rafmacalaba/data-use-mentions-extended huggingface dataset:
3240 12 20 183 194<br>15 12 12-9 122 Iss101 11G 7<br>10<br>1 2 345 12 34 5 1 2 34 5<br>Moscow, 1992-95 Vladimir, 1993-96 Gorodets, 1993-96<br><!-- End of picture text --> Note: 1 - lowest quintile, 5 - highest quintile Sources: The Moscow Longitudinal Household Survey, Jan., 1996; Vladinir and<sup>Gorodets Longitudinal Household Survey, Dec., 1996</sup> Mobility (low or high) was largely determined by the progress of privatization (examined above in Section 1). At the end of 1996, the proportion of private dwellings was 42% in Moscow, 48% in Vladimir, and 66% in Gorodets. A direct link with the level of mobility is obvious enough. According to surveys conducted in these cities, owners of privatized housing exhibit a relatively low potential mobility<sup>as</sup> compared to households who rent housing from the state (Table 2.6).

Table 2.6. Household plans to move by owner/renter status, %

|!?cun-owe.yvs.<br>rented<br>.............<br>_ ..................................<br>_....|Moscow,<br>....<br>. _ .............................|1996<br>................|Vladimir,<br>...|1996|Gorodets,|1996<br>|
|---|-
group by improving labor market prospects (Autor, 2001; Hjort and Poulsen, 2019). The overall extent to which the internet has enabled the international recruitment of jihadists is, therefore, theoretically ambiguous.

This paper addresses this question empirically by using a unique dataset on Tunisians who joined Daesh in Syria and Iraq between early September 2013 and late 2014. The data contain information on recruits’ ages, education levels, and delegations (district) of residence before traveling abroad, allowing us to exploit variation in enrollment both between and _within_ geographical areas, and between age and education groups.<sup>1</sup> These granular data are matched with equally granular socio-economic information obtained from the 2014 Tunisia Census of Population and Housing. Thus, for each delegation-education-age cell, we are able to associate

> 1Tunisia’s smallest administrative units are the communes, which form the country’s 264 delegations, which in turn aggregate into 24 governorates.

1
especially in India, will become much more important for the continued reduction of global inequality.<sup>27</sup> Third, climate change places considerable uncertainty on any such growth projection.

Regarding the overall level of global inequality, Hellebrandt and Mauro (2015) predict a decrease in the global Gini of almost 4 percentage points by 2035, which is substantial but leaves global inequality at a high level. Their results also show that growth (in GDP per capita proxying for survey incomes) will be crucial: In a scenario where poor countries grow slower than the baseline projections, the Gini index declines only by 1 percentage point. In contrast, overturning the decline in global inequality would require an increase of around 6 percentage points in within-country inequality in all countries, which is substantial.<sup>28</sup>

# **VI. Research agenda and concluding remarks**

More and better data have to be the top priority for future research on inequality in developing countries. First, good quality data on living standards are still missing in a number of countries, especially in the Middle East, the African continent, the Caribbean and the Pacific. Recently, the World Bank committed to support countries such that all poor countries have a survey at least every three years (World Bank, 2015b). Second, in middle-income countries, where agriculture and own-consumption is becoming less important, more attention ought to be paid to income data, as opposed to consumption expenditure. Levels and trends in inequality can be different if they are measured in terms of income or consumption expenditure, especially if the growth has been concentrated at the top where expenditure might be a poor measure.<sup>29</sup> Third, very little is known about capital incomes in developing countries, since many income surveys do not even attempt to collect this information.

Finally, and closely related, the measurement of top incomes needs to be improved in developing countries. The administrative records that have been used in developed countries
# **3.2 Outcomes**

The primary outcomes in this paper are intimate partner violence and sexual activity. For sexual activity, we focus on behaviors that may be mechanisms through which the interventions operate, such as changes in sexual partnerships (both quantity and quality). We also explore gender attitudes and risk perceptions around violence, SRH, and STIs. These outcomes are measured at both baseline and endline.

For each group of outcomes, we followed Kling, Liebman and Katz (2007) to create an overall index by (1) redefining each outcome in the group to be oriented in the same direction; (2) standardizing each outcome at baseline and endline separately to the mean and standard deviation among adolescents in control communities who were not assigned to the _Goal_ treatment; and (3) taking the unweighted mean across all standardized outcomes in the outcome group.

**Intimate partner violence.** For females, we measured intimate partner violence (IPV) based on the responses to three questions that capture her experience of violence from their most recent partner within the last two years. Violence categories included physical (pushing, shaking, or throwing something at her), psychological (threatening to hurt or harm her or someone she cares about), and sexual (being physically forced to have sexual intercourse). These questions are standard questions on IPV and are used in the Tanzania Demographic and Health Surveys (DHS, 2016). The response options are often, sometimes, not in the past 12 months, or never. Interviews were conducted in private and confidentiality was assured to participants. In cases where females reported violence, they were provided a violence hotline number to seek support. We generated two sets of indicators to capture whether the violence happened (i) often or (ii) at all in the last year. We generate an index for each frequency set of psychological abuse, physical abuse, and forced sex—IPV often and IPV in last year—by standardizing each component to the
predicting household famine in Uganda between 2004 and 2005 using household data.

The importance of using systematic approaches to predicting food crises and allocating humanitarian resources effectively is likely to increase in coming years as key drivers of food insecurity are expected to worsen into the 21st century. Historical achievements in eradicating poverty have largely coincided with substantial degradation of environments (Stern et al., 1996; Andr ́ee et al., 2019). Degrading environments, climatic extremes, and growing populations will continue to put pressure on future agricultural systems (Grainger, 1990; Ingram et al., 2010; Myers et al., 2017; Diogo et al., 2017). These developments place obstacles in the path to zero hunger, specifically for the rural poor that rely on local natural assets for income and food consumption (Duraiappah, 1998; Barrett and Bevis, 2015; Barbier and Hochard, 2018). A further benefit of model-based predictions of food insecurity is that they offer an alternative to the allocating of scarce resources based on qualitative assessments, instead relying on readily-verifiable and openly available data in a systematic way to predict the deterioration in food security when action is delayed.

The paper is structured as follows. Section 2 introduces the data, section 3 develops a framework for the validation and calibration of probabilistic predictions, paying particular focus to balancing false positives and false negatives. It then details an application using a Random Forest algorithm. Section 4 presents key results, and section 5 concludes. Additional results are found in the supplementary appendices.

> 2Apart from the food insecurity literature mentioned here, the paper also relates to the work of Celiku and Kraay (2017) who explore predicting conflict outbreaks in the similar context of weighted prediction loss functions.

3
Using a purpose-designed company survey, we then estimate likely economic responses to changes in trade costs. We find the trade-cost elasticity of trade across Malebo Pool to be high, possibly even exceeding the value of 1. This means that cuts in the price of cross-Pool transport will stimulate a strong expansion of trade – so strong that it might even increase revenue for transport operators and for customs. Trade facilitation across Malebo Pool would promote mainly trade in locally produced goods and trade by small-scale producers. It thus holds particular promise for unlocking local productive potential.

What can policy makers do? While large foreign-funded infrastructure projects exist on the drawing board, considerable uncertainty remains over their realization and future viability. Hence, we explore options for regulatory measures and small-scale donor interventions aimed at unleashing “bottom-up” local entrepreneurial activity.

We propose that customs procedures be brought in line with existing legal prescriptions, and in particular that the decreed restriction on the number of agencies present at border crossings be enforced. Moreover, customs procedures ought to be simplified further, and fare structures should be made transparent. We also propose a liberalization of the cross-river transport market. Such measures would be comparatively cheap, would yield large gains to the general population, should be relatively easy to enforce given the proximity to the seats of government, and could have high symbolic value as evidence of political goodwill between the two nations.

Our policy recommendations can be taken as complements to more general trade-facilitating reforms through regional trade agreements and customs reform, as proposed in the World Bank’s recent Diagnostic Trade Integration Study. They also could be seen, at least in the short-to-medium term, as substitutes for the project of building a bridge to link Kinshasa and Brazzaville. Technical support, adjustment financing and some infrastructure funding from external donors could well be envisaged.

6
|
|with children<br>28.1|
|with children + parents<br>30.8|
|Marr-ied<br>working agisi**E** sEEe<br>p ole-|
|childless<br>38.8|
|childless + parents<br>37.3|
|with children<br>26.3|
|with children + parents<br>27.2|
|-.AverefoE i<br>37.|

**Source: The** Moscow Longitudinal Household Survey, December 1994.
that determine lack of adoption is critical to define policy priorities; including areas that deserve further experimentation with impact evaluations that would provide more rigorous evidence of interventions. Yet, perceived obstacles do not necessarily imply that are the most relevant issues faced by the firms. Firms do not know what they do not know. Thus, we now investigate these obstacles based on factual information associated with them. We group them into three main groups: i) Financial constraints; ii) Information and knowledge; and iii) Access to markets and competition, which is associated with uncertainty of demand and consumers’ preference.

# **6.2 Financial constraints**

Previous studies suggest that an inefficient financial system may reduce the firm-level technology adoption within a country even if a technology is more profitable. For example, by studying a model of establishment dynamics with a producer-level data, Midrigan and Xu (2014) found that financial friction distort firm entry and technology adoption decisions, which results in lower level of aggregate productivity. Cole et al. (2016) provides a dynamic 23
>than 75 hp.<br>132.2|<br>2,964.4|22,418.02|
|Cars n.e.s.<br>317.4|<br>6,322.1|19,915.86|
|Total<br>449.7|<br>9,286.6|20,651.65|
|Mexico (1975)|||
|<br>4cylinder cars<br>152.0|<br>6,038.0|39,712.58|
|<br>6cylinder cars<br>60.3|<br>3,183.1|52,813.89|
|8 cylinder cars<br>45.1|<br>3,002.2|66,626.81|
|Total<br>257.4|<br>12,223.3|47,492.67|

Source: Appendix Tables A17.2, A17.3 and A17.4.

Car output in the three countries was therefore divided into<sup>two</sup> groups: cars with 4 cylinders or less and those with "ore tha& 4 cylinders. Although, at first sight, this may seem a rather crude way of assessing passenger car quality, it appears to be appropriate for the purpose at hand. In the mid-1970s car output in the United States consisted largely of 6 and 8 cylinder models while in Brazil and Mexico it consisted mainly of 4 cylinder models.

The first step was to estimate quantities for all the three countries distinguishing between 4 cylinder cars and those with 6 or 8 cylinders. For Mexico we get this information directly from the census material (see table A.1). For the USA we used information from Automotive News, 1975 Almanac Issue, which is the most important trade journal of the automobile industry in the USA. It shows US production
from EAC-I data to match each EA to the SPEI grid cell and calculate rainfall shocks at the EA level. Drought occurred if and only the SPEI value is below -1, which captures moderate to extreme droughts (Vicente-Serrano et al., 2010). Interestingly, the SPEI index accounts for the joint effects of precipitation, potential evaporation, and temperature. This measure then allows to control for weather variables strongly correlated with rainfall. This index is, therefore, less susceptible to omitted (weather) variables threats.

In Mali, rains are brought seasonally by monsoon winds that feed the lower layers of 19
000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Secondary enrollment rate|0.00868<sup>***</sup>|0.00976***|0.00911***|0.00704<sup>***</sup>|0.007<sup>***</sup>|0.008***|
|<br>_(initial level, logs)_|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|ICRG Political Risk Index|0.00620<sup>***</sup>|0.00621***|0.00655***|0.00681<sup>***</sup>|0.007<sup>***</sup>|0.007***|
|_(principal components)_|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Credit to private sector|-0.0115<sup>***</sup>|-0.0107***|-0.0107***|-0.0135<sup>***</sup>|-0.013<sup>***</sup>|-0.013***|
|<br>_(% of GDP)_|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000
1(“worst practice”) to 5(“best practice”)**

<!-- Start of picture text --> 5<br>4.5<br>4<br>3.5<br>3<br>2.5<br>2<br>1.5<br>1<br>0.5<br>0<br>Source: Own elaboration based on WMS dataset.<br>Note: The country score is calculated as a simple average across firms, for each country<br>United States Japan Germany Sweden Canada Singapore UK France Australia Italy Mexico Poland Nigeria Chile New Zealand Portugal Argentina Republic of Ireland Spain China Greece Turkey Brazil Vietnam Zambia India Colombia Mozambique Ghana<br><!-- End of picture text --> Some of these subcomponents of overall management quality are especially relevant to innovation. In principle, innovation activities are, by definition, long term and highly uncertain. In

> 13 In a separate analysis - also drawing from WMS data, Malaysia is benchmarked against a quite similar set of countries and its average management practices is also ranked below the United States and Japan, but in line with large Australasian countries and Southern Europe. For further details, see World Bank (2017) chapter 4.

18
countries at different points in time (such as the money supply or exchange rate). Closely related, we do not take into account changes in monetary policy tools or frameworks over time. Finally, we focus on a sample of 24 advanced economies (including the euro area), but do not consider emerging and developing economies, many of which would likely have very different rate cycles.

# II. Rate Cycles: Methodology, Data, and Dates

This section adapts the methodology used in the extensive literature on business cycles to identify cycles in policy interest rates. We also incorporate information on central banks’ balance sheet programs—large-scale asset purchases (QE, quantitative easing) when short-term policy rates had reached the lower bound, and subsequent asset sales (QT, quantitative tightening). This section begins by introducing the methodology and then describes the data on policy interest rates and asset purchase programs used to identify the rate cycles. It concludes with the resulting dates for easing and tightening phases used in the remainder of the paper.

# II.1. Dating Methodology

Our goal is to identify the turning points of rate cycles using a methodology that links to the longstanding literature on business cycles and can be applied consistently over a long period and across countries. Because of the substantial volatility in interest rates early in our sample period and differences in monetary policy frameworks across countries and time, we cannot use an off-theshelf approach, rely on country-specific analyses, or employ simple rules of thumb as is sometimes done for business cycles (such as the two quarters of negative GDP growth popularly used as a shorthand to identify recessions).

Instead, we modify the BBQ algorithm proposed by Bry and Boschan (1971) and then developed in Harding and Pagan (2002).<sup>5</sup> This algorithm evaluates increases and decreases in a series to locate local maxima and minima over specified windows. If an adjacent local peak and trough of policy interest rates meets the censoring criteria set in the algorithm, they define the start
- **UNDESA.** 2020. “International Migrant Stock 2020.” United Nations Department of Economic and Social Affairs, Population Division.

- **United Nations, Network on Migration.** 2022. “Guidance on Bilateral Labour Migration Agreements.”

- **Wooldridge, Jeffrey M.** 2023. “Simple approaches to nonlinear difference-in-differences with panel data.” _The Econometrics Journal_ , 26(3): C31–C66.

- **World Bank.** 2022. “Global Bilateral Migration _|_ DataBank.”

- **World Bank.** 2023. _World Development Report 2023: Migrants, Refugees, and Societies._ The World Bank, Washington D.C.

31
~ 80%<br>a 60% 0 ~ ~ , ~ ~ ~~ > 6 ha<br>.9 40% ~ 2 -6 ha<br>0<br>20 ~1- 2 ha<br>20% Ej 0.4-1 ha<br>0% 00%<br>~~0 ~ 1953-54 1961-62 1971-72 1982<br><!-- End of picture text --> Source: NS S data, reported in Sharma (1 994) 8
appear to be a relationship between perceptions of the helpfulness of donors and non-state actors and the willingness to defer to the police and to the courts. Individuals who believe that donors and non-state actors exert too much, rather than, too little influence over one’s government is associated with the willingness to defer to the court and to the police. Findings also suggest that citizens who believe non-state actors are responsible for providing law and order are less likely to be willing to defer to the police and to the courts than respondents who believe the state is responsible for providing law and order.

# **7.4 Conclusion**

This paper demonstrates that the logic of the fiscal contract is relevant to a wide variety of contemporary African states. Findings from a cross-national — analysis of survey data from Africa link citizens’ legitimating beliefs indicated by a willingness to defer to the tax department, the police and the — courts to a government’s fulfillment of a fiscal contract. Citizens who are satisfied with their government’s provision of services and goods are more likely to be willing to defer to the tax department, courts and police than citizens who disapprove of government service provision. There is also evidence that the more competent, honest and fair a government is in serving its citizens, the more likely it is to produce a virtuous cycle of citizen compliance with its extractions, leading to better government and greater compliance. There is little evidence that the presence of infrastructure in neighborhoods is itself linked to citizens’ legitimating beliefs.

In Sub-Saharan Africa, NGOs, donors, churches, traditional leaders, and other non-state actors provide a significant portion of essential goods and services. The provision of services by non-state actors and donors is not unique to Africa and occurs throughout the world in both OECD and non-OECD countries. The growth of non-state actor service provision has sparked a debate in political science and sociology and in the aid community over the conditions under which non-state actors are likely to affect citizens/state relationships (Bratton and van de Walle
businesses, rendering samples that are representative of the underlying population of informal businesses at the geographical area being covered.

This paper introduces the data collected across twenty-four cities in seven countries through the survey method examined in the companion paper (Aga et al., 2022) and provides a look into some of the descriptive findings from this combined and standardized data. The data from the Informal Sector Enterprise Surveys are made publicly available by the World Bank's Enterprise Analysis unit.<sup>3</sup> Section 2 introduces the data, briefly outlining the survey method (i.e.,

> 2 These methods include creating a random sample using the economic censuses that cover the informal sector (which is extremely rare), snowballing, a 1-2 method, and various simple area-based sampling methods.

> 3 Data can be downloaded from the Enterprise Surveys data portal: https://login.enterprisesurveys.org/ and the citylevel Informal Sector Enterprise Surveys indicators can be viewed or downloaded from the Informal Sector

2
**Table 8: The Dutch disease hypothesis: manufacturing output shares (** % **non-oil GDP) regressions**

||Marginal Efects|
|---|---|
|Population (logarithm)|-0.0851***<br>(0.0314)|
|GDP per capita|0.0872***<br>(0.0253)|
|Real efective exchange rate|0.0004<br>(0.0003)|
|Oil rents (% of GDP)|0.0017**<br>(0.0007)|
|Monthly minimum wage (2011 US dollars)|-0.0000735<br>(0.0002)|
|Observations|27|

Marginal Effects are reported. Standard errors in parentheses. Results based on fixed effects fractional logistic regressions in equation (2) for Cameroon, Ghana, Nigeria, and South Africa. _∗p <_ 0 _._ 10 _, ∗∗ p <_ 0 _._ 05 _, ∗∗∗p <_ 0 _._ 010 sub-Saharan Africa’s manufacturing experience.

# **7 Concluding Remarks**

This paper investigates the cross-country patterns and trends in the share of manufacturing in national output and employment among sub-Saharan Africa. Rodrik (2016) claims that several developing countries including those from subSaharan Africa are prematurely deindustrializing because manufacturing has begun to shrink at levels of income that are much lower than those at which the advanced economies started to deindustrialize. We study the extent to which African countries differ regarding the scale, timing and causes of “deindustrialization” using recent panel data methods for fractional responses. We use two main measures of industrialization, namely the share of manufacturing valued added in GDP at constant prices and the share of manufacturing employment in economywide employment. Our data come from a variety of sources and comprises of an unbalanced panel of 41 African countries. We also explore potential explanations or correlates of