rafmacalaba/datause-encoder-data huggingface dataset:
ZIMBABWE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 23. Consumption of infrastructure services in Zimbabwe is highly differentiated by budget**

a. Mode of water supply, by income quintile b. Prevalence of connection to power grid among Mozambican population, by income quintile <!-- Start of picture text --> 120% 120%<br>100% 100%<br>80% 80%<br>60%<br>60%<br>40%<br>40%<br>20%<br>20%<br>0%<br>0%<br>Q1 Q2 Q3 Q4 Q5<br>Q1 Q2 Q3 Q4 Q5<br>Piped water Stand posts<br>Power<br>Wells/boreholes Surface water<br>% population<br>% population<br><!-- End of picture text --> _Source_ : Banerjee and others 2009.

_Note_ : Q1—first budget quintile, Q2—second budget quintile, and so on.

ZESA‘s distributional losses of 11 percent are not that far from the best-practice 10 percent benchmark for power, but they still result in $10 million in losses. Losses are more pronounced in the water sector, where nonrevenue water accounts for as much as 46.3 percent of total water production. This costs Zimbabwe about $27 million a year, equivalent to 0.61 percent of GDP. Zimbabwe could avoid this cost by increasing the bill collection efficiency and reducing losses for water and power services. Across both the power and water sectors, the burden of utility inefficiencies in Zimbabwe is considerably higher than for the benchmark countries (figure 24).

**Figure 24. Zimbabwe’s power and water utilities: The burden of inefficiency**

a. Uncollected bills and unaccounted losses in the power sector, as a percentage of GDP b. Uncollected bills and unaccounted losses in the water sector, as a percentage of GDP <!-- Start of picture text --> 7.000<br>6.000<br>5.000<br>4.000<br>3.000<br>2.000<br>1.000<br>0.000<br>Zimbabwe LIC-fragile<br>Collection inefficiencies Unaccounted losses<br>Percenatage of GDP<br><!-- End of picture text --> <!-- Start of picture text -->
1.20<br>1.00<br>0.80<br>0.60<br>0.40<br>0.20<br>0.00<br>Zimbabwe LIC-fragile<br>Collection inefficiencies Unaccounted losses<br>Percenatage of GDP<br><!-- End of picture text -->

_Source_ : Derived from Briceño-Garmendia, Smits, and Foster (2009). _Note:_ GDP = gross domestic product; LIC = low-income countries.

48
used poverty metrics that take into account the intensity and severity of poverty. The FGT estimates the weighted sum of the poverty gap ratios of a group of observations under an arbitrary poverty line, and includes a parameter � that measures the sensitivity of the income distribution within those observations. Based on the final market income aggregate defined in (1) and (4), the poverty rate can be defined as: where _N_ is equal to the total number of individuals in the economy. _z_ is an scalar-valued poverty line. ��� is the final market income of individual _i._ �� is an indicator value taking the value of one if ��� �� and zero otherwise. � is a parameter reflecting the weight placed in the severity of poverty.

In particular, when ��0, this index becomes the poverty headcount ratio. This metric represents the number of households under the poverty line but fails to capture the extent to which each household income falls below the poverty line. When, ��1 this index becomes the income-gap ratio for the mean poor income. This ratio measures the total shortfall of the poor households with respect to the poverty line. However, the income-gap ratio is not sensitive to the distribution of income among the poor. When ��2, the FGT Index becomes the squared income-gap ratio. This index computes the severity of poverty more accurately, since it represents the squared income-gap ratio for the mean poor income. In this form, the index incorporates information on both poverty and income inequality among the poor households. Higher order classes of poverty indices can be derived as � becomes larger. Finally, as �→∞ the FGT family of poverty measures tends to a Rawlsian social welfare function, i.e. the index depends only on the welfare of the poorest household in the population.

_Shared Prosperity_ 19
COST RECOVERY, EQUITY, AND EFFICIENCY IN WATER TARIFFS IN AFRICA declines at the average consumption of 10 m<sup>3</sup> , then rises again (figure 11). The price at the survival consumption of 4 m<sup>3</sup> is roughly comparable to the price at 20 m<sup>3</sup> of consumption.

**Figure 11. Average water tariffs for Africa at different consumption levels**

<!-- Start of picture text --> 0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>4 m3 10 m3 15 m3 20 m3 30 m3 40 m3 50m3<br>Consumption per month<br>Average Average w/o ELECTRA Median Median w/o ELECTRA<br>USD/m3<br><!-- End of picture text --> _Note: ELECTRA is an outlier with high effective tariffs. Source:_ AICD WSS Survey Database, 2007.

It is important to further discuss the merits of IBT in fulfilling its premise, as the majority of utilities in Africa use this type of tariff structure. First, the implementation of the IBT structure is based on the implicit assumption that small consumers are poor and large consumers will cross-subsidize the small ones. This assumed relationship between poverty and consumption is very important in evaluating the subsidy incidence of the IBT. Second, households in the higher-income bracket usually consume more water. Therefore, they are expected to pay more for the additional consumption. Third, a sufficiently high price in the last blocks discourages wasteful water use and enables households to conserve water. Fourth, charging low tariffs for small consumers brings a larger proportion of the population into the fold of network coverage, and therefore creates public health externalities generated by superior quality water (Whittington and Boland, 2003).

The IBT assumptions rest on the fact that all consumers are metered, so it is possible to exactly estimate their water consumption and bill them for it (Whittington and Boland, 2003). In Africa, though water metering is relatively high, it is still low in a few cities, such as those in Nigeria and DRC. Another problem is that housing is shared among many households in Africa, making it difficult to exactly estimate how much each household is consuming—though households devise ways of dividing the water bill based on household size, number of rooms, and so on. But since so many households are consuming a relatively large quantity of water, which falls in a higher block, the bill is consequently higher. The IBT structure, therefore, has an unintended consequence for poor households consuming piped water (Whittington, 1992). For these reasons, the use of IBT in meeting the goals of efficiency and equity has been questioned in recent years.

The two-part tariff structure, implemented in many utilities in Africa, can fail to favor small consumers because of two reasons. First, the fixed-fee and minimum consumption charges place an enormous burden on low-volume consumers. This is the part of the water bill they cannot control 19
regressions we control for asset composition and find that the effect of governance on performance is not driven by this source of heterogeneity. We use fixed capital (i.e. property plant and equipment) to total sales ratio, denoted K/S, as a measure of the relative importance of fixed capital in the firm's output." Another source of endogeneity could arise because of differences in unobserved growth opportunities. Firms with good growth opportunities will need to expand and raise external financing and may therefore find it optimal to improve their governance mechanisms as better governance and better minority shareholder protection will likely to lower their cost of cost of capital.'<sup>2</sup> If Tobin's-Q is higher for firms with good growth opportunities, this could also be a cause of endogeneity of governance in the performance regressions and result in positive spurious correlations with governance. Unfortunately there is no good measure of the growth opportunities besides Tobin's-Q. As an arguably imperfect measure, we use average real growth rate in sales for the last 3 years, denoted SalesGR, as a proxy for future growth (and growth opportunities).<sup>13</sup> Finally, we also explore the effects of differences in firm size on governance. The effect of size is ambiguous as large firms may have greater agency problems (because it is harder to monitor them or because of the "free cash flows" argument of Jensen (1986)) and therefore need stricter governance mechanisms to compensate. Alternatively, small firrms good governance mechanisms to compensate for their bad legal system. However, if the enforcement of contracts is weak, the firm will not be able to do that as is the fact that the legal system does matter.

> " Himmelberg et al. (1999) also use research and development intensity (R&D) and advertising expenses as additional measures of the "intangibility" of the assets. Unfortunately, the Worldscope database does not provide variables with advertising expenses and the R&D data is unavailable for most firms in our sample. **2** See La Porta et. al. (1999a), Lombardo and Pagano (2000) and Himmelberg, Hubbard and Love (2001) among others on the relationship between investor protection and the cost of capital.

'3 Past growth rates will be correlated with future growth if there are investment adjustment costs, "time to build" (i.e. it takes several periods to make new investment fully operational), or if the shocks to productivity are serially correlated.

12
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III. **THE EVOLUTION OF INFLATION DURING 1993-1997** As a result of the wide-ranging price liberalization of August 1992, the inflation rate reached its historical peak of 236 percent at the end of that year. Following the introduction of the stabilization program in the second part of 1993, however, the rate of inflation has declined steadily. Indeed, inflation declined noticeably between 1993 and 1995 as a result of tight financial polices and stable (even appreciating) exchange rates along with strong economic growth.

Table 2 shown below, depicts some of the key variables which are expected to influence the inflationary process in Albania.

**Table 2. Key Variables Influencing Inflation (in %)**

||Inflation<br>(e.o.p.)|Budget<br>Deficit'|Exchange<br>Rate Depr.b|MB<br>Growth|M2 Growth|M3 Growth|RER Depr.'|Real GDP<br>Growth|
|---|---|---|---|---|---|---|---|---|
|1993|30.9|<br>9.3|-1.0|<br>-|83.0|75.0|-23.7|<br>9.6|
|1994|15.8|<br>7.1|-3.0|<br>37.1|<br>41.0|40.5|-14.0|<br>8.3|
|1995|6.0|7.2|-0.8|<br>28.1|<br>_50.0_|52.0|-3.4|<br>13.3|
|1996|17.4|<br>10.2|<br>8.4|14.0|<br>42.3|44.0|-5.4|<br>9.1|
|**1997d**|31.6|<br>-|37.1|<br>38.4|<br>40.4|33.8|3.7|-|

Source: Ministry of Finance, Bank of Albania, and the IMF's Intemnational Financial Statistics.

Notes: (a) Domestically financed deficit as a % of GDP. As of September 1997, the budget deficit was 40 % higher than the corresponding period of 1996. (b) Year-on-year depreciation against USD and minus sign indicates appreciation. (c) The real exchange rate defined as the ratio of the exchange rate against the USD times the US Whole Sale Price Index (WPI) to Albanian CPI, and minus sign indicates real appreciation. (d) Figures for 1997 are as of September and represent percentage changes from September 1996 to September 1997.

A careful look at Table 2 reveals the unique combination of strong economic growth and low inflation that the country enjoyed during 1994 and 1995; interestingly, strong growth and low inflation took place in the presence of high monetary growth and high fiscal deficits. This phenomenon can be attributed to three factors. First, vigorous economic growth can, to a large extent, be explained by the convergence hypothesis, 7
urban households than rural households, as the latter benefit from the corresponding increase in income (Fallon & Lucas, 2002).

Banking crises typically raise government debt due to the direct costs of financial sector bail outs (e.g. as in the case of Ireland in 2009). At the same time, banking crises reduce tax revenues through a fall in real economic activity. Increases in government debt and a tightening of the current fiscal budget may lead to a reduction in the provision of public services, such as health, education or transport, impacting on households which rely on those services. Evidence from financial crises in the 1990s shows that public expenditure on health and education in the East Asian economies (Indonesia, Korea, Malaysia, Thailand) fell in absolute terms. In Mexico, expenditure on health fell by 16 percent and expenditure on education fell by 10% between 1994 and 1996 as a result of the Tequilla crisis. A tightening of government budget constraints may also reduce public spending on social safety nets leading to lower coverage or reduced benefits at a time when reduced employment puts stronger pressure on these safety nets. The experience of emerging economies in the 1990s shows that the response of social safety net expenditures to financial crises may vary substantially. While Mexico cut social spending significantly in response to the Tequilla crisis, Indonesia and Korea increased spending on social security programs during the East Asian crisis.

# **2.4 The Impact of Crises on Household Income, Consumption, Health and Education**

What do we know about the impact of banking crises on households, especially in emerging economies? In this section we briefly review the evidence on how households were hit by the crises in Latin America, East Asia and Russia during the 1990’s. We hereby focus on changes in household income, consumption, health and education.

McKenzie (2006) uses repeated cross-sectional household data from the period 1992-1998 to examine the impact of the **1994 crisis in Mexico** (Tequilla crisis or Peso crisis) on household income and consumption patterns. His study shows that average real household income fell by 23% between 1994 and 1996, coupled with a relative price increase for staple food items. The rural poor seem to have been much less affected by the crisis than the richer, urban population. On average households cut back much more in durable consumption goods (-27%) than on basic food expenditures (-9%), so that the share of income spent on food, and in particular staple goods rose during the crisis. The share of income spent on health services was reduced during the crisis, especially among the poor. By contrast, spending on education increased during the crisis for all income groups. McKenzie (2006) suggests that the reallocation of spending from durable goods and health to basic food items was at 10
# 1. Introduction

Using a synthetic panel methodology, this paper analyzes the evolution of Moroccan NEETs, an acronym for young people (between 15 and 29, or 15 and 24, depending on the definition) who are Not in Employment, Education or Training.

Appearing for the first time in the mid-1990s, the acronym was formulated to capture the social situation of a growing category of the population: youth who do not build human capital in the traditional way through work, education or training. Part of the reason the term was formulated is that development experts began to recognize that the conventional metrics and predictors of success— such as employment, academic education, and/or vocational training—no longer sufficiently captured the multidimensional nature of the challenges faced by many young people during their schooling years or during their transition from school to the labor market, nor the resulting long-term fragility that marks their lives.

According to the most recent national census (RGPH, 2014), there are about 6 million Moroccans between the ages of 15 and 24. Morocco is currently in a development window that demographers call a “demographic bonus”. This means that the proportion of working-age people in the total population is high, compared to the share of the population who are either younger or older than the productive age bracket (15–64 years old).

HCP-WB (2017) estimates that Morocco’s demographic bonus will end in 2040 when the progressive aging of the population, combined with increased life expectancy, begins to raise the share of the population aged 65 and above. With such a high proportion of people in the productive age range, and a low proportion of dependents, a demographic bonus therefore presents a country—for a limited number of decades—with a one-time opportunity for accelerated economic growth.

The current age distribution of Morocco’s population represents such an opportunity, but it also presents the major challenge of harnessing that human capital and putting it to the best use (HCPWB, 2017). Until now, the Moroccan labor market has not been able to absorb all of its new entrants in an optimal way. Calculations based on subsequent rounds of the Moroccan Labor Force Survey (see data section) indicate that of some 390,000 new entrants in the national workforce every year, barely a third manage to find employment in the formal or informal sector.

2
any subject at the WTO, exemplifies the centrality of subsidies in fisheries reform efforts (WTO, 2022).

Despite the near consensus on the connection between fuel subsidies and fisheries depletion, there is no causal evidence of the effect of fuel subsidies on fishing. The absence of empirical evidence reflects the fact that subsidy reforms are typically implemented at the country level, leading to a lack of credible quasi-experimental variation in subsidy levels across producers operating in the same setting. Understanding the effect of subsidies on individual producers’ actions is a key input for designing optimal subsidy reform because producers’ actions can result in both a private channel deadweight loss (caused by a difference between the private marginal cost and the buyer’s willingness to pay) and an external channel loss (caused by externalities in stock dynamics).

In this paper, we compile new vessel-level panel data on the Chinese distant water fishing fleet to estimate the effects of subsidies on production decisions. We leverage vessel-level variation in fuel subsidies that was induced by China’s 2016 fuel subsidy reform. The reform created 25 separate thresholds at which fuel subsidies discontinuously increase. These thresholds depend entirely on predetermined vessel characteristics, which cannot be manipulated to obtain higher subsidy payments. We measure fishing behavior using real-time data from Global Fishing Watch (GFW).

Many features of our data and research design make it a compelling setting to study the impact of input subsidies. First, the fishing effort data from GFW are derived from Automatic Identification Systems (AIS) transponder signals. This means we observe fishing effort in real time at the vessel-level and that our main outcome variable is not subject to misreporting.<sup>1</sup> Second, we leverage vessel-specific quasi-experimental variation in subsidy levels, alleviating concerns about reverse causality (e.g., subsidies being increased when the industry experiences a negative shock) and other sources of omitted variables bias (e.g., subsidizing less-profitable producers). Third, the reform we analyze was in effect for six years, which allows us to interpret the derived elasticities as long-term elasticities. Long-run elasticities are the benchmark necessary to measure the economic and ecological costs of

> 1Vessels have no incentive to manipulate their AIS activities in response to the subsidy program because the regulator does not use AIS data to calculate fuel subsidies.

3
The global financial crisis, well under way by the third quarter of 2008, did not originate in the developing world. It sparked immediate concerns, however, that its effects would be felt widely, particularly in those economies in which a substantial share of the workforce was engaged in export-oriented activities. China met the onset of the crisis with a strong fiscal stimulus program, coupled with active labor market policies, aimed both at providing training to laid-off migrant workers and at supporting the medium- and small-scale enterprises that were more exposed to shocks from the crisis. This paper reviews evidence on the incidence of shocks related to the financial crisis in China, documents employment effects, and presents evidence of the recovery in 2009.

# **1. Analyzing the Effects of the Crisis**

The lack of publicly available and nationally representative firm, labor force, and household surveys complicates an analysis of the precise effects of the financial crisis on China. Incidental surveys—such as a firm survey carried out by the People’s Bank of China, a rural household survey conducted by China Center for Agricultural Policy (CCAP) at the Chinese Academy of Sciences, and the China Urban Labor Survey (CULS) conducted by the Chinese Academy of Social Sciences—may nonetheless be used in conjunction with information from national surveys and published research to tease out the employment effects of the crisis and recovery. This paper reviews critically the evidence from these sources, with an eye toward highlighting data and measurement issues, while documenting a consistent narrative of crisis and recovery in China.

According to evidence from multiple sources, migrant workers were exposed more than other workers to the financial crisis. Given that migrant workers typically lack the formal employment contracts enjoyed by urban workers, they were easier for firms to dismiss, providing flexibility to employers who needed to reduce costs in the face of crisis-related shocks. As migrants also typically lack the benefits that urban workers have, they were in a much more precarious position with little access to formal safety nets protecting them against unemployment. The recognition of 2