rafmacalaba/data-use-mentions-extended huggingface dataset:
- Kersten, R., J. Harms, K. Liket, and K. Maas (2017). Small firms, large impact? a systematic review of the sme finance literature. _World Development 97_ , 330–348.

- Kuntchev, V., R. Ramalho, J. Rodr ́ıguez-Meza, and J. S. Yang (2014). What have we learned from the enterprise surveys regarding access to credit by smes? _World Bank Policy Research Working Paper 6670_ .

- La Porta, R. and A. Shleifer (2014). Informality and development. _Journal of Economic Perspectives, 28_ (3), 109–126.

- Lewis, H. G. (1974). Comments on selectivity biases in wage comparisons. _Journal of Political Economy 82_ (6), 1145–1155.

- Maloney, W. (2004). Informality revisited. _World Development, 32_ (7), 1159–1178.

- Perry, G., W. Maloney, O. Arias, P. Fajnzylber, A. Mason, and J. Saavedra-Chanduvi (2007). _Informality: Exit and Exclusion_ . World Bank, Washington, DC.

- Quinn, S. and C. Woodruff (2019). Experiments and entrepreneurship in developing countries. _Annual Review of Economics 11_ (1), 225–248.

- Rozo, S. and H. Winkler (2021). Is informality good for business? the impacts of idp inflows on formal firms. _Journal of Human Resources, forthcoming_ .

- Tanaka, M., N. Bloom, J. M. David, and M. Koga (2020). Firm performance and macro forecast accuracy. _Journal of Monetary Economics 114_ , 26–41.

- Ulyssea, G. (2018). Firms, informality, and development: Theory and evidence from brazil. _American Economic Review 108_ , 2015–47.

21
have been employed under the old regime, is currently without work. Apparently, this is a large decline in the utilization of labor. However, despite this big decline, the employment ratio in most transition economies is still within the OECD range.

# **Figure 1  Transition has been associated with a substantial fall in the employment-topopulation ratio**

### **Employment/Population Ratio, 2002**

<!-- Start of picture text --> 80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Geo Aze Kaz Cze Slv Rus Est BRU Bel Lat Ukr LitOECDCIS-7 + K CEEEU15 Mol Uzb Kyr Rom Hun Bul Pol Slk Cro Arm Taj Alb SEE Mac SAM<br><!-- End of picture text --> Source: UNICEF TRansMONEE database; OECD Employment Outlook, 2003 4
of migrants (i.e., living in a place that is not where one was born, having been born outside Russia, and having lived there less than 10 years), the proportion of migrants ranges between just 1% and 1.6% of employment in RLMS for the period 2010-2016. This is similar to the data from the LFS which contains a straight question about citizenship. Using LFS, the proportion of migrants within employment ranges between 0.2 and 0.3 percent for the same period. These latter numbers underscore the point often made that these surveys fail to capture illegal migrants either because respondents mislead the surveyors or because the sampling design fails to capture this population <u>group.</u> 15/67 Informal Employment and Worker’s Wellbeing in Russia
One possible identification issue regarding the exclusion restriction may be that fluctuations in oil prices directly affect the relative attractiveness of wage and self-employment activities in the home country (El-Mallakh and Wahba 2021). This might occur, for instance, when wage and self-employment work are concentrated in different sectors in Bangladesh. Two arguments mitigate this concern: First, our estimation conditions on a full set of year effects, so that only the interaction with destination country-specific oil shares in GDP provide the identifying variation.

Second, in our sample, the majority (two-thirds) of returned migrants living in rural and semi-urban areas work either in small-scale agriculture or retail businesses. According to the 2016 industry-level Input-Output tables for Bangladesh, both sectors have a very small share of their input values coming from “Coke or refined Petroleum”.<sup>23</sup> We do, however, observe a slightly higher importance of the transportation sector for the self-employed (21 percent) compared to wage workers (15 percent) in the sample. Since transportation is more dependent on oil-derived inputs compared to other sectors, we also run our IV estimation on a sample that excludes people employed in transportation. The results of this robustness check are reported in Table A2, and show that the IV coefficients are virtually identical when the transportation sector is excluded.

We next investigate changes in the share of self-employment among non-migrants over time, and a possible association with fluctuations in oil prices. We explore these potential connections to provide further evidence that oil prices do not directly affect the relative attractiveness of self-employment and wage work. We use several waves of the Bangladesh Labor Force Survey, which is nationally representative and available at several points in time between 2000 and 2017. We focus on workers who have not migrated overseas. As shown in Figure A1, the fraction of those who did not migrate and who are self-employed in rural and semi-urban areas (the areas covered by the BRMS) is fairly stable over time. In short, we do not observe any noticeable association between the
channels. The findings show that the employment effects vary strongly depending on the type of trade considered (exports, intermediate imports, final imports, GVC participation). Assessing the relationship for employment and labor value added separately, the analysis finds the income channel to be stronger than the employment channel. The trade-and-labor links also critically depend on the sector under study, with manufacturing sectors showing the highest job and income growth associated with expanding exports in a sector. Not surprisingly, the way in which countries engage in GVCs matters for the magnitude of export-employment elasticities. But a country’s sectoral specialization also matters for the indirect job creation potential in supplying sectors. Finally, this study sheds light on the types of job activities embodied in exports. From a GVC perspective, tracking job activities that countries specialize in for their export production over time allows to detect upgrading patterns and allows to study aspects of job quality.

This paper contributes to the literature in a number of ways. First, this study provides new descriptive analysis drawing on recent employment-in-exports data covering over 50 high- and middle-income countries (HMICs). A major strength of these employment estimates is that they account for indirect linkages of an export sector to domestic supplying sectors. Increases in exports can lead to domestic job creation not only within the export sector, but also in domestic supplying sectors, allowing for a more accurate representation of the trade and labor links. As our analysis shows, the indirect job creation from manufacturing exports is higher than the direct job creation in these sectors, while for business and especially other services exports the bulk of employment is created directly in these services sectors. Some studies have used direct measures of employment in exports or GVCs, but they focus on measurement aspects and do not cover more recent years (Calì et al. 2016, <mark>Horvát, Webb and Yamano 2020</mark> ) or a narrow set of countries (Timmer et al. 2014).

Second, while trade research focused on skills intensity, labor productivity
# **MAIN ABBREVIATIONS & ACRONYMS**

**ANMEB National Agreement for the Modernization of Basic Education (Acuerdo Nacional para la Modernización de la Educación Básica) ENIGH National Household Survey of Income and Expenditures (Encuesta Nacional de Ingresos y Gastos de los Hogares) ENEU National Urban Employment Survey (Encuesta Nacional de Empleo Urbano) INEGI National Institute of Statistics, Geography, and Information (Instituto National de Estadística, Geografía e Informática) SEP: Ministry of Education (Secretaría de Educación Pública) SNTE: National Union of Education Workers (Sindicato Nacional de Trabajadores de la Educación)**

2
## CLEMENS & TIONGSON

Table 10 explores how the households of test-failers in the survey sample differ from the same outcomes in a nationally-representative survey conducted by the Philippine government.<sup>25</sup> We leave out test-passers so as to remove the effects of EPS-Korea migration.

Households in the survey sample are much more likely to already have a member abroad than typical households in the Philippines. Sample households have somewhat more income (about 35% more) than typical households, a difference entirely accounted for by the fact that they have more remittance income. Sample households are less likely to have monthly savings (and when they save, save less), are much less likely to have businesses, and live in somewhat better-quality houses. They are more likely to be in Luzon. Their heads of household are younger and have 3.5 years more education, and their children are 12 percentage points more likely to be in school.

In short, relative to the country as a whole, the survey sample captures households that have similar incomes in the absence of remittances, have more experience with migration and thus somewhat higher incomes due to remittances, are more likely to invest in human capital and work for wages than to run a business, and save less. The broad pattern is that households in the survey sample emphasize investments in human capital (education, migration) over physical capital (entrepreneurship, savings).

# 9. Conclusion

We find that migration from the Philippines to temporary jobs in Korea has important effects on migrants’ households. These are theoretically and empirically different from the effects of remittances, as remittances are just one portion of the bundled treatment that is migration. For example, Yang (2008) finds that remittances to the Philippines encourage some types of entrepreneurial activity, conditional on the household already

> 25We use a household-matched nationally representative sample from the 2006 Family Income and Expenditure Survey (FIES) and Labor Force Survey (LFS). 2006 is the most recent matched FIES-LFS microdata publicly-available from the National
MALI’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 29. Mali’s power and water utilities burden of inefficiency**

<!-- Start of picture text --> a. Uncollected bills and unaccounted losses in the power sector, as a percentage of GDP<br><!-- End of picture text --> <!-- Start of picture text -->
1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>Mali nonfragile low-income countries<br>collection inefficiencies unaccounted losses<br>b. Uncollected bills and unaccounted losses in the water sector, as a percentage of GDP<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>Mali nonfragile low-income countries<br>collection inefficiencies unaccounted losses<br>% of GDP<br>% of GDP<br><!-- End of picture text -->

- b. Uncollected bills and unaccounted losses in the water sector, as a percentage of GDP

_Source_ : Derived from Briceño-Garmendia, Smits, and Foster 2009. Note: Estimations based on operational performance data up to 2007.

# Annual funding gap

Mali’s infrastructure funding gap amounts to $283 million per year, or about 5 percent of GDP. More than half of the funding gap is in the water sector, for which the annual shortfall for meeting the Millennium Development Goals is $200 million (table 21). Another significant part of the gap is found in the transport sector, which requires an additional $77 million to meet the country’s development goals. Our analysis finds no funding gap in the power sector since the potential efficiency gains could compensate for the shortfall.

47
changes such as greater monsoon volatility (B.N. Goswami et al., 2003). Given the limited history of existing rainfall data and the skewness of the insurance return distribution, however, statistical tests of structural change are not likely to be powerful.

In part A of the Online Appendix we simulate a simple model of insurance demand to investigate more formally whether the insurance is potentially valuable to households at the prices offered, in the absence of non-price frictions such as liquidity constraints or limited trust. This model is calibrated to match the payout ratio and distributional features of ICICI Lombard contracts, in which payouts are realized on only around 10% of phases, but with high maximum returns. We assume a conservative level of 40% for the payout-to-premium ratio, and consider a range of assumptions about basis risk. Results suggest that the insurance product is valuable at

> 5 US insurance premiums data were generously provided by David Cummins of Temple University, based on the 2007 Best’s Aggregates and Averages. The ratio of aggregate claims to premiums is 76.2% for private passenger auto liability insurance, 68.4% for private passenger auto physical damage, and 64.7% for homeowners insurance. The ratio for earthquake insurance is much lower, 20.4%, but this may reflect the relatively small number of recent earthquake events.

7
price. As described above, we observe votes from our sample of leaders, whose job is to represent their village, and a subsample of individuals within the village, who vote their own preferences. We use responses to the referendum to estimate each community’s collective minimum willingness to accept payment for enrollment, based on leaders’ responses, and the payment that would induce the median household member to vote yes, based on the household data.

# 4.1 The question

The following question, based on standard stated preference methodology (Phaneuf & Requate 2017), was presented to all of the leaders and households in our sample: Suppose that your ejido/community were voting another time to decide if they wanted to participate in the program. The decision would be taken according to the normal voting rules of your village. If the community were to receive an amount of [X] per hectare, equivalent to [X x number of hectares in total], would you vote in favor of or against participating?

Here [X] refers to an amount between 80 and 770 pesos (US $4 and $41). Values offered in the referendum question were randomized, with a higher proportion of values offered below the actual payment received (or that would have been received in the case of the non-beneficiaries). This distribution was chosen because we assumed that true opportunity costs were likely to be less than the payments, given that all surveyed communities had already voted once to participate at these rates. The question was asked in reference to the specific parcel of land that was submitted in the most recent PSA application. After answering, a follow up question was offered at a higher (lower) value in the event that the respondent said no (yes) to the first value.

# 4.2 Minimizing strategic response

The referendum-style question was used, rather than an open ended or checklist format, because prior research has shown that the referendum format can induce truthful preference revelation in specific contexts<sup>11
in parentheses. PSI-PMI = Progressive Science Initiative and Progressive Mathematics Initiative; WASSCE = West African Secondary School Certificate Examination. *** p < 0.01, ** p < 0.05, * p < 0.1.

_School covariates_ variables include: presence of electricity in school, good desks in school, school has a library, a computer lab, running water in the school, student enrollment, student-teacher ratio, percentage of qualified teachers, percentage of female teachers, experience of the school principal, age of school principal, administration experience of school principal, level of education of school principal, school principal is female, share of students with high performance in mathematics, English, and science on the WASSCE. _Student-level covariates_ variables include the following: percentage of students not repeating any grade, percentage of students earned credit and above on GABECE mathematics, percentage of students earned credit and above on GABECE English, percent of students earned credit and above on general science, all at baseline. And socioeconomic characteristics of students—percent of students in households that has a quality roof, a wall, television, car, access to grid electricity, parents have some education.

10 The WASSCE is graded on a nine-point scale, with 1 being the best score and 9 being a fail. A satisfactory grade is locally known as “credit,” which is a score between 1 and 6, inclusive.

21
labor survey data for Egypt to arrive at a larger estimate of the capital share in Egypt, 0.6.

- The annual capital depreciation rate: � = 0.04.  This is the depreciation rate used in the estimation of the capital stock and follows the seminal work of Nehru and Dhareshwar (1993).

- The annual growth rate of the labor force: ��� = 0.025.  This is the average growth rate of the number of workers for the period 2001‐2008, as estimated from Egypt’s national employment statistics.  This represents an update of the estimate presented in Loayza and Honorati (2007).

- The annual average increase in education: ����� ���� = 0.12.  Education is proxied by the average number of schooling years in the adult population, as reported in Said (2008) for Egypt for the period 1980‐2000.  This estimate for the average increase in schooling is similar to that obtained using the Barro and Lee (2001) database for the same period.

- The average annual rate of return to education: � = 0.05.  This is proxied by the average rate of return for each year of schooling, as reported in Herrera (2009) for Egypt for the period 1988‐2006.

- The current (or targeted) level of net foreign liabilities as ratio to GDP: � = 0.2.  This corresponds to the official “international investment position” in average for the period 2001‐2007, as reported by the IMF’s Balance of Payments Statistics.

- ���

- Net income plus transfers from abroad, as ratio to GDP : ����� � = 0.052.  The ��

- numerator of this ratio is equal to the difference between Gross National Disposable Income (GNDI) and Gross Domestic Product (GDP), and the ratio corresponds to the average for the period 2001‐2007.  It is obtained from statistics reported by the World
Revised International Capital Framework. For example, using bootstrapping<sup>30</sup> techniques Majnoni _et al_ (2004b) and Gutierrez Girault (2007) find evidence indicating that the IRB formula for corporate obligors may not be properly calibrated to unexpected losses in commercial portfolios of banks in certain Latin American countries. With data from the Argentine PCR, Balzarotti _et al_ (2004) revised how the IRB model might be recalibrated to ensure it appropriately covers credit risk losses.

- **Validation** . Supervisors of banks adopting the IRB approach are expected to revise the internal validation of bank rating systems. This revision has a qualitative dimension, focused on data quality and rating system use, design and documentation, and a quantitative dimension to assess their predictive power. In the latter case, and by means of statistical tests (e.g. the Kolmogorov-Smirnov test), graphical tools (e.g. the Cumulative Accuracy Profile or ROC curve) and database programming, supervisors can validate these systems with the credit information stored at their PCR. Their results can be used to evaluate how the discriminatory power of a bank rating system evolves through a business cycle, or if different bank’s rating systems concerning the same type of portfolio display a significantly different predictive power. PCRs can also be helpful to validate banks’ estimates of other risk dimensions required by the IRB. In some countries

> 30 Given a real portfolio of borrowers that displays certain loss rate, thousands of hypothetical portfolios are simulated drawing randomly with replacement borrowers from the real portfolio. For each simulated portfolio a loss rate is computed. The resulting simulated loss rates are an empirical approximation to the distribution of the loss rate for that type of portfolio.

12
the 80 institutions ranked 21-100 on the _h_ -index, 61 are in the top-100 on all four indices. Most of the 39 not in the top-100 on all four measures appear in the lower part of the top-100 on the _h_ -index. It is noteworthy that many of the top-100 institutions are not universities.

Table 7 shows the 10 most cited publications of each of the top-10 institutions (based on the _h_ -index, as listed in Table 6). The table suggests some differences in topical specialization across the institutions. This is borne out by Table 8 which shows the distribution by topic of the most-cited 50 publications of the top-5 US institutions and Europe‘s top institution. The (normalized) Herfindahl index shows (in this instance) the degree of concentration of an institution‘s publications on a small number of topics. A value of 0.33 would occur if an institution‘s top-50 publications were evenly split across just three topics. Harvard U is the least specialized—appreciably less specialized than MIT (which has a high degree of specialization in
Our study makes several new contributions to the literature. First, we propose and evaluate a novel typology of FHHs consisting of four main types and several sub-types, which are based on self-reported responses, demographic characteristics, and socio-economic characteristics. This approach allows us to employ more nuanced headship definitions that reach beyond the traditional identification solely based on the household head’s gender to better include other aspects of household female composition. Our proposed typology also calls for more attention to the important role of children in defining FHHs, since FHHs with children could show remarkably different, static and dynamic, poverty outcomes from those of FHHs without any children or those of non-FHHs. Second, we study the trends in the FHH poverty–gender nexus and poverty dynamics, for six countries across the Arab region—namely the Arab Republic of Egypt, Iraq, Jordan, Mauritania, the West Bank and Gaza (Palestine), and Tunisia—for which little knowledge exists regarding poverty by FHH status.

Third, despite the absence of actual panel data, we construct synthetic panels that allow us to examine FHH poverty dynamics for these countries. By conducting analyses on both poverty incidence and dynamics, we contribute to a better understanding of the dynamic economic wellbeing of FHHs over time. In fact, to our knowledge, we offer the first multi-country study that investigates to what extent FHH poverty exists across a number of countries in the Arab region, and whether FHHs, according to a variety of household types, are more likely to enter or escape poverty over time, using recent survey data. We also make a new data contribution by carefully assembling and harmonizing relevant, up-to-date surveys from multiple sources in a region that is well recognized for limited data access.

We find that the shares of FHHs widely vary, ranging from 10 percent to more than 40 percent depending on the countries and definitions. Compared with non-FHHs, most types of FHHs 4