rafmacalaba/data-use-mentions-extended huggingface dataset:
||**India**|**Pakistan**|**International**<br>**Benchmark**|
|---|---|---|---|
|**Generation Planning**|57%|29%|56%|
|**Transmission Planning**|75%|25%|72%|
|**Procurement of Generation**|95%|100%|85%|
|**Transmission Procurement**|83%|100%|64%|

Source: Note: Scores based on index developed for the Rethinking Power Sector Reform Project. For more details go to project website at http://www.esmap.org/rethinking_power_sector_reform On procurement for both generation and transmission Pakistan gets the maximum score but this conceals a different reality. Despite allowing for international competitive bidding Pakistan has struggled to attract investment in generation—there is still a large deficit in generation (about 4GW in 2017). The China-Pakistan Economic Corridor is now bringing large generation capacity (according to their website 14 projects worth over $18 billion and with 11.1 GW capacity are at various stages of development/construction) but none of these have been awarded through international competitive bids or auctions—all have been awarded through direct negotiations between the Government of Pakistan and the Chinese Government/Project company. Thus, while the country allows for good practices in procurement these are hardly followed in practice.

# **_3.2 Access and affordability_**

Access and affordability are key variables when considering the benefits of the electricity system to the poorer members of society. Governments in developing countries often find it difficult to increase access while keeping electricity affordable. First, the households most eager to be connected have the highest incomes and may well live in the same area making it easier on a per household basis to supply this group who tend to purchase larger amounts of electricity. Second, the costs of
estimates of effects from these studies to discuss the relative importance of these age windows. We also discuss which period of exposure has more consistent evidence of persistent effects. For this, we rely on the five studies that examine the effect of early life shocks on adult height.

There is fairly consistent evidence that shocks experienced in the first and second year of life affect child nutrition status and that this effect is persistent (see table 6 for a summary of the evidence). The evidence is less convincing for exposure in the child’s third year of life. For the effect of exposure to a shock in the first year of life, 17 of the 26 estimates gathered from the studies (or 65 percent) are statistically significant. Besides, shocks that hit in these periods of life appear to have persistent effects as illustrated by four of the six estimates of the effect on adult height. Of the 14 estimates gathered from the studies of the effect of exposure to a shock in the second year of life, 11 (79 percent) are statistically significant. In contrast, evidence is relatively weak for the effect of exposure to a shock in the third year of life. None of the four estimates on child HAZ and only one of the five estimates on adult height is statistically significant.

The evidence on the effect of exposure to a shock while in utero is not as compelling as for the first two years after birth, particularly in terms of persistent effects. Overall, 10 of the 19 estimates gathered from the studies for exposure to a shock while in utero suggest adverse effects. None of the five estimates of the effects on adult height is statistically significant while all four estimates

> 7 Measurement error in consumption data could be behind this.

14
countries. An origin-destination matrix of all flights in a week in East Africa shows that Uganda, after Tanzania, has the highest number of flights per week from Kenya and Ethiopia (figure 13). Uganda also benefits from frequent services provided by other international carriers such as Emirates.

**Figure 12. Evolution of seats and city pairs in Uganda (2001-2009)**

<!-- Start of picture text --> a. Seats b. City pairs<br>3,000,000 30<br>2,500,000 25<br>2,000,000 20<br>1,500,000 15<br>1,000,000 10<br>500,000 5<br>- 0<br>2001 2004 2007 2009 (Est) 2001 2004 2007 2009 (Est)<br>Total Total International<br>International<br>Intercontinental excluding flights between NA and SSA Intercontinental Domestic<br>Domestic<br>City Pairs<br>Number of seats<br><!-- End of picture text --> _Source:_ Bofinger 2009.Derived from AICD national database (www.infrastructureafrica.org/aicd/tools/data). _Note:_ As reported to international reservation systems.

NA = North Africa; SSA = Sub-Saharan Africa.

**Figure 13. All flights in one week in East Africa, 2007**

|||Burundi|**_Ethiopia_**|D<br>**_Kenya_**|estinatio<br>Rwanda|n<br>Sudan|Tanzania|Uganda|
|---|---|---|---|---|---|---|---|---|
||Burundi||_7_|_8_|20|||7|
||**_Ethiopia_**|_7_||_11_|_7_|_15_|_21_|
typically those in the lowest wealth brackets (Pakistan Bureau of Statistics, 2021). Additionally, PSLM data were collected in 2019-2020 while the present data were gathered in late 2021/early 2022.

With respect to the second research question, we found some variables had strong positive associations regardless of child age and gender (psychosocial stimulation, ECE enrollment) and some associations were negative and further moderated by gender (parental distress, with girls showing greater sensitivity at ages 0-35 months than boys). Higher psychosocial stimulation was consistently and positively associated with better child development outcomes for both girls and boys and across both age cohorts. This was true even after controlling for relevant covariates, underscoring its powerful role in favorable child development. While psychosocial stimulation was a strong predictor of ECD outcomes for both girls and boys in the younger cohort (0-35 months), the slope for girls was marginally steeper. In other words, girls experienced lower ECD outcomes on average than boys when psychosocial stimulation levels were low. Among children aged 36-72 months, gender did not moderate the results; the presence of adequate stimulation was equally highly predictive of positive school readiness outcomes for both boys and girls. Results differ from prior work in rural Sindh, where stimulation was positively associated with verbal skills for 4-year-old boys but not for girls, and no differences in child gender were observed in associations between stimulation and executive functioning (Rathore et al., 2023). This discrepancy could stem from differences in measurement or outcome of focus. Rathore et al. used direct observation and mother-reports in the Home Observation for Measurement of the Environment Inventory (HOME; Caldwell & Bradley, 1984) to assess psychosocial stimulation and focused on verbal skills and executive function. In contrast, the current study uses phonebased caregiver-reports of stimulation and a multidimensional ECD outcome. Nonetheless, findings corroborate existing research affirming the essential role of psychosocial stimulation for 11
3.20) per person per day at PPP exchange rates<sup>34</sup> – are not the focus of most of the work on economic inequality being published today. Nor are its causes. Therein lies an excellent reason why research on inequality by World Bank and IMF staff remains deeply relevant and much needed.

What that research should focus on and how it should be conducted is a matter for the excellent researchers working in the two institutions. My own view, for what it is worth, is that it should cover at least four areas, all of which already build on their comparative strengths – either at the World Bank or at the Fund.

First, a more systematic and in-depth exploration is needed of the quality and comparability of the data on incomes and consumption expenditures assembled by the Bank from national statistical offices.<sup>35</sup> Household surveys were difficult to conduct even before the COVID pandemic, and missing incomes at the top are only one of their many shortcomings. Experimental evidence has suggested that (apparently) small changes in questionnaires – e.g., in recall periods for the consumption of certain items – can make a large difference in estimates of well-being (Beegle et al., 2012). Household durable goods, like fridges and televisions, which are purchased infrequently but provide service for long periods, are valued differently in different countries. Similar differences afflict the imputation of rental service values of owner-occupied housing. The coverage and granularity of consumption items affect the extent to which expenditures by middle- and upper-income households are captured. And all of these issues are prior to the perennial matter of comparing (and sometimes combining) inequality and poverty estimates for income and consumption distributions.

> 34 These numbers are for 2018, from the World Bank’s Poverty and Inequality Platform. The year 2018 is the last year for which the Bank judges there is sufficient available data to underpin a global estimate.

> 35 Limited survey availability and poor comparability over time also
household floor material, access to electricity, access to improved drinking water, and access to improved sanitation as well as region fixed effects. Source: EHCVM and World Bank estimates.

Considering the specific food items in which the lean-season drop in consumption was concentrated indicates particularly extreme forms of seasonal deprivation. In particular, the difference between the lean and non-lean season waves in terms of expenditure on staple cereal goods was particularly large. Pooling the data from Burkina Faso, Niger, and Senegal, the seasonal difference in expenditure on cereal foods was as much as 15.2 percent without controls and 15.8 percent with controls (Table 5). Similar effects are seen when looking at the quantities of cereals consumed in the lean and non-lean season. At the same time, any differences in dietary diversity – captured by comparing the World Food Programme’s Food Consumption Score (FCS) – between the lean and non-lean season are far less clear cut.<sup>24</sup> These season-to-season changes in consumption do no match the more ‘typical’ ways in which households would cope with price and income shocks, whereby consumption of more expensive or nutritious food 24 The FCS measures dietary diversity by counting the number of days out of the last seven days in which a food from each food group was consumed, then aggregating across food groups using a weighted sum (WFP, 2008). Households with a FCS of less than 42 are said to have ‘poor or borderline’ food security. When Equation 1 is estimated with a dummy variable for households having poor or borderline food security as the dependent variable – using the pooled data from Burkina Faso, Niger, and Senegal – the difference between the lean season is only around 1.9 percentage points and is not statistically significant at the 5 percent level, with or without controls. For Burkina Faso, Niger, and Senegal, around 1 in 5 people live in households with poor or borderline food security as per the FCS, when pooling data from the two
and immediate consequence of the rise in the working-age share of the population. The effect is straightforward, since a larger share of working age people means that the economy would have proportionally more people able to produce at the most productive stages of their lives. The second demographic dividend arises if changes in age structure create space for higher savings and lead to increasing investments on human and physical capital. Thus, the paper focuses on how changes in age structure may affect growth per capita, savings, and poverty, as key outcomes associated with the first and second demographic dividends.

We examine the impact of the share of the working-age population on several economic outcomes (per capita growth, savings, and poverty) using a common framework and econometric techniques to deal with endogeneity issues. Addressing the endogeneity issue is critical since changes in income per capita are known to affect fertility, mortality, and migration, and may thus affect

> 3 Gross domestic product (GDP); gross national income (GNI).

> 4 The database includes information from the World Development Indicators, Penn World Table, Barro and Lee (2013), and World Population Prospects.

> 5 Throughout this paper, high-income, middle-income, and low-income will refer to the income per capita–based country classification used by the World Bank Group for FY 2016.

2
in the NSS-2017 relative to our estimates. In this section, we corroborate our main findings using a range of independent data sources.

## **6.1 Headcount poverty has declined after 2011 with larger reductions in rural areas**

**Estimated consumption levels sit well with private final consumption expenditure (PFCE) reported in national accounts** . A number of earlier studies have shown that there are systematic differences in consumption growth reported in national accounts statistics (NAS) and household surveys (see e.g. Ravallion, 2003; Datt

> 27Mean consumption per capita in the 2004 survey is 83.88 PPP dollars. The mean imputed 2004 consumption is 82.684 (1.4 percent lower than the survey mean).

47
that tariff declines have a more pronounced impact on the extensive margin of imported intermediate products relative to final goods. DeLoecker et al. (2016) show that trade liberalization reduces prices and that output tariff cuts have pro-competitive effects. They find that price reductions are small relative to the declines in marginal costs due to the input-tariff liberalization. Recent studies focused on the role of input-trade liberalization in shaping firms’ export performance. Using firm-level data from Argentina, Bas (2012) finds that firms producing in industries with larger input-tariff cuts have a greater probability of entering the export market. Bas and Strauss-Kahn (2015) show that Chinese firms that have benefited from input tariff cuts bought more expensive inputs and raised their export prices. These findings suggest that input-trade liberalization induces firms to upgrade their inputs at low cost to upgrade the quality of their exported products.

The next section describes the main empirical facts on Indian firms importing intermediate inputs and capital equipment goods. Section III presents a simple theoretical framework of endogenous foreign technology adoption that reflects the main features of the data and rationalizes the mechanisms through which input-trade liberalization affects firms’ decision to upgrade technology. Section IV describes the testable empirical implications. Section V presents the trade-policy background in India, the estimation strategy and the empirical results. Section VI explores alternative explanations. Section VII introduces several robustness tests. The last section concludes.

# _II. EMPIRICAL MOTIVATION_

Before analyzing the relationship between input-trade liberalization and firms’ decision to upgrade foreign technology embodied in imported capital goods, this section provides a first inspection of the data. We document several empirical facts on firms sourcing intermediate inputs and capital equipment goods from foreign countries that will guide the assumptions of our theoretical model.

Only a small subset of Indian firms produces with foreign technology embodied in imported capital 6
# [Table 3 about here]

While the direct effect of oil production is to increase the likelihood of civil war, oil also reduces the chance of war onset for countries with a high _risk of coup d’état_ . The interaction reach conventional levels of statistical significance for the Humphreys oil production and the Ross oil and gas rents measures for small scale wars. The results are similar for the larger sample for which we have available the _history of coup d’état,_ but, in this sample, only the Fearon and Laitin oil exports significantly reduce the risk of civil war for coup threatened regimes for both small and large war onset. _Military regimes_ are also helped by oil resources to reduce the risk for civil war, with statistically significant interaction terms in the models for small war onset for Humphreys oil production and Fearon and Laitin oil export indicator.<sup>19</sup> The results for both diamond and oil endowments provide support for the ideas behind the rentier state hypotheses, in that coup vulnerable regimes appear able to use revenues from diamond and oil production to deter civil war onset. Closely related to our hypothesis and our results, Collier and Hoeffler (2007) find that high risk of coup d’état results in increased military expenditures. Their findings apply particularly to Africa where coup d’état risk has remained elevated and where the higher spending on the military reduces significantly the risk of coup d’état. Our own findings further suggest that countries with rich mineral endowments that are at risk of coup d’état can use increased spending on the military not just to reduce the risk of coup but also reduce the risk of rebellion. A cautionary point in this account is that, on their own, a high risk of coup d’état, a history of coups or a military regime generally pose a higher risk of civil war, and the coefficients for these variables are usually statistically significant.

> 19 This result also holds for the Lujala (2010) off-shore oil production indicator.
Figure 23: Temporary employment by gender. (Early 2000s/Mid-2010s) <!-- Start of picture text --> 100%<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>2000s 2010s 2000s 2010s 2000s 2010s 2000s 2010s<br>Georgia Kyrgyzstan Turkey Armenia<br>Female Male<br><!-- End of picture text --> Source: Own calculations based on Household surveys In summary, the evidence does not suggest a clear trend across countries regarding the prevalence of non-standard employment but rather identifies a heterogeneous panorama by countries and types of non-standard employment.

# 4.2.2 Profile of Non-Standard Employment

In this section, we investigate possible changes in the profile of non-standard employment, usually associated with lower productivity and greater vulnerability. Like in the case of the LAC countries, the analysis of the employment profile was made based on the education, wages and the content of tasks performed.9 From the educational point of view, a general tendency can be observed in the countries analyzed to improve the profile of workers linked to non-standard work contracts. In fact, in most of the countries in our sample, it is observed that taken together, the prevalence of workers with secondary and tertiary educational levels increases to the detriment of workers with a lower educational level.

In the case of part-time employment (Figure 25), there is a first group of countries which present a decrease in the prevalence of workers at the secondary level, but, this decrease is compensated by the greater incidence of tertiary workers, so that, taken together, workers at the secondary or higher education increased their share within part-time employees (Russia, Kyrgyzstan, Armenia, and Moldova). Therefore, we can conclude from this group that part-time employment presents a better

> 9 For limitations
the household surveys varies largely from slightly under 3,000 (Uganda 2009/10) to around 27,000 (Peru 2014). The average survey size is about 11,000 households and the median is 9,000. While the required sample size can differ significantly across countries, for the current exercise, we use a normative sample of 7,000 households. The sample size of 7,000 households within a two-stage cluster sampling framework is envisioned to yield poverty and inequality statistics at national- and five to ten sub-national(regional) levels. The sample size is multiplied by the unit cost associated for each of the 78 countries and the number of surveys to be conducted by each country over the 15-year period (i.e. 5 surveys) while defining the total implementation budget envelope. Since the reliability of the estimates depends on the variability of consumption or income data in each country, the robustness of the survey implementation cost estimates is also assessed under alternative sample sizes of 5,000, 9,000 and 11,000.<sup>16</sup>

> 15 - The list of “fragile situations” is available at: <u>http://siteresources.worldbank.org/EXTLICUS/Resources/511777 1269623894864/FY15FragileSituationList.pdf. We refer to fragile and conflict-affected situations as “fragile states”</u> or “fragile countries.”

> 16 The World Bank Household Survey Strategy notes that larger countries would consider larger sample size to produce statistics at the sub-state level. For small area statistics, the use of model-based estimates could be promoted as an alternative to increased sample sizes.

9
)|0.74(0.4)|0.71(0.5)|0.71(0.5)|0.71(0.5)|0.71(0.5)|0.74(.4)|
|<br>Urban PHC|<br>0.51(0.5)|<br>0.51(0.5)|<br>0.51(0.5)|<br>0.51(0.5)|<br>0.51(0.5)|<br>0.51(0.5)|

Sample means with standard deviations in parentheses.

# **_B._** **_<u>Main results and sensitivity analysis</u>_**

Table 5 reports the screening status of study participants in the 5 study groups in the e-health database. From a baseline of no screening for all participants, 3.5 percent of participants in the control group went for both hypertension and diabetes screening during the study period (July 17
policies in government procurement and the broader implications for international trade.

To begin our analysis, we introduce a novel dataset about domestic laws that discriminate against foreign suppliers of goods and services in government procurement. For 140

> 1 According to reports from the U.S. GAO (Government Accountability Office 2021), the U.S. federal government spent $35 billion on medical supplies and pharmaceuticals in fiscal year 2020 alone to treat COVID-19 patients (half of the total increase in federal spending between 2019 and 2020). The Chinese government has spent over $21 billion on COVID-related expenditures between 2020 and 2022. The U.S. government has spent over $19 billion on defense under authorizations following the Ukraine-Russia crisis.

1
086|-0.091|0.047|0.057|0.010|
|Between-district component|0.030|0.029|-0.001|-0.014|-0.009|-0.001|0.024|0.014|-0.016|
|Covariance term|-0.033|-0.032|-0.011|0.015|-0.005|-0.014|-0.030|-0.025|0.030|
|Total|0.042|0.019|-0.087|-0.093|-0.100|-0.106|0.041|0.045|0.024|
|C. Decomposition: Griliches and R|ejev (1995)|||||||||
|Within-district component|0.029|0.006|-0.080|-0.087|-0.089|-0.098|0.032|0.044|0.025|
|Between-district component|0.013|0.013|-0.007|-0.006|-0.012|-0.008|0.009|0.001|-0.001|
|Total|0.042|0.019|-0.087|-0.093|-0.100|-0.106|0.041|0.045|0.024|

Notes: Table decomposes changes in urban shares. Column headers indicate metrics and time periods. Panel A presents the urbanization change using a balanced panel of districts employed in the decomposition. Decomposition technique follows Foster et al. (2001), Baily et al. (1992), and Griliches and Regev (1995). For the Bailey et al. (1992) technique, the within component represents