rafmacalaba/datause-encoder-data huggingface dataset:
36 whether the payment was made in full, or in part, or whether it was to pay for arrears. Nevertheless, a large percentage of grid‐connected households reporting zero expenditures could signal many households not paying fully, if at all, for electricity.

The results, summarized in Figure 11, show that Angola, Botswana, Ethiopia, Malawi, South Africa, Uganda, and Zambia had one‐fifth or more of households connected to the grid reporting zero expenditures on electricity, with Angola (46 percent), Zambia (38 percent), and Botswana (31 percent) leading. By contrast, Nigeria—where bill collection losses have been documented to be very high—significantly under‐reported non‐payment, showing a non‐payment rate of only 4 percent. The survey in Senegal, which asked for expenditures over the last 12 months, found no households connected to the grid not having made payments. The results by quintile are shown in Table A.20 in the annex. Generally, the share of grid‐ connected households reporting zero expenditures declined with quintile, but Ethiopia and Uganda showed the opposite trend, with the top quintile having the highest proportion of grid‐connected households reporting zero expenditures. There are several potential explanations. The rich may be more likely to get jobs with generous benefits, including free electricity. They may be more likely to rent houses with electricity included in the rent. Or they are able to manipulate meters or bribe utility employees to avoid bill payment, in which case they should be targeted for reducing commercial and bill collection losses.

Figure 11: Share of households connected to the grid with zero expenditures on electricity <!-- Start of picture text --> 80<br>Urban Rural Total<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>% of households<br><!-- End of picture text --> _Source_ : World Bank staff calculations using household survey data.

Among the countries with one‐fifth or more of grid‐connected households reporting zero expenditures, only South Africa and Zambia enable further analysis. Of the two, only Zambia isolates electricity for inclusion in rent, whereas South Africa includes water in addition to electricity, making disaggregation of electricity from other items not possible. If every appearance of combined electricity and water bills paid is assumed always to include electricity, and if everyone receiving free electricity is considered to rely only on free electricity, which is unlikely—the percentage of households receiving free electricity increases from 2 percent in the bottom two quintiles to 3 percent in the top three quintiles—the share of households not paying for grid electricity without justification declines from 29, 11, and 24 percent for urban, rural, and national to 2 percent each in South Africa. The reduction is primarily from inclusion of electricity in rent or electricity and water bills being bundled.

In Zambia, the number of grid‐connected households who had zero expenditures on electricity but whose rent included electricity was significant in urban areas. The share of non‐paying households decreases from
# 3.2.1 The voracity effect

Tornell and Lane (1999) develop a model in which a number of fiscal claimants (ministries, provinces, unions, and so forth) attempt to appropriate resources in good times without taking into account the effects of their actions on other claimants (like fishing from a common pool), which they refer to as the “voracity effect.” As the intensity of fiscal competition increases in good times, the rise in government spending could be higher than the windfall. Government spending will thus be procyclical. Further, the more claimants there are (which they interpret as power being more dispersed), the higher the level of government spending in good times (i.e., the more procyclical government spending is).

While the voracity effect is certainly an attractive idea to think about procyclical government spending and captures a key political friction, how to quantify power dispersion for econometric purposes is far from trivial. Specifically, the empirical measure used by Lane (2003) is the Political Constraint Index (POLCON), taken from Henisz (2000) and Henisz and Zelner (undated).<sup>22</sup> This (0,1) index counts the number of veto points in the political system and the distribution of preferences across and within the different branches of government.<sup>23</sup> As Lane (2003) himself discusses, the empirical complications stem from the fact that this index can be interpreted as capturing the voracity effect or actually measuring the opposite effect. On the one hand, we could argue that a larger number of veto power points implies that power is more dispersed and hence should lead to a larger voracity effect (i.e., power dispersion is bad). In such a case, we would expect that the higher is POLCON, the larger is the correlation between the cyclical components of government spending and GDP. On the other hand, Henisz (2000) concludes that POLCON is positively correlated with higher growth because a larger number of veto points enhances property rights, ensures effi cient and predictable bureaucratic procedures, and limits the executive branch’s ability to introduce legal or constitutional changes (i.e., power dispersion, as measured by the number of veto points, is good).

This tension on how to interpret POLCON is clearly reflected in Lane’s (2003)

> 22The POLCON index starts in 1960 for more than half of the countries and 1980-1990 for the rest. It is currently updated up to 2016 for all 86 current countries.

> 23In actuality, the construction of this index is quite complex and the reader is referred to Henisz and Zelner (undated) for details.

13
4 fraction of discretionary consumption; and those that leave a household’s nonmedical consumption (total consumption net of out-of-pocket spending) below a pre-specified multiple of the poverty line. This first definition is close to what has been used to date; the second is new and provides perhaps a stronger justification for a policymaker to be concerned about catastrophic payments. We also offer a simple financial protection index that reflects the percentages of households incurring immiserizing, impoverishing, catastrophic, non-catastrophic, and zero outof-pocket payments. We illustrate our approach using data from the World Health Survey and international poverty lines. We show some broad patterns, and present some more detailed results for the BRICS countries.

# **2. Recap**

We arrive at our unified measure by reworking the classic catastrophic payment measure. Wagstaff and van Doorslaer (hereafter WVD) define out-ofpocket spending as catastrophic when out-of-pocket medical spending, _M_ , exceeds some pre-specified fraction of consumption, _C_ , or _C_ minus some deduction for necessities.<sup>2</sup> This deduction, they suggest, could be a fixed amount (a minimum threshold for nonmedical consumption, call it _NM*_ ), or the household’s actual food spending food, _F_ , or its spending on a broader range of budget items. WVD note that if the fixed deduction approach is used, it is possible that the denominator could be

> 2 WVD relate _M_ to prepayment income in their theory section, but income is notoriously hard to measure in developing countries, and in their empirical illustration – and in the bulk of empirical work in the developing world since – _M_ is related not to income but to consumption.  Consumption is, of course, also closer to welfare than income.
Table 42

|Dependent variable: Fiscal adju|stment wh|en needed|based on E|scolano et|al.(2014)|
|---|---|---|---|---|---|
|Variables|(1)|(2)|(3)|(4)|(5)|
|Rigid expenditure minus|0.026|0.014|0.073**|-0.021|0.047|
|structural as % GDP|(0.022)|(0.024)|(0.030)|(0.034)|(0.046)|
|**Economic factors**||||||
|GDP growth (t-1)|-4.827**|-2.283|-4.534*|-3.709|-4.139*|
||(2.415)|(2.214)|(2.499)|(2.454)|(2.249)|
|Inflation (t-1)|-0.216|0.866|-0.002|0.757|0.056|
||(1.044)|(1.150)|(1.087)|(1.164)|(0.991)|
|U.S. Interest rate|-0.083***|-0.075**|-0.095***|-0.088***|-0.076**|
||(0.032)|(0.029)|(0.031)|(0.032)|(0.031)|
|**Political factors**||||||
|Gini|0.015**|0.009|0.028***|0.012|0.014**|
||(0.007)|(0.006)|(0.008)|(0.007)|(0.007)|
|Rule of law|0.055|0.063|0.060|-0.021|0.067|
||(0.051)|(0.044)|(0.051)|(0.069)|(0.049)|
|Margin of Majority|0.577|0.302|0.563|0.408|0.864|
||(0.362)|(0.320)|(0.358)|(0.369)|(0.699)|
|**Interactions**||||||
|EMEs||0.126||||
|||(0.305)||||
|EMEs * Deviation||-0.027<br>(0.019)||||
|Gini * Deviation|||-0.001|||
||||(0.001)|||
|Rule of law * Deviation||||0.009*<br>(0.005)||
|Majority * Deviation|||||-0.043|
||||||(0.054)|
|lambda|0.453*|0.170|0.402|0.303|0.377|
||(0.271)|(0.240)|(0.279)|(0.279)|(0.254)|
|Constant|-1.556*|-0.677|-1.900***|-0.725|-1.612|
||(0.802)|(0.836)|(0.717)|(0.910)|(0.975)|
|Observations|162|162|162|162|162|
|R-squared|0.113|0.150|0.149|0.128|0.110|
|CountryFE<br>Standard errors in parentheses<br>*** p<0.01, ** p<0.05, * p<0.1|No|No|No|No|No|

- 71 -
**Minimum capital requirements (in % of average yields)**

||Averag<br>|e operating pr<br>|ofit margin (in<br>|% of average<br>|yields)<br>|
|---|---|---|---|---|---|
||5%|10%|15%|20%|25%|
|Cocoa|58.2%|54.7%|49.4%|46.2%|41.4%|
|Banana|19.7%|13.1%|4.3%|2.9%|1.4%|
|Source: Authors.||||||

The amount of capital required to ensure the viability of the business in the long run may be high and it increases with the exposure of the crop yield to extreme events. The concept of _catastrophic risk adjusted (CRA) crop yield_ is introduced to examine the impact of catastrophic events on the crop business profitability. It is defined as a crop yield adjusted for catastrophic events where, following an actuarial approach, catastrophes are defined as infrequent events, e.g., occurring once in twenty years or more. Therefore, the downside risk caused by catastrophic events is removed with an hypothetical put option priced at its fair value. The minimum capital requirements are estimated from the operating losses adjusted for the catastrophic risk. Obviously, they are lower than those non-adjusted for catastrophic risk because the catastrophic events have been removed. The value added created by the catastrophic coverage increases with the degree of exposure of the crop to extreme events. This is illustrated in Box 2.

# **Box 2. Catastrophic risk adjusted crop yields and minimum capital requirements**

Detrended data on cocoa yields and banana yields from 1961 to 2002 in a South American country are used for the purposes of illustration. A catastrophic event is defined here as an event occurring on average once in 20 years or less frequently. Given the simulated cumulative distribution function of the crop yields, this catastrophic event occurs when the national cocoa yield falls below 70 kg/ha (strike). This event has occurred twice since 1961 (1983 and 1987). The actuarially fair price of this hypothetical coverage (i.e., put option with a strike at 70 kg/ha) is estimated at 0.72% of the average yield.

# **Crop yields and catastrophic risk adjusted crop yields (one in 20 year event), national cocoa yield**

<!-- Start of picture text --> 350<br>300<br>250<br>200 yield<br>CRA yield<br>150<br>trigger<br>100<br>50<br>0<br>year<br>196119631965196719691971197319751977197919811983198519871989199119931995199719992001<br>kg/ha<br><!-- End of picture text --> 7
A third class of placebo test corroborates the confounding due to non-parallel nonlinear trends. If spurious trends explain the NQ results, then any variable that is elevated in the 1980s and 1990s relative to the 1970s and 2000s would correlate spuriously with the outcome variable in the regular food aid recipient group, even when keeping NQ’s instrument as a control. The placebo test is whether we can replicate NQ’s findings using an obviously spurious instrument that follows the same inverted U pattern over the sample period, even while controlling for their instrument, just so as to ensure that the spurious instrument is not serving as a coarse proxy for the true causal mechanism represented by the instrument. Rejection of the null hypothesis that the spurious instrument has no effect indicates failure of this placebo test. As detailed in Appendix 3, instrumenting for food aid deliveries using a time series of global audio cassette tape sales, a clearly spurious instrument chosen for its inverse-U time series over this period, rather than US wheat production, generates remarkably similar IV results to NQ’s. When we include NQ’s instrument as a control the point estimate is effectively zero while the coefficient estimate on the spurious IV term in the second stage is statistically insignificantly different from NQ’s original point estimate and significantly different from zero. This test corroborates the hypothesis that their original estimates are picking up long-run trends rather than the inter-annual variation that underpins their hypothesized causal mechanism.

# **III. Monte Carlo Evidence**

The preceding set of placebo tests call into question the causal interpretation NQ give their IV estimates. To show that it is possible to replicate the NQ estimates without the need to interpret their findings causally, we go one step further and show that their results are in fact entirely consistent with a data generating process in which either (i) food aid is statistically independent of conflict in recipient 19
diversification for the resource rich, and more for the resource poor. Fourth, most of the overall export growth of the selected ECA countries was explained by growth along the intensive margin: selling more of the same products to the same markets; although the share of growth explained by the extensive margin (diversification) declines with economic size. Extinction rates of export flows are also negatively associated with economic size.

The remainder of this paper is structured in four sections. In the second section, we explore export diversification along the product dimension. We first introduce a method to classify economies as resource-rich and non-resource rich. Then, we examine the link between resource abundance and the extent of diversification along the product dimension. We look at the diversification performance of ECA countries in comparison with that of other countries with similar characteristics in terms of resource abundance, level of development and size. We examine the differential impact that the commodity boom that took place during the second half of last decade had on the diversification performance of resource-rich and resource-poor countries in the region. The third section focuses on diversification along the market dimension, exploring the links between resource abundance and the commodity price boom, and it presents country-specific indicators of diversification. In the fourth section we explore export performance, including the role of diversification in export growth and the evolution of market shares in the main export products and markets. The fifth section concludes.

Figure 1: Oil and Gas Prices over the last 20 years. Figure 2: Annual Export Growth ECA Region <!-- Start of picture text --> 120.00 10.00<br>50%<br>Crude oil, average 9.00<br>100.00 8.00 40%<br>Natural gas, US<br>80.00 7.00 30%<br>6.00<br>20%<br>60.00 5.00<br>4.00 10%<br>40.00<br>3.00<br>0%<br>2.00<br>20.00<br>-10%<br>1.00<br>0.00 0.00 -20%<br>-30%<br>-40%<br>Source: Comtrade from WITS.<br>Crude Oil (Average, $/bbl) Natural Gas (US, $/mmbtu) 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011<br>1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010<br><!-- End of picture text --> Source: Prospect Group, World Bank.

# **2. Export Diversification along the Product Dimension: Resource Abundance and the Commodity Boom**

In this section we proceed as follows: first, we classify countries into resource rich or abundant and resource poor; second, we place the diversification performance of ECA countries in perspective from a cross-country point of view, using a model that links diversification with resource abundance, level of development and size; and third, we examine whether the commodity boom taking place in the second half of the last decade impacted the diversification performance of resource-rich and resource-poor countries in the ECA region differently. Finally, we present country-specific descriptive statistics on export diversification along the product dimension.

3
preceding the survey states that the births were wanted then, 7 percent were wanted later, and only 5 percent were unwanted. Marriage is almost universal for women in Nigeria: 90 percent are currently married, 3 percent are divorced or separated, 3 percent are widowed; and remarriage is not uncommon. About 34 percent of women have a polygynous husband, 10 percent are the head of the household, and 90 percent of women live with their husband.

**Birth spacing** Medical research has shown that short birth intervals are associated with poor child and maternal health outcomes (Setty-Venugopal and Upadhyay, 2002).<sup>10</sup> With respect to maternal health, relative to women who give birth at 9- to 14-month intervals, those who have their children at 27- to 32-month birth intervals are: 1.3 times more likely to avoid anemia; 1.7 times more likely to avoid third-trimester bleeding; and 2.5 times more likely to survive childbirth (Conde-Agudelo, and Belizan, 2000).<sup>11</sup> Several studies also find that short birth intervals and reduced breastfeeding time have deleterious effects on child health and mortality (Palloni and Millman, 1986; Palloni, Pinto Aguirre, and Lastiri, 1994; and Jayachandran, and Kuziemko, 2011). Palloni and Millman (1986) observe that close birth spacing does not allow a woman to regain her physical strength and the nutrients required to have a successful new pregnancy. The effects go through retardation of fetal growth as well as the mother’s inability to properly breastfeed the child, all leading to increased risk of death of the child. Moreover, competition for resources among siblings born in close succession may aggravate these negative effects.<sup>12</sup>

In the 2008 NDHS, of all births reported by each woman, 8 percent are less than 15 months apart, and 33 percent less than two years. The mean birth interval is 32.6 months, and the median is 27. The survival status of the child who opens the birth interval matters: the median interval is 29 months if the previous child is alive, 24 months if dead.

Given the association between birth spacing and child and maternal health outcomes, it is important to understand whether the desire for sons affects the pace at which mothers try to conceive and give birth.

> 10Birth spacing refers to the time interval (number of months) between births.

> 11See Conde-Agudelo et al. (2007) for a review of medical studies on the relationship between birth spacing and maternal health.

> 12There is a striking negative relationship between the length of the birth interval and child mortality. For example, 252 children (out of 1000 live births) die under the age of 5 if the preceding birth interval is shorter than 24 months, while the number of children who die if the interval is 4 years or longer is reduced to 92 (NPC and ICF Macro, 2009).

10
different areas: “the technical nature of the common task,” the Hirschmans ventured to hope, “helps in making both [ethnic groups] ‘forget’ about the other’s skin.”<sup>39</sup> If properly reorganized, the Ugandan electric project would yield strong social benefits.

At the opposite side of the spectrum of projects with institution-building potential, one might consider highways. As a matter of fact, highway construction always left ample margins for improvisation, sloppiness, cutting corners, and sacrificing quality for quantity without any specific drive toward the implementation of more structured and effective institutions.<sup>40</sup> Moreover, no natural or technical constraint limited road constructions, thereby making them an activity particularly prone to political pressures and the disrupting effects of political struggle on national cohesiveness. This characteristic was shared by thermoelectric power as opposed to hydro. While hydroelectric power generation is limited by the actual availability of natural resources, a thermoelectric plant can be built virtually anywhere. Investments in thermoelectric plants therefore appeared to be much less protected from political pressures. In Hirschman's terminology, this was an opposition between “foot loose” (roads and thermoelectric power generation) and “resource tied” public utilities.<sup>41</sup> If we consider projects from the point of view of institution-building, irrigation would produce the maximum effect, highways the minimum, and railroads and electric power would fall somewhere in between.<sup>42</sup> Highways were nonetheless an interesting case study for the links between social phenomena and economic development. Often, Hirschman argued, road maintenance is prompted by a combination of physical deterioration and public protest: there is no doubt that the truck drivers refusing to pay road tolls because of the roads' poor condition will negatively affect the financial resources needed to repair the roads, but, at the same time, their actions signal that the roads have reached an unacceptable level of deterioration, and this will probably induce a reaction (i.e., road maintenance).<sup>43</sup> In his _The Strategy of Economic Development_ (1958), Hirschman had discussed at length the fact that in less developed countries, often the resource that was actually lacking was not capital or any other physical asset, but rather the ability to make decisions; he urged to introduce “inducement mechanisms” that function as substitutes for this missing ability. The circular mechanism of (i) road use, (ii) lack of

> 39 “Uganda,” no date, Albert O. Hirschman Papers, Box 57, Folder 2. 40 Sarah Hirschman, “Latin America,” April 19, 1965, Albert O. Hirschman Papers, Box 57, Folder 2. 41 Sarah Hirscman, “Nigeria,”,August 18, 1965, Albert O. Hirschman Papers, Box 57, Folder 2.

> 42 “Ideas – Miscellaneous,” no date, Albert O. Hirschman Papers, Box 57, Folder 2.

> 43

> Sarah Hirschman, “Latin America,” April 19, 1965, Albert O. Hirschman Papers, Box 57, Folder 2.

19