rafmacalaba/datause-encoder-data huggingface dataset:
upstream large dams. However, the negative impact of large local dams is again somewhat larger than that for the sample using only pure cropland cells. As before, these differences are not statistically significant.

Finally, one should note that underlying the identification of the IV strategy is the assumption that agricultural production would not have varied in response to the policy changes considered as a function of land suitability in the absence of irrigation dam construction. An insightful placebo test in this regard would be to conduct a similar analysis using all nonirrigation dams in South Africa. More specifically, we employ the same IV strategy as above using nonirrigation dams from the DWA database. There were 90 large and 772 small nonirrigation dams in the data, the main functions of which differed widely, ranging from water and industrial supply to recreational use. The coefficients on the nonirrigation dams are reported in the last column of table 5. As shown, reassuringly, none of these is statistically significant. Hence, these findings provide at least secondary support for the validity of our identifying assumption.

# _River Flow Dependence_

Arguably, the storage of water in dams will be reduced during drought years, resulting in limited release and hence ability of dams to provide irrigation benefits. To this end, Duflo and Pande (2007) and Strobl and Strobl (2011) identify drought events by considering local precipitation. These authors find that the estimated impacts depend on these events.

Of course, the river flow local to the dam actually determines the amount of water stored, and, as argued earlier, this depends on the complete hydrological cycle rather than only 37
CAMEROON’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 15. Annual gain in access each year to various modes of water supply and sanitation, 1998–2006**

<!-- Start of picture text --> a. Water b. Sanitation<br>6<br>6<br>5<br>5<br>4 4.0 4 4.0<br>3<br>3<br>2.3<br>2 2.3<br>2<br>1 1<br>0.5 0.5<br>0 0<br>-1 National Urban Rural -1 National Urban Rural<br>-2 -2<br>-3 -3<br>-4 -4<br>-5 -5<br>Flush Toilets Improved Latrines<br>Piped Water Standposts<br>Wells/Boreholes Surface Water Traditional Latrines Open Defecation<br>Annualized Growth Annualized Growth<br>Population gaining access per year (%) Population gaining access per year (%)<br><!-- End of picture text --> Source: WHO 2010a and 2010b, from the 1998 Demographic and Health Survey and 2006 Multiple Indicators Cluster Survey.

Cameroon has made significant institutional reforms affecting urban water supply. By the end of the 1990s the operational and financial performance of the national urban water utility, SNEC,<sup>8</sup> had become problematic (World Bank 2007a). Facing unreliable services, commercial and industrial users started to develop their own alternatives. In October 2005, the government created a public holding company (CAMWATER<sup>9</sup> ) to plan sector development and investments (such as construction, rehabilitation, and management of potable water infrastructures). In addition, the government signed a 10-year _affermage_ contract with CDE<sup>10</sup> commencing in May 2008 for the production, transport, and distribution of water in 106 urban and peri-urban centers (figure 16).

> 8 Société Nationale des Eaux du Cameroun.

> 9 Cameroon Water Utilities Corporation.

> 10 Camerounaise des Eaux.

27
**_Mixing national accounts and surveys._** Next we test sensitivity to using instead the geometric mean of the survey mean and its expected value given NAS consumption; as noted in section 4, this can be given a Bayesian interpretation. Table 11 gives the estimates implied by the geometric mean; in all other respects we follow the benchmark methodology. The expected value was formed by a separate regression at each reference year; a very good fit was obtained using a log-log specification (adding squared and cubed values of tke log of NAS consumption per capita did little or nothing to increase the adjusted R<sup>2</sup> ).

In the aggregate for most years, and most regions, the level of poverty is lower using the mixed method than the survey-means only method. In the aggregate the 2005 poverty rate is 18.6% (1017 million people) using the geometric mean versus 25.2% (1374 million) using unadjusted survey means. Nonetheless, the mixed method still gives a higher poverty rate for 2005 than implied by the 1993 PPPs. Using the $2.00 line, the 2005 poverty rate falls from 47.0% to 41.0%.

Figure 6 compares the aggregate headcount indices for $1.25 a day between the benchmark and mixed method. The trend rate of poverty reduction is almost identical between the two, at about 1% point per year. (Using the mixed method, the OLS trend is -0.98% points per year, with a standard error of 0.04%, versus -0.99% with a standard error of 0.06% using only the survey means.) The linear projection to 2015 implies a poverty rate of 9.95% (s.e.=1.02%), less than one third of its 1990 value.

The mixed method gives a higher poverty rate for LAC and MENA and makes negligible difference for SSA. Other regions see a lower poverty rate. The $1.25 a day poverty rate for East Asia in 2005 falls from 17% to 12%. The largest change is for South Asia, where by 2005 the poverty rate for India falls to about 20% using the mixed method versus 42% using the unadjusted survey means; the proportionate gap was considerable lower in 1981 (42% using the mixed method versus 60% using the survey mean alone).

India accounts for a large share of the discrepancies between the levels of poverty between the benchmark and the mixed method, reflecting both the country’s population weight and the large gap that has emerged in recent times between the NSS and NAS consumption aggregates for India (Ravallion, 2003). Figure 6 also gives the complete series for $1.25 a day excluding India; it can be seen that the gap between the two methods narrows over time. If we focus on the poverty rates for the developing world excluding India then the difference between 31
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# Table 15: Pakistan: Demand for Real Money Balances. 1973-1992

|Variable|**LnA**<br>Lny||r|_Ln_(Bp )-|
|---|---|---|---|
|Coefficient value|-0.376<br>0.256|-0.011|0.757|
|t-mtio|C-Oil)<br>(1.70)|**(-3.34)**|(6.06)|
||D.W.=**2A1,**AdjustedIt=|0.98||

Using these results and expression (3), the relationship between seignorage and inflation is shown in Graph 8. The graph suggests that in Pakistan the demand for real balances is pretty sensitive to inflation. Seignorage grows noticeably with inflation reaching a maximum of about 3.2% of GDP at an inflation rate of 20%, and then falls as higher inflation cuts into the base of the inflation tax and reduces revenue despite the higher tax rate. During the past two decades, Pakistan mobilized some 2% of CGDP p.a. on average as inflation tax, running an average inflation rate at below 10% p.a. While there is some scope to mobilize higher revenues from inflation tax, the price will need to be an acceleration of inflation in the 15-20% range with adverse consequences for other economic variables. But most importantly, even if the Government were to accelerate inflation to the 15-20% range, on average it would mobilize only an additional 1.2% of GDP from seigcorage. So, with positive real interest rates, the end result of the large fiscal deficits will be a continuously rising debt to GDP ratio which cannot be sustined in the long runt<sup>2</sup> .

# Sustinable Current Account and Fiscal Deficits-Implications **for** the 1990s

29. We now have all the elements of the analytical framework to pull together the various threads and draw the mplications for sustainable current account and fiscal deficits for Pakistan in the 1990s. Let us first examine what constitutes sustainable current **account** deficits.

30. Sustinable current account deficits: Estinating sustairable current account deficits involves determining Paldstan's room for additional external borrowing. This is turn involves two considerations: solvency and creditworhiness. It can be shown that solvency requires that = **Note also dcat the relationship between seignorage and inflation is not a static one. Pakistan seems to be an oudier** in terms **of its ability to generate higher than average revenue from seignorage than other countries at comparable inflation raes.** For **example, Easterly and Schmidt-Hebbel (1993) show that over nearly 20 years across 51 countries,** three **quarers of anumal observations of inflation tax revenues were less than 2% of GDP. One important reason for the higher seignorage revenue yield in Pakistan is the high rate of economic growth. Another reason is the large ratio of base money, particularly currency, to GDP resulting frin the low financial depdt of the Pakistni economy. So, with greater financial deepening, the ability to raise seignorage revenue is likely to fal even with similar GDP growth rate and inflation.**
again, but from 1999 on has eventually decreased.<sup>31</sup> All in all, Figure 8 obviously suggests that TFP growth in Guatemala was closely associated with political events.

## **7.4 Comparison of Results with International Evidence**

How do these estimates compare to other Latin American countries? The Appendix summarizes the results of a study that applies a comparable methodology. Loayza et al. (2002) focus on the growth performance of 20 Latin American and Caribbean countries. Similar to the approach used here, they adjust for changes in the quality of labor associated with increased educational attainment.<sup>32</sup> Consistent with international evidence, Loayza et al. find that during the 1990s the recovery in output growth for the ‘best’ performers in the Latin American region was driven by increases in their rates of TFP growth, and less so by factor accumulation.

However, in most Central American countries TFP growth was only moderate. In some cases it was even negative. While TFP growth in Guatemala appears to be on the high side compared to its Central American neighbors, it is worth recalling that the estimate presented in the Appendix does not take into account quality changes of the physical capital stock. Given the decay of Guatemala’s quality-adjusted capital stock, TFP growth is likely to be overstated. In addition, a one-to-one comparison is hampered by the nature of the different data sources.<sup>33</sup> Overall, Guatemala’s growth experience shows some similarities with its neighbors, in particular with Costa Rica and El Salvador. During the 1990s these countries have experienced much faster growth than during the 1980s. In particular, quality-adjusted labor — associated with increased educational attainment — was the main source of growth.

# **8. Conclusion**

Human capital has a highly significant and positive impact on long-run growth in Guatemala. The importance of human capital is substantial. An increase by 1 percentage point of average years of schooling would raise output by about 0.33 percent. The effect is of similar magnitude to that in micro studies. A disaggregated analysis by level of education reveals that primary schooling is most important for productivity growth, followed by secondary schooling. Over the past decades, it appears that general education and basic technical skills have been the main

> 31 This finding is in agreement with other recent growth accounting studies for Guatemala, which are presented in Box 3.

> 32 Roldós (1997) examines the growth experience for Chile, and adjusts for changes in the quality of labor _and_ capital. These results are in the Appendix.

> 33 For example, Loayza et al. (2002) rely on the Barro and Lee (2001) data set on educational attainment.

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4 capita incomes of less than 80 US cents per day (Appendix Table A2). And since much of their cotton production is exported, they compete directly in international markets with highly subsidized exports from the United States.

Cotton usage, on the other hand, is distributed across countries roughly in proportion to their volumes of textile production.<sup>1</sup> Because of high domestic usage by exporters of textiles and clothing in developing Asian countries (and Mexico because of its preferential access to the US and Canadian markets under NAFTA), even relatively large cotton producers such as China, Pakistan and India (see column 1 of Table 1) export only a small fraction of their crop, in contrast to Sub-Saharan Africa where textile production is relatively minor. This explains the pattern of net exports of cotton and textiles across regions (columns 2 and 3 of Table 1), an understanding of which is helpful in explaining the signs of the welfare effects of the technology and policy shocks considered below.

# **3. The GTAP model and database**

The standard Global Trade Analysis Project (GTAP) model of the global economy is used to provide insights into the likely effects of reforming cotton subsidy and trade policies globally and of governments allowing GM cotton technology adoption in some countries without and then with cotton trade and subsidy policy reform globally. The GTAP model (see Hertel (1997) for comprehensive documentation) is a neo-classical multi-regional, static, applied general equilibrium model that assumes perfect

> 1 That usage pattern has been distorted considerably by import tariffs on textiles and clothing, even after the removal by end-2004 of quotas restricting exports of those products from developing countries: compare the columns in Appendix Table A4 with and without protection as of 2005.
encompassing factors such as R&D spending, foreign technology imports, and capital-intensity—has been negative for female employment.

Timely flow of information and raising awareness could encourage women to work. In villages outside Delhi, India, for example, providing information to women and recruiting them for employment in business processing increased their employment in that sector and their wage employment in general. The intervention also increased women’s likelihood of expressing interest in working throughout their lives, even after marriage and child birth (Jensen, 2012).

Investing in education and skills development for women could increase female employment. Mehrotra and Parida (2017) postulate that women are not able to compete for jobs in the manufacturing sector, where demand for skilled labor is increasing, as they have lower education levels.

Male migration could also affect female employment, earnings, and empowerment, as observed in Nepal and India. Shrestha (2017) finds that large-scale male emigration increased female wages in Nepal indirectly through reduction of male labor supply. Increased male emigration between 2001 and 2011 increased average women’s wages by 14 percent, agricultural wages by 15 percent, and casual wages by 12 percent. On the other hand, Loshkin and Glinskaya (2009) find that male household members’ migration reduced women’s labor force participation in Nepal by 5.3 percentage points. In terms of empowerment, Desai and Banerji (2008) concluded that husbands’ absence did not imply less influence on wives’ decisions as men who migrate tend to leave their wives and children in the care of male relatives. Phadera (2016) also found that male emigration in Nepal either increases women's workload, potentially overburdening them, or forces them to realign their priorities and fill home production and family farm roles vacated by the men. Overall, male migration increases both household and community responsibilities for women.

Many South Asian countries are either experiencing conflict or are in post-conflict situations, calling for special focus on how conflict affects women’s workforce participation. Conflict can either cause women to seek employment or discourage them from working: that is, women may enter the labor force to augment household income—the “added-worker “effect—or they may withdraw from the labor force because of the unsafe environment. Whether the added-worker or the security effect dominates is unclear based on the literature. Kuhnt and Pasha (2017) found that conflict imparts a short-lived negative impact on women’s employment in Pakistan based on temporary fear created by violence. Berrebi and Ostwald (2014), using a global panel dataset of 165 countries and terrorism data from 1980 to 2007, found that terrorist attacks decreased female labor force participation. In contrast, Menon and Rodgers (2011) found evidence of increased likelihood of women’s employment associated with civil conflict in Nepal.

# 2. **Data and Methodological Challenges**

6
Supervisor Demonstrating Placement of Clay Plate Respondent Takes 2 of 6 Mirt Stove Parts Home Source: Randall Bluffstone Source: Randall Bluffstone In the home or separate kitchen the SUM devices were initiated and set to record the temperature of the stove every ten minutes. This was done four times over the course of a year beginning in June 2013 and ending in July 2014. The four monitoring periods are June-August, 2013; August-October, 2013; March-May 2013 and May-July 2014. During each monitoring period a SUM device recorded data for between 37 and 56 days. The median recording period was 49 days.

The traditional technology in most of Ethiopia is the three-stone tripod fire. It is not technologically possible to reliably monitor this type of stove using the SUMs. The use of the traditional stove was therefore not monitored and we must imperfectly infer the degree to which the Mirt stove is exclusively used and cannot say much about possible rebound effects in which efficiency gains are eroded by increased cooking.

Two features of the Mirt stove likely mitigate large rebound effects. <mark>First, the Mirt stove is highly specialized for</mark> _<mark>injera</mark>_ <mark>baking, which makes it very unlikely that it will be shifted to other uses (a potential rebound effect). As will be discussed below, we find that the Mirt stove is on average used 2-3 times per week, which is a very traditional and typical interval for</mark> _<mark>injera</mark>_ <mark>baking. It is also almost exactly the mean reported baking interval reported in G</mark> ebreegziabher (2015). <mark>It is therefore very likely that on average most if not all</mark> _<mark>injera</mark>_ <mark>baking is done on the Mirt stove and therefore captured by our monitoring.</mark> <mark>Second, the Mirt stove has the capacity to do cooking with waste gases before they are vented and over 80% say they use the second burner for cooking stews and coffee. This feature offers additional efficiencies that likely reduce the need to cook on two stoves simultaneously. In sum, while we cannot rule out major rebound effects, there is little reason to expect they would be large.</mark>

# _3.3 Treatments_

The participating households received the stoves under 6 randomized treatments. There were three aspects to each treatment, with only two levels of each aspect (present or absent) divided equally so one-third of all sites received each treatment aspect. These aspects are: 1) payment for stove use; 2) cost of the stove and 3) networking.

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each Leone 1.00 of additional value added in agriculture generates Leone 0.29 of nonagricultural value added. But the linkages emanating from increased export crop production are weaker than in Nigeria--Leone 0.42 of value added in nonagriculture for each Leone 1.00 of additional value added in agriculture.

These results are generally consistent with the size of our regional multipliers. This would seem to suggest that any positive spillover effects arising beyond a region's boundaries are largely offset by negative spillover effects.

There are no directly comparable studies for Asia, but modeling studies of India (Rangarajan, 1982) and South Korea (Adelman, 1984) suggest stronger linkage effects from agricultural growth on the national economy than in Sub-Saharan Africa.

# VIII. CONCLUSIONS

# A. ImDlications for Polic=

Several themes have recurred throughout this review. Together, they point in clear directions for policy makers and practitioners interested in balanced rural growth and in maximizing the rural nonfarm spinoffs of agricultural progress.

e Agricultural growth will be essential in launching successive rounds of growth in rural areas. Consumption linkages appear particularly important. Raising fcrm labor productivity is therefore important, not only because it permits the release of labor from agriculture to nonagricultural pursuits, but because it boosts per capita income to levels that enable consumer diversification from food into nonfood items.

* Government policies affect not only the magnitude of agricultural growth but also the ability of rural nonfarm enterprises to respond to the increased demand. Investment codes and related legislation which have
care givers in 2013 may have been joined by their husbands and others absorbed into the households of relatives by 2018. The other notable change over time is in the distribution of male PA households across family types. Most male PA households are in couples with children (66 and 72 percent in 2013 and 2018 respectively). However, the share of single male PAs falls from one in six male PA households in 2013 to one in 14 in 2018 (17 to 7 percent). In contrast among female principal applicants single women account for one in five principal applicants in both 2013 and 2018.

**Table 2.** Household composition by head

||**20**<br>|**13-14 Wav**<br>|**e**<br>|**20**<br>|**17-18 Wa**<br>|**ve**<br>|
|---|---|---|---|---|---|---|
|Variable|Male<br>PA|Female<br>PA|All<br>PAs|Male<br>PA|Female<br>PA|All<br>PAs|
|Household size|4.2|3.6|4.0|4.7|3.5|4.2|
|Children (%)|52.6|59.2|54.2|52.7|53.1|52.9|
|Boys (%)|27.3|30.5|28.1|26.9|27.1|27.0|
|Girls (%)|25.3|28.8|26.1|25.8|26.0|25.9|
|Adults (%)|47.4|40.8|45.8|47.3|46.9|47.1|
|Men (%)|26.6|7.8|22.0|25.7|12.8|21.6|
|Women (%)|20.8|33.0|23.8|21.6|34.0|25.6|
|Dependency ratios|||||||
|Children|1.09|1.76|1.28|1.19|1.43|128.|
|Children and elderly|1.12|1.82|1.31|1.23|1.53|1.34|
|Children, elderly &|||||||
|disabled|1.14|1.84|1.34|1.27|1.58|1.38|

_Source_ : Own calculations based on ProGress and JD-HV database. _Note_ : PA = principal applicant. PA is determined at the time of registration. Dependency ratios are defined as the proportion of the groups in the rows to adults.

On average, family size has remained the same over time for female PAs but has increased slightly – by about 0.6 to 4.7 – in male PA households. In other words, about half of male-PA households have an additional family member in 2017-18. Households with a female PA have fewer male adults than households with male PAs in both waves. In the average household of four people, in male PA households’ adult males account for one of the household members, in contrast most female PA households have no male adults. In 2013 only 8 percent of female PA households had a male adult member, increasing to 13 percent in 2018. This reflects that the path to female headship is often separation or widowhood, which are common after displacement.

13