rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text -->
- Bangladesh:Education<br>Se<br>53<br>0<br>5<br>2<br>me}5.3<br>7<br>co<br>)<br>o<br>ns]<br>eT<br>Wl<br>1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>+—— Quintile2 +—— Quintile 3<br>+——  Quintile4 +——— Quintile 5<br>Generated by regressing years of education on wealth, urban, higher education and interactions with<br>year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text -->

<!-- Start of picture text -->
- India:Education<br>Se<br>%<br>om<br>rs<br>Sy<br>223)<br>a<br>=<br>co<br>°<br>5]<br>B..<br>Ti<br>1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>+— Quintile2 t-—— Quintile 3<br>-—— Quintile4 H—— Quintile 5<br>Generated by regressing years of education on wealth, urban, higher education and interactions with<br>year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text -->

<!-- Start of picture text --> 5. Nepal:EducationP<br>Ss<br>Be<br>re)c<br>ER<br>a.o= ee ae oe ee<br>3.<br>=<br>1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>+— Quintile2 +——— Quintile 3<br>—— Quintile4 +——— Quintile 5<br>Generated by regressing years of education on wealth, urban, higher education and interactions with<br>year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text --> <!-- Start of picture text -->
- Pakistan:Education. .<br>Oo<br>3<br>2°°<br>5<br>no]oE<br>8<br>2o<br>Ww 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995<br>Year of birth<br>——+ Quintile 2 t—— Quintile 3<br>— Quintile 4 +———— Quintile 5<br>Generated by regressing years of education on wealth, urban, higher education and interactions with<br>year-of-birth and state fixed effects. Standard errors clustered by state.<br><!-- End of picture text -->
appropriate measures such as reducing entry barriers, providing better access to finance and improving the business climate. Furthermore, policies that benefit small firms and improve public amenities in small cities may also increase female presence in top managerial presence in retail firms.

While having more female managers of firms contributes directly to the cause of gender equality and better opportunities for women, other indirect effects cannot be ruled out. For example, anecdotal evidence suggests that females in top positions tend to serve as role models for other women encouraging them to seek education and jobs; females in top managerial positions are also less likely to discriminate against other females seeking jobs (the so called “Revolving door hypothesis”). In fact, in our sample, we do find that female employment is significantly higher among firms with female managers than male mangers.<sup>1</sup> The broader positive effects of gender equality on the economy have been well documented in the literature (Klasen and Lamanna, 2009; Dollar and Gatti, 1999).

To summarize, this study contributes to the literature in the following ways: (i) it investigates the relationship between a firm’s sector and the likelihood of having a female top manager complementing the literature on female firm ownership and female employment, (ii) uses a sample of unique cross-country firm level datasets for developing countries that follow the same sampling methodology and design allowing for cross-country comparisons, and (iii) shows that female presence in top managerial positions is much higher among retail firms when compared with the other sectors and that this difference between retail firms and the rest is magnified among the relatively smaller firms and firms located in the relatively smaller cities.

The structure of the remaining sections is as follows. In section 2, we introduce the data and discuss the variables along with the estimation method used for the regression analysis. Our

> 1 This result holds with or without controlling for firm-size (total number of employees at the firm).

4
convergence with native Australians, fertility declined from one generation of immigrants to the next among Lebanese, but not among Egyptians who had since their arrival a lower fertility than average Australians<sup>17</sup> .

The second remark on adjustment of migrants to their host societies is that convergence might happen faster in demography than in other family related issues. A survey among immigrants from Turkey and Morocco carried out in Belgium in the early 1990s found that in matters directly related with fertility, such as the desired family size, the preference for boys or girls, the utility of children and contraception, migration produces a decisive change. For example, the percentage of married women aged 25-29 using contraceptive was respectively 79% and 71% among Turkish and Moroccan women living in Belgium, compared with 44% and 35% in their countries of origin the same year. When it comes to marriage the choice of partner and female autonomy, however, only a “prudent shift in the code of conducts” is observed: marriage decided on free individual choice without parents interfering remains very rare and most often a source of conflict. Social and cultural changes would thus proceed at different paces according to domains (Lesthaeghe and Surkyn 1995).

# **4.  Patriarchal vs. individualistic values sent back home by migrants**

From the mid-1970s until the late 1980s, Arab countries were displaying a puzzling pattern of fertility differentials: contrary to what is observed at the level of the world—a negative correlation between GDP per capita and birth rates—the richest Arab countries were also those with the highest birth rates. As it will be briefly recalled in the next paragraph, this

> 17 TFR had declined from 5.09 children per women among Lebanese immigrant women in Australia born in 1917-21 to 4.35 for those born in 1937-41 (youngest generation having completed its fertility in 1981), while among Egyptians the decline was only from 2.57 to 2.42 (Young 1991).

13
thirds of the country’s districts. In parallel, more than 100 major violent events are identified and geocoded based on the Global Terrorism Database (GTD).

The study builds its understanding of the formal sector response to conflict by analyzing the dynamic of mobile phone traffic and casualties during the 2015 Taliban attack on Kunduz, Afghanistan’s fifth largest city. It then estimates a dynamic specification linking the number of firms active in district and month to the number of major violent events in that district, over a 12-month period spanning a quarter YY<sup>FF</sup> ii before the event and three quarters afterward: tt CC The specification includes fixed effects for districts ( ) and months ( ) as well as a quadratic time trend at the district level. It does not include other control variables. ii tt δδ ττ The results show no impact in the three months preceding the violent event. The number of active firms falls by 4.9 percent in the month of the event, with the decline growing to 6 percent in the following month and persisting for up to five months. Six months after the event the impact becomes statistically insignificant. A more disaggregated analysis shows that larger firms are more responsive to violence.

As for illicit activities, Lind et al. (2014) explore how the intensity of conflict in Afghanistan changes the incentives faced by farmers and spurs opium production. Poppies are more drought-resistant than wheat, the main alternative crop. They also take little space relative to their value and can easily be transported off roads. The destruction or disabling of irrigation and transportation networks resulting from conflict therefore makes poppies relatively more profitable than wheat.

Data are from 329 Afghan districts from 2001 to 2007. The study notes that there are no available data on the amount of fighting during this period. One possible alternative was to rely on the number of combat activities by year, but information on such events was scarce and mostly based on media coverage. For this reason, the study bases its measure of conflict on the number of casualties from hostile encounters involving either NATO International Security Assistance Force (ISAF) forces or US forces participating in Operation Enduring Freedom (OEF). The conflict measure does not include Afghan casualties. The study argues that international forces tend not to be involved in poppy eradication or other anti-narcotic actions, implying that the chosen conflict indicator is plausibly exogenous to opium poppy production.

8
# **1 Introduction**<sup>**1**</sup>

Recent figures from the Internal Displacement Monitoring Centre (IDMC) estimate that in 2019, 24.9 million people across the world were newly displaced due to natural disasters, with another 8.5 million people forcibly displaced due to conflict and violence (IDMC 2020). Currently close to 46 million people are internally displaced in their home country, with 26 million living as refugees<sup>1</sup> in a host country (UNHCR 2020). Some have moved for short periods, while others have been forcibly displaced for years or decades. In 2019, fewer than half a million forcibly displaced individuals had returned to their homes – signaling the protracted nature of displacement that has increased throughout the last decade, partly due to ongoing political instability in North Africa and the Middle East, and Sub-Saharan Africa (IDMC 2020). And while the displaced population amounts to only 1% of the global population, they are disproportionately affected by deprivation, often chronic. For instance, over 80% of all displaced people reside in countries and areas affected by acute food insecurity and malnutrition (UNHCR 2020), and many of the internally displaced and refugee families live in temporary housing or camps with basic living conditions and have limited access to services and employment.

Existing gendered analyses of forcibly displaced persons tend to center gender-based violence as the organizing vulnerability in people’s lives, rather than poverty status (Fiddian-Qasmiyeh 2014). Admasu et al.’s (2021) inclusion of the MPI as an element of examining gender difference added a new dimension to this field, finding that women were more likely to head multidimensionally poor households than men in most of the five countries studied here – Ethiopia, Nigeria, Somalia, South Sudan, and Sudan. As the MPI is a household-level measure of multidimensional poverty, strictly reporting the MPI headline results obscures the divergent experience of individuals within the household. This paper builds on the work of Alkire, Ul Haq, and Alim (2019) with its focus on individual deprivations and intrahousehold analysis using the gender-sensitive refugee

> [†] World Bank, Washington, D.C, USA

> [‡] Oxford Poverty & Human Development Initiative, University of Oxford, Oxford, UK

2
# **Appendix A1: Methods and Sources on Disaggregated Tariff Data**

We construct a comprehensive tariff dataset for ten Latin American countries— Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Peru, Paraguay, Uruguay and Venezuela—from 1990 to 2001. The dataset includes MFN applied tariffs and bilateral applied preferential tariffs at the ISIC 4-digit level.

The compilation of bilateral preferential tariff rates among all of the countries in our sample involved three steps:

- (1) Identification of the official text of the trade agreements “in force” during the 1990-2001 period and their corresponding tariff liberalization schedules (annexes). In many cases this

information was only available as hardcopy documents and required a formatting exercise into a standard database file.

(2) Conversion of the tariff reduction programs of each agreement into yearly bilateral preferential tariff rates. This was done using the text of the agreements (see below), which in some cases listed preferential tariffs and in some cases tariff cuts. For example, tariff reductions under Mercosur are in some cases gradual, with a given different amount each year, in some cases linear with a set reduction each year, and in some cases automatic, immediately reduced to zero. All tariff reductions were converted to preferential tariff levels for each year.

- (3) Conversion of product-line preferential tariff information into a single common nomenclature

using ISIC Rev 2 (4 Digits), since agreements negotiated in the 1990-2001 period used different tariff nomenclatures (NALADISA, NANDINA, HS) and correlation tables were only available to ISIC codes. All conversions were done as simple averages.

38
<!-- Start of picture text --> GDP Debt-to-GDP<br>-0.4 2<br>-0.6<br>15<br>0.8<br>A<br>1<br>A2<br>4 0.5<br>26 26<br>24 16 24 16<br>22 2 =«'4 22 | (2 4<br>Land sensitivity20 18 16 0 2 4 Period6 8 10 Land sensitivity20 18 16 0 2 4 PeriodA 8<br><!-- End of picture text -->

<!-- Start of picture text --> GDP Debt-to-GDP<br>-0.7 2<br>08 15<br>-0.9<br>1<br>4<br>0.5<br>Aa<br>A2 0<br>44<br>°21 7 6 "10 >182 1 " 6 m 10 a<br>Government response o oo 2 Period Government response o 0 2 Period<br><!-- End of picture text -->
# Figure 8. Potential Growth Prospects A. Potential growth

B. Share of countries and GDP of countries with potential growth in 2018-27 below its longer-term average <!-- Start of picture text --> Percent Baseline Percent Percent Share of countries<br>2.6 Demographic trends 5.2 100 Share of GDP<br>Migration<br>2.4 Other factors 4.8<br>80<br>2.2 4.4<br>60<br>2.0 4.0<br>1.8 3.6 40<br>20<br>0<br>World AEs EMDEs<br>World EMDEs (RHS)<br>2013-17 Contribution 2018-27 2013-17 Contribution 2018-27<br><!-- End of picture text --> Source: World Bank estimates.

A. GDP-weighted averages. Derived using the production function-based potential growth. “Other factors” reflects declining population growth, convergence-related productivity growth, policy changes, cohort effects, and a slowdown in investment growth relative to output growth. “Contribution” reflects the percentage-point changes between the averages of 2013-17 and 2018-27.

B. Share of countries and share of GDP of 80 countries in which potential growth in 2018-27 is below longer-term average potential growth (1998-2017), in percent of all countries or global GDP among 80 advanced economies and EMDEs. Horizontal line indicates 50 percent.

Source: United Nations World Population Prospects: The 2017 Revision.

Note: EAP = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa. A. The sample of each study differs from each other. Aiyar and Mody (2011): Indian states, 1961-2001; Bloom and Williamson (1998): 78 countries, 1965-90; Bloom and Canning (2004): Over 70 countries, 1965-95; Bloom et al. (2000): 70 countries, 1965-90; Amer and Cruz (2016): 160 countries, 1960-2010. B.C. Population weighted averages. The working-age population is defined as people aged 15-64 years. D. -F. GDP-weighted averages. Other factors include contribution from policy changes, cohort effects, changes in population growth, convergence-driven productivity growth, and investment. “Contribution” reflects percentage-point changes between the averages of 2003-07 and 2013-17.

25
connection between the relative evolution of personnel versus nonpersonnel expenditures, and what ultimately happens to the share of government expenditures going to educatiom A fall in civil service wages relative to the average price of nonpersonnel expenditures, other things being equal, seemingly leads to a reduction in the share of government spending accruing to the most labor-intensive sectors, among which is education (see box 111.1). This tendency is further exacerbated where teachers' salaries have declined more than the average civil service wage.

3.12 The Bolivia report is an interesting exception in this respect. It acknowledges that the country's adjustment program has resulted in a decline in government social spending in real terms and as a share of total expenditures (spending declined from 35 percent in 1984 to 25 percent in 1986 and then recovered to 30 percent in 1988). It argues, however, that the "social cost of adjustment" is not as high as the evidence suggests because the expenditure item that has fallen is salaries, particularly of teachers, whereas purchases of school materials and health supplies were about ten times higher in 1988 than in 1984. The report concludes that, whiie the fall in teachers' salaries would lower the quality of education in the long run if not remedied, expenditures on materials and supplies "have a more direct short-term relationship with the quality of the services rendered." Hence, the evidence indicates "that quality has improved following the adjustment."<sup>2</sup> ' 3.13 Public expenditure reviews should give more attention to the relationship between structural adjustment and public resource allocation to social sectors. This issue is much more complex than can be observed from aggregate intersectoral resource allocation percentages, which are sometimes targeted in policy-based Bank lending for education. They are rather unreliable indicators of government intentions and performance, unless these expenditures are broken down by purpose or by end use, and can be compared with sector objectives.

# B. Non-Central-Government Resources

3.15 With a few exceptions, all reports cover non-central-government financing at various levels of the education system, providing scattered quantitative or qualitative evidence (see figure III.1). PER emphasis on the mobilization of nongovermnent resources is most prevalent for low SRM countries, as well as for high PE countries where sustaining a high primary enrollment rate requires the continuing availability of complementary financing.

l/Bolivia--Public Sector Expenditure Review with a Special Emphasis on the Social Sectors (Report No. 7746-BO, September 1989), Chapter III, pp. 25-27.

21
Policy Research Working Paper 8984

# **Abstract**

This paper investigates to what extent media impacts political decisions. A viable practical approach to test the relationship between mass media and political actions is through the use of the World Bank’s _Doing Business_ data, specifically, by assessing local media coverage of _Doing Business_ and implementation of business regulatory reforms. The tested hypothesis is that countries with higher media coverage of _Doing Business_ tend to carry out more business regulatory reforms, assuming one- and two-year lags between media coverage and reform implementation. To achieve this objective, the study put together a comprehensive data set that encompasses country-specific local media coverage of the _Doing Business_ report in 190 economies. The study finds that local media coverage of _Doing Business_ has a significant influence on regulators’ actions. First, the analysis shows that the number of local media articles tends to increase the probability of whether a country does any reform. Second, countries with greater media coverage of _Doing Business_ indicators tend to have higher numbers of implemented reforms.

This paper is a product of the Global Indicators Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at rramalho@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Figure 1.11 Average inventory levels (weighted average), 2005-2010 <!-- Start of picture text --> 15.0%<br>10.0%<br>5.0%<br>0.0%<br>2005 2006 2007 2008 2009 2010<br>Private SOEs<br><!-- End of picture text --> Source: Authors estimates based on the NBRB dataset.

**But there is a longer answer to this question which is important to discuss in view of the current situation of the economy.** SOEs were then (and now) under enormous pressure to minimize the negative social impact of the crisis. In the absence of an independent social safety net, SOEs perform the role of social insurers of last resort providing de facto income transfers to their employees during a recession.  While this is understandable it is also extremely costly and, in the jargon of economists, suboptimal.  It is understandable because many of the poor performing enterprises are located in monocompany towns where they are the single largest employer. Cutting labor in these towns was bound to have a very high cost in terms of unemployment.  Even relatively successful companies such as MAZ were pressured to take over other poorly managed enterprises, effectively bailing them out.  At the same time, making SOEs perform this function is extremely costly and sub-optimal.  What sense does it make to continue producing when there is no demand?  A far better alternative would be to pay directly to the employees and save in the raw materials and intermediate products used in production.  It is also sub-optimal because the firm affected by a negative shock is the insurer, which clearly does not allow spreading risks in a larger society pool.

**This does not mean that SOEs remained immobile to market changes: in fact they reduced number of hours of work, cut bonuses etc. and imposed wage cuts about three times larger than private enterprises** (see Figure 1.12).  It just means that the adjustment in employment was significantly smaller in SOEs than in private enterprises (which shed about 10 percent of their employment in 2009).

15
higher wages than workers with temporary contracts. Therefore, the policy implemented after Independence to protect employees seems not to have affected wages directly as they are higher than those of unprotected workers are. This finding is coherent with what Fallon and Lucas (1991) found estimating wage equations using time series data. However, the labor legislation may have affected the number of permanent jobs created negatively because firms have invested more in physical capital than in long-term engagement to employment. There does not seem to be a trade offbetween enhanced job security and wages. Rather the contrary, job security endows insider workers with bargaining power enhancing the possibility of achieving higher wages.

**Table 5 Apprenticeship and Contracts**

||Prod|uctivity|||Wages||||
|---|---|---|---|---|---|---|---|---|
||Coef.|Std. Err.|<br>t|P>Itj|Coef.|Std. Err.|<br>t|P>JtI|
|dpermem|-0.245|0.098|-2.500|0.013|0.118|0.048|2.468|0.014|
|apprmeta|0.027|0.056|0.478|0.633|0.107|0.027|3.939||
|dappr|-0.064|0.121|-0.531|0.596|0.282|0.059|4.780|0.000|

The productivity differential associated with holding a permanent contract is negative and statistically significant. Is the impact from the type of contract of the same size on wages and productivity? We reject the hypothesis of equality of productivity and wages of permanently employed, with a p-value of effectively zero, (F=13.17, Prob > F = 0.00). This finding contradicts the intuitive explanation presented in Fallon and Lucas (1991) that temporary workers lack the incentive to work hard because they are not covered by Zimbabwe's permission clause. Temporary workers are more productive than permanent indicating that the former may be working hard in an attempt to obtain a permanent contract.

In the sub-sectors we find that the wage premium obtained by permanently employed workers is statistically insignificantly different from zero in woods, textiles, and metals, 19