rafmacalaba/data-use-mentions-extended huggingface dataset:
although the impact of ICT on productivity growth could be greatest when firms are far away from the technological frontier, lack of adequate complementary factors such as skilled workers and late ICT adoption could constrain the extent to which ICT impacts firm productivity. While there is a plethora of anecdotal evidence regarding the ICT sector in Africa, there is very little evidence on the impact of ICT in other productive sectors of the economy more broadly; which is where most of the potential gains for poverty reduction and shared prosperity are concentrated.

To explore these questions empirically, we use firm-level data for six African countries - DRC, Ghana, Kenya, Uganda, Tanzania and Zambia, from the enterprise survey 2013 and the companion 2014 innovation module. The survey has an ICT module that measures computer, software and internet use; and it is comparable across the six African countries.

Overall, the findings of the paper suggest that larger, younger, more internationalized –foreign owned, importers, certified and with foreign technology license firms that are financially unconstrained and operate under higher degrees of competition are more likely on average to adopt ICT practices. The results also suggest a positive and significant impact of ICT on innovation; measured along the dimensions of the firm’s products, processes and organizational practices. Consequently, we find that ICT acts as an important enabler of innovation. The impact of these innovations on productivity are, however, only significant when more “radical” definitions of innovation are adopted. The results for the country by country regressions are more heterogeneous and show a more complex picture, but the positive impact of ICT on innovation is robust across countries and types of ICT.

The paper is structured as follows. The next section summarizes the existing evidence on the impact of ICT on productivity, mainly in OECD countries. Section 3 briefly defines ICT and section 4 describes the methodology used. Section 5 provides a description of ICT use in these six African countries. Section 6 assesses whether ICT firms are more productive, as well as measuring the impact of
<!-- Start of picture text --> Figure 7. Effective tariffs across various consumption levels<br>a. Highly increasing b. Moderately increasing<br>40 40<br>30 30<br>20 20<br>10 10<br>0 0<br>50 75 100 150 200 300 400 450 500 900 50 75 100 150 200 300 400 450 500 900<br>monthly consumption, kWh monthly consumption, kWh<br>Cape Verde Côte d'Ivoire Madagascar<br>Chad Kenya Mali Tanzania Uganda Zimbabwe<br>c. Neutral d. Decreasing<br>40 40<br>30 30<br>20 20<br>10 10<br>0 0<br>50 75 100 150 200 300 400 450 500 900 50 75 100 150 200 300 400 450 500 900<br>monthly consumption, kWh monthly consumption, kWh<br>Cameroon Malawi Senegal<br>Burkina Faso Congo, Dem. Rep. Niger Zambia Congo, Rep. Botswana<br>US cents per kWh US cents per kWh<br>US cents per kWh US cents per kWh<br><!-- End of picture text --> _Source:_ Africa Infrastructure Country Diagnostic Power Tariff Database

# **b. What is the level of average effective nonresidential tariffs?**

As for residential tariffs, one commercial and one industrial schedule per country were selected for our analysis of nonresidential tariffs. Representative or typical _commercial_ customers are defined as small to medium business users with an average consumption level of 900 kWh/month. Representative or typical _industrial_ customers are medium to large business users usually associated with high-voltage, highusage tariffs. But in order to exclude very large industries with preferential tariffs from our analysis, we did not use the highest voltage bracket included in tariff schedules (box 1). In cases where tariff schedules for commercial and industrial users are not differentiated or where several tariffs apply to commercial users, tariff
parental involvement in children’s education due to migration. In the next section, possible transmission channels will be discussed in more detail.

# VI.  TRANSMISSION CHANNELS AND ROBUSTNESS

According to the community leaders interviewed in the survey, the most widely perceived constraint to school quality is not a scarcity of staff but of other inputs, such as teaching materials or utilities (table S.10). Parental education inputs could be affected by the public funding situation of local schools, causing omitted variable bias.<sup>28</sup> Thus, we match our household data with administrative school-level expenditure data from an open budget initiative of the

> 28. Private educational spending responds to public funding, see for example Houtenville and Conway <u>(2008).</u>

14
# **Conclusion**

This analysis makes possible an evidence-based discussion of labor markets and jobs in Haiti. Using three harmonized household surveys from 2001 to 2012, the paper provides insights into the evolution of labor markets in a particularly turbulent decade for Haiti marked by the political crisis of 2004 and the earthquake of 2010. The focus is the determinants of labor income, providing a household-level perspective on the larger dynamics of labor markets.

The main message of the analysis is that in spite of the shocks of the period, labor markets in Haiti presented more continuity than change. Self-employment in low-productivity sectors remains the norm outside of the farm sector, a cause for worry. While the share of workers in non-primary informal activities has decreased, this has not translated into an expansion of the formal private sector, but into the swelling of the public sector and NGOs. This puts in question the sustainability of poverty reduction in urban areas, especially in the Metropolitan area, in an environment of decreasing aid. Furthermore, the significant rise in employment rates in recent years was driven mainly by young people taking unpaid work in family businesses.

The analysis of the determinants of labor income in urban areas further echoes those results, showing no signs of sustained structural transformations in the endowments of the labor force or the quality of jobs. Additional analysis details the role of the public and NGO sectors in the wage increase observed, particularly for the lower end of the wage distribution. The analysis also found a stable premium on education and an overall reduction of the wage gap, except in low-productivity sectors where this gap increased over the period to 60 percent.

Generating more and better jobs largely depends on macro-economic factors that are largely outside of households’ control. But the analysis points to persisting structural challenges weighing down the returns workers get from their labor. For that reason, the obvious role that the private sector will have to play in generating growth and employment will need important help from the Haitian state in helping households improve their assets and use them in
>_ <mark>,</mark> _<mark>15</mark>_ <mark>(12), 123005.</mark> **<mark>[</mark> 1]** <mark>McNamara, K. E., Bronen, R., Fernando, N., & Klepp, S. (2018). The complex decision-making of climate-induced relocation: Adaptation and loss and damage.</mark> _<mark>Climate Policy</mark>_ <mark>,</mark> _<mark>18</mark>_ <mark>(1), 111-117.</mark> **<mark>[</mark> 1]** Michler, J. D., Josephson, A., Kilic, T., & Murray, S. (2022). Privacy Protection, Measurement Error, and the Integration of Remote Sensing and Socioeconomic Survey Data. _arXiv preprint arXiv:2202.05220._ **[3]** <mark>Minet, J., Curnel, Y., Gobin, A., Goffart, J. P., Melard, F., Tychon, B., ... & Defourny, P. (2017).</mark> 46
# EXECUTIVE SUMMARY

Developing countries, particularly those in Asia, are fast adopting industrial pollution control standards similar to those in developed countries. However, formal regulation has been greatly hampered by the absence of clear and legally binding rules; limited institutional capacity; lack of appropriate equipment and trained personnel; and inadequate information on emissions. At present, the government-imposed 'price of pollution' is nearly zero for many manufacturing facilities in these economies.

A conventional analysis would predict highly pollutionintensive production under such conditions. However, our research has uncovered strongly contradictory evidence. Despite weak or nonexistent formal regulation and enforcement, there are many clean plants in the developing countries of South and Southeast Asia. Of course, there are also many plants which are among the world's most serious polluters. What explains such extreme interplant variation? This paper reviews the evidence from a survey of pollution abatement by 26 pulp and paper plants in four countries: Bangladesh, India, Indonesia and Thailand.

Our analysis incorporates three sets of factors which may affect the pollution intensity of an industrial process: Relevant **plant characteristics** may include choice of technology, vintage, ownership, management quality, available human resources and technical expertise. Firms' responsiveness to pressure for abatement may also vary significantly with **economic considerations:** input prices, profitability, market characteristics, availability of information on abatement technology, and financing possibilities. Finally, plants may adapt to **external pressure** from government regulators, buyers or investors, and neighboring communities which suffer damage from pollution.

Our results show that all three factors play significant roles. Abatement is positively associated with scale and competitiveness; negatively associated with pubic ownership; and unaffected by foreign links (in ownership or financing). Community pressure, or informal regulation, emerges as a clear source of interplant differences. Under some circumstances, communities successfully pressure plants to abate even if little or no support is available from formal regulation. Our results suggest that local income is a powerful predictor of effective informal
Policy Research Working Paper 9314

# **Abstract**

This paper uses high-resolution satellite data on the proportion of buildings in a 250x250 meter cell to study the evolution of human settlement in Ghana over a 40-year period. The analysis finds a strong increase in built-up area over time, mostly concentrated in the vicinity of roads, and also directly on the coast. There is strong evidence of agglomeration effects in the static sense—buildup in one cell predicts buildup in a nearby cell—and in a dynamic sense—buildup in a cell predicts buildup in that cell later on, and an increase in buildup in nearby cells. These effects are strongest over a radius of 3 to 15 kilometers. No evidence is found that human settlements are spaced more or less equally over the landscape or along roads. By fitting a transition matrix to the data, this paper predicts a sharp increase in the proportion of the country that is densely built-up by the middle and end of the century, but there is no increase in the proportion of partially built-up locations.

This paper is a product of the Development Research 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 fshilpi@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
example by determining whether the registry is updated regularly and whether the rules for operation are appropriate and reasonable. The assessment indicates that overly complex frameworks that are contradictory or cannot be implemented as intended create uncertainty and opportunities for arbitrary enforcement. The report argues that even private providers complain about the lack of oversight, which allows low-quality providers to continue to operate.

While it relies on surveys of experts in each country for information on both governance policies and performance, the IFC study tries to ensure comparability by providing a detailed and clear set of coding principles for all indicators.

# **Measuring Service Quality:  A Parallel and Related Agenda**

At the same time, governments and donors will need indicators of the quality of service delivery. Conceptually, what we want is a set of indicators that let us know how effective the delivery of services is—in effect, how much the services can be expected to improve the health or education of the client. These quality measures can differ from the governance performance measures described in the previous section, because other non-governance factors also affect quality (as represented in Figure 1). The line separating these indicators from the governance performance indicators is a blurry one, but it is useful to try to distinguish the two. For example, an important determinant of the quality of schooling could be whether or not there is a roof over the students’ heads. While the availability of school buildings ultimately depends on governance, it would be a stretch to consider this one of the short- or medium-term ―governance 30
). COVID-19 and gender disparities: Labour market outcomes. Research in Economics, 76(3), 206–217. https://doi.org/10.1016/j.rie.2022.07.011 Tribín, A., Gómez-Barrera, A., Pirela-Rios, A. (2022). Distribución del cuidado, roles de género y poder de negociación en Colombia: Un análisis a partir de la ENUT 2020-2021. Informe Quanta - Cuidado y Género. Recuperado de https://cuidadoygenero.org/distribucion-cuidado-enut

- Tverdostup, M. (2022). COVID-19 and Gender Gaps in Employment, Wages, and Work Hours: Lower Inequalities and Higher Motherhood Penalty. Comparative Economic Studies. https://doi.org/10.1057/s41294-022-00198-z

Urquidi, M., Valencia, H., & Durand, G. (2020). Brecha de ingresos laborales por género en Bolivia: un análisis de su evolución en el periodo 1993 a 2018 (No. 1986; Nota Técnica).

Viollaz, M., Salazar-Saenz, M., Flabbi, L., Bustelo, M., & Bosch, M. (2022). The COVID-19 Pandemic in Latin American and Caribbean Countries: The Labor Supply Impact by Gender (No. 15091; Discussion Paper Series). www.iza.org World Bank. 2023. From Infection to Inflation. LAC Poverty and Labor Brief. © Washington, DC.

Zhou, M., & Kan, M. Y. (2021). The varying impacts of COVID-19 and its related measures in the UK: A year in review. PLoS ONE, 16(September 09). https://doi.org/10.1371/journal.pone.0257286.
P, et al (2015) Estimating Poverty Rates in Target Populations: An Assessment of the Simple Poverty Scorecard and Alternative Approaches. World Bank Group.

Doorenbos, J. & Kassam, A, (1979). Yield response to water. FAO Irrigation and Drainage Paper No. 33. Rome, FAO FEMA (2002). Rapid visual screening of buildings for potential seismic hazards. FEMA, 2002. Retrieved from: <u>http://www.fema.gov/media‐library‐data/20130726‐1646‐20490‐ 8071/fema_154.pdf.</u> Fermont, A, and Benson, T, (2011). Estimating Yield of Food Crops Grown by Smallholder Farmers: A Review in the Uganda Context. International Food Policy Research Institute, IFPRI Discussion Paper 01097, June 2011 Hill, Ruth and C. Porter (2014). The Changing Nature of Vulnerability In Ethiopia. In <u><mark>Ethiopia Poverty Assessment 2014. World Bank Group. 2015. Washington, DC.</mark></u> <mark>https://openknowledge.worldbank.org/handle/10986/21323</mark> 30
Policy Research Working Paper 7920

# **Abstract**

Although the measurement and determinants of poverty have been widely studied, vulnerability, or the threat of future poverty, has been more difficult to investigate due to data paucity. This paper combines nationally representative household data with objective drought and price information to quantify the causes of vulnerability to poverty in Ethiopia. Previous estimates have relied on self-reported shocks and variation in outcomes within a survey, which is inadequate for shocks such as weather and prices that vary more across time than space. Historical distributions of climate and price shocks in each district were used to simulate the probable distribution of future consumption for individual households; these were then used to quantify vulnerability to poverty. The analysis shows that many Ethiopians are unable to protect their consumption against lack of rainfall and sudden increases in food prices. A moderate drought causes a 9 percent reduction in consumption for many rural households, and high inflation causes a 14 percent reduction in the consumption of uneducated households in urban areas. Vulnerability of rural households is considerably higher than that of urban households, despite realized poverty rates being fairly similar. This finding reflects that the household survey in 2011 was conducted during a year of good rainfall but rapid food price inflation. The results highlight the need for caution in using a snapshot of poverty to target programs, as underlying rates of vulnerability can be quite different from the poverty rate captured at one point in time. The results also suggest that significant welfare gains can be made from risk management in both rural and urban areas.

This paper is a product of the Poverty and Equity Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at rhill@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage
the relationship of the migrants to the household.<sup>11</sup> However, because these variables are measured at the household level it is easier to think of arguments that can invalidate them as instruments. In particular, there could be a selection effect where the types of households that send migrants for longer periods of time or who send closer relatives abroad may differ in many ways from other households, including differing in financial access. Hence, though Table A.1 and A.2 show that these instruments pass the exclusion restrictions and our main results are confirmed when using these instruments, we prefer to focus on what we think are likely to be more exogenous instruments: economic conditions in US states where Salvadoran migrants reside.

Table 7A and 7B present the results of the first stage estimations where the likelihood of receiving remittances and the amount of remittances received per capita, respectively, are instrumented with the weighted average of real GDP per capita and/or the poverty rate for US states where Salvadoran migrants reside. We use these instruments separately and jointly. Both in Tables 7A and 7B, the size of the Cragg-Donald F-statistics exceed the Stock and Yogo (2005) critical values, indicating that we do not have a weak instruments problem.

We find that GDP per capita in US states has a positive effect on the likelihood that the household receives remittances (Table 7.A columns (1), (4) and (7)) and on the amount of remittances received (Table 7.B columns (1), (4) and (7)) when this variable is included on its own, without the poverty rate. In turn, the poverty rate has a negative impact on the likelihood that the household receives remittances (Table 7.A columns (2), (3), (5), (6), (8) and (9)) and on the amount received (Table 7.B column (2), (3), (
# **1 Introduction**

The dramatic rise in pirate attacks off the coast of Somalia over the years 2005-2011 stunned the international community. In total, 1,101 reported attacks have been attributed to Somali pirates, resulting in the hijacking of 217 vessels and their crews and an estimated US$338m paid in ransoms. Equally astonishing was its collapse in 2012, which has been largely sustained until now. The eradication of Somali piracy has been attributed to the deployment of naval assets in the Western Indian Ocean, celebrated as a rare show of international military collaboration, and to the increased use by shipping companies of private security contractors on board vessels sailing through pirate-infested waters.

In this paper, we focus on the tension between the two aforementioned forms of protection against crime, one publicly- and the other privately-provided, which led to its demise. To do so, we set up a structural model of Somali piracy, which we estimate using novel and rich data on incidents attributed to Somali pirates. On the one hand, the effect of international navy patrols is found to have been modest overall. On the other hand, the private provision of security was instrumental and characterized by both deterrence and crime displacement externalities.

The Somali piracy business model that we look at is exclusively a kidnap-and-ransom model, whereby the sole purpose of hijacking a vessel is to “sell” her back in her entirety to the shipping company as opposed to cargo and vessel theft, more prevalent elsewhere in the world. Attacks are launched against vessels sailing through the Gulf of Aden and beyond. When successful, vessel and crew are brought back to Somalia’s shores and a separate team takes over to protect and maintain the ship and feed the crew while negotiation with the shipping company for their liberation takes place.

Therefore, we model pirates as infinitely-lived agents who, in each period, decide whether to launch an attack against ships sailing off the coast of Somalia and when they do, choose what vessel to target. If successful, a bargaining game
is not as internationally comparable and available than data on trade (Egger, Nigai, and Strecker, 2019). Further, to our knowledge, the literature has not identified a credible instrumental variable for capital openness (Magud, Reinhart, and Rogoff, 2011; Alfaro, Kalemli-Ozcan, and Volosovych, 2005).39 Notwithstanding, we provide here some evidence on the impact of capital liberalization based on an event-study design.

We rely on Chari, Henry, and Sasson (2012) who identified capital liberalization events in 25 developing countries corresponding to the date when foreign investment in the domestic stock market was first allowed.40 The paper shows that these seemingly narrow events actually greatly expand foreign capital flows into the country, including foreign direct investment (FDI), and raise the import of capital goods.41 Compared to other reforms aimed at lifting restrictions on FDI, opening the domestic stock market internationally occurs at a precise point in time (other policies are often less precise and staggered); is not marked by policy-reversal or by net capital outflow; and is unambiguously related to capital liberalization (Henry, 2007; Eichengreen, 2001).

We employ the same empirical design as in in Section 6, and create a synthetic control for each treated country and outcome of interest (see Appendix C.3 for details). We measure capital openness as the sum of foreign assets and liabilities, as a share of GDP (Lane and Milesi-Ferreti, 2017). Figure 8 reports the results.42 Starting from a stable pre-trend, we observe a rise in capital openness, precisely at the time of the event, which keeps on building over the post-event decade. The _ETRK_ also increases, but with a few years lag relative to the event: in the medium-run, the effect is precisely estimated and significant

> 39Trade and capital flows may also exhibit strong co-movement. Per example, as the cost of importing intermediate goods decreases, a firm can decide to outsource the production of intermediate goods abroad – which may result in an outflow