rafmacalaba/datause-encoder-data huggingface dataset:
- 60 -

# Taft A.4: Loeatinal **C e** Population, Wokforce an Nonfa rmplo ymnt

h~ hda, 196181 In~~ ola WM

|||||Urban Areas|||
|---|---|---|---|---|---|---|
|Yea|r|Rural<br>Areas|Rural<br>Towns|Large<br>Urban|Total|Total<br>Natlonal|
|||||(Percent)|||
|l)|Population||||||
||1961|82.0|9.3|8.7|18.0|100|
||1971|80.1|8.8|11.1|19.9|100|
||1981|76.2|9.4|14.3|23.7|100|
|II)|Pull-the<br>Workers||||||
||1961|86.0|7.3|6.7|14.0|100|
||1971|82.3|9.8|8.0|17.7|100|
||1981|79.3|8.2|12.5|20.7|100|
|Ill)|Nontarm Workers||||||
||<br>1961|65.8|20.8|.3.3|44.2|100|
||1971|44.8|21.0|.4|50.4|100|
||1981|44.9|18.8|36.2|55.1|100|

> S~a~e: c_POPslo _WMwi_ d 1981, 1971, 1981. See hdb (1961a., 1971SAb, 191b). Raw data are reproduced In Appendhx Table A.1.
and Appendix Table S2. The figure shows an overall decline in informality rates over the period that we study. This decline, however, confounds general trends in health insurance enrollment, macroeconomic conditions, and the effects of the SR. Our empirical strategy will disentangle these effects to identify the effects of the SR.

Figure 1 also shows that in the years prior to the onset of the SISBEN interviews (shaded area), the informality rates of early and late adopters were almost identical. The informality rates diverge after the onset of the interviews in 1994 for the early adopters. Notably, the decline in the informality rate is lower than that observed among the late adopter group of municipalities. In 1996, after the late adopters start, their decline in informality rates also slows. Appendix Table S2 shows the summary statistics using data prior to the onset of the SISBEN interviews. We find that although the largest cities started conducting SISBEN interviews earlier, importantly, the proportion of informal workers on the eve of the first SISBEN interviews is almost the same across the groups.<sup>17</sup> To address the possibility of any labor market or demographic municipal-specific changes, in our analysis, we include labor market, demographic, and education controls.

# **Panel Using Individual-Level SISBEN Data**

As an alternative data source and to corroborate our results, we use a panel dataset at the individual level that we constructed from the first and second SISBEN. The first SISBEN was conducted between 1994 and 2003, and the second was conducted between 2003 and 2007.

Because of manipulation concerns after 1998 (Camacho and Conover 2011), we use data for

> 17We tested whether the early and late adopters had different pre-adoption informality rates by running a municipal-level regression of the informality rate in the pre-period on year and interactions between year and adoption date. An F-test of the interaction terms jointly equal to zero indicates that we failed to reject the null hypothesis of a common trend among the two groups of municipalities. This test, however, uses only 20 observations.

12
measuring profitability.<sup>8</sup> In addition to standard entries from the balance sheet and income statements, the dataset contains qualitative information on the lending style employed by the MFI (group versus individual-based lending), the range of services it offers, its profit status, ownership structure, charter status, and sources of funds. Many of these serve as important controls in the regressions that follow.

We estimate the following basic regression: _(1) MFI Outcomeit = α + β1Bank Penetrationit_ + _β2Real Yieldit_ MFI Productivity + _β3Capital Costs/Assetsit_ + _β4Labor/Costsit_ + _β5Village Bank Lendingit_ MFI Lending Method + _β6Solidarity Group Lendingit_ + _Β7Ln(age)it_ Other MFI Characteristics + _Β8Ln(assets)it_ + _β9Inflation Rateit_ Country Characteristics + _β10Real GDP Growth Rateit_ + _β11 KKM Index of Inst. Developmentit_ + _Β12Rural Population Shareit_ + _Β13Rural Population Growthit_ + _Β_ **_14_** _Regionit + εi_ Where _Outcome_ is a measure of the profitability or “depth of outreach” of microfinance institution _i_ in year _t_ . The profitability measures that we use are the Financial SelfSufficiency (FSS) Index and return on assets (ROA). Both measures are adjusted as described above. The FSS ratio is a measure of an institution’s ability to generate sufficient revenue to cover its costs.<sup>9</sup> Values below one indicate that it is not doing so. We prefer that ratio because it offers a more complete summary of inputs and outputs than standard financial ratios such as return on assets or equity. Our proxies for the depth of outreach of a microfinance institution are the share of its borrowers that are women

> 8 These include adjustments for inflation, the cost of subsidized funding, current-year cash donations to cover operating expenses, donated goods and services, write-offs, loan loss reserves and provisioning, a reclassification of some long-term liabilities as equity, and the reversal of any interest income accrued on non-performing loans.

> 9 The financial self-sufficiency ratio is adjusted financial revenue divided by the sum of adjusted financial expenses, adjusted net loan loss provision expenses, and adjusted operating expenses.  It indicates the institution’s ability to operate without ongoing subsidy, including soft loans and grants.  The definition is from _MicroBanking Bulletin_ (2005), p. 57.

10
over 80% of caregivers in either group. Migration reduces barriers in general and financial barriers in particular (table S.9: panel B). The income effect in education is thus strong, in stark contrast with its effect on petty corruption.

As a supporting _ad hoc_ assessment of the mechanism, log remittances received by the household can be used in place of the migration dummy as the endogenous variable (results available on request). In this case, no more significant correlation between the endogenous variable and informal payment is found in the second stage, which may be taken as tentative evidence that variation from the instrument does not affect bribe-paying through the remittance channel. Even though one has to be careful interpreting such evidence because it is no longer a valid IV approach, this may be interpreted as suggesting that, instead of remittances, other aspects of migration are likely to be the source of the bribe-reducing effect. In line with other research, one might hypothesize that the negative coefficient of migration is explained by a lower willingness to bribe officials in the education system. This could be due to former migrants’ own likelihood of bribing teachers or through social remittances (cf. Ivlevs and <u>King 2014, Barsbai et al. forthcoming). Irrespectively of whether it is the migrants themselves or</u> their families who decrease bribe-paying, our finding is promising from a normative point of view. From an economic standpoint, the money not given to teachers as informal “service fees” or “presents” (i.e., for rent-seeking) could be used more productively on other household expenses and would stop distorting incentives for teachers and students. The emerging picture is thus a reduction in bribes and a simultaneous increase in the frequency of parental involvement in children’s education due to migration. In the next section, possible transmission channels will be discussed in more detail.

# VI.  TRANSMISSION CHANNELS AND ROBUSTNESS

According to the community leaders interviewed in the survey, the most widely perceived constraint to school quality is not a scarcity of staff but of other inputs, such as teaching materials or utilities (table S.10). Parental education inputs could be affected by the public funding situation of local schools, causing omitted variable bias.<sup>28</sup> Thus, we match our household data with administrative school-level expenditure data from an open budget initiative of the

> 28. Private educational spending responds to public funding, see for example Houtenville and Conway <u>(2008).</u>

14
# **Multi-Hazard Groundwater Risks to the Drinking Water Supply in Bangladesh: Challenges to Achieving the Sustainable Development Goals**

Mohammad Shamsudduha<sup>2</sup> , George Joseph, Sabrina S. Haque Mahfuzur R. Khan, Anwar Zahid and Kazi Matin U. Ahmed

# **1. Introduction**

Groundwater is the largest store of freshwater that provides drinking, irrigation, and industrial water supplies globally (Taylor et al., 2013). In Bangladesh, approximately 32 km<sup>3</sup> of groundwater is withdrawn annually of which 90% is used for irrigation, and 10% for domestic and industrial purposes combined (Figure 1) that is equivalent to ~4% of global groundwater withdrawal (Hanasaki et al., 2018). However, the sustainability of groundwater resources is threatened by hydrological and socioeconomic factors such as poor water quality, overabstraction, inadequate governance, and impacts of changing climate that are not well understood. Effective management of groundwater resources is critical in meeting national and international agendas for improved public health, economic development, and poverty alleviation (Conti et al., 2016).

About 98% of drinking and 80% of dry-season irrigation water supplies come from groundwater at shallow depths (<150 m below ground level, bgl) (Shamsudduha, 2018). However, widespread arsenic (As) contamination of shallow aquifers affects some 26% of all tubewells across Bangladesh (World Bank 2018), making it the largest mass poisoning of a population in history (Smith et al., 2000). Furthermore, a recent World Bank led study estimates that nearly 40% of all tubewells have dangerous detections of fecal bacteria (World

> 2 Corresponding author; George Joseph, Global Water Practice, The World Bank, gjoseph@worldbank.org, Mohammad Shamsudduha, m.shamsudduha@ucl.ac.uk,  1Institute for Risk and Disaster Reduction, University College London, London WC1E 6BT, UK, , Sabrina S. Haque, sabrina.sharmin.haque@emory.edu, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA, Mahfuzur R. Khan, m.khan@du.ac.bd, Department of Geology, University of Dhaka, Dhaka 1000, Bangladesh,  Anwar Zahid, anwarzahidb@gmail.com, Bangladesh Water Development Board, Green Road, Dhaka 1205, Bangladesh, and Kazi Matin U. Ahmed, <u>kmahmed@du.ac.bd, Department of Geology, University of Dhaka, Dhaka 1000, Bangladesh</u>

This work was made possible by the Swedish International Development Cooperation Agency and benefited from funding from the Government of Japan through the Japan Trust Fund for Scaling Up Nutrition. The findings, interpretations, and conclusions expressed in this paper do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent.

2
the current numbers. Finally, it is important to note that the estimated annual cost is barely 20% of the resources raised through the national Tariff Compensation Fund in the year 2000.

**Figure 9: Simulated distributional incidence of social tariffs for electricity**

_Source:_ OPSM, May 2002

**Table 5: Simulation of social tariffs for electricity**

||**Reality**<br> <br>||**Simulation**<br> <br>||**Transfer**|**Error**<br>**f**|<br>**Error**|**Ctti**|
|---|---|---|---|---|---|---|---|---|
||No.<br>of<br>beneficiarie<br>s|Total value<br>of subsidy|No.<br>of<br>beneficiarie<br>s|Total<br>value<br>of subsidy|**from**<br>**national fund**|**o**<br>**inclusio**<br>**n**|**of**<br>**exclusion**|**oncenrao**<br>**n coefficient**|
|Córdoba|||62,894|5,503,731|3,579,100|0%|84%|-0.80|
|Catamar|||30,362|601,167|6,047,157|45%|0%|-0.23|
|Chaco|||43,209|2,592,540|2,594,925|19%|75%|-0.43|
|Formosa|||31,820|2,688,153|5,643,196|45%|65%|+0.07|
|Entre<br>Rí|||31,762|133,400|3,853,880|32%|83%|-0.42|
|Jujuy|||38,378|1,586,400|2,702,808|22%|66%|-0.43|
|La Rioja|||11,184|1,124,237|3,680,017|60%|51%|-0.16|
|Mendoza|||22,892|1,301,951|2,654,816|77%|97%|-0.03|
|Misiones|||3,618|108,540|3,723,654|47%|97%|-0.42|
|Río<br>N|||1,476|106,272|2,717,131|100%|100%|0.00|
|Salta|||12,909|656,353|2,597,224|0%|90%|-0.80|
|San Juan|||6,038|144,912|2,868,409|100%|100%|0.00|
|San Luis|||22,303|441,599|2,886,601|39%|63%|-0.01|
|Santa Fe|||76,046|1,387,078|1,172,555|74%|93%|+0.12|
|**Total**|||**394,891**|**18,376,338**|**46,721,473**|**39%**|**93%**|**-0.37**|

_Source:_ OPSM, May 2002 25
size. Yet refinements of the von Thflnen hypothesis predict that the width of concentric circles and the strength of the spatial division of labor depends critically on the magnitude of urban demand and thus on town size. Second, the equation fails to account for the possible effect of more distant cities and towns. As Isard (1956) has shown, the organization of economic activity over space reverts around a hierarchy of cities and partially overlapping concentric 'circles' (or rather, hexagons). Recent contributions also emphasize a possible overlap between the effect of multiple cities (Fujita et al. 1999b). A better test of the theory should thus allow for town size and the possible effect of multiple towns. Such a test can be constructed provided we have data on urban population residing at various distances _h_ from household i. Let this information be denoted as _{pi(h)}._ An alternative, more general test of spatial division of labor can then be constructed by estimating equations of the form: The presence of two unknown functions in equation (2.2), the fact that function g(.) is multiplied by population _pi(h),_ and the presence of censoring in the dependent variable make estimation by conventional non-parametric techniques very difficult. To turn the above equation into an estimable regression model, we choose instead to discretize both functions _f (.)_ and g(.): where _£i_ is a dummy variable taking the value 1 if j-1 _< di <_ j, and 0 otherwise. **_pFh_** is the urban population residing within, say, _h_ and _h -_ 1 hours of travel from household i, i.e., **_pih == fh__** _pi(s)ds._ Parameter _H_ is chosen large enough that proxmity effects die out, that 9
|GreTai|Yes|Licensed by<br>the Financial<br>Supervisory<br>Commission|Yes, conducted by<br>the exchange|Exchanges<br>may reject IPO<br>applications<br>associated<br>with punished<br>Advisor for a<br>certain period<br>of time|For at least 6<br>months|
|---|---|---|---|---|---|
|Bovespa Mais|No|—|—|—|—|
|WSE<br>NewConnect|Yes|Yes.<br>Authorized<br>by the WSE|Yes|Yes|At least 3<br>years after<br>the listing<br>date|
|BIST ECM|Yes|Yes.<br>Licensed by<br>the Capital<br>Markets<br>Board and<br>authorized<br>byBIST|Yes|Yes|Throughout<br>the listing<br>life on the<br>SME board|

_Source:_ WBG compilation of exchange information. _Note: — =_ not available.

# **_E. Improving Trading and Liquidity_**

# 1. The Need for Specialized Secondary Market Intermediaries

Larger intermediaries often do not find it economically viable to be active in the SME market. Bulge bracket firms typically do not want to work with companies with less than $50 million market capitalization because they are less financially viable for them as the time and effort going into an SME listing is the same as for that of a large firm, and commissions are typically charged as a percentage of offer size.

As a result, SME exchanges need to encourage a layer of small, specialized intermediaries to support SME equity issues. In some SME markets such as Poland, a group of specialized intermediaries, usually brokers or small investment banks, have arisen to fill this niche. These specialized intermediaries are often less expensive than the bulge bracket firms.

Thus the ability of intermediaries to be profitable from the SME exchange is key because there is little trading and liquidity. Many small-scale intermediaries lack the experience to originate companies. It is often useful to pair them with investment banks that have origination capabilities but that do not have a distribution network to exchange investors. A multibroker system, whereby specialist intermediaries can syndicate capital raising in a more efficient way, can be considered. A final consideration is to look for ways in which the exchange can extend the time whereby specialist intermediaries are with companies as the company and market capitalization grow. Specialized brokers tend to lose SMEs to bulge bracket firms as they grow.

31
attributed to the extensive margin on an annual basis for China’s exports to the US at the 10-digit level from 1993 to 2005. What is striking about this fi gure is the large peak in the growth in the extensive margin around 1996, where there were major reclassi fi cations, and in the following year there is a big fall in variety growth using both measures. This likely re fl ects that some new classi fi cations were used in the middle of 1996 and old classi fi cations were not retired until the following year. Although the size of the reclassi fi cation e ff ect is smaller using the Feenstra index, reclassi fi cations still clearly play an important role in calculations of the extensive margin using both measures.

To measure growth in the extensive margin, it is more insightful to consider changes over a longer horizon since the value of exports in new product codes are generally small when they are fi rst introduced. But if one just compares year to year changes they would no longer be grouped in the new goods category. In order to minimize the reclassi fi cation issues, we report the growth in extensive margin from 1997 to 2005 in Table 3. Using an earlier period as a base yields wide variations in measures, and comparable US and China data give vastly di ff erent results. Panel A of Table 3 shows calculations using China’s 8-digit data. In the fi rst row, where we use data on China’s exports to the world from 1997-2005 in all 8-digit categories, we see moderate net variety growth of 10 percent, with the extensive margin accounting for 26 percent of total export growth. Recalculating the extensive margin with exports only to the United States, in the second row, we see that the magnitudes of the extensive and intensive margins are roughly the same as with total exports. In order to eliminate the potential problem associated with reclassi fi cations that take place from year to year in China’s HS 8-digit data, we also calculate the margins for product codes that existed over the whole period. In this case, we fi nd that the growth in exports to the United States accounted for by new varieties falls markedly, to just 2 percent. This implies that part of the large variety growth found with the full sample is likely a result of reclassi fi cations pushing up the extensive margin. The existing products codes are likely not to be a random sample since entirely new products—such as a digital camera—will by de fi nition require a new code, 12
emulsion in which the insecticide is dissolved.<sup>Different</sup> emulsions may have different effects in deterring<sup>mosquitoes from</sup> even entering the sleeping areas. Work continues<sup>on this problem</sup> and on the development of waterproof emulsions<sup>which can resist</sup> washing.

It should be noted that in both the PHC and<sup>the non-PHC</sup> villages, weekly blood slides were made for<sup>all children with a</sup> temperature of over 37.50. Those rith<sup>parasitaemia were referred</sup> to the Village Health Worker for treatment.<sup>Field workers were</sup> asked to follow up on these children and<sup>to arrange further</sup> treatment outside the village if necessary.

# Theoretical explanation

The results indicate a strong direct effect<sup>of the treated</sup> bed-nets in an area where the use of bed-nets<sup>was well</sup> established before the intervention began.<sup>If such high levels</sup> of compliance can be achieved nationally,<sup>major reductions in</sup> both malaria-specific and overall childhood<sup>morta'lity can be</sup> anticipated. The effects described here are<sup>clearly much larger</sup> than can be anticipated in the national programme<sup>but the trial</sup> has brought to light some new aspects of the<sup>disease. One is the</sup> proportional reduction in the numbers of infected<sup>bites, in mild</sup> and severe cases of malaria as well as<sup>in malaria-related deaths.8</sup> Some mild cases still became savere cases<sup>but the additional</sup> effect of the Maloprim was to reduce the<sup>numbers of severe cases</sup> as well as deaths. The bed-nets and chemo-prophylaxis<sup>therefore</sup> have different effects on the demography of<sup>malaria since</sup> Maloprim is effective on just one part of<sup>the continuum from</sup> infected bite to malaria death whereas the<sup>effects of bed-nets</sup> were seen at every level in this transition.<sup>It seems that the</sup> reduction in malaria mortality is due to<sup>reduction in biting</sup> 8 See BM Greenwood, K Marsh and RW Snow, Why do<sup>some</sup> African children die of severe malaria? Parasitol<sup>Today 17(10):</sup> 277-81.

14
**Table 9. Measuring the Impact of the Organizational Structure of Reserve Management Operations on Investment Policies**

|Independent variable|(1)<br>Number of<br>eligible assets|(2)<br>Number of<br>eligible<br>currencies|(3)<br>Estimated risk<br>of the portfolio|(4)<br>Investment<br>horizon – Total<br>tranched and<br>untranched<br>portfolio<br>(months)|
|---|---|---|---|---|
|Back office, middle office, and front office are in<br>the same department|-0.842|-1.532|-0.243|-15.575*|
||(0.603)|(1.010)|(0.194)|(8.952)|
|Government Effectiveness|0.388|1.019|0.220|17.076**|
||(0.431)|(0.723)|(0.147)|(6.974)|
|Reserves to GDP (%)|4.110**|5.188*|-0.702|-6.832|
||(1.651)|(2.796)|(0.758)|(23.460)|
|Short-term external debt stocks (% of reserves)|0.000|-0.000|-0.000|0.016*|
||(0.000)|(0.000)|(0.000)|(0.009)|
|Current account balance (% of GDP)|0.066|-0.054|-0.006|-0.885|
||(0.041)|(0.069)|(0.013)|(0.581)|
|Number of currency crisis (1971–2017)|0.153<br>(0.232)|0.661*<br>(0.392)|-0.048<br>(0.074)|1.374<br>(3.738)|
|Constant|6.122***<br>(0.719)|6.111***<br>(1.215)|2.012***<br>(0.267)|25.570**<br>(10.165)|
|Observations|83|85|63|48|
|R-squared|0.188|0.120|0.106|0.350|
|Sta<br>***|ndard errors in pare<br>p<0.01, ** p<0.05,|ntheses<br>* p<0.1|||

**_Obligation of the Ministry of Finance to Cover Central Bank Negative Equity._** The distribution of profits and losses within the government is a sensitive issue for central banks. Although central banks commonly share their earnings with ministries of finance, there are questions regarding the source of those profits (i.e., foreign exchange revaluation or changes in market prices) and the timing (i.e., realized versus unrealized). Despite significant variation in their practices, central banks tend to make partial distributions of realized profits. Our regression analysis confirms that the finance ministry's obligation to cover central banks' negative equity influences investment policy. Reserve portfolios in countries where finance ministries must cover negative equity are less diversified in terms of eligible currencies, even when controlling for reserve adequacy and the macro and broader governance environment. On average, central banks operating in countries where the Ministry of Finance had an obligation to cover negative equity held 2.4 to 2.7 fewer eligible currencies across the various regression specifications (see Table 10). It appears that this obligation impacts investment policies narrowly, as we cannot find any robust results for asset diversification or level of risks, nor for the investment horizon.

**Table 10. Measuring the Impact of the Obligation of the Ministry's of Finance to Cover Central Bank Negative Equity on Investment Policies**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Independent variable|Number of|Number of|Estimated risk of|Investment|

17