rafmacalaba/datause-encoder-data huggingface dataset:
parental consanguinity, which is consistent with the hypothesis that the maternal grandparent may prefer a consanguineous union for both economic and cultural reasons. In separate models including a full set of parental survival indicators only the maternal grandfather is significant, whereas effects of survival of other grandparents were both statistically insignificant and of negligible magnitude. Several cultural explanations for this finding center on the important role played by fathers in their daughters’ marital decisions in Muslim societies (Holy, 1989), combined with both patrilocality and the fact that grooms cannot credibly commit _ex- ante_ to treat a prospective wife well (Jacoby and Mansuri, 2010).<sup>18</sup> In patrilocal societies like Pakistan, daughters leave their parental homes while married sons do not. As daughters move to a new household, the monitoring costs of her treatment increase significantly and a marriage to a relative could decrease the likelihood of poor treatment. In this context, the death of the patriarch would diminish the ability of the family to provide protection to a daughter who is then more likely to move to an unrelated household. The signs of the estimated coefficients are broadly consistent if one limits parental consanguinity to the marriage of first cousins only (columns 3 and 4 in Table 2), but in this case fewer estimates are statistically significant at 1 percent level.

# **_6.2. Consequences of Consanguinity for Children: Ravens Test Results and Stunting_**

**Consanguinity and Cognitive Performance** . Children born into consanguineous unions have lower cognitive abilities, as captured by Ravens test scores (Table 3). OLS estimates, shown in column (1) suggest that children with related parents score 0.14 standard deviations lower on a Ravens test than children with unrelated parents. Other measures of consanguinity, the F-coefficient and treating parents as first and second cousins separately, also suggest a negative, but insignificant impact of consanguinity. Further, when including district fixed-effects, to control for unobservables related to local economic development, access to off-farm labor markets and local customs, we note that children with related parents have a statistically insignificant score that is 0.1 standard deviations lower than those with unrelated parents.

As suggested in the discussion above, the economic motives behind consanguineous unions are likely to improve the financial health of households and thus also access to child inputs (food and health care). Thus, there will be an upward bias on estimates of the biological effects of consanguinity on child outcomes. We thus next introduce an instrumental variables approach, estimated through an

> 18Botticini and Siow (2003) and Jacoby and Mansuri (2010) also invoke patrilocality combined with the incompleteness of marriage contracts to justify the practice of dowry payments in and bride exchange in South Asia and Pakistan, respectively.

13
<!-- Start of picture text --> 0.25 wm Suburban<br>0.20 mCUA<br>5 0.15 = +1.64°S.E.<br>2 010 = -1.64*S.E. ;<br>Oo '<br>2°ooO 0.050.00 ~- a ;<br>% -0.10<br>Ww<br>-0.15<br>-0.20<br>Price Time Transfer BOTH Unsafe Uncom-<br>fortable<br><!-- End of picture text -->
WPS3381

# Measuring the international mobility of skilled workers (1990-2000) - Release 1.0

Frédéric Docquier<sup>a;c</sup> and Abdeslam Marfouk<sup>b;c</sup>

> a CADRE, Univ. of Lille 2 (France) and IZA-Bonn (Germany)

b Université Libre de Bruxelles (Belgium)

> c IWEPS, Regional government of Wallonia (Belgium)

## Abstract

In this paper, we provide new estimates of skilled workers’ emigration rates for about 190 countries in 2000 and 170 countries in 1990, including both developing and industrial countries. Using various statistical sources, we revisit Carrington and Detragiache’s measures by incorporating information on immigrants’ educational attainment and country of origin from almost all OECD countries. Our database covers 92.7 percent of the OECD immigration stock. In absolute terms, we show that the largest numbers of highly educated migrants are from Europe, Southern and Eastern Asia and, to a lesser extent, Central America. Nevertheless, as a proportion of the potential educated labor force, the highest brain drain rates are observed in the Caribbean, Central America, Western and Eastern Africa. Repeating the exercise for 1990 and 2000 allows us to evaluate the changes in brain drain intensity. Western Africa, Eastern Africa and Central America experienced a remarkable increase in the brain drain during the past decade.

## JEL Classi...cation: F22, J61.

Keywords: Brain drain, Human capital, Migration.

The ...rst authors thanks the World Bank for ...nancial support (Contract PO. 7620076 - UPI 269656). Comments from Richard Adams, Marjorie Gassner, Olivier Lohest, Hillel Rapoport and Maurice Schi¤ were very helpful. We would like to express our gratitude to statisticians from the OECD countries’ Institutes of Statistics. Their comments on data and assumptions were appreciated. Of course, the usual disclaimers apply. Corresponding author: Frédéric Docquier, CADRE University of Lille 2, 1 Place Déliot, F-59024 Lille, France. E-mail: <f.docquier@skynet.be>.

1
while on average individual liability lowers drop out, it does so change the composition of the clients in the program. We will examine the net effect on profitability below.

Table 5 examines the main outcomes at the center level. We estimate the following specifications using OLS: (1) ygt = α + βTgt + δt + θg + εgt, where ygt is either the proportion of missed weeks, center size, retention rate,<sup>17</sup> new accounts, number of dropouts or center dissolution for center g at time t, δt is an indicator variable equal to one for time period t (time fixed effect), θg is a center fixed effect, and Tgt is an indicator variable equal to one if group g at time t had been converted to individual liability. The time period is three months. The coefficient of interest is β. We test whether the liability rule matters by examining whether the coefficient β is significantly different from zero. Notice that we use information from _all_ clients who belonged at some point to the center between August 2004 and January 2005...

We find that individual liability is much better at attracting new clients (Column 4), leading to larger centers (Column 2) and that individual liability makes existing centers 10% points less likely to be dissolved (Column 6).

# **_V. Additional Results on Specific Mechanisms_**

We now turn to three sets of auxiliary data. First, we examine the results of two activitybased costing exercises completed by the credit officers in order to measure the change in their allocation of their time across centers. Second, we examine the results of a client follow-up survey conducted in November 2005 (over one year after the initial conversion) on clients in both the treatment and control groups. This survey includes several questions intended to tell us more about three possible mechanisms that could be influenced by the liability structure: center activities, selection and the flow of information (monitoring). The survey was conducted during center

> 17 The retention rate between t and t+1 is defined as the percentage of clients at t that are still clients at t+1.

15
3. Sales and supplies – covering variables such as annual sales, ISIC code for the main product of the firm, percentage of sales exported, the process of exporting and importing.

4. Competition – covering variables such as number of competitors and use of foreign technology.

5. Capacity utilization –covering variables such as capacity utilization of staff and machinery.

6. Land and permits – covering variables such as time to obtain a construction permit.

7. Crime – covering variables such as the sales lost to theft and cost of security services.

8. Finance – covering variables, such as the percentage of investments financed through bank loans, percentage of working capital financed through trade credit, the type of collateral used to secure a bank loan.

9. Business-government relations – covering variables such as senior management time spend on dealing with regulations, the incidence of informal payments, the frequency of visits from tax inspectors.

10. Labor –covering variables such as the number of permanent and temporary employees, education level of workers.

11. Ranking of obstacles – covering the most important of 15 potential obstacles to conduct business.

12. Performance – covering obstacles such as cost of labor and cost of raw materials.

Indicators computed from these surveys are regularly posted and updated on the web site of the Enterprise Analysis Unit <u>(www.enterprisesurveys.org) and the anonymous raw data are</u> available to the researchers shortly after the completion of the surveys.

The ES are composed of representative random samples of firms. The universe of inference for the sample is composed of the manufacturing and service sectors, including retail 6
# Cashew Processing Production Flow

<!-- Start of picture text --> nu ~_ -__ u<br>mL<br>I CNSL<br>aT- CNSL holinng CNSL<br>dryin gdCNSL<br>|acntrifg ng F nut*<br>second size caibrao<br>|decortictl }- ohs" xan<br>| 1i| |rehumidification| 13 lfng<br>Ebds~~~~~~~~~NPe w<br>i pgrading and ktg<br><!-- End of picture text -->

## Figure 1
domestic sales for Southern producers relative to exporting to the North. As a result, they export less and sell more at home.<sup>9</sup> As stressed in Section 3, most of the EIAs containing a harmonization clause and included in our database involve the EU. Accordingly, it is worth focusing on EU importers (column 5). The results are similar to the results in column (4). Thus, the negative trade effect of regional harmonization comes mostly from the high regulatory standards imposed by the EU. For the international harmonization, the magnitude of the coefficient in column (5) is slightly smaller than the one in column (4), but the difference is not significant. This last result is not surprising given that regardless of the importing country, international harmonization implies the adoption of the same level of regulation.

Columns (6)-(8) show three robustness checks. Column 6 first restricts the sample to manufactured products to disentangle the effect of TBT and SPS regulations (SPS are sanitary and phytosanitary regulations applied mainly to agri-food products; TBT are technical regulations that can be applied to all manufactured products). Because the results in columns (4) and (6) are very similar, excluding agricultural products from our sample leaves estimates unaffected, suggesting that non-sanitary technical regulations matter in EIAs.

Column (7) uses only three-year interval data (1991, 1994, 1997, 2000, 2003, and 2006) to avoid the potential bias associated with fixed effects estimations on data pooled over consecutive years. The results are unaffected.

Finally, column (8) includes a lag in the estimation. The results are again unaffected. Harmonization to regional standards is trade-restricting, whereas harmonization to international standards is trade-enhancing.

> 9 By the same token, Northern producers also enjoy protected access to the Southern market, which encourages North-South flows. Our estimates suggest that the trade-inhibiting effect on South-North flows more than offsets the encouragement effect on North-South flows.

29
ASIA DEPARTMENT **11**

# **1.** Estimates **and** Projections

|**_Vow_**|pqmAa&tiu|D.<br>m rtio|Pwled|Growth<br>**rate**|<br>cm|CDR|TF3|go<br>ftLm|0<br>**Firn**|to|9s<br>XIOOO|
|---|---|---|---|---|---|---|---|---|---|---|---|
|im<br>**1990**<br>1995<br>2000<br>2005<br>2010<br>2015<br>2020<br>2025<br>**2050**<br>2075<br>2100<br>2125<br>**2150**|272315<br> <br>300409<br>32876<br>3S6139<br>382349<br>406685<br>**.30524**<br>454359<br>4M94<br>561862<br>597573<br>613859<br>624166<br>**629270**|71.4<br>**66.3**<br>62.4<br>57.3<br>52.8<br>48.5<br>45.8<br>45.6<br>47.2<br>58.3<br>66.8<br>70.4<br>n.6<br>73.7|1985-89<br>1990-94<br>1995-99<br>2000-04<br>2005-09<br>2010-14<br>2014-19<br>2020-24<br>2025-49<br>2050-74<br>2075-99<br>2100-24<br>2125-49|1.96<br>1.80<br>1.60<br>1.42<br>1.23<br>1.14<br>1.08<br>0.99<br>0.65<br>0.25<br>0.11<br>0.07<br>0.03|28.0<br>2S.6<br>23.0<br>20.7<br>18.7<br>17.7<br>17.1<br>16.3<br>14.1<br>12.7<br>12.2<br>11.9<br>11.8|7.8<br>7.2<br>6.6<br>6.2<br>6.2<br>6.2<br>6.3<br>6.4<br>7.7<br>10.2<br>11.1<br>11.2<br>11.4|3.42<br>3.00<br>2.70<br>2.45<br>2.23<br>2.14<br>2.13<br>2.11<br>2.06<br>2.07<br>2.06<br>2.06<br>2.06|62.3<br>63.7<br>65.3<br>66.9<br>68.1<br>69.3<br>70.5<br>71.8<br>74.9<br>78.3<br>80.2<br>81.6<br>82.1|66.5<br>68.4<br>70.4<br>72.3<br>73.6<br>74.8<br>76.2<br>77.6<br>80.9<br>84.S<br>86.6<br>88.3<br>88.9|49<br>41<br>34<br>28<br>24<br>21<br>18<br>14<br>8<br>4<br>3<br>2<br>2|6S<br>54<br>43<br>35<br>31<br>26<br>22<br>18<br>10<br>5<br>4<br>3<br>3|

## 2. Age structure (percent): 1990 and 2025

<!-- Start of picture text --> 75 +<br>70.74<br>65.69<br>60-84<br>55.59<br>50-54<br>45-49<br>40-44<br>35-39<br>30-34<br>25-29<br>20-24<br>15-19<br>10.14<br>5.9<br>0-4<br><!-- End of picture text --> <!-- Start of picture text --> 10 8 6 4 2 0 2 4 6 8 10<br><!-- End of picture text --> <!-- Start of picture text --> 10 8 6 4 2 0 2 4 6 8 10<br><!-- End of picture text -->

### 3. Distribution of population (percent): 199C and 2025

<!-- Start of picture text --> ASS CS C 7. M AS 2 cli M<br>AN~( C3.<br>A CW<br><!-- End of picture text --> <!-- Start of picture text --> ~~~~~~~ASS C7 41) S sA2C1 %<br>AS, (3 )<br>a2<br><!-- End of picture text --> 29
Box 2 provides more examples of the strong and unmet demand for Islamic microfinance in selected OIC countries.

# **Box 2 – Strong demand for Islamic microfinance in different countries**

- In the West Bank and Gaza, more than 60% of low-income survey respondents prefer Islamic products to conventional products, and more than half of them still do if the Islamic products come at a higher price. (PlaNet Finance 2007)

- In Jordan, 24.9% and 32%, respectively, of those interviewed cite religious reasons for not obtaining conventional loans. 18.6% of those interviewed rank religious reasons as the single most important factor in obtaining a loan. (IFC and FINCA 2006)

- In Algeria, a 2006 study by Bankakademie International revealed that 20.7% of micro enterprise owners do not apply for a loan primarily due to religious reasons. (Bankakademie International 2006)

- In Yemen, it is estimated that 40% of the poor demand Islamic financial services, regardless of a higher price. (source: Phone interview with Executive director of the National Microfinance Foundation, Yemen)

- In Syria, an IFC survey revealed that 43% of respondents considered religious reasons to be the largest obstacle to obtaining a microcredit. In addition, 46% of respondents who had never applied for a loan stated that religious reasons were the primary reason they had never applied. Nearly 5% of current borrowers said they would not apply for another loan for religious reasons. (IFC/ The World Bank 2007)

- In Indonesia, according to a 2000 Bank Indonesia report, 49% of the rural population of East Java considers interest prohibited and would prefer to bank with Sharia-compliant financial institutions.

- In Lebanon, the success in outreach of Islamic programs relative to conventional _-_

- MFIs strongly suggests that large numbers of poor people prefer Sharia compliant finance.<sup>1</sup> In addition, microfinance practitioners report that many of the Lebanese poor refuse financial services unless they are Sharia-compliant. (Hamze 2001)

- Microfinance practitioners working in certain regions in Afghanistan, Syria, and Indonesia report similar results from their market surveys. (The Dubai Islamic Bank)

Source: World Bank Memoriam 27
funds, which are theoretically long-only investors, perform an important role by providing longterm financing and liquidity to the rest of the financial system. These large institutional investors are often thought of as stabilizers for the financial system and are expected to behave in a patient, counter-cyclical manner, making the most of cyclically low valuations to seek attractive investment opportunities. Moreover, since pension funds are usually thought of as investing for the long-term, these institutions have generally not been thought of as adding to systemic risk but this belief is fast changing (Shin, 2013).

This paper highlights how financial regulation may alter the behavior of pension funds and other long-term institutional investors. The MRG is intended to protect the interests of the working population by limiting unnecessary risk taking by pension fund managers. However, by relying on a benchmark based on peer returns, the regulation effectively incentivizes herding. Consequently, asset prices in the domestic market move in the short and medium run due to forces independent of fundamentals. Furthermore, these short-term considerations make these long-horizon traders also behave pro-cyclically, adding to systemic risk rather than stabilizing the system as was previously thought. Whether the welfare loss from this increased financial market inefficiency is clouded by the reduction in other forms of risk taking is still an open question and requires further investigation.

The evidence in this paper can be seen as providing credence to a large theoretical literature which emphasizes the role of reputational and relative performance concerns among institutional money managers on asset prices. The main contribution over a bulk of the existing literature can be seen in the fact that we are able to identify demands due to peer-group effects. The empirical literature typically measures herding indirectly as decision clustering. However, decision clustering may be driven by multiple forces acting simultaneously and it is hard to differentiate the role of relative performance concerns in correlated trading. Further, by being able to differentiate herding that exclusively results due to peer benchmarking considerations from that due to informational advantages, we are able to clearly identify the asset price effects associated with such herding.

While the evidence presented in this paper is from Colombian pension funds, and results are linked to the Colombian domestic market structure and size, the results of this paper should be 17
of the weaknesses in the use of exchange rates is one based on purchasing power parities (PPPs). A PPP is the number of units of a national currency needed to purchase the same amount of goods and services as a reference currency unit (for example, the US dollar) would buy in the reference country. PPPs allow more meaningful comparisons to be made across countries for many indicators—but they are not appropriate for some purposes. For example, international trade, capital flows, and the values of foreign debt must be measured at market exchange rates. Still, it seems clear that PPPs are the appropriate conversion factor for country classification purposes, compared with market exchange rates.

The major constraint to the use of PPPs has been the availability of regular and reliable time-series estimates for all countries of interest. This issue has been repeatedly discussed by World Bank Executive Directors (for example, World Bank, 1989, 1994 and 2000) but the consistent conclusion has been that the coverage and quality of annual PPP data (rather than the PPP estimates produced at each benchmark year) are not sufficiently robust for operational use. The international statistical community has undertaken substantial work in recent years to improve the quality of PPPs, especially in the 2005 and the more recent 2011 benchmark rounds of the International Comparison Program (ICP). The number of countries participating in the ICP has increased over time, and price collection procedures, valuation, and computation methods have all improved substantially.

Despite the improvements, difficulties with using PPP conversion factors for the annual classification of economies remain, because the ICP produces data for benchmark years only. This means that the classification system would have to rely on extrapolated or modeled annual estimates, using proxy measures. While extrapolated estimates are produced and published in _World Development Indicators_ , each benchmark round so far, including the latest results from the 2011 round, has resulted in substantial revisions to this series. In turn, this would have likely resulted in substantial revisions to the classification of countries, which would be both difficult to explain to users and provide another source of classification volatility.

Possible solutions are to improve extrapolation and interpolation methodologies, or for the ICP to collect prices in years between benchmarks and publish annual estimates of PPPs. Another approach could be to restrict changes in country classification to benchmark years only. While this latter proposal would potentially strengthen the basis for comparison between 21
Policy ReseaRch WoRking PaPeR 4327

# **Abstract**

Since the early 1980s, Turkey has been going through a rapid urbanization process at a pace beyond the World average. This paper aims at assessing the impact of this rapid urbanization process on the country’s sector productivity. The authors built a database combining two-digit manufacturing data and some geographical, infrastructural, and socio-economic data collected at the provincial level by the Turkish State Institute of Statistics. The paper develops a parsimonious econometric relation linking sector productivity to accessibility, localization, and urbanization economies, proxying variables in the tradition of the New Economic Geography literature. The estimation results suggest that both localization and urbanization economies, as well as market accessibility, are productivity-enhancing factors in Turkey, although the causation link between productivity and these agglomeration measures is not clearly established.

The sector-by-sector estimation confirms this result, although the localization economies effect is negative for the non-oil mineral sector, and the urbanization economies effect is weak for natural-resource-based sectors such as the wood and metal industry.

Although the data cover the period up to 2000 and thus ignore the financial crisis that hit Turkey in 2001, the current structural transformation of the country away from the agricultural sector gives room to use the insights of these results as a preliminary step to understand the new challenges faced by the Turkish manufacturing sector. The results provide a discussion base to revisit the policy agenda on the improvement of the accessibility to markets, the improvement of the business environment to ease the creation and development of new firms, and a well-managed urbanization process to tap in the economic potential of cities.

This paper—a product of the Urban Unit, Sustainable Development Network in the Europe and Central Asia region—is part of a larger effort in the department to assess the impact of the growing urbanization on productivity in the Europe and Central Asia region. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at scoulibaly2@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