rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 8355

# **Abstract**

Although Sri Lanka has made significant progress in social and economic development over the past decade, the Northern and Eastern provinces that faced the brunt of the decades-long conflict remain disproportionately poor. To understand the labor market dimensions of poverty in these regions, this paper examines a range of job-related indicators, using data from 2011 to 2015. The overall labor force participation rate in these provinces is significantly lower than in the rest of the country. Much of the difference can be attributed to adult women, although the participation rates of youth and those with lower educational attainment are also low. The distribution of wages for male and female wage workers in these provinces is similar to that in other parts of the country. The pattern of low employment rates and comparable wages is consistent with a combination of low demand for labor and greater reluctance to work in these regions, which each depress employment but have counteracting effects on equilibrium wages. Skills are an issue, as adults in these provinces tend to score lower on literacy tests and have lower self-reported skills in reading, writing, and numeracy. Households in these provinces have less access to formal finance, which may also contribute to a lack of self-employment opportunities.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at asilwal@ worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
introduces 728 new country pairs with developing borrowing countries, compared to the OLS sample, and only 248 country pairs with developed borrowing countries. Hence, here again the main effect comes from the extensive margin.

Overall, these results are consistent with our hypothesis that migrants enhance the flow of information across countries, which facilitates cross-border financial flows.<sup>14</sup>

# V.  CONCLUSION

This paper investigates the role of migration as a determinant of international financial flows. We introduce migration into a standard gravity model and find a strong correlation with financial flows. Our results are consistent with the view that migration affects bilateral financial flows through the information channel. Indeed, we find that the effect of migration on financial flows is strongest where informational problems are more acute. This is the case when we compare country pairs characterized by different levels of cultural proximity (e.g., countries sharing versus not sharing a common language), migrants’ source countries characterized by more information imperfections (i.e., developing countries), asset types that differ in terms of informational sensitivity (e.g., short-term versus long-term bonds issued by developing countries) and types of migrants that differ in their ability to disseminate information across borders (e.g., high-skill versus low-skill migrants). Overall, our results suggest that migration contributes to reduce home bias and information frictions across countries.

Agrawal, A., D. Kapur, J. McHale, and A. Oettl. 2011. “Brain Drain or Brain Bank? The Impact of Skilled Emigration on Poor Country Innovation.” _Journal of Urban Economics_ 69: 43–55. Akbank, Annual report, 2015.

> 14. When we interact the dummy variable of developing countries with skilled and unskilled migration separately, the main result is preserved, mainly in the Poisson regressions. Namely, migration is more important a determinant of financial flows for developing countries. However, we cannot identify robust differences between skilled and unskilled migrants. These results are available upon request.

15
28 most public enterprises record a significant volume of data on volume carried, number of trips and the main characteristics of the largest clients for freight passengers or reasonable surveys of their client base. It is generally not sufficient to do much more than a valuable input into a more sophisticated analysis of prospects.

# _A. 1.2 Disaggregated models_

The second type of model is disaggregated and focuses on the individuals trip generation characteristics. The users' population and its movements are divided into homogeneous categories within which there is some degree of forseeability in the trip types and numbers. For instance, residence-office, work-related trips, private trips for private business, week end leisure trips and holidays leisure trips. The users of the transport service can then be classified according to more specific criteria: income, household composition and size, age, ownership or not of a vehicle, employment type and location characteristics.

The distinction into these various categories is important since it determines the various elements a private operator may consider in discriminating prices across users and usage types, explicitly through the design of tolls or other prices, or implicitly, through targeted discounts to frequent users. From a mode political view point, it is also important to use this kind of information to ensure that the poor are not penalized as users. 26 From a regulator's viewpoint, their value is quite significant in particular in an urban transport context since it provides a snapshot of the users' constituency of this regulator. This in turn is likely to be critical information in most instances of conflicts between service providers and users. Indeed, the valuation of the service will significantly be determined by their individual characteristics and differences across users are important to understand for any referee or arbitrator which the regulator often is.

# **A.2. Trip distribution models**

The distribution is the stage allocating traffic from a center to the various possible destinations and its use in the context of specific projects considered in the context of privatization is mostly concentrated in urban issues. An intercity road or rail project have In practice, these models suggest great constancy of total daily urban or suburban trips (on average 3.5 per day per person for the last 20 years around Paris and between 3-2 and 2.4 in the country side). The main change is taking place in the modal choice with a significant increase in the use of cars. Motorized trip vary between 1.7 and 2.1 per day-increasing with the distance from the center (LEFEVRE et OFFNER (1990)). Also, while these studies in France also show an increase in the average length of the trip, the speed also increases.
# Annex D: Qualitative Data Collection

The quantitative survey tool was developed using insights from qualitative interviews, the analysis of which also provides essential context to interpreting the results of this quantitative study. The fieldwork was conducted in 3 provinces during November 2022: Madhesh Province, Bagmati Province, and Sudurpashchim Province. In-depth semi-structured interviews were conducted with both men and women, divided equally between those working for pay and those not working for pay within each gender group. A detailed analysis of the qualitative data is presented in World Bank (2024, Forthcoming).

Qualitative interviews revealed that social norms, along with beliefs, culture, traditions, intra-household relationships, and family circumstances shape women's decisions to work and the nature of their jobs. A key finding was the strong adherence to traditional gender roles within the home, with women primarily seen as caretakers in the household for which men were not considered good substitutes. Women’s presence outside the home came with concerns about the family’s reputation being harmed if the woman interacted with other men or the possibility of her being seen as unfaithful, as well as disapproval of women having a long commute for work. These findings guided the focus of social norms explored in the quantitative survey across two broad themes: (i) gender roles at the household level, and (ii) women’s mobility in the public space. Interviews also revealed that women’s participation in paid work outside the home is context dependent, influenced by factors such as having young children, financial status of the family, and job characteristics such as work location. As such, specific situations are explored in the quantitative study using a set of context dependent behaviors and characteristics. Additionally, marital status and reference groups seem to be crucial in shaping women's work decisions. Married women faced more significant social restrictions, and their decision to work was observed to be primarily influenced by household dynamics, particularly their husbands' beliefs and expectations. Though women's social circles also include other community members, such as teachers and social workers, men, overall, have much wider social circles. These findings highlighted the value of focusing on social norms governing married women’s decisions and reference groups of individuals within the household to better understand how norms are enforced.

64
_-_ 9 the balance of payments. This section will focus on our adjustments to the government budget and the balance of payments in Tanzania.' However, we have not attempted to adjust the official data on the level and growth rates of GDP. While for the sake of comparability it might have been useful to similarly adjust the data of the comparator countries, that is beyond the sc'-e of this paper. The data deficiencies would appear less severe in other countries in the sample, however, and are unlikely to affect our principal conclusions.

The national accounts severely underestimate the level and growth rate of GDP in Tanzania.<sup>5</sup> This goes beyond the usual problem of capturing data on the level of activity in the informal sector of the economy, which is certainly an issue in Tanzania-and leads to an underestimation of both its level of GDP and its growth rate (since the informal sector has been the fastest growing sector)-but is also common in other developing countries. In addition, GDP growth is also underestimated because even the growth that has occurred in the formal sector has not been fully accounted for. This is because the dismantling of the pervasive state control in many sectors of the economy that has accompanied the reforms has eliminated some of the national accounts' traditional sources of data, such as the large state trading corporations. Centralized reporting requirements, such as in construction, are also no longer in place. In the absence of an accurate assessment of the magnitude of this problem, this paper does not attempt to adjust the level and the growth rate of GDP.<sup>6</sup>

- 4 To ensurm consistency, we have used a flow-of-funds model for Tanzania developed by Ahmed (1992), which adjusts somne of the key macroeconomic data for inter-sectorml flows.

- .5 Estimates by Maliyamkono and Bagachwa (1990) indicatc tht the official statistics undertimate the level of GDP in Tanzania by at least a third.

- 6 It should be borne in mind that this eould lead to an exaggeration of nur esulta. Since the underestimation of GDP is likely to be larger than in the comparator countries, all ratios may overstate the degree of aid dependency and inefficiency of invcstment in Tanzania.
Policy Research Working Paper 6707

# **Abstract**

The ease of starting a foreign investment in various sectors is a relevant consideration for investors seeking to establish an investment project abroad. Two thematic areas will be analyzed in this paper to answer the following questions: Which economies impose equity ownership restrictions on foreign investors and which procedural barriers do foreign companies face when establishing foreign-owned subsidiaries in these economies? The analysis is based on findings from the Foreign Direct Investment Regulations indicators, which measure 103 economies, on whether they restrict foreign ownership across economic sectors and on the establishment process they impose on foreign-owned companies. Nearly 80 percent of the economies covered in the Foreign Direct Investment Regulations database restrict foreign companies from entering in some sectors of their economies. In addition, establishing a foreignowned company takes longer and requires more steps than starting a domestically-owned company in 94 percent of the economies observed. Overall, economies in Eastern Europe and Central Asia and high-income OECD economies have fewer equity restrictions on foreign ownership than economies in the other regions and require the least number of additional procedures of foreign companies to establish a subsidiary. The findings are significantly correlated with inflows of foreign direct investment on a per-capita basis.

This paper is a product of the Global Indicators and Analysis Department, Development Economics Vice Presidency. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The authors may be contacted at cdelamedinasoto@worldbank.org and tghossein@ifc.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Table 3: First Stage Probit – Determinants of Family Planning Program Placement

|Variable|Program|
|---|---|
||available<br>in 1990|
|Total area of district|_−_0_._021<br>|
||(0_._027)|
|Rainfall (mm/100)|_−_0_._717<sup>_∗∗_</sup><br>|
||(0_._338)|
|Rainfall squared (mm/100)<sup>2</sup>/100|3_._715<sup>_∗∗_</sup><br>|
||(1_._478)|
|Elevation (m/100)|0_._999<sup>_∗∗_</sup><br>|
||(0_._425)|
|Elevation squared (m/100)<sup>2</sup>/100|_−_3_._050<sup>_∗∗∗_</sup><br>|
||(1_._134)|
|Urban area|0_._474<br>|
||(0_._989)|
|Market in PA/kebele|0_._994<sup>_∗∗∗_</sup><br>|
||(0_._368)|
|Road access - all year|0_._296<br>|
||(0_._558)|
|Road access - dry season|_−_0_._120<br>|
||(0_._540)|
|Percent with no education in zone|_−_0_._018<br>|
||(0_._165)|
|Percent with 1-6 years of education in zone|_−_1_._601<sup>_∗∗∗_</sup><br>|
||(0_._393)|
|Percent with 7-8 years of education in zone|3_._427<sup>_∗∗∗_</sup><br>|
||(1_._003)|
|PA/kebele population / 1000|0_._063|
||(0_._044)|
|Constant|0_._745<br>|
||(14_._332)|
|**Ranking of Zones**||
|Total population|0_._155<sup>_∗∗∗_</sup><br>|
||(0_._032)|
|Urbanisation|0_._085<sup>_∗∗∗_</sup><br>|
||(0_._026)|
|Percent with no education|_−_0_._126|
||(0_._078)|
|Percent with 1-6 years of education|0_._785<sup>_∗∗∗_</sup>|
||(0_._180)|
|Percent with 7-8 years of education|_−_0_._579<sup>_∗∗∗_</sup><br>(0_._139)|
|**Ranking of PA/kebeles within Zone**||
|Total population|_−_0_._511<sup>_∗∗∗_</sup>|
||(0_._163)|
|All ranks equal to zero F(6,96)|6_._14<sup>_∗∗∗_</sup>|
|<br>Observations|109|

**Notes.** * sign. at 10%; ** sign. at 5%; *** sign. at 1%. Weighted probit with robust clustered standard errors in parentheses estimated using Stata’s svy command. Dependent variable is whether family planning was available within 40 km of community in 1990.

ments are statistically significant. Relatively more populated and urbanized zones are more likely to have access to a family planning program. Within a zone, communities with relatively smaller population are more likely to have access to family planning programs. Policy-makers also appear to target zones with a relatively larger share of people with 1 to 6 years of education. The effects of the two other education rank13
16 Table 3: Median Retail Prices in January 2013 in U.S. Dollars and Sample Size

|**Category**|**Gasoline**<br>**$/liter**|**Diesel**<br>**$/liter**|**No. of**<br>**countries**|**Kerosene**<br>**$/liter**|**No. of**<br>**countries**|**LPG**<br>**$/kg**|**No. of**<br>**countries**|
|---|---|---|---|---|---|---|---|
|Income||||||||
|Low|1.34|1.22|15|0.98|12|1.77|10|
|Lower middle|1.12|1.02|24|0.84|17|0.80|22|
|Upper middle|1.21|1.08|24|1.15|12|1.04|18|
|High|1.97|1.52|8|a|1|a|2|
|Oil trade||||||||
|Net importers|1.28|1.22|51|0.99|32|1.24|35|
|Net exporters|0.87|0.93|20|0.56|9|0.61|15|
|Region (excluding high-income cou|ntries)|||||||
|East Asia and Pacific|1.25|1.03|9|1.11|4|1.20|8|
|Europe and Central Asia|1.16|1.23|4|a|1|a|1|
|Latin America and the Caribbean|1.24|1.14|16|1.18|8|1.01|14|
|Middle East and North Africa|0.67|0.44|8|0.41|4|0.40|7|
|South Asia|1.25|0.91|5|0.86|5|1.44|5|
|Sub-Saharan Africa|1.24|1.22|21|0.96|19|0.97|15|

_Sources_ : See Table A1.2 in Kojima (2012).

_Note_ : Median prices are followed by the number of countries in each category. Gasoline and diesel have the same number of sample countries.

a. Too few countries in the sample for meaningful statistics.

# **Price Movements between 2009 and 2013**

Table B.3 in appendix B shows pass-through coefficients for January 2009−January 2012 (first time interval) and January 2009−January 2013 (last time interval). Although the results for the first time interval were previously published, the revised results take benchmark FOB prices from December 2008 and December 2011 to be consistent with the revised calculation methodology. Figure 6 shows the distribution of the coefficients for the four fuels for the last time interval, 2009–2013.

Figure 6: Distribution of Pass-through Coefficients, January 2009–January 2013 <!-- Start of picture text --> 300<br>Gasoline<br>250<br>Diesel<br>200 Kerosene<br>LPG<br>150<br>100<br>50<br>0<br>-50<br>Percentile<br>Pass-through coefficient, %<br>0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100<br><!-- End of picture text --> _Sources_ : Author’s calculations using data from sources cited in Table A1.2 in Kojima 2012.
# **Figure 13. Catch per unit effort in Kenyan waters of Lake Victoria, 1979-2000:**

<!-- Start of picture text --> 35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>1979 1982 1983 1985 1986 1988 1989 1991 1995 2000<br>Tonnes per boat<br><!-- End of picture text --> _Source: Own calculations_ Traditionally, almost all animal protein eaten by the communities surrounding Lake Victoria was derived from the lake, although in recent years fish consumption has been in decline. Abila (2000) suggests that this is the direct result of the Nile perch fishery that has resulted in reduced access to fish by lakeside consumers. Abila and Jansen (1997) estimate that 48 percent of all Nile perch landed is sold to the industrial fish processors and that the only Nile perch available to the local population is either small juvenile fish and/or fish rejected by the industrial processors. Further, the demand for fish from the export supply chain has driven up prices beyond the means of low much of the local population.

Questions have been raised about the long-term sustainability of the Nile perch fishery. For example, Jansen (1997) and Goulding (1997) argue that the Nile perch fishery is leading to a decline in the resources of the Lake and threatens food security of local people. On the one hand, investment in excess processing capacity has generated an almost ‘unlimited’ demand for raw fish. On the other, since 1991 the landed catch of Nile perch has been in decline despite a continued increase in the total fishing effort (Bokea and Ikiara, 2000; McCormick and Mitullah, 2002). Simultaneously, the average size of fish has diminished and processors have been forced to accept smaller and smaller fish in order to maintain throughput<sup>27</sup> . In turn, over-fishing and use of illegal fishing gear are now widespread<sup>28</sup> . This has been further exacerbated by the proliferation of water hyacinth that has rendered the Lake inaccessible to some landing beaches.

# **5. EXPORT PERFORMANCE TO 1996**

This section reviews the evolution of the Nile perch sector in Kenya to the end of 1996. In so doing it provides an overview of the development and state of the sector when restrictions were

> 27 Previously or at the beginning of Nile perch trade, only fish exceeding 2-3Kg (and typically up to 200Kg) were accepted for processing.  Today, at times, processors accept fish under 1Kg.  Virtually all good quality fish exceeding 2Kg is supplied to the industrial processing sector.

> 28 Whilst regulations are in place, these are poorly enforced and rates of non-compliance are high.

34
U.S. data. Some of these studies consider how hypothetically combining banks with other types of financial or even non-financial firms would affect the variability of accounting measures of income or stock returns.<sup>5</sup> Other studies look at the risk implications of actual combinations of traditional banking and other financial activities.<sup>6</sup> Among these, the closes to our study is Stiroh (2004) which considers how the share of non-interest income of U.S. banks has affected their risk and return.

Specifically, Stiroh (2004) finds that Z-scores are highest for U.S. banks with a non-interest income share close to zero so that even a small exposure to non-traditional banking activities increases risk. Our paper goes beyond Stiroh’s (2004) analysis of the relationship between fee income on bank risk by considering an international data set, by providing estimation of the determinants of the fee income share, and by subjecting the relationship between bank risk and fee income to additional robustness tests.

Laeven and Levine (2008) use an international sample of 296 banks from 48 countries in 2001 to examine how bank-level risk, measured alternatively by the Z-score and stock return variability, is affected by bank-level corporate governance and national bank regulations. They show both factors affect bank risk. In this paper our focus is not on regulations but we include country fixed effects in our estimation that are meant to capture this and other time-invariant country traits. Controlling for time-invariant measures of bank regulation, we find that banks that rely on fee generating activities to a greater extent are subject to greater risk.

Risk and return should be reflected in bank stock prices and thus stock market valuations can provide information about whether banks can create value by mixing different activities. DeLong (2001) considers stock price reactions to announcements of U.S. bank mergers over the 1988-1995

> 5 See Boyd and Graham (1988), Boyd, Graham, and Hewitt (1993),  Lown et al. (2000 and ), and Saunders and Walter (1994) .

> 6 See also DeYoung and Roland (2001), Geyfman (2005), Gayle (2001), Kwast (1989), Rosen et al. (1989), and Templeton and Severiens (1992).

8