rafmacalaba/datause-encoder-data huggingface dataset:
greater, or stated differently, that population density does not have the same benefits for health where sanitation is poor. These results are biologically plausible because open defecation leads to environmental contamination with germs from feces, and these germs are more likely to cause disease where people are more likely to come in contact with them.

Although resolving longstanding debates about the health advantages or penalties of living in urban or densely-populated areas is well beyond the scope of this paper, our results suggest some clarifications about the importance of place for child health in developing countries. We have isolated that high population density and poor sanitation _in combination_ are particularly threatening to early life health. Our results suggest that high density _without_ poor sanitation is substantially less dangerous, such that the advantages of access to health care and other resources might dominate the disadvantages of disease externalities, yielding a net health benefit of living in dense cities (Leon, 2008). Additionally, urban settings with low population density may not be disadvantaged relative to rural settings with high population density.

Our result has an important implication for policy-makers: for a given level of open defection, concentrate attention on improving sanitation where population density is high, or at minimum include population density as a factor in allocation decisions. To emphasize, this does not exclusively or even necessarily recommend that sanitation policy attend to urban places. Population density is a continuous variable, and many parts of the developing world that are classified as rural have higher population densities than places classified as urban. The latest estimates of open defecation and population density in the developing world suggest an increasing concentration of open defecation in densely populated parts of rural India, which poses a significant threat to the health of children in these regions, despite their “rural”<sup>13</sup>

> 13According to the Unicef-WHO statistics, open defecation is increasingly a South Asian, and particularly an Indian, problem. Although Bangladesh has drastically reduced open defecation, and Pakistan has seen marked improvements, there continues to be more open defecation in India than there is toilet or latrine use. 60% of open defecation in the world occurs in India, a country where 70% of households live in rural areas, and 70% of rural households defecate in the open. Primarily rural Indian states like Uttar Pradesh and Bihar, home to about 300 million people, have population densities that exceed 800 persons per square

23
remaining ASEAN member countries. Indeed, data from _Doing Business_ suggest that even Malaysia and Thailand have room for further streamlining and simplification of customs procedures.

One caveat in relation to these conclusions relates to data availability. Tables 1-3 summarize the extent of the available information for the period 2000-2005 across ASEAN member countries. Our dataset is most complete for trade data (export and import flows). Table 1 shows that data are missing over all years only for Laos and Myanmar. Although Vietnam, Brunei, and Cambodia are each missing one or two years of information, the dataset is reasonably complete as regards other ASEAN member countries. In relation to applied tariffs, Table 1 indicates that data are available for all ASEAN member countries, albeit with some missing observations for around half of them.

The picture is generally less detailed in relation to our other indicators. While _Doing Business_ indicators on the cost and time of exporting and importing have good country coverage—all except Brunei and Myanmar—they are only available for two years (time) or one year (cost). However, data from the Global Competitiveness Report are not available at all for Brunei, Cambodia, Laos, or Myanmar.

This short review of the available data highlights two issues that will need greater attention in future work. First, lack of data across these basic indicators means that there are a number of ASEAN countries—Brunei, Cambodia, Laos, and Myanmar—for which it will be very difficult to perform individualized analysis and to tailor policy measures to their particular situations. For the moment, we will essentially be extrapolating from other countries’ experiences, which is not entirely satisfactory. Second, we have only addressed one subset of the possible indicators that might be of interest in a trade facilitation setting. Other indicators, such as the pervasiveness of

- 11 -
# **I Background Information**

Data collection was assisted by our partner, the NGO PRADAN. Its main mission is the improvement of forest-based livelihoods and natural resource management of socioeconomically disadvantaged people. It pioneered the creation of SHGs (consisting entirely of women) as an instrument to achieve its mission (PRADAN, 2005).

In 2006, all the PRADAN SHGs created in the Mayurbhanj and Keonjhar districts of Odisha were surveyed, independent of whether the groups were still actively meeting or not. The data set contains of 532 SHGs and 8,589 women who, at some point, belonged to these groups (Baland et al., 2008). In the autumn of 2010, we complemented this data set in two ways. First, we revisited these SHGs to gather information on the collective actions they undertook. Second, we performed a ward survey to collect data on the characteristics and activities of ward members. As PRADAN started working in Odisha in 1998, and as we needed information dating back to the period before the creation of the first SHG, we interviewed the ward members elected in 1992, 1997, 2002 and 2007.<sup>5</sup> We asked them to recall the types of issues they dealt with, i.e. the type of issues for which they visited a higher official or intervened directly in the ward.<sup>6</sup> In total, we gathered information on 425 SHGs, and we have complete information on 441 ward members, covering 108 villages and 141 wards.<sup>7</sup> Wards are in most cases smaller than villages. On average, there are 1.3 wards per village. Villages and wards coincide for 75% of the villages in our data set. Wards are larger than villages for 8 small villages only. These 8 villages belong to 4 different wards.

> 5Elections take place every 5 years. Ward members can be re-elected.

> 6To avoid a recall bias - which occurs if ward members elected in 1992 remember less of their interventions than those elected in 2007 - we gathered information as follows: first, we conducted focus group discussions in a subset of wards to list (as many as possible) ward problems. Based on this information, we defined the six broad categories that are described in the Appendix S1 (for example, problems related to a well or a road are both categorised as “public infrastructure”). Second, when interviewing the ward members, we first asked the type of issues they dealt with as an open question and then we proposed the categories they had not mentioned.

> 7We were not able to resurvey 21 villages (62 SHGs) because of social tensions created by a private mining firm (the roads to those villages were blocked). Another 45 groups that no longer meet refused to be re-surveyed. 34 of those groups are based in wards where other SHGs are still meeting. Thus, for those we obtained all the information needed for our analysis.

5
those appearing in the income and consumption regressions (4). We see that family background variables are signi fi cant. Using this selection regression we construct the two Mills ratio shown in equation (6), one for migrants and one for non-migrants, and we reestimate the income and consumption regressions with these additional regressors, obtain corrected<sup>�</sup> δ s and �η s estimates, and reestimate the destination choice regressions. Results are nearly indistinguishable from those reported in Tables 4 and 5. They are omitted here to save space.

� When constructing E[ys<sup>h</sup> |z<sup>h</sup> ] we implicitly assume that migrants are well informed about incomes in all potential destinations. But it is possible that they are better informed about certain destinations, for instance, destinations chosen by migrants from their district in the past. Failing to control for this possibility may lead to an attenuation bias in the income coe ffi cient. To investigate this possibility, we interacted the income variable with a proxy for the availability of income information. If migrants only respond to income di ff erences for those districts on which they have more accurate information, the coe ffi cient of the interacted term should be signi fi cant even if the uninteracted term is not. As proxy for the availability of information, we use the number of adult males who migrated more than 5 years ago (that is before the migrants themselves) from the district of origin to each of the districts of destination. The coe ffi cient of the interacted term is minuscule in magnitude and uniformly non-signi fi cant. The same fi nding obtains whether we use all migrants or only work migrants.

As a fi nal robustness check, we reestimate the model using migrant data from the NLSS 2002/03. The number of migrants is signi fi cantly smaller, so results may be less precise. The advantage of this approach is that it serves as cross-validation. Results are presented in Tables 6 and 7. Table 6 should be compared with Table 4, and Table 7 with Table 5.

Comparing Tables 6 and 4, we again fi nd that anticipated income, whether absolute or relative, is either non-signi fi cant or negative. Most of our other results obtain. Exceptions 28
# **Infrastructure and Economic Growth in Egypt**

## **I. Introduction**

Over the last five decades, infrastructure in Egypt has experienced a remarkable improvement. This has undoubtedly supported the relatively strong economic growth performance of the country, as well as contributed to the progress in social and economic well-being of its citizens. Despite this progress, in the last years there has been a slowdown or even a decline in some areas of infrastructure, particularly power generation and transportation. Associated with this decline, capital expenditures in Egypt have been reduced in the last decade, raising concerns that the country may have reached an unsustainably low level of infrastructure investment.

This paper analyzes the situation, trends, and effects of infrastructure in Egypt. It does so by placing the Egyptian experience in an international context. The paper examines the major sectors of infrastructure, including electricity generation, transportation, telecommunication, and water and sanitation. It assesses how infrastructure measures in Egypt currently compare with the rest of the world, particularly countries at similar level of economic development. It also reviews the historical trends in these infrastructure measures and projects their likely improvement in the future. Then, the paper describes the trends in infrastructure expenditures in Egypt, comparing to the extent possible their differing patterns across types of infrastructure and for different times in the last five decades. To serve as benchmark, the paper also presents the trends in infrastructure expenditures in a few other countries, paying special attention to the increasing role in private investment in certain infrastructure sectors.

The paper links the progress in infrastructure with an increase in the rate of economic growth in the country. This is a central task of the paper. It consists of first estimating how infrastructure investment expenditures have led to infrastructure improvements and this, in turn, to higher economic growth. Estimating the connection between expenditures and growth cannot be done in a single step for lack of sufficient data. Thus, it is done in two steps. First, using panel (cross-country and time-series) data, the paper estimates the link between the level of infrastructure and economic growth.

2
Hlasny, V., and P. Verme. “Top Incomes and the Measurement of Inequality in Egypt.” _World Bank Economic Review_ 32 (2018): 428-455.

- Hirschman, A. O., and M. Rothschild. “The Changing Tolerance for Income Inequality in the Course of Economic Development.” _The Quarterly Journal of Economics_ 23 (1973): 544566.

- Ianchovichina, E., Mottaghi, L., and S. Devarajan. _Inequality, Uprisings, and Conflict in the Arab World_ . Economic Monitor, World Bank Group,Washington, D.C., 2015. - -

- <u>http://documents.worldbank.org/curated/en/303441467992017147/Inequality uprisings and-conflict-in-the-Arab-World</u>

- Khan, Haider A., Human development and capabilities in MENA economies with special emphasis on Egypt, Working Paper 39381, Munich Personal RePEc Archive, 2011. <u>https://ideas.repec.org/p/pra/mprapa/39381.html</u>

- Khan, H. A., Schettino, F., and A. Gabriele. _Polarization and the Middle Class in China: a NonParametric Evaluation Using CHNS and CHIP Data_ . Working Paper 86133, Munich Personal RePEc Archive, 2017. <u>https://mpra.ub.uni-muenchen.de/86133/</u>

- Khan, H.A., and F. Schettino. _Income Polarization in the USA: What Happened to the Middle Class in the Last Few Decades?_ Mimeo, 2019.

Kolm, S. “Unequal Inequalities, I.” _Journal of Economic Theory_ 12: 416-442.

- Massari, R., M. G. Pittau, and R. Zelli. “A Dwindling Middle Class? Italian Evidence in the 2000s.” _Journal of Economic Inequality_ 7 (2009a): 333-350.

- Massari, R., M. G. Pittau, and R. Zelli. “Caos calmo: l'evoluzione dei redditi familiari in Italia.” In _L'Italia delle disuguaglianze_ , edited by L. Cappellari, P. Naticchioni and S. Staffolani, 19-28. Rome: Carocci editore, 2009b.

- Milanovic, B. “Global Inequality Recalculated and Updated: The Effect of New PPP Estimates on Global Inequality and 2005 Estimates.” _Journal of Economic Inequality_ 10 (2012): 1-18.

- Milanovic, B. “True World Income Distribution, 1998 and 1993: First Calculation Based on Household Surveys Alone.” _Economic Journal_ 112 (2002): 51-92.

- Muller, E. N. “Income Inequality, Regime Repressiveness, and Political Violence.” _American Sociological Review_ 50 (1985): 47-61.

- Niño-Zarazúa, M., L. Roope, and F. Tarp. “Global Inequality: Relatively Lower, Absolutely Higher.” _Review of Income and Wealth_ 63 (2017): 661-684.

37
as a protected reserve. World Bank (2011) therefore values protected areas at the same perhectare value as what is, on average, the least productive agricultural land in a given country – hence the notion of a ‘quasi-opportunity cost.’<sup>10</sup> The assumption is that the government establishing a protected area values the newly protected land at least as much as if it were in its alternative agriculture use. As such, the quasi-opportunity cost is therefore a lower bound on the value of protected areas.

What we analyze in the following subsections is therefore easily a third-best measure of the value of biodiversity in national balance sheets. But the analysis is not without interest, and it leads to some tentative policy conclusions.

# _Protected area rents in relation to GDP_

While World Bank (2011) publishes the asset value of protected areas – it forms part of the aggregate value of natural capital and, more broadly, comprehensive wealth – here we focus on the annual land rent from protected areas (‘PA rents’) per capita.<sup>11</sup> The natural question to ask is how this is related to GDP per capita across countries, and Figure 1 provides the answer.

**Figure 1.  PA rents per capita vs. GDP per capita, 2005**

<!-- Start of picture text --> 1,400<br>1,200<br>1,000<br>800<br>600<br>400<br>200<br>0<br>0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000<br>GDP, $ / capita<br>Annual PA rent, $ / capita<br><!-- End of picture text --> Source: Derived from data published in World Bank (2011)

> 10 In practice, World Bank (2011) uses the lower of cropland and pastureland average per-hectare values in each country. For simplicity we refer to ‘opportunity costs’ in lieu of ‘quasi-opportunity costs’ in what follows. 11 World Bank (2011) attempts to value the wealth available to the current generation, and therefore calculates land asset values as the present value of land rents over a 25 year horizon.

11
environmental issues.” Cohen, Stanley States of Denial: Knowing About Atrocities and Suffering, Polity Press, 2001.

Cohen provides in depth coverage of how people avoid uncomfortable situations on the personal level, as well as how personal avoidance is translated into political avoidance and vice versa. Using case studies from the Holocaust as well as other cases of genocides, torture and political massacre, Cohen examines the denial behaviors of both perpetrators and bystanders, discussing the phenomena of the "passive bystander" and “compassion fatigue.” Immerwahr, John 1999. Waiting for a Signal: Public Attitudes toward Global Warming, the Environment and Geophysical Research. Public Agenda/ American Geophysical Union.

One of the first studies to examine why there is an indirect link between a person’s knowledge of climate science and whether or not they take action (e.g. to go against the information deficit approach). Immerwahr conducts focus groups on climate change (and other issues) and concludes regarding climate change in particular that respondents, “seemed to have hit a wall.” Respondents did show deep concern regarding global warming, but their concern did not translate into action: “our research suggests that what the public is most skeptical about is not the existence of problems but our ability to solve them.” Thus, Immerwahr cautions that “informing the public of the problems can increase frustration and apathy rather than build support.” In order to promote action regarding climate change the author suggests not more information, but actions that can be taken.

Kellstedt, Paul, Sammy Zahran and Arnold Vedlitz 2008. Personal Efficacy, the Information Environment, and Attitudes Toward Global Warming and Climate Change in the United States <u>Risk Analysis 28( 1): 113-126.</u> Authors use survey data to examine the role of information, confidence in scientists and personal efficacy in shaping respondent’s risk assessment regarding climate change. Their results strongly counter the information deficit approach. Specifically, they find that the degree of information a person has regarding climate change, their confidence in scientists and their personal efficacy regarding climate change interact so that the more informed respondents both feel less personally responsible for global warming and also show less concern.

Krosnick, Jon, Allyson Holbrook, Laura Lowe and Penny Visser 2006 “The Origins and Consequences of Democratic Citizen’s Policy Agendas: A Study of Popular Concern about Global Warming” Climate Change 77:7-43.

Stanford social psychologist Krosnic has a long history of work in this area. This paper contributes to work on the complexity of the relationship between efficacy and action regarding climate change. The authors evaluate both causes and 56
shortly. In addition to this increase in exports, we observe a higher rate of new products exported to the US than to the EU at the HS6-level during the period.<sup>5</sup> We proceed as follows. Section 2 describes the conditions for preferential access of African apparel to the US and EU markets and the introduction of the Special Rule under AGOA. Section 3 describes the timing of the introduction of the Special Rule and the evolution of aggregate exports of Textiles and Apparel. The remaining sections turn to estimates at the disaggregate level (HS-4 or HS-6 levels) to capture the effects of technical requirements which are defined at the HS-4 level in Textiles and Apparel. Section 4 presents the data and the econometric strategy to deal with the many zero observations in the sample. Section 5 reports the results from disentangling the effects of the Special Rule from those following from the reduction in tariffs in the US market. Section 6 then studies the evolution of new apparel varieties during the period using a count model. Section 7 concludes.

# **2. Qualifying for Preferential Market Access Under EU and US Preferences in Textiles and Apparel**

_Market Access to the EU: Apparel under the Generalized System of Preferences (GSP) and Everything But Arms_ . Since 1971, the Generalized System of Preferences (GSP) provides nonreciprocal preferential access to the EU market. For textiles and apparel, the product-specific RoO required that apparel should be manufactured from qualifying yarn (i.e. yarn originating in the country or in the EU). Production from yarn entails that a double transformation process (yarn → textile → apparel) must take place in the beneficiary country with the yarn being woven into fabric and then the fabric cut and made-up into clothing.<sup>6</sup>

> 5 Strong response to a reduction in fixed costs associated with meeting origin requirements are also obtained by Cherkashin et al. (2010) who study the effects of granting preferences with and without RoO for exports of woven apparel from Bangladesh. Their study is for a cross-section of 200 Bangladeshi firms (data collected over the period 1999-2004) exporting woven textiles to the EU and US markets under much the same assumptions as ours: all production is for exports, and exports are destined to one or both the EU and US markets.  They estimate that a $1 reduction in fixed costs would generate an increase in exports in the range 10$-40$ and conclude that easy-to-obtain preferences and/or reduction in fixed costs can have a catalytic effect and that preferences need not divert trade from other markets as predicted in a setting with no fixed costs. Though the methodology is different and they do not study the costs of RoO in a dynamic context panel like us, the magnitude of their estimates are in line with ours.

6 Under the EU’s “Single List”—also called ‘PANEURO’-- in operation since 2000, the EU GSP system also accepted bilateral cumulation between the EU and a beneficiary country (cumulation provisions allow contracting parties to use intermediate goods from each other without losing origin status). Similar rules were applied for Everything But Arms and 5