rafmacalaba/datause-encoder-data huggingface dataset:
ZIMBABWE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE from 34 percent in 1999 to 37 percent in 2005, conceals a major contraction in the use of stand posts, from 10 to 5 percent over the same period. In fact, 0.8 percent of the population per year lost access to standposts and around 0.3 percent of the population each year has been gaining access to wells and boreholes, a lower-quality form of water supply (figure 8a).

**Figure 8. While access to improved water supply has kept pace with population growth, sanitation levels lag (annualized growth)**

<!-- Start of picture text --> Population gaining access per year, 1999–05<br>a. Water b. Sanitation<br>2<br>2<br>1.4<br>1.4<br>1<br>1<br>0.2<br>0.2<br>0<br>0<br>National Urban Rural<br>National Urban Rural<br>-0.5<br>-0.5<br>-1<br>-1<br>-2<br>-2<br>Piped Water Standposts Flush Toilets Improved Latrines<br>Wells/Boreholes Surface Water Traditional Latrines Open Defecation<br>Annualized Growth Annualized Growth<br>Population gaining access per year (%)<br>Population gaining access per year (%)<br><!-- End of picture text --> _Source:_ WHO 2010, from the 1999 and 2005 Demographic and Health Surveys.

Access to improved water is highly inequitable, with the poorest quintiles of the population not connected to piped water. Access to improved water in urban areas—where most of the better-off population lives—is 99 percent versus 67 percent in poorer rural areas (figure 9a), according to the 2005 Demographic and Health Survey (DHS). The main driver of the inequity is that piped-water service is more affordable in the more densely populated urban areas than it is in rural areas. The limited reach of piped water into rural areas makes the population largely reliant on springs and wells. Matters are made worse by the fact that more than two-thirds of these groundwater sources are unprotected, raising waterquality risks.

Zimbabwe‘s sanitation sector has deteriorated over time, causing an increase in reliance on open defecation and a sharp decline in access to improved latrines. Reliance on open defecation increased from 27 to 29 percent between 1999 and 2005 (table 7), implying that, on average, 0.5 percent of the population was losing access to other forms of sanitation each year. Strikingly, access to flush toilets remained relatively steady, while access to improved latrines dropped from 25 to 14 percent between 1999 and 2005, exposing more people to unsafe sanitation options.

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Table 7 presents our main results on the relationship between withholding tax rates and firm‐specific variables. More specifically, we test whether withholding tax rates drive the variation in profitability and leverage across MNEs with different ownership structures, documented above.

_Table 7: Impact of withholding on firm level variables_

|Random effects estimation|||||
|---|---|---|---|---|
|Dependent variable|Return on|assets|Leverage|ratio|
|Explanatory variables|(1)|(2)|(3)|(4)|
|Withholding tax|0.05***|0.04*|‐0.15***|‐0.19**|
||(0.02)|(0.02)|(0.08)|(0.08)|
|Log(tangible assets)|0.37 ***|0.39***|‐1.50***|‐1.50***|
||(0.07)|(0.07)|(0.17)|(0.17)|
|Log(employees)|0.07|0.07|0.68***|0.68***|
||(0.08)|(0.08)|(0.21)|(0.21)|
|Size of group|‐0.00***|‐0.00***|0.01*|0.01*|
||(0.00)|(0.00)|(0.00)|(0.00)|
|Country‐specific effects|‐|Yes|‐|Yes|
|Observations|40064|40064|40254|40254|
|Adj. R2|0.01|0.01|0.02|0.02|

The first column shows that withholding tax rates help explain reported profitability. Controlling for industry and year fixed effects, the amount of reported tangible assets, the number of employees, and MNEs’ group‐size, we find that a one percentage point increase in withholding taxation increases reported profitability by 5 percentage points. The impact is statistically significant at the 1% level. When additionally controlling for the presence of an affiliate in one of the most important partner countries (Cyprus, UK, Germany, Netherlands, Russia, Austria, Poland, Luxembourg), using a set of dummy variables, the estimated impact decreases only slightly in magnitude and remains significant at the 10% level, as shown in column 2. The observed effect thus also seems to be relevant outside the main partner countries.

In columns 3 and 4, we examine whether the observed correlation between withholding tax rates and firm profitability is driven by a change in leverage ratios. In line with our expectations, we find that higher withholding taxation decreases the leverage ratio significantly. More specifically, we find that a one percentage point increase in withholding taxation decreases the debt share by 19%.

28
10 these two models. These risk mis-pricing indicators measure capital market integration; with no arbitrage, the price of risk should be equalized across national borders. Greater mis-pricing may reflect poor information about firms, high transactions costs, and official barriers to international asset trading. We refer to greater mis-pricing as indicating less stock market development. The APT and ICAPM mis-pricing indicators give similar country rankings. Brazil, Turkey, Mexico have relatively large mis-pricing values, while the United States, Japan. Jordan, and Pakistan yield mis-pricing estimates that suggest a high level of international integration.

CAPM measures domestic market risk mis-pricing. Korajczyk (1994) fits a domesticCAPM model to compute the degree of risk mis-pricing across stocks within the country. This indicator measures the efficiency of domestic risk pricing compared with a benchmark portfolio of domestic stocks. One shortcoming with this measure is that as a country becomes more integrated internationally, the relevant benchmark portfolio shifts away from being a benchmark of domestic assets. The relevant benchmark becomes more "internationalized." Thus, domestic risk mis-pricing as measured by CAPM may rise even as the stock market becomes more integrated and efficient. We include this measure for completeness but focus on the results using the international benchmark portfolios.

These three mis-pricing indicators rely on the success of equilibrium models of asset pricing that investigators sometimes rejected as good representations of the pricing of risk. However, these measures allow us to incorporate indicators, albeit imperfect indicators, of the ability of agents to diversify risk domestically and internationally. Furthermore, we analyze the evolution of the degree of integration between each domestic market and the world market over time.
_46_ _Ing countries had when growth was hlgh In the Industrial countries. I thlnk_ **_It Is_** _rather dlsappolntlng that their actual growth rate was only 4.2 percent given that world trade growth over this period must have been signlficantly higher._

**_Exchange rates of developing countries..._**

_Now I wonder_ **_if_** _this does not have something to do with the fact that, durlng this period, developlng countries' exchange rates generally were extremely overvalued and became increasingly so, which essentially distorted the relative price structure in these countries._ _MR._ **_BiANETH:_** _We have just completed a research project looking at oil-Importing developing countrles' exchange races from 1960 to 1984 in real terms [Adrian Wood, "Global Trends In Real Exchange Ratos, 1960 to 1984",_ **_World_** _Bank Discussion Papers, 35, 1988], which shows that with only a few exceptions they were on a devaluing trend, in real terms, relative to those of industrial countries. And that_ **_Is_** _until 1985 when the dollar [began to fall.]_ _MR. LARSEN: I agree that they were on a devaluing trend, but I believe that they may still have been overvalued._ _In other words, if the exchange rate problem is being corrected, I think that there_ **_is_** _a significant potential for the developing countries' trade to expand but It doesn't follow necessarily that there is significant scope for expanding their shares of world markets as much as Japan expanded_ **_its_** _share of the world market previously or as the Asian ;JIEs are expanding_ **_their_** _share now._ _In order for them to be able to do that, it is necessary that investment be stepped up again. On my recollection,_ **_IMF_** _figures show that the investment ratio in the developing countries fell very sharply in the first half of the 1980s compared to the previous period._ _What kind of policies are needed to increase the investment ratio again in order to allow these countries to exploit their potential and to build up an export potential?_ _I think that is at least as important a question as the question of the pull from the industrial countries._ _MR. LIPSCHITZ: Andrea Boltho has raised the point of whether we can get internally-generate_ **_d_** _emand growth in the LDCs? And I think Steve Marris raised the point of whether we can get internally-generated demand growth in Europe, given its current structure._ WP/COLTHO/SF:19
24

# **Table II. The Seven Most Frequent Targets of Intervention, 1960–96**

|Target|Interventions|
|---|---|
|Zaire|33|
|Iraq|22|
|Egypt|22|
|Pakistan|19|
|Chad|18|
|Israel|17|
|Thailand|17|

Computed from data in Pickering (1999).

We have defined five sub-types of democratic interventions: democratic interventions involving the US, interventions involving the UN, interventions occurring after the end of the Cold War, and two variables denoting whether the interventions were in support of a democratic or an autocratic regime.

There are two timing issues to consider: First, interventions may be initiated as a result of institutional change. To avoid this potential endogeneity problem, we lag the intervention variables by one year. Second, the initiation of an intervention may not lead to an immediate democratization. Even so, institutional changes that occur within a limited time-frame following the intervention may be attributed to the intervention. To allow for different post-intervention dynamics, we coded three different pairs of intervention variables: _Recent democratic intervention_ and _Recent autocratic intervention_ are used to study political change that occurs within five years of the termination of an intervention. For each country-year we coded _Recent democratic intervention_ as 1 if a democratic intervention had been initiated (or was still on-going) from one to five years earlier. A zero value on this variable includes cases where the country has never been the target of a democratic intervention as well as cases where the intervention ended more than five years ago. The Recent autocratic intervention variable was coded in parallel fashion.

The two variables _Lagged democratic/autocratic intervention_ are more restrictively coded. Country-years are scored 1 on these variables only if the intervention occurred in the previous year. For the third and most restrictive pair of variables, _Lagged democratic intervention onset_ and _Lagged autocratic intervention onset,_ country-years are scored 1 only when the _onset_ of an intervention occurred in the previous year.
the coverage in the Central ar.d Eastern region3 was es high as in the Western region around Banjul. The mortality figures have to be interpreted in the context of this high immunization coverage, sincea some common causes of childhood mortality in West Africa, such as measles and tetanus, are almost absent from the cause of death data from Farafenni.

A second interesting feature of the mortality data by age is the high rates for the age group 1-4 relative to the infant mortality rates. It was once thought that one explanation for the high later childhood mortality in West Atrica might be measles but this is clearly not the case since measles mortality has been drastically reduced by tht. immunization programme. Another factor must be responsible for the high ratio of the of mortality of 1-4 year-olds to the mortality of infants. These dramatic reductions in mortality of the 1-4 age group were not matched in the non-PHC villages for the same period. Some fall in infant mortality was recorded in tha PHC villages. This seems surprising but there is good evidence that more infant deaths than previously thought are related to malaria in this area. In addition, there appear to have been some complex interactions between malaria and other illness which complicate the identification of the effect of the bed-net intervention.

Table 3: National immunization coverage rates estimated from the annual EPI coverage surveys (percentages)

|Antigen[|<br>1985|1986|J1987|1989|1990|
|---|---|---|---|---|---|
|BCG|92|97|90|98|98|
|DPT (3)|68|72|77|83|87|
|Polio (3)|62|69|83|89|92|
|Measles|75|80|82|81|85|
|Yellow fever|70|73|81|87|85|
|Fully<br>immuniz -d|52|',|61|70|78|

9
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and financial losses for more than 16,000 sudden-onset (such as floods, storms, earthquakes) and slow-onset (drought) events from 1900 to present. Primary data are compiled for various purposes, such as informing relief and reconstruction requirements internationally or nationally, and data are generally collected from various sources and, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. The other database is the proprietary Munich Re NatCat Service database, which mainly serves to inform insurance and reinsurance pricing. This database contains fewer entries focusing on the about 300 largest events since 1950, yet data exhibit a higher reliability as often crosschecked with other information. We focus on the monetary losses (direct impacts or risk) listed in constant 2000 USD terms. In both datasets, loss data follow no uniform definition and are collected for different purposes such as assessing donor needs for relief and reconstruction, assessing potential impacts on economic aggregates and defining insurance losses. We distinguish between sudden and slow onset events. Key sudden-onset events are extreme geotectonic events (earthquakes, volcanic eruptions, slow mass movements) and extreme weather events such as tropical cyclones, floods and winter storms. Slow-onset natural disasters are either of a periodically recurrent or permanent nature; these are droughts and desertification.

We broadly associate the loss data with asset losses, i.e. damages to produced capital. This is a simplification, as indirect impacts, such as business interruption, may also be factored into the data. Yet, generally, at least for the sudden onset events, analysts generally equate the data with asset losses, and an indication that this assumption can be maintained is the fact that loss data are usually relatively quickly available after a catastrophe, which indicates that flow impacts emanating over months to years are usually not considered. Losses are compared to estimates of capital stock from Sanderson and Striessnig (2009), which estimated stocks using the perpetual inventory method based on Penn World table information on investments starting in 1900 and assuming annual growth and depreciation of 4 percent.

15
are federated into a block- level federation (KVK), and SHGs in a cluster of villages form a cluster-level federation called a Cluster Development Association (CDA).

_Sanghamitra Mandala Mahila Samakhya (SMMS)_ : SMMS is located in the Hindupur mandal of Anantpur district in Andhra Pradesh. In contrast to the nested structure in KVK, SMMS has the more common three-tiered structure observed in federated organizations. The mandal federation is a federation of Village Organizations (VOs), and Village organizations are federations of SHGs. Anantpur is among the least developed regions in Andhra Pradesh. SHGs in the area were promoted in the area 1996, and the federation was started in1998. Society for Elimination of Rural Poverty (SERP) supports SMMS.

_Sri Viswabharthi Association of Women Thrift Cooperatives (SVAWTC)_ : SVAWTC, formed in 1991, is a federation of thrift cooperatives in Warangal District of Andhra Pradesh. The thrift cooperatives are village-level organizations and are hence larger than SHGs. The federation is one of the oldest women thrift cooperatives promoted by Cooperative Development Foundation (CDF).

In all the cases except SVAWTC, membership is restricted to the poor, who are identified by Participatory Rural Appraisal techniques.<sup>8</sup> Though the membership of SVAWTC is not exclusively poor, the majority of members are poor. A CDF study on the member profile of SVAWTC in 1997 found 44% of members to be landless and 22% to hold less than 2 acres (CDF 1997). Land ownership is a good proxy for wealth in rural areas. The small size of the required general savings and the system of loan eligibility being a proportion of general savings (rather than total savings that may include other deposits), also make the cooperative unattractive to the rich. The thrift amount in most cooperatives is low enough (Rs.20 per month) for the poorest member to be able to save. Annex 2 gives a more detailed description of the structure and systems in the federations studied. Annex 4 gives the profiles of the promoter agencies of the federations studied.

> 8 Participatory Rural Appraisal techniques are tools used to collect reliable information regarding a village, street, etc. by a process of consultation with area residents, often in a group.  PRA tools require less time and cost compared with conventional survey methods.

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11

**FIGURE 4**

<!-- Start of picture text --> Third Scenario of Bond Rates<br>(pessimistic view of inflation trends)<br>50<br>45<br>40-<br>35-<br>30-i<br>25-,<br>!20<br>1 5D<br>~ 51 .<br>0'<br><!-- End of picture text --> <!-- Start of picture text --> D Scenario A Scenario C<br><!-- End of picture text --> <!-- Start of picture text --> Evolution of Subsidies<br>according to Alternative Rate Scenarios<br>100<br>90- R Scn oCocus7 1Bllo oit<br>lo would be required in 1991.<br>780-125 additiona. nominal subsidies are<br>E' 60- | ,required to compensate for the increasing<br>=O. 50- i l _ inflation in Scenario C.<br>40-<br>20-1#l=<br>1989 2017<br>subsidies (Scen. A) addit. subs. (Sc.C)<br><!-- End of picture text -->
23 was poor and that wealthy people who were<sup>not connected had their own sources of</sup> water.

_Table 2. Sensitivity Analysis_ (Annualized net present value in millions of 1994 US dollars as percentage<sup>of 1994 sales)</sup>

|Welfare/<br>1994 Sales|GOV.|INVES|TORS|WORKERS|CONSUMERS|TOTAL<br>DOMESTIC<br>|TOTAL<br>WELFARE|
|---|---|---|---|---|---|---|---|
|||FOREIGN|DOMESTIC|||WELFARE||
|Base|0.88%|21.53%|18 .57%|2.11%|17.65%|39.21%|60.74%|
|Random Rationing<br>Elasticity of 5%<br>more<br>Elasticity of 5%<br>less|0.88%<br>0.88%<br>0.87%|21.53%<br>21.53%<br>21.53%|18.57%<br>18.57%<br>18.57%|2.11%<br>2.11%<br>2.11%|31.53%<br>16.73%<br>19.02%|53.09%<br>38.29%<br>40.58%|74.62%<br>59.82%<br>62.11%|
|Price Increase<br>40%|2.10%|21.92%|18.91%|2.15%|17.04%|40.19%/|62.11%|
|25% Foreign<br>Ownership<br>75% Foreign<br>Ownership<br>Equal Cost of Int.<br>Inputs|0.88%<br>0.88%<br>-1.99%|10.55%<br>31.66%<br>20.64%|29.55%<br>8.44%<br>17.81%|2.11%<br>2.11%<br>2.02%|17.65%<br>17.65%<br>17.65%|50.19%<br>29.08%<br>35.50%|60.74%<br>60.74%<br>56.14%|

As table 2 shows, changing assumptions about the<sup>initial price increase and</sup> elasticities change the consumer surplus only slightly.<sup>Changing assumptions about the</sup> ownership of the company has large effects only on<sup>the distribution of gains between</sup> foreign and domestic owners of the private operating<sup>company. Not surprisingly, if the</sup> private operator is not more efficient in using intermediate<sup>inputs that the publicly</sup> operated SEDAPAL, then welfare will decrease, although<sup>the magnitude is not large</sup> because our base assumption was conservative.

_iv. Welfare Effects ofActual Reforms._ Using the<sup>same methodology, we estimated</sup> the welfare gains from the reforms that actually occurred<sup>compared to no reform at all.</sup> Since the quality of the data for 1990-1991 was<sup>poor because of hyperinflation, we relied</sup> largely on data from 1987 to 1989 to predict the behavior<sup>of SEDAPAL without reform</sup>
|Bottom 50% income<br>share|26.44%|26.45%|26.83%|
|---|---|---|---|
|Middle<br>40%<br>income<br>share|44.33%|44.32%|44.12%|
|Top10%income share|29.23%|29.23%|29.06%|

_Source: Own simulations based on administrative tax data._ _*Sample includes wage earners and those who move out of formal employment (assumed to move to other employment opportunities in the formal or informal sector with close to zero earnings). This represents the lower bound of inequality reduction._ _**Sample restricted to wage earners, assuming all dismissed workers move to unemployment or inactivity._ _Note: The Gini coefficient and Theil Index are measured over labor income and do not include non-labor income sources._ _Scenario 2: Convergence to Living Wage Estimate_

**Aligning the statutory minimum wage with a living wage estimate is expected to result in a substantial short-term increase in average wages. However, it may also lead to notable job losses, particularly affecting low-wage workers and the younger demographic.** Table 7 illustrates the results. The increase directly influences a significant portion of full-time employees, accounting for 16.41%. Among those directly affected, formal employment reduction is projected to be significant, around 7.72% in the short run and 11.22% in the long run, with the most significant job losses occurring among the youngest workers. Among all formal sector employees, the minimum wage hike is also expected to result in moderate job losses, affecting 1.44% of full-time employees in the short run and 2.09% in the long run.

**While aligning the statutory minimum wage with a living wage estimate offers sizable short-term benefits for a specific group, it poses potential long-term adverse effects on employment, particularly for other demographics.** When assessing earnings, there are winners and losers among potentially affected employees. Those retaining employment expect significant earnings gains due to higher wages (13.19%). However, these gains may be offset to some extent by the earnings decline in the group facing job losses, resulting in an average net labor income increase in the short term (4.45%). In the long run, the net gains diminish (0.49%), indicating positive but substantially reduced labor income increases due to more significant disemployment effects. The youth demographic continues to benefit more from the increased wages in the short term. Still, their net gains are minimal, especially over the long term, owing to significant job losses.

38