income groups more than others. But the study also shows that most companies have extended their coverage (access) so that the poor in developing countries, who initially enjoyed the least coverage, are benefiting the most from this aspect of privatization.

Similar research was carried out for Latin America by the Inter-American Development Bank. The case study presented here is about the privatization of water distribution in two provinces of Bolivia, La Paz–El Alto, and Cochabamba (Barja, McKenzie, and Urquiola 2005). As was seen above, when discussing the simple economics of privatization, the two main determinants of the impact of privatization on consumer welfare are price and access. In the case of Bolivia, the 1997 privatization of water distribution in La Paz and El Alto produced only a slight increase in prices (Figure 8), but in Cochabamba, where privatization took place in 1999, prices increased enormously months later.

To evaluate the welfare impact of privatization on consumers, access needs to be taken into account. Figure 9 shows the impact of privatization on households in La Paz and El Alto according to their initial access to water. The welfare of those households that enjoyed access before privatization did not change much, as prices did not increase substantially. For households that gained access, there was a large positive impact on welfare. If it can be proved that this improved access was caused by privatization, privatization might have had a huge impact on consumer welfare.

In Cochabamba privatization was very short-lived. The privatization took place in October 1999. In March 2000 widespread protests occurred—the so-called Water War—and the government decided to give the water operation back to the original SOE. Barja, McKenzie, and Urquiola (2005) estimated the impact of the price increase on income groups in the population, looking simply at the share of water expenditure in household budgets and calculating how much households would have to pay in addition. Figure 10 shows that the impact of privatization in 15
However, with clean energy and climate policies emerging, and renewable energy capacity in the electricity generation mix expanding, a recent study by IEA (IEA, 2023a) predicts that global demand for coal is expected to decline in the coming years. As demand declines, coal prices are also expected to fall in the future. To reflect these changes in coal prices, we did a simple sensitivity analysis of the reduction in total costs of brick production with different combinations of coal and biomass pellets (Figure 9). We find two key inferences from the sensitivity analysis. First, decreasing coal prices leads to a lower reduction in total costs and vice-versa with varying combinations of coal and pellets. Second, the higher the share of biomass pellets, the higher the reduction in total costs and vice-versa.

<!-- Start of picture text --> 35<br>30<br>30 25% coal:75% pellet<br>50% coal:50% pellet 25<br>25<br>75% coal:25% pellet<br>20 20<br>20<br>17<br>15 13 13<br>10<br>10 9 8<br>7<br>5 4<br>5 3<br>2<br>0<br>Current 50% lower 25% lower 25% higher 50% higher<br>Coal price<br>coal and pellet combination<br>% reduction in total costs wrt different<br><!-- End of picture text -->

**Figure 9. Variation in reduction in total brick production costs with different coal prices and the combination of coal and biomass pellets**

# 5 _.1.3 Electric or hydrogen-based brick kilns_

Since all fossil fuels are imported in Nepal, a promising environmentally friendly and carbonneutral<sup>15</sup> cost-effective alternative could be electric kilns powered by green electricity generated from renewable energy sources. Currently, electricity is commonly used for machine operation

> 15 Despite electric kilns powered by green electricity is carbon-neutral, there are significant process-related CO2 emissions, due to the release of carbonates contained in the clay and the combustion of additives.

21
<!-- Start of picture text --> Flgur 2. Output no lntmrational mpilIovers, case 2<br>-0.05<br>-0.1<br>rp.i Germany<br>-0.15 ad t-- France<br>UK<br>-0.2--<br>-0.25-<br>-0.3<br><!-- End of picture text --> _Simulation 2 No international spillovers in knowledge accumulation_ p 9 -P 10 **=-** J314 '- 0 In this exercise the second source of knowledge spillover, acting directly through _Tw,_ is eliminated in addition to the first one . Output losses are reported in **fig** 3 where the results for Germany on the one hand and for France and the UTK on the other look quite different<sup>45</sup> . Table 11I also shows that differences in aggregate performance are reflected in differences in sectoral performance and in the change of the specialization structure as well as in the consequences on domestic knowledge accumulation. These results highlight the consequences of different intensities in "technological integration" on growth. In the previous section we have seen that these differences play a relevant role in the dynamic behavior of the national models.

> This simulation was not carried out for Italy and Japan as 0 9 was set to zero in estimation in these two country cases

34