rafmacalaba/data-use-mentions-extended huggingface dataset:
or even lower odds of experiencing adequate stimulation through responsive interactions, ranging from 26 percent in Punjab, to 29 percent in Khyber Pakhtunkhwa to 45 percent in Sindh (Tomlinson et al., forthcoming).<sup>2</sup> However, more recent data collected in Punjab during the first year of pandemic disruptions indicated higher levels of psychosocial stimulation from caregivers relative to playing (86 percent), looking at a book (90 percent), or telling a story (86 percent) in the prior 15 days (ITA, 2021).

Access to child-oriented learning materials at home is also low. In addition to the critical stimulation that occurs through engaging interactions, children learn through exploration and manipulation of objects such as toys, picture books, dress-up objects, and other playthings. Across provinces and settings, less than 9 percent of 3- to 5-year-olds in Pakistan and less than 2 percent of 0- to 2-year-olds have access to books at home (Tomlinson et al., forthcoming). These low rates of access to learning materials at home contribute further to insufficient opportunities for early learning for too many children, and those living in poverty or experiencing losses in the face of the pandemic are most likely to be left out. The cumulative lack of adequate social-

> 2 Data on caregiver engagement with stimulating activities was not collected for children in Balochistan under the age of 3 in the 2010 MICS survey. The 2019-2020 data in Balochistan is forthcoming, but not yet available.

6
# **6. Conclusion**

In this paper, we have estimated the impact of COVID-19 on global inequality and poverty in 2020. Due to sparsity of income and consumption data for 2020 from traditional household surveys, we have relied on a combination of alternative data sources. In particular, we use household survey data available for 20 countries; for a further 8 countries, we use tabulated income data reported by national statistical offices; next, for 37 low- and middle-income countries, we use information from High-Frequency Phone Surveys together with pre-pandemic welfare vectors and sectoral growth rates to model the impact of the pandemic along the countries' income distribution; for a further 26 countries, we rely on data from country studies in the literature. Finally, for countries without the aforementioned data sources, we rely on per capita growth observed in national accounts.

We find that the pandemic caused the largest single-year increase in global inequality and poverty since at least 1990. On both fronts, the pandemic erases at least three years of progress. Concretely, we find that the global Gini index in 2020 increased by 0.7 point (or around 1%) compared to 2019 and that the number of people living below the international poverty line of $2.15-a-day PPP USD increased by 90 million people. The increase in poverty is driven by the countrywide economic shocks that almost all countries experienced. The increase in the Gini is driven by poorer countries facing larger economic shocks from the pandemic. Changes to inequality within countries, on the other hand, counteracted the increases to global inequality and poverty as many countries, particularly populous ones, experienced a decline in inequality. If the pandemic had hit all people within countries equally, its impact on global inequality would have been even larger. In low-income countries, this is likely due to the pandemic not hitting rural areas (where the poor predominantly live) as forcefully, while in high-income countries this is likely due to the extensive social protection programs implemented in 2020.

All our results relate to
school level, teachers complete the questionnaires delivered to them. These questionnaires are collected by district government officials and returned to the provincial education department, where the information is digitized.

Using the annual censuses, we construct a school-level panel.<sup>13</sup> On the basis of this panel, we construct the outcome measure—the absolute change in school-level girls’ enrollment in secondary grades for six subperiods of different lengths originating from baseline (2003): 2003–05, 2003–07, 2003–09, 2003–11, 2003–13, and 2003–15.

# _Empirical strategy_

We estimate program effects on the basis of a sharp RD design. One of two outcomes is possible for school s, conditional on the district literacy rate X�. Schools in districts with a literacy rate below 40 percent ( _X D_  40) are covered by the program. These schools have a potential girls’ secondary school enrollment outcome of<sup>_Y_</sup> _s_  1 . Schools in districts with a literacy rate equal to or above 40 percent ( _X D_  40) are not covered by the program. These schools have a potential outcome of _YS_ (0) . In theory, the average observed outcomes, given _X D_ , are two functions:  _YS_ (1)| _XD_  if _X D_  40 and  _YS_ (0)| _X D_  if _X D_  40 . The sharp

RD program effect at the cutoff,  _RD_ , reflects the difference between  _YS_ (1)| _XD_  and

(1)

> 13 While government schools are assigned unique identification (ID) numbers, school ID protocols were adjusted by the provincial and district education departments in certain years and assigned school IDs were not strictly adhered to during data collection, entry, and processing. Consequently, to construct an accurate school-level panel, we worked closely with provincial education department officials with intimate working knowledge of the Annual School Census data
with direct compensation for work as a cadre. In short, our results indicate that in rural China cadre households may have some advantage from cadre status to in gaining privileged access to jobs in businesses and economic activities managed by villages, but these may derive from either political connections or the information advantages that come along with cadre status. These jobs were usually well paid relative to farming and in high demand by villagers. According to the RCRE panel data, this is the only source of higher incomes associated with cadre status in rural China.<sup>28</sup>

**_Relationship to Returns to Communist Party Membership_** _._ Cadre status and membership in the Communist Party are closely related in rural China. First, only Communist Party members can be inducted into the village party committee. Second, although the village committee (as opposed to village party committee) does not require its members to be a Communist Party members, being a Communist Party member helps one to be nominated to the village committee. In the early period covered by this survey, when the township government appointed village cadres, it typically gave priority to Communist Party members in the village. However, since the introduction of village elections, the village committee is elected by villagers and as a result it is not necessarily comprised of Party members.

> 28 One of the potential indirect benefits of being a cadre could be that being a cadre helps the other members of the family gain access to local off-farm employment or higher wages in such employment.  If some of the benefited family members move out and form their own households and their income is no longer included in the cadre‘s own household income, then the long-term benefits of being a cadre will be understated by the income returns to cadre households shown in the paper.  Unfortunately, since the RCRE survey was conducted at the household level and did not collect data on each family member and track each family member, we are not able to examine how being a cadre affects the incomes
.576|

_Notes_ : The regressions are OLS estimations of equation (2) for the period 1999-2005. The dependent variable is the logarithm of firm _f_ ’s export sales to country _j_ in year _t_ . Fixed effects by firm, country and year and a constant are included in all specifications. The destinations are China and other Asian countries that already integrate WTO such as India, Indonesia, Korea, Japan, Pakistan, Philippines, Singapore and Thailand. Tariff _fjt_ is the tariff measure faced by firm _f_ when exporting to country _j_ in year _t_ . Tariff _fjt ×_ China _j_ is an interaction term between the firm level tariff measure and a dummy variable equal to one when the country of destination of exports is China and zero otherwise, China _j_ . GDP _jt_ is the natural log of the GDP of country _j_ from the Penn World Tables. RER _jt_ is the bilateral real exchange rate between France and China and countries in the control group using producer prices of France and importer countries from the International Financial Statistics (IFS). Heteroskedasticity-robust standard errors clustered by firm-country pairs are reported in parentheses. _∗∗∗, ∗∗,_ and _∗_ indicate significance at the 1, 5 and 10 percent levels respectively.

# _Unilateral Trade Liberalization and Foreign competition_

The findings presented in the previous section might suffer from an important omitted variable bias related to foreign competition faced by each firm in the destination market. To control for this issue, the baseline specification in (2) is extended to include our three firm-level measures of foreign competition.<sup>20</sup> A positive and significant coefficient for both Herfindahl indexes implies that an increase in foreign competition in destination _j_ faced by each firm (i.e. a reduction in the firm level Herfindahl concentration index) reduces the number of products exported and export sales to that destination. On the other hand, for the intensive margin competition measure, we expect a negative and significant coefficient. This measure captures the variation on the volume of
Table A.2: Share of second-generation refugees in Greece (European Social Survey: rounds 2002, 2004, and 2010)

||Percentage<br>|of respondents with<br>||
|---|---|---|---|
|Decade of birth|Parents born<br>in Turkey|Foreign-born parents<br>(outside Turkey)|Number of<br>respondents|
|1910–1920|2.82|2.82|71|
|1920–1930|10.91|4.65|559|
|1930–1940|14.70|3.09|1102|
|1940–1950|9.18|3.13|991|
|1950–1960|3.59|1.64|976|
|1960–1970|1.32|1.23|1137|
|1970–1980|0.36|1.19|1097|
|1980–1990|0.26|2.08|768|
|1990–2000|0.00|7.58|211|

**Notes** This table shows the share of respondents with at least one parent born in Turkey and with at least parent born in another foreign country other than Turkey across decades of birth. Source: European Social Survey, Greece sample for rounds 2002, 2004, and 2010.

Table A.3: Descriptive statistics: numbers of schools in the 1920s

||Low-refugee Province|High-refugee Provi|nce|
|---|---|---|---|
||(1)|(2)|(2)-(1)|
|Number of schools in 1921 per 1000 children|7.335|3.184|-4.151***|
||(0.213)|(0.382)|(0.456)|
|Number of
# **4.2 Estimation Strategy**

Here we proceed in two stages. First, we describe the methodology to assess the relationship between services sector reform and performance, and second, that used to assess the link between services sector reform and manufacturing productivity.

## **4.2.1. Reform and Perception-Based Performance**

For reforms in the services sector to have an effect on manufacturing productivity, a preliminary condition is that these reforms affect somehow the performance of the services sector, either by affecting the quality, availability or price of the services provided in the economy.

Unfortunately, data on services performance in Indonesia are scarce. For this reason, here we use a perception based indicator of services performance. To construct them, we combined data on perceptions from the World Bank Enterprise Survey and on input-output data from BPS, and proceeded in the following steps:

1. We looked at firms’ responses to questions on whether electricity, transport or communications were ‘no obstacle’ to doing business, a minor obstacle, a moderate obstacle, a major obstacle or a very severe obstacle in 2003 and in 2009. Across all three sectors, the proportion of firms reporting ‘no obstacle’ increased significantly (electricity: 22.3%, telecommunications: 20.8%, transport: 17.8%) between 2003 and 2009. This suggests improved service sector performance.

2. We looked at how the degree of restrictiveness on FDI evolved over this period, relying on the OECD restrictiveness indicator. We found moderate increases in openness in the transport and electricity sectors, while restrictiveness increased after 2007 for the telecommunications sector.

3. Using data from input-output tables we constructed for each manufacturing sub-sector an index of performance of the services sub-sectors from which they sourced inputs, and an index of restrictiveness toward FDI in those same service sub-sectors (see Figure 9, a formal description of the way in which the index is calculated is presented below).

4. We then explored the link between these
changes, representing a successful case of deep integration.<sup>4</sup>

# 3.2 Firm Size and Integration Status

In order to see how the post NAFTA/devaluation affected the performance of Mexican manufacturing firms, we use firm-level data from the Annual Industrial Survey (EIA) covering the period from 1993 to 2002. EIA surveys more than 5,000 firms covering 85 percent of total industrial production. The survey provides plant-level information on characteristics such as number of employees, hours worked, wages, value of production and sales, exports, value of intermediate inputs, inventories, investment, etc. (for more detail see Iacovone (2008)).

As we mentioned before, using the theoretical considerations discussed in Section 2 we allocate firms into one of the following four mutually exclusive groups according to their integration status: (1) exporters, (2) importers, (3) fully integrated, and (4) nonintegrated firms. The first group consists of firms that are exporting into the foreign markets without importing intermediate goods; the second group is made up of firms whose only link with the global markets is via the import of intermediate inputs. The third group is formed by all those firms that sell part of their final production in the foreign markets while importing part of their intermediate inputs. Finally, the last group consists of firms that do not have any direct link with foreign markets.<sup>5</sup> Figures 3 shows information regarding the number of firms and their size by integration status for a given year (1997). In 1997, 2,372 firms, representing more than 40 percent of the total manufacturing firms in Mexico, had no direct linkage with the international markets. In that same year, 10 percent of Mexican manufacturing firms were integrated to international markets via exports, 19 percent via imports, and 28 percent were importing intermediate inputs and exporting their final product (fully integrated).

4 By means of an explicit econometric model linking tariff reduction
allows to increase the sample of LLMs significantly with respect to the official number of 59 Metropolitan Areas defined by the Statistical Institute (INEGI). Using a combination of commuting flows and satellite night light data, the authors group 2,446 municipalities into 1,534 functional territories. The assumption is that groups of municipalities that exhibit high levels of commuting flows among them, and that represent a single geographical unit according to the night light data form a functional territory. These functional territories include large metropolitan areas such as Mexico City, which contains 88 mu-

12
# IV. Summary and Conclusions

Our analysis of the data on exports to the United States over the period 1990-2000 yields several stylized facts regarding export quality. In addition to the considerable initial heterogeneity in the relative quality of exports across countries and across goods within countries, we find that countries vary substantially in the rate at which they improve the unit values of their exports. Specifically, the fastest rise in unit values is seen in exports from the richer (OECD) countries, implying an evolving divergence in product quality across regions. This divergence obtains despite evidence of conditional convergence in quality over time (with goods with lower initial relative quality levels experiencing faster growth in quality). The data suggest that the divergence in quality between OECD and non OECD countries is partially driven by the product mix (i.e., the fact that products exported by the OECD experience intrinsically higher growth rates), consistent with the argument of Hausmann, Hwang and Rodrik (2007) that what you export does matter for growth. However, it is also driven by the higher average growth rate in OECD countries, controlling for product mix, suggesting that other country-specific factors impeding convergence are at work. Finally, there is very limited technological “leap-frogging” by countries across product lines as the relative quality of new exports, on average, is roughly the same as incumbent exports, both in OECD countries and elsewhere.

> 2403914390 (Hammers and Sledge Hammers) from Turkey, HS 5205121000 (Cotton Yarn and Sewing thread) from Turkmenistan, HS 8506500000 (Primary batteries, Lithium) from Russia and HS 7209270000 (Flat and Cold Rolled Iron/Steel) from India.

13
the lessons learned are directly applied to such efforts.

The overall goal of this study is to generate information about mobility patterns in Freetown and assess the impact that weather-related events have on the city’s mobility. In particular, the project set out to achieve the following: (1) Generate OD matrices, (2) Generate individual-based mobility characteristics and (3) Use the above outputs and other data to perform in depth analysis such as that on travel demand and impact of weather on mobility.

Additionally this paper aims to share good practices for working with mobile network data in the transport sector in a cost-effective manner. We share lessons in the following areas: – Data access. We share best practices and lessons on how to work with mobile network operators (MNOs) and telecom regulators in low-income regions.

-

- Methods. What models to use to produce data products such as OD matrices.

– Technology, infrastructure and platforms. We share insights on which technologies, platforms and frameworks to use for large-scale data processing.

## **Context**

Sierra Leone (SL) is a country in West Africa on the Atlantic Ocean. The country is divided into four provinces: Southern, Eastern, Northern and Western (see figure 1). Our project focuses on the western region, which contains the capital city Freetown. Sierra Leone has a population of 7,092,113 (Census 2015) with a density of 97.2 persons per sq. km while in the western region, the population density is _20 times higher_ at 2,154.6 persons per sq. km.

3
firm size – especially for Shanghai listed firms – we use the average total assets in 2010-12 to predict the probability of being connected within each exchange. In doing so, we remove most of the ex-ante difference in size between connected and unconnected firms (Appendix Figure 4).

We find a positive and significant impact of the Stock Connect program for firms in each stock market (Table 8). Among firms listed in Shanghai, the ratio of equity raised over assets increased by about 7 p.p. more for connected firms relative to unconnected firms in 2015 (Figure 6, Panel A). The cumulative difference was 17 p.p. in 2020 (Figure 6, Panel B). Among firms listed in Shenzhen, the ratio of equity raised over assets increased by 22 p.p. for connected firms relative to unconnected firms in 2016 (Figure 6, Panel B), and the cumulative difference was 42 p.p. in 2020 (Figure 6, Panel B). Since firms listed in Shanghai are, on average, larger than firms listed in Shenzhen (Appendix Figure 4), the fact that connected firms in Shenzhen reacted more than connected firms in Shanghai is consistent with our size-related results.<sup>29</sup>

# **4.3 Investment Activity**

To examine the effect of internationalization on firms’ investment activity, we focus on capital expenditures (capex), spending on acquisitions, R&D, and cash and short-term investments.<sup>30</sup> While cash and short-term investments are measured as stock values each year, capex, acquisitions, and R&D are flows, so the changes in those variables are not easily comparable.

We study again the differences between connected and unconnected firms. We run the baseline difference-in-differences specification (Equation 1) using the following dependent variables in turn: capex over total assets, acquisitions over assets, R&D over assets, and cash and short-term investments over assets. Assets are measured
average prices to to give estimates of marketing costs in other years. This same general approach was also used in treating rubber, sugar and cotton, but as regards the first two it was incorporated in the treatment of processing costs, discussed separately below.<sup>9</sup>

# _Processing costs_

A number of farm commodities are processed before they are traded internationally, or even very widely in the domestic market. The methods used to treat processing costs are described in the original commodity studies and in the background papers. In three cases ( rice, rubber and copra) the processing margins were not separated, so the protection estimates are for the combined activity of growing and processing. In the case of rice, to the extent that rice mills possess some local monopsony power,<sup>1 0</sup> it is possible that changes in milling margins rice would not be fully reflected in the prices of paddy, and the nominal protection estimates for rice would not accurately represent the incentives to paddy farmers. It was originally intended to separate milling from paddy fanning, but we were not able to obtain satisfactory India-wide data on processing margins or on competition in the rice milling industry. Among other things, to do so was complicated by the need to separate out the processing from the trading functions of the mills. However Sharma's study of marketing and transport costs suggested that rice milling and marketing by private traders is highly competitive, and we have judged that our estimates of nominal protection for milled rice are generally reliable indicators of farm level incentives for paddy. As regards rubber and copra, according to the original commodity studies, the processing margins required to transform latex to smoked rubber sheets and coconuts to copra are very small relative to the international prices of these commodities, and in any case are typically performed by the farmers themselves or in villages in the farming areas. Consequently we believe that the nominal protection estimates for traded rubber sheets and for copra are also reasonably reliable estimates of protection for rubber
>0%<br>Market Income plus pensions Net market income Disposable income Consumable income<br>$4/day poverty line Extreme poverty line (official) Moderate poverty line (official)<br>B. Percent changes in poverty indices from market income plus pensions to<br>consumable income<br>0%<br>-3%<br>-10%<br>-20%<br>-22%<br>-24%<br>-30% -27%<br>-36%<br>-40%<br>-41%<br>-45%<br>-50%<br>-51%<br>-55%<br>-60%<br>Incidence Intensity Severity Incidence Intensity Severity Incidence Intensity Severity<br>$4/day poverty line Extreme poverty line (official) Moderate poverty line (official)<br><!-- End of picture text --> _Source_ : Author’s elaboration based on Martinez-Aguilar and Ortiz-Juarez (2016). _Notes_ : The indices measuring the incidence, intensity, and severity of poverty correspond to the FGT family of poverty indices (Foster, Greer and Thorbecke, 1984). The incidence represents 27 The official extreme and moderate poverty rates in 2013 are, respectively, 4.5 and 14.4 percent, and these figures are conceptually comparable with the poverty rates resulting from the disposable income concept in this paper: 3.9 and 12.5 percent, respectively. The differences occur because the methodology implemented in this paper includes the near-cash transfers as part of direct transfers, whereas near-cash transfers are not considered in the income used by the Ministry of Social Development in the estimation of national poverty rates.

16