rafmacalaba/data-use-mentions-extended huggingface dataset:
|0.082|23.7|25|
|Between|0.114|0.091|33.0|27.8|
|Overlapp<br>Source: World Bank Staff|0.149<br>Calculations using O|0.155<br>fficial Household I|43.3<br>ncome and Expend|47.2<br>iture Surveys.|

As addressed next in the paper, these findings are partly attributed to policy decisions taken in the country to redistribute the economic returns of this boom towards governorates using mechanisms such as cash transfers, education and health services and more importantly public sector employment. While these tools have had some success so far, they come at a very high fiscal cost and have reached their limits. The economic crisis in the country since 2009 has revealed the weakness of these tools in addressing equity concerns, and their fiscal costs have indeed exacerbated macro volatility in the country, therefore jeopardizing recovery in economic activity and long-term sustainable future growth<sup>41</sup> . It can be argued that since these tools have not been utilized extensively since 2009, as it did previously in the decade, it has contributed to reversing the pro-poor economic growth trend<sup>42</sup> . This has therefore contributed significantly to the general population’s perception of increased inequality and poverty. Having said this, the

> 41 Refer to the World Bank’s Jordan Development Policy Review (2012) for an extensive analysis of the role of macro volatility, fiscal policy, public sector employment, subsidies, trade, service delivery, and political reforms on Jordan’s economic growth and competitiveness.

> 42 As explained in previous sections.

21
actual views, seem to be correlated with decision making about women’s work, and especially by perceptions of acceptability of woman’s work and traditional gender roles. Husbands are also uncomfortable with women working with other men (the publicness and mixing index). Interventions targeting married women need to include their husbands as well. It may be the “breadwinner and protector norm,” rather than social empirical expectations of women working per se, that drive the choices of married women.

For unmarried women, these results suggest that social empirical expectations, i.e. expectations of what other women do, are likely to be important perceptions for women’s labor force participation. The influence of male counterparts (fathers and brothers) may not be as binding. This prescribes a different set of policy tools messages when targeting unmarried women.

# **What explains liberal social norms?**

Table 7 presents OLS results on the revised social norms index consisting of social empirical and social normative items after factor analysis.<sup>9</sup> We regress the index on a number of observables in the survey data as shown in Columns 1-3. Results are presented for all respondents before we show separate results for women and men.

Overall, women have more liberal social norms towards women’s work, although this is driven largely by working women. Being married leads to increasingly negative perceptions towards women working, compared to men. Women in Amman appear to also have more negative perceptions of women working and consequences. Age squared is positively correlated with liberal social norms, and somewhat counter intuitively, having a younger child is also positively correlated for women. As expected, education and household income are positively and significantly correlated for both men and women. These variables, together, explain between 9% to 14% of the variation in social norms.

> 9 The results are robust to using an index of all of the original social empirical and social normative items asked to respondents.

21
|19|11|12|
|Median|66|13|34|7|65|33|6|11|

_Source_ : World Bank staff analysis of household surveys a. The statistics for Togo are not for those who are connected to the grid because that question was not asked, but for those who reported positive expenditures on electricity utility bills.

Differences in access rates according to the metrics as defined on page 6 are shown in Figure 3. The difference in the rate of access between definition 1 and definition 5 represents largely people who use electricity other than grid electricity and people who failed to report grid connection (possibly those connected to neighbors’ grid and did not consider themselves connected to the grid). The difference was striking in Mali, especially in rural areas and among the poor where the differences reached 50 percentage points. Two factors accounted for this difference. For rural residents, the most important cause of the difference was extensive use of solar panels. For the urban poor, it was non‐zero expenditures on electricity by those who did not cite electricity as the main source of lighting or cooking. These expenditures were small in urban areas. However, in rural areas, spending on electricity by those who did not cite electricity as the main source of lighting or cooking, did not indicate connection to the grid, or did not own a generator or a solar panel was much higher when expressed as a share of total household expenditures, and significantly
process... [and] boost legitimacy by making government more responsive to citizen needs” (Diamond, 1999, pp. 124-125) The alleged benefits of decentralized public service provision have been largely debated in the academic literature, with special attention paid to its potential conflict-mitigation strategies in the context of fragile and ethnically diverse polities (Brancati, 2006; Horowitz, 1985; Treisman, 2007). Few studies test the extent to which local government performance and decentralized service provision shape citizens’ beliefs toward political authorities and enhance the prospects of political legitimacy. This paper contributes to fill this gap by examining the antecedents of trustworthy local government authorities in a post-conflict and fragile setting, Sierra Leone, using longitudinal household data that was collected one year after an ambitious program of decentralization reform was launched and two times thereafter. Our argument is that the quality of decentralized public services, as well as the competence and perceived honesty of local government authorities, shape citizens’ beliefs towards local political authorities. In other work (Sacks and Larizza, 2011), we examine how government trustworthiness translates into behavioral legitimacy, as reflected by quasivoluntary compliance with state demands. Together, these studies complement other ongoing research examining the development of procedural justice and its role in generating beliefs about state legitimacy in rural and peri-urban Sierra Leone (Manning, 2008, 2009).

2
2

# **I. Introduction**

Most Latin American and Caribbean (LAC) countries implemented economic reforns encompassing a broad range of market-oriented policies during the late 1980s and early 1 990s. Partly because of the relatively short period of time that has elapsed since the implementation of the new policies, few studies have dealt with the effects that these policies have had on total factor productivity.' The present paper attempts to contribute to this research by estimating average rates of total factor productivity (TFP) growth for eighteen LAC countries in the period 1950-1995, and testing for the existence of changes in these rates during periods of economic reforms. For the categorization and timing of the latter, we follow the criteria suggested by Sachs and Warner (1995) for the characterization of an economy as "open," which we interpret as concurring with periods of broader economic reforms. It should be noted that it is widely recognized that trade liberalization has been accompanied by other policy reforms in Latin America and the Caribbean (see IDB 1996 and Burki and Perry 1997). Based on the Sachs and Warner criteria, all 18 countries "reformed" their economies in the last decade, while 10 of them had temporary episodes of "reform" in the previous decades (mainly in the 1950s). The data that we use comes from the data base on physical capital stocks, working-age population and output, constructed by Nehru and Dareshwar (1993), which we updated until 1995.

Several studies have analyzed the impact of economic reforms -- measured by performance and policybased indicators -- on the rate of growth, see Easterly, Loayza, and Montiel (1997). Solimano (1996) argues that the growth effects of stabilization and structural reforms may be ambiguous in the short-run, with positive effects being more likely in the medium to long run.
CAMEROON’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Table 7. Benchmarking of Cameroon’s air transport indicators**

|Country|Cameroon|Central<br>African<br>Rep.|Gabon|Chad|Nigeria|Congo,<br>Rep. of|
|---|---|---|---|---|---|---|
|Total|975,865|44,503|769,912|197,682|13,116,015|913,478|
|Domestic seats (seats per year)|105,742|N/A|374,400|N/A|9,304,568|443,634|
|Seats for international travel within Africa (seats per year)|472,089|20,661|272,792|109,074|1,373,745|351,882|
|Seats for intercontinental travel (seats per year)|398,034|23,842|122,720|88,608|2,437,702|117,962|
|Seats available per capita|0.05|0.01|0.59|0.018|0.089|0.24|
|Herfindahl-Hirschmann Index—air transport market (%)|10|50|39|36|11|31|
|Percent of seat km in newer aircraft|92|100|98|100|71|73|
|Percent of seat km in medium or smaller aircraft|32|24|28|94|28|51|
|Percent of carriers passing IATA/IOSA Audit|0|0|0|0|28.6|0|
|FAA/IASA Audit Status (as of February 2011)|No audit|No audit|No audit|No audit|Passed|No audit|

_Source:_ Bofinger 2009. All data as of
**Figure 7: Graduation by Cumulative Classes Completed in Year 5.**

<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>Tier 1 Tier 2 Tier 3 Tier 4<br>Graduation rate On−time graduation rate<br>Percent<br><!-- End of picture text --> _Source_ : SPADIES. Students belong to the 2006 entry cohort (first semester).

_Notes_ : The figure refers to students who start year 5 and classifies them into tiers based on their cumulative classes completed by the end of the year. For each tier, the blue bar shows the percent of students who graduate, and the green bar shows the percent of students who graduate on time, relative to all graduates from that tier.

**Figure 8: Average Number of Classes Attempted in Year 1, by Ability.**

<!-- Start of picture text --> 20<br>19.5<br>19<br>18.5<br>18<br>17.5<br>17<br>1 2 3 4 5 6 7 8 9 10<br>Ability decile<br>Avg. number of classes taken<br><!-- End of picture text --> _Source_ : Calculations based on SPADIES for students from the 2006 entry cohort (first semester). _Notes_ : Figure shows the average number of classes attempted by students in year 1 by ability decile.

# **5 Model**

We model a representative cohort of high school graduates who differ in ability, family income, and idiosyncratic preferences. They choose whether to enroll in college or enter the labor force as high school graduates. College graduation requires the completion of a set number of classes. The combination of ability, effort, and performance and dropout risks determines class completion and college outcomes.
trade then increases emissions by 10% in 1990 and by 3.5% in 2000, the fall largely a reflection of the all-around decline in emissionintensity. Second, they consider emissions caused by international transport. Using a rough decomposition by mode of transport, they estimate that international-trade related emissions accounted for about 5-9% of total SO2 manufacturing emissions. Adding trade and transport-cost related emissions, their estimates suggest that for SO2 transport-related emissions have gone from accounting for roughly one third to three quarters of total trade-related emissions over the 1990-2000 period.

12Estimates draw on GTAP data so they include only CO2 emissions from fossil-fuel combustion, cement production and gas flaring. Differences in emissions across transport modes are substantial. Taking an estimate of their emission averages per tonnes-km (t-km) of transport services (table 3) gives (CO2 grams per t-km in parenthesis): maritime( ≈10g/t-km); land (≈70g/t-km); air(≈700g/t-km).

11
[3.15]|
|GDP growth|0.063***|0.058***|0.062***|0.063***|0.016**|0.013**|0.012**|0.019***|
||[5.69]|[5.89]|[5.74]|[4.97]|[2.67]|[2.09]|[2.37]|[2.95]|
|Investment environment||0.078**||||0.048**|||
|||[2.53]||||[2.29]|||
|Chinn-Ito index of capital account openness|||0.044||||0.056||
||||[1.05]||||[1.60]||
|Bank assets, % of GDP||||0.007*||||0.008**|
|||||[1.73]||||[2.61]|
|Country fixed-effects|Yes|Yes|Yes|Yes|Yes|Yes|Ye|Yes|
|Observations|2,232|2,210|2,128|1,980|2,229|2,207|2,125|1,977|
|R-squared|0.123|0.134|0.126|0.124|0.022|0.026|0.025|0.035|
|# of countries|29|29|29|29|29|29|29|29|

_Notes:_ The dependent variable is “other” inflows as % of trend GDP in Columns 1-4 and other outflows as % of trend GDP in Columns 5-8.
The results on the supply of secondary schools suggest that they are less of a binding constraint on either group and have no statistically significant effect on educational mobility. For males, it is found that the local supply of secondary schooling significantly raises attainment levels on average, but not differentially by parents’ schooling. This suggests that the supply of secondary schooling is a binding constraint on attainment for males, but is equally binding regardless of the level of parental education. In the case of females, the supply of secondary schools does not appear to be a binding constraint since higher local supply does not appear to raise educational attainment, and secondary schools do not seem to matter for educational mobility either. This suggests that, from a policy perspective, increasing the local supply of public basic schools seems to matter more for enhancing the equality of opportunity across all individuals than investing in public secondary schools.

# VII. ROBUSTNESS CHECKS

Several robustness checks are conducted in order to address various concerns about the baseline results. Due to space constraints, the results of this section are relegated to a supplemental appendix. First, one may be concerned that the local supply of schools is observed in the individual’s subdistrict of birth and not in the subdistrict of parent’s residence when the individual was of age to access school. In particular, it is possible that parents moved with their children between the child’s birth and the year they entered basic or secondary schools. Fortunately, however, the JLMPS 2010 sample allows identifying “movers,” those individuals who changed their subdistrict of residence between age zero and 15. Thus, as a robustness check, these individuals are excluded from the sample and equation (2) is re-estimated for both males 22
2

# **1.  Introduction**

Recent models of monopolistic competition and trade have emphasized that productivity levels are endogenous. For example, Eaton and Kortum (2002) allow for stochastic differences in technologies across countries, with the lowest cost country becoming the exporter of a product variety to each location. In that case, the technologies utilized in a country will depend on its distance and trade barriers with other countries. Melitz (2003) allows for stochastic draws of technology for each firm, and only those firms with productivities above a certain cutoff level will operate. A subset of these firms – the most productive – also become exporters. Melitz shows how the average productivity in a country is determined by the cutoff productivity level, which in turn depends on trade barriers faced by the exporters and other features of the world market. In Melitz’s model and that of Eaton and Kortum, trade volume and variety are endogenous and are jointly determined with average productivity.

Empirical testing of this class of models can proceed by utilizing firm-level data and inferring the productivity levels of firms. That approach is taken by Bernard _et al_ (2003) for U.S. firms; Eaton, Kortum and Kramarz (2003, 2004) for French firms; and Helpman, Melitz and Yeaple (2004) for U.S. multinationals operating abroad. When firm level data are available, it is highly desirable to make use of them like these authors do. But for many countries such data are not available, and in those cases, we are still interested in estimating the joint relationship between the productivity of countries and their trade volume and variety. The objective of this paper is to examine the effects of export variety on productivity at the country level, using a broad cross-section of advanced and developing nations and disaggregating across sectors.

Rather than modeling heterogeneity across firms, as in above-cited papers, we rely instead on product differentiation across firms to generate productivity gains. This idea is
commonly gains exceptional political influence, which they can use to entrench themselves in office. Oil-rich monarchs have been overthrown in the past – including in Libya and Iraq in the 1960s, and Iran in the 1970s – but these transitions have failed to produce democracies. This does not mean that democracy activists in Libya, Bahrain, and other oil exporters will fail, only that they face a more difficult challenge than their counterparts in Egypt and Tunisia.

16. The qualitative literature on democratic transitions suggests that countries with denser networks of civil society organizations are likely to have more successful, and more peaceful, transitions from authoritarian to democratic rule. Having a denser network of civil society groups – e.g., Latin America during the democratic transitions of the 1980s and 1990s; Indonesia in 1998-99 – seems to help resolve or deter conflict among opposition groups, and helps them build stable coalitions that can run the government after a dictator falls.

17. In the Middle East, the oil-rich countries in North Africa and the Persian Gulf tend to have weaker civil societies than the oil-poor ones, like Tunisia, Egypt, and Jordan. Oil wealth, in undemocratic states, seems to crowd out independent civil society: studies of Algeria (Moore 1976) and Libya (First 1980; Vandewalle 1998b), and Angola (Messiant 2001) have suggested that oil-funded rulers have deliberately used their patronage to prevent independent social groups from forming. One reason that Iraq fell into civil war after the departure of Saddam Hussein was that his regime had systematically crushed the independent civil society organizations that populated Iraqi society in the 1950s and 1960s.

18. The prevailing governance indicators in MENA suggest the need to unbundle governance dimensions in the region, with a view to better assessing potential political transitions and conflict potential. A key question is to provide a dynamic interpretation of the interplay between institutions characterizing state-society relationships, rents, and conflict potential.

# **_Political Typologies and Prospective Transitions_**

19. A variety of contributions have been made concerning political economy typologies
# 6 Policy Implications

Our findings on the salience of geographic boundaries and the caste-composition of settlements have important implications for school allocation decisions in rural Pakistan. We illustrate this point by comparing the following hypothetical policies targeted to the population of 9-12 year-old children (the most recent 3-year cohort) in all PRHS-II villages: Policy 1: Provide a girl’s school to every settlement currently lacking one.

Policy 2: Provide a school to a low-caste dominant settlement in every village currently lacking one.

Based on our estimates (using only statistically significant coefficients), Policy 1 will induce only more high-caste girls to enroll in school, whereas Policy 2 will draw in only additional low-caste boys and girls. To level the playing field somewhat on the cost-side, we restrict the first policy to settlements with at least a 10% high-caste population and the second policy to villages with at least a 10% lowcaste population, thus avoiding the construction of a large number of "superfluous" schools.<sup>14</sup> The question is: Which policy increases enrollment rates most costeffectively?

Table 5 summarizes the horserace. Our analysis uses estimates from column (4) of Table 4 combined with village census data to obtain population weights for each settlement as well as the proportion of low-caste households within each settlement.<sup>1516</sup> As mentioned, the enrollment impacts of Policy 1 are zero for boys as well as for low-caste girls. High-caste girls increase their enrollment, but not by much (5.3 percentage points). The reason is that, since higher population settlements typically already have a school, Policy 1 disproportionately serves smaller settlements and thus does not greatly increase school access on a population-weighted basis. Policy 2, by contrast, does not suffer the same defect; more populous settlements tend to be in villages without a low-caste dominant school. Thus, Policy 2

> 14From the village census, we know that only 0.1% of the high-caste population resides in settlements that are more than
Table 5: Average Annual Household Income in 1999: Central City, Tokyo, Greater Tokyo, National Capital Region and Japan

||Central City<br>(23 wards)|(a) Tokyo<br>Metropolis|(b) Greater<br>Tokyo|National Capital<br>Region|Japan|
|---|---|---|---|---|---|
||||(a)+3Pref.*|(b)+ 4 Pref.*||
|Annual Income***||||||
|(1,000 yen)|6,502|6,592|6,860|6,849|6,494|

*3 prefectures include Kanagawa, Saitama and Chiba around Tokyo. **4 prefectures include Gunma, Tochigi, Ibaraki and Yamanashi around greater Tokyo.

*** Based on total households (including single person households) Source: Statistics Bureau, Kenmin Keizai (Economic Conditions of Prefectures).

Table 6: TMG’s Corporate Income Tax Revenues by Industry, 2001

||Taxable<br>Income<br> (1 millionyen)|Percent<br>Shares|
|---|---|---|
|Total|8,620,822|100|
|Manufacturing|2,075,887|24.0|
|Wholesale, retail trade|1,910,211|22.1|
|Services|1,808,722|20.9|
|Transport, telecommunication|979,798|11.4|
|Real estate|554,525|6.4|
|Finance|372,216|4.3|
|Construction|326,022|3.8|
|Others|612,078|7.1|

Source: Tokyo Metropolitan Government, Bureau of Taxation.

Table 7: Percent Shares of Industrial R&D investment
labor supply and earnings of adult family members, the health and education of children, the consumption and poverty levels of the household, and fertility choices. However, the above illustrates some of the many ways that migration is itself determined by different aspects of the family that then may differ between otherwise identical individuals with different migration statuses. This complicates identifying the impacts of migration if these family characteristics that determine migration also are likely to affect the outcomes of interest.

Let us illustrate with an example that often captures considerable policy attention when discussing migration’s impacts on families: the impact on children left behind. Save the Children in Sri Lanka (2006) claims there is a “clear negative impact that migration of women has on the education of children” as well as an emotional and psychological impact. UNICEF (2022) argues that while “children who remain behind while their parents migrate may benefit from improved living conditions and access to education and other services due to remittances [...]. Migration also brings potential emotional harm as a result of separation from one or both parents”. Such policy statements typically are based on comparisons of children in migrant and non-migrant households. Bilsborrow (2016) also recalls that the World Bank started including a module with retrospective questions on the occurrence of migration episodes in the LSMS out of concern for the children left behind.<sup>11</sup> For example, consider a regression that attempts to examine the relationship between an outcome _Yj,h_ for child _j_ in household _h_ , such as child education or emotional state, and household participation in migration _Mh_ , after controlling for observed characteristics of the child and her household **_X_** : _j,h_ For this type of comparison to identify the causal impact of migration we require _E_ ( _Mh × εj,h|_ **_X_** _j,h_ ) = 0. That is, after conditioning on observed characteristics in **_X_** _j,h_ , the migration decision is