rafmacalaba/data-use-mentions-extended huggingface dataset:
# 1. Introduction

Employment is a key challenge in Pakistan. While its unemployment rate is low at 6.0%,<sup>2</sup> the quality of employment is not high. Among the employed people, three-quarters work in informal sectors; 36% and 24% are self-employed and family workers, respectively; and only 12% are wage workers with a written contract (Pakistan Bureau of Statistics, 2015; Bossavie et al., 2018). The youth, despite being more educated, face a three times higher unemployment rate and are more likely to work in informal sectors than older people (Bossavie et al., 2018).<sup>3</sup> Facing a youth bulge—a large influx of a young labor force—in coming years, the Pakistani economy needs to create more jobs by taking advantage of the relatively well-educated young labor force. However, the higher unemployment rate of the educated young labor force raises the concern that skill development in the current education and training system does not respond well to skill demands in industries.<sup>4</sup> The objective of this paper is to provide new descriptives about labor market conditions and skill demand and supply in Pakistan based on novel data from a leading online job portal, Rozee.pk. Online job portal data have unique features that can supplement traditional data such as labor force surveys in four respects.<sup>5</sup> First, online job portal data provide real-time information, whereas traditional data are published after a time lag of months to even a year. As technologies and economic conditions are rapidly changing, real-time information of labor markets is becoming more important. Second, the data provide rich, granular text information about skill demand and supply. For example, included in the data are the job’s title, description, and qualification requirements and jobseeker’s education, skills, professional experience.<sup>6</sup> Third, the data include
In order to check for potential issues of selection in participation, we also run empirical models for all the outcomes on the sample of girls eligible to the program irrespective of their likely participation in the program The sample for this includes girls ages 12-19 that were eligible for the program even though they were never enrolled in grades 6-8 during the duration of the program. However, although impacts estimates based on this larger cohort are closer to the intent-to-treat parameter, a problem of this approach is that the results of this analysis are likely to get diluted as the units of observations may include a significant number of girls that did not participate; they could have left school before the program started and never rejoined.<sup>41</sup> Yet, some of the results from the base models remain.<sup>42</sup> A final concern for internal validity is that certain impacts on educational outcomes could be mistakenly attributed solely to the program when they are actually the combined effects of the stipend (a demand-side intervention) and changes on the supply side. This may be the case if more schools — particularly public schools — were built at the same time as the program in stipend than non-stipend districts. There is, however, no evidence of such systematic change in school supply. In fact, data from the annual Punjab school census (EMIS) for the period 2003-10 shows that the number of public schools was more or less unchanged. For instance, during 200407, the number of schools in stipend and non-stipend districts increased by only 0.34 and 0.15 percent, respectively, compared to the number of schools at baseline. Furthermore, the trends in the school supply of stipend and non-stipend districts are very similar in the period before and during the program, 2000-07 (Figure 1).

# **8. Conclusions**

This paper aims to fill the evidence gap on longer-term impacts of CCTs by evaluating a femaletargeted CCT program in Pakistan, the Female School Stipend Program. The evidence indicates
Conclusion Understanding the impact of Covid-19 on households in different parts of the welfare distribution was an important factor when considering appropriate policy responses in response to the pandemic and will provide lessons for similar events in the future. We combined the High-Frequency Phone Surveys collected by national governments since the beginning of the pandemic with older surveys with information on household consumption to shed light on this question. We find that the initial impact of Covid-19 has been fairly widespread throughout the consumption distribution. In the initial aftermath of the crisis, poorer households were equally likely to report income declines but less likely to report the inability to work as usual. While government assistance slightly favored poorer households initially, this progressive targeting disappeared quickly and the share of households receiving government assistance was similar for the bottom 40 and top 60 percent for the year after the crisis. In the summer and fall of 2020, there was a large increase for households in the bottom 40 in farming activities and non-farm household enterprises. This coincided with economic recovery, as seen by large reductions in food insecurity and distressed asset sales among the bottom 40 during this time, as well as a reduction in the prevalence of income declines. However, the engagement of children in educational activities remains a concern. By the end of 2020, only about one third of households with children reported that children aged 6 to 18 were engaged in educational activities, a decline of about 15 percentage points.

To sum up, the results suggest that the initial impact of the shock was severe throughout the welfare distribution, and that there was a marked recovery for poor households associated with an increase in farming and non-farm household enterprises. However, poor households remained more likely than nonpoor households to report income declines and not working as usual in the medium term. The impact on educational engagement was severe and felt throughout the distribution. The results highlight the importance of policies to ensure productivity in the agricultural sector, as well as non-agricultural household enterprises, in response to the crisis.

The analysis in this note could be extended
# **VI.   APPENDIX**

## **Figure VI-1: Spectral Density Function of Real Credit**

## **A- Oil exporter**

<!-- Start of picture text --> Bahrain: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<br>Frequency<br>Evaluated at the natural frequencies<br>Kuwait: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<br>Frequency<br>Evaluated at the natural frequencies<br>6<br>6.00<br>4<br>4.00<br>2<br>2.00<br>0<br>0.00<br>log Periodogram -2<br>-2.00<br>-4<br>-4.00<br>-6<br>-6.00<br>6<br>6.00<br>4<br>4.00<br>2<br>2.00<br>0<br>0.00<br>log Periodogram -2<br>-2.00<br>-4<br>-4.00<br>-6<br>-6.00<br><!-- End of picture text --> <!-- Start of picture text --> Iran: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<br>Frequency<br>Evaluated at the natural frequencies<br>Oman: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<
Central Staistical Bureau of Latvia (2003b), Labour Force Surveys: main indicators in 1996-2001.

Central Staistical Bureau of Latvia (2004), Labour Force Surveys: main indicators in 2003.

Ehrenberg, Ronald G. and Robert S. Smith (2003). Modern Labor Economics, Theory and Public Policy. 8th ed., Addison Wesley.

Hazans, Mihails (2002), “Age-Earnings Profiles and Human Capital in Transition: Evidence from the Baltic States”. http://www.eurofaculty.lv/papers/DownloadsEconomics/mihails_hazans.pdf Hazans, Mihails, John Earle, and Raul Eamets (2002), "Labour Markets in the Baltic States", Background paper for the OECD (2003) publication “Labour Market and Social Policies in the Baltic Countries”.

Hazans, Mihails (2003a), “Commuting in the Baltic States: Patterns, Determinants, and Gains” ZEI (Center for European Integration Studies, Univ. of Bonn) Working Paper No. B02-2003 (available at www.zei.de) Hazans, Mihails (2003b), “Determinants of inter-regional migration in the Baltic Countries,” _ZEI_ (Center for European Integration Studies, Univ. of Bonn) Working Paper No. B17-2003. (available at www.zei.de) Hazans, Mihails (2003c), “Potential emigration of Latvian labour force after joining the EU and its impact on Latvian labour market”, _<u>http://www.gdnet.org/cf/search/display.cfm?search=ALLKB&act=DOC&docnum=DOC14353</u>_ Hazans, Mihails (2003d), “Returns to Education in the Baltic Countries,” paper presented to the conference „ _Human Development in EU Accession Countries_ , Riga, 1-2 June 2003.” (http://www.biceps.org/documents/Hazans_RETURNSTOEDUCATION.pdf).

Hazans, Mihails (2004a), “Does Commuting Reduce Wage Disparities?”, _Growth and Change,
# **1. Introduction**

A growing body of evidence points to the role of risks, shocks and vulnerability in perpetuating poverty (Morduch, 1990; Skoufias and Quisumbing, 2003; Dercon, 2004; Dercon, Hoddinott and Woldehanna, 2005). While all households are negatively affected by uninsured shocks, relatively poorer households are likely to lack the necessary human and physical capital to recover from them (Del Ninno and Marini, 2005). Some shocks can have long-lasting effects leading to chronic poverty (Dercon, 2004; Dercon, Hoddinott and Woldehanna, 2005) and adverse human development outcomes (Foster, 1995; Jacoby and Skoufias, 1997; Jensen, 2000). Thus, understanding the nature of shocks, identifying those vulnerable to them, and analyzing households‟ ability to cope with shocks is important to help design programs and interventions to prevent households from falling into poverty and/or compromise their human capital.

While Bangladesh has witnessed a remarkable 28 percentage point drop in poverty over the last two decades (from 59% in 1990 to 31.5% in 2010 using Household Income and Expenditure Survey data), a sizeable number of Bangladeshis remain clustered around the poverty line. This implies that even a small shock can cause large movements in poverty rates as many non-poor remain highly vulnerable in an environment with limited insurance markets. But what type of shocks really matter to Bangladeshi households and how do they cope?

Despite the pervasive nature of shocks in Bangladesh, particularly weather related covariate shocks, there is limited knowledge of their incidence and the coping mechanisms adopted by households to deal with them. Quisumbing (2007) in a longitudinal study in rural Bangladesh finds more than half of all sampled households to have been affected by shocks in a ten year period (1997-2006/07). The three most frequent shocks reported include expenses and foregone income due to illness, dowry and wedding related expenses, and floods. The data suggests households with lower endowments in terms of education, and land/asset ownership, are
TABLE 111.2. FEDERAL BONDED DEBT GROWTH: 1995-1998

||December<br>1994|December<br>1998|Variation|Percent<br>Variation|
|---|---|---|---|---|
|Federal Bonded Debt<br>(R$ Millions)|60,255|322,624|**262,369**|435.7%|
|GDP (R$ Millions)|537,555|912,456|374,901|69.7%|
|Federal Bonded Debt (% GDP)|11.2|35.4|24.1|216.1%|

Initially, we will aggregate the other accounts in the federal government and Central Bank aggregate balance sheet in three groups, each one of them standing for one of the following reasons to issue federal bonded debt'<sup>8</sup> , as laid out in Table 111.1.

# 1) To finance the federal government's (+ Central Bank's) deficit;

# 2) To accumulate foreign and domestic assets; and

# 3) To repay other previous debts (non-bonded debt).

Item #1 represents the difference in the two net worth figures (a fiscal deficit is a loss, and a fiscal surplus is a profit); item #2, the asset accumulation during the period; and item #3, the decrease in the aggregate of all other liability accounts. Thus, considering the federal bonded debt as the "sources", and the other accounts as the "uses" we can observe these uses on Table III.3 and 111.4, expressed in R$ and percentage of GDP, respectively. 1<sup>9</sup>

> 18Here, we are not determining whether the debt movements resulted from the fiscal, monetary, or exchange rate policy.

'9 The total of the uses (in
-13-

# Table 2 United Nations Definitions of Value Added

# General Definition

"Value added is the increment to the value of commodities and services that is contributed by the producing establishment, that is, the value created by the establishment. Aggregated for all establishments in a given industry, value added is the incremental value of goods and services attributable to that industry". "Value added avoids the duplication in the value of shipments (or production) which results from the inclusion of shipments of establishments producing materials and components together with the shipments of establishment! producing finished products. Therefore, value added is considered to be the best value measure for comparing the relative economic importance of different industries and geographical areas".

# Census Concept of Value Added

"Respondents do not report value added but rather the items required for the calculation of value added. Value added, in the census concept, is defined as the value of output less the cost of matc.ials and industrial services used. The calculation of value added is made by the national statistical organisation in the processing of the establishment data".

# National Accounts Concept of Value Added

"Value added, defined in the above manner, is not net value created in relation to the economy as a whole but is net only in terms of the agricultural and industrial sectors of the economy. To derive a wholly net value added, it is necessary to exclude, in addition to the cost of materials and purchased industrial services, the purchases of non-industrial services, and to include non-industrial receipts. This additional calculation moves towards value added in the national accounting sense. The national income concept in the national accounts also excludes depreciation charges, that is, the consumption of fixed capital".

"The collection of data on the cost of non-industrial services at the establishment level is, however, fraught with difficulty in the case of multi-unit enterprises. In such enterprises, data are only available at that level for certain non-industrial services, such as communication costs and rental payments. Other non-industrial
42 Shah, A. T. Thompson and H.F. Zhou (2004), “The Impact of Decentralization on Service Delivery, Corruption, Fiscal Management and Growth in Developing and Emerging Market Economies: A Synthesis of Empirical Evidence”, _CESifo Dice Report_ 2: pp.10-14 Reinikka, R. and J. Svensson (2002), “Coping with poor public capital”, _Journal of Development Economics,_ 69 (1), pp51-69 Shapiro, C and R. Willig (1990), “Economic rationale for the scope for privatization”, in E.N. Suleiman and J. Waterbury (eds), **The political economy of public sector reform** , Westview Press Shleifer, A. and R. Vishny (1994), “Corruption”, _Quarterly Journal of Economics,_ 109, pp995-1025 Svensson, J. (2003), “Who must pay bribes and how much? Evidence from a cross section of firms”, _Quarterly Journal of Economics_ , Vol. CXVIII, February, 208-230 Rock, M.T. and H. Bonnett (2004), “The comparative politics of corruption: Accounting for the East Asian paradox in empirical studies of corruption, growth and investment”, World Development, 32(6), pp999-1017 Rossi, M. and E. Del Bo (2004), “Corruption and Inefficiency: Theory and Cross-Country Evidence from Electricity Distribution Firms ”, in Rossi, M (2004), **Essays in Applied Regulatory Economics** , PhD thesis, University of Oxford, available at ~ <u>http://users.ox.ac.uk/ rossi/Paper%202.pdf</u> Tanzi, V. andH. Davoodi (1997), Corruption, Public Investment and Growth”, IMF Working Paper, No 97/139, available at http://www.imf.org/external/pubs/ft/wp/wp97139.pdf wb14570 N:\Antonio
and, from 1980 on, crude oil has generally accounted for 40 percent to 60 percent of Cameroon’s export revenues. The rapid decline in oil prices in 1985 and 1986 is generally identified as the source of Cameroon's economic crisis.

Cameroon's lack of export diversification is illustrated by the fact that its five principal exports account for 74 to 81 percent of total export revenue over the last five years. All these products are either agricultural (broad-bean cocoa, and raw cotton) or natural resource-based (crude oil, wood processing, and refined petrol).<sup>6</sup> The top five imports in 2003 were hydrocarbons, machinery, chemicals, transport equipment, and flour. During the last five years, the top five product clusters have accounted for 65 to 68 percent of the total value of imports.

The European Union (EU) is by far the most important trading partner of Cameroon. In 2003, 64.5 percent of Cameroon’s exports and 54.6 percent of Cameroon’s imports were exchanged with the EU.<sup>7</sup> The EU is followed by Africa (13.6 percent of exports and 22.5 percent of imports), Asia (10.3 percent of exports and 15.6 percent of imports), North America (7.6 percent of exports and 5.5 percent of imports) and Latin America (1.4 percent of exports and 2.1 percent of imports).

# **2. Modeling Features and Data**

Our CGE microsimulation model involves 10,992 households, as compiled from the “ECAM II” household survey undertaken in Cameroon in 2001 (CNIS 2002a; 2002b; 2003). Other data were processed from the Cameroon’s 2001 Supply and Use Tables (SUT) of Cameroon, and from the underlying Integrated Economic Account Tables (IEAT). The general

> 6 Other products that have been among the top five exports for at least one
that are owned and managed by men, none of the businesses these women had started relied on foreign investors for start-up capital.<sup>23</sup> The challenges that aspiring and successful businesswomen encounter are further illustrated by the qualitative work that was undertaken for this report. A female youth from Khartoum who had a university degree and was the owner of a small pastry shop said, “Because my capital wasn’t enough, so I took things from home and my mother helped me ... because I have no experience in this field my big brother did everything related to taxes and rent fees and everything, he is responsible about the legal papers ... they were supporting me, my mother, brother and my father were very supporting, and my father supported me financially too, thanks God for having them and their support.” The KIIs and FGDs revealed that youth face many of the same struggles as women. For example, a male youth from Nyala who had a university degree and was the owner of a medium-size agricultural business said, “Sometimes you don’t have possibilities, you can take loans from banks and sometimes when you need money you don’t find loan in the suitable time for you.”

# **Women in agriculture tend to earn less than men and face similar challenges as female entrepreneurs**

Sudan is rich in arable land and water, with two-thirds of the population living in rural areas and a large share of the population engaged in agricultural activities. Before the separation of South Sudan from Sudan in July 2011, Sudan had “7% of [Africa’s] cropland, 13% of its pastureland and 10% of its livestock” (Ibnouf 2011, 216). The idea of turning Sudan into the Middle East’s or Africa’s ‘breadbasket’ has been repeatedly proposed by Sudanese leaders, regional leaders, and development organizations for the last 50 years. However, since Sudan experienced rapid nationalization followed by rapid privatization and
of competence and professionalism of small importers and customs brokers, who often do not exercise due diligence in the clearance process. This results in considerable delays in payment and slows down the entire logistics chain. The capacity and professionalism of the private sector have a large effect on the clearing process, even greater than expected. For instance, an analysis of Douala port by a major freight forwarder found that customs procedures cause only one percent of very long—20 days or more—cargo delays. The same analysis calculated that lack of or erroneous documentation by the importer or delays by the pre-inspection company are far more time-consuming than customs procedures.

# **Findings from firms’ surveys**

By using data from firm surveys launched in five SSA countries - Kenya, Nigeria, South Africa, Uganda, Zambia we attempt, through statistical analysis, to validate some of the theoretical assumptions presented in the previous section. The main objective of the analysis of firm surveys is to 20
political support needed for reforms. A 1995 UN financed survey suggested that about 75% of the Latin American population actually supported privatization policies then.<sup>3</sup> The main residual vocal group against the reform were the public sector workers (and their families) who lost jobs, and often associated privileges. They were not too concerned either that their jobs were financed by taxes paid by the contemporary population, or bonds to be repaid by the following generation.

To conclude this quick overview of the baseline situation, it may be useful to point out that all of these reforms were taking place in an environment in which the cost of private funds was at an historical low levels. Indeed, there was an unusually high excess supply of funds on the international capital markets favoring FDI and other forms of international of capital flows. This eased PPPI in politically committed countries. The necessary commitment was in fact relatively easy to obtain because the 1990s also saw a wave of ideological changes favoring market oriented reforms among leaders of all political sides. Many of the leaders elected on left leaning platforms (e.g. Menem in Argentina, Cardozo in Brazil or Wade in Senegal) during the 1990s were in fact among the strongest supporters of these reforms.

It may also be useful to point out that in almost all countries, privatization and infrastructure reforms were actually part of a wider reform agenda and that when some of the reforms did not work out as planned, many of the successful ones saw their effectiveness eroded. For instance, Benitez et al. (2003) provide a test of the relative impact of PPPI and of financial markets reforms on the macroeconomic performance. They show for Argentina that

> 3 UN (1999)

3