rafmacalaba/datause-encoder-data huggingface dataset:
from transferring knowledge to their local suppliers or clients, spillovers from FDI are more likely to be negative along the horizontal dimension and positive along the vertical dimension. Javorcik uses firm-level data from Lithuania and Blalock and Gertler (2008) use data for Indonesia to show that positive FDI spillovers take place through backward linkages (between foreign affiliates and their local suppliers); however, there is no robust evidence of positive spillovers occurring through either the horizontal or the forward linkage channel.

One recent manuscript that investigates both horizontal and vertical FDI spillovers in China is Lin, Liu, and Zhang (2009). In contrast to Javorcik (2004), Lin, Liu, and Zhang find bigger forward and smaller backward spillovers. Our results will differ from theirs, in part because we focus on total factor productivity and they examine value-added productivity and also use a different estimation method. We also expand the analysis to explore the relationship between trade policies, tax incentives, and externalities from foreign investment. To our knowledge, ours is the first study to explore—in China or elsewhere--how productivity gains from foreign investment vary with tax and tariff policies.

There are also a set of theoretical studies demonstrating that positive FDI spillovers are more likely to operate across industry rather than within an industry. These studies emphasize efforts to minimize the probability of imitation, especially under imperfect intellectual property rights in the host country. As Markusen and Venables (1998) point out, proximity to potential domestic competitors with absorptive capacity to reverse engineer proprietary technology would be detrimental to a multinational, thus motivating it to set up its subsidiaries where potential rivals cannot erode its market share. By contrast, the multinational can benefit from knowledge diffusion when it reaches downstream clients and upstream suppliers, which will encourage vertical flows of generic knowledge that lead to inter-industry spillovers.

This study goes further by investigating the implications of the institutional context for the nature of spillovers. In particular, we examine three institutional features that comprise aspects of China‘s ―special characteristics‖: the different 3
SIERRA LEONE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 15. Expansion of water and sanitation technologies at the national, urban, rural levels**

Population gaining access per year between 2000–2008 <!-- Start of picture text --> b. Sanitation<br><!-- End of picture text --> <!-- Start of picture text --> a. Water b. Sanitation<br>5<br>5<br>4 4.0 4 4.0<br>3.3<br>3.3<br>3 3<br>2.8<br>2 2<br>1 1<br>0 0<br>National Urban Rural Nationa l Urban Rural<br>-1 -1<br>-2 -2<br>Piped Water Standposts Septic tanks Improved Latrines<br>Wells/Boreholes Surface Water Traditional Latrines Open Defecation<br>Annualized Growth Annualized Growth<br>Source: Access figures calculated by AICD using data from the 2000 Multiple Indicators Cluster Survey as published by the JMP in March 2010<br>and the 2008 Demographic and Health Survey.<br>Rapid population growth (particularly in urban areas) has been an important contributor to declining<br>access (figure 16). Between 2000 and 2008 Sierra Leone‘s population grew at a pace of 3.4 percent per<br>year, one of the highest among Sub-Saharan African countries. In urban areas, where the average<br>population growth has been 4 percent per year, experienced important inflows of refugees who fled<br>during the civil conflict in the 1990s.<br>Figure 16. Urban versus rural access to water supply and sanitation, 2008<br>a. Water supply b. Sanitation<br>100 100<br>90 90<br>80 80<br>70 70<br>60 60<br>50 50<br>40 40<br>30 30<br>20 20<br>10 10<br>0 0<br>Piped Stand Posts/ Wells and Surface Water Flush toilets Improved Traditional Open<br>Shared Boreholes Latrines Latrines Defecation<br>Urban Rural Urban Rural<br>Population gaining access per year (%) Population gaining access per year (%)<br>% population % population<br><!-- End of picture text --> Source: Access figures calculated by AICD using data from the 2000 Multiple Indicators Cluster Survey as published by the JMP in March 2010 and the 2008 Demographic and Health Survey.

Rapid population growth (particularly in urban areas) has been an important contributor to declining access (figure 16). Between 2000 and 2008 Sierra Leone‘s population grew at a pace of 3.4 percent per year, one of the highest among Sub-Saharan African countries. In urban areas, where the average population growth has been 4 percent per year, experienced important inflows of refugees who fled during the civil conflict in the 1990s.

Source: AICD water supply and sanitation utilities database downloadable from http://www.infrastructureafrica.org/aicd/tools/data. Access figures calculated by AICD using data the 2008 Demographic and Health Survey.

33
**WHAT MATTERS TO AFRICAN FIRMS? The Relevance of Perceptions Data**

**Alan Gelb (World Bank) Vijaya Ramachandran (Center for Global Development) Manju Kedia Shah (World Bank) Ginger Turner (Oxford University)**

The authors are grateful to George Clarke, Michael Clemens, William Cline, Benn Eifert, Ana Fernandes, Alan Hirsch, Alvaro Gonzalez, Giuseppe Iarossi, Aart Kraay, Steve Knack, Phil Keefer, Taye Mengistae, Jean Michel Marchat, Luis Serven, David Roodman, and seminar participants at the Center for Global Development, Cornell University, and the World Bank for helpful suggestions. Comments are welcome and can be sent to Alan Gelb at agelb@worldbank.org or Vijaya Ramachandran at vramachandran@cgdev.org.

The findings, interpretations and conclusions expressed in this paper do not represent the views of the World Bank, its Executive Directors or the countries they represent.
# Competition, Imitation, and Technical vs. Change: Quality Variety

Ana Cusolito<sup>_∗_</sup> The World Bank

## **1 Introduction**

In a recent paper, Imbs and Wacziarg[32] find that the path of development is remarkably related to the pattern of sectoral diversification. Furthermore, Acemoglu and Zilibotti[2] provide a theory that links sectoral diversification and market incompleteness to capital accumulation and growth. Other contributions in this literature, including Gurley and Shaw[26] and SaintPaul[44], highlight the relation between productive specialization and economic progress. This paper explores the role of product market competition and intellectual property rights protection on the pattern of sectoral specialization.

In doing so, the paper develops an endogenous growth model in which high-productive firms innovate and low-productive companies imitate. Innovating firms can perform two different types of innovations. They can improve the quality of existing products, or they can create new but on average low-quality goods. Imitating firms decide what kind of good to copy. The framework includes knowledge spillovers from the R&D activity, and a

> _∗_ The Development Economics Research Group. The World Bank. 1818 H NW, MSN MC3-303. Washington DC, 20433 USA. acusolito@worldbank.org. This research was funded by The World Bank’s Multi-Donor Trust Fund No. TF093822. I am indebted to Antonio Cabrales, Daniel Lederman, Gino Gancia and Jaume Ventura for helpful discussions. I am grateful to the Central Bank of Italy for providing me with data.

1
- 15 -

26. Almost all the DTCs were affected by the recession. The apex co-operative to the DTCs, the Co-operative Central Bank (CCB) with 363,749 members and total deposits of M$1.5 billion, also began to face problems of non-performing loans. The 1987 audited accounts of CCB showed accumulated losses of over M$726 million, and a capital deficiency of M$652 million. The CCB was put into receivership and the Government made available a standby facility of M$323 million to help its liquidity needs. By the end of 1987, Bank Negara had 32 DTCs under its investigation or supervision, involving total deposits of M$3.1 billion or an estimated 77% of the total deposits of the 38 identified DTCs (35 original DTCs and three in Sabah) in the country.

27. Amongst the non-bank financial intermediaries, the insurance industry was also not spared from the ravages of the recession. In the financial year ended 1986, 14 out of 61 insurance companies did not comply with the minimum solvency requirement of 20% of their net premium income. Inspection findings of the Office of the Director-General of Insurance revealed that solvency problems had been compounded by the underprovisioning of outstanding claims reserves, bad debts from poor agency collection and falls in value of investments in quoted securities and landed properties. To co-ordinate supervision of the financial system as a whole, the duties and responsibilities of the Director-General of Insurance, previously a department of the Treasury, were transferred to the Central Bank with effect from April 1, 1988.

# PART 3: ISSUES AND RESOLUTION

3.1 Approach towards ailing financial institutions 28. Financial stress arising from a sudden Malaysia: Real interest rate downward shift in relative Sim _W prices causes fundamentally a shrinking of enterprise balance sheets. This **s** contraction occurs primarily _ through a reduced cash flow 7 and deterioration in the I\ profit and loss account. Initially, enterprises which , /\ were not able to adjust their a\ expenditure to the shortfall 2\ in income begin to suffer large operating losses. In **-I1A** addition, they may also 56 49s" is,= **1auu9** **_lis_ .u,** . **i,** suffer substantial capital + a _n r"Mt_ losses, since forced disposal of assets in order to realize Figure 6 cash, arising from a liquidity crisis often leads to a solvency crisis. Faced with survival problems, many cash-strapped enterprises engaged in "distress borrowing", paying exceptionally high rates for funds just to meet temporary
Our estimations yield a number of interesting results. First, we find a strong positive association of higher outreach with the traditional indicators of financial development (Table V).<sup>14</sup> Specifically, we find a positive and significant correlation of private credit to GDP, liquid liabilities to GDP and total deposits to GDP with all our indicators, with the notable exception of loan-income and deposit-income ratios. Also, it does not appear to be the case that greater outreach comes at the expense of higher overhead costs to total assets or higher interest margins.<sup>15</sup> Second, not surprisingly, we find outreach to be correlated with population density and economic size. In particular, more densely populated countries have higher geographic branch and ATM penetration, while there is no robust correlation with the indicators measuring demographic penetration of bank outlets and the indicators measuring the use of banking services. This is confirmed by the regressions in Tables VI-IX. At the same time, we find that larger economies have higher bank and ATM penetration and show higher use of loan and deposit services. This suggests economies of scale in banking service delivery.<sup>16</sup> Third, the positive association of institutional and financial development extends to the access to and use of banking services (Table VI).<sup>17</sup> Here we use as one of our measures of institutional quality the Kaufman, Kraay and Mastruzzi (2003) _Governance Index_ , which averages six sub-indices measuring rule of law, control of corruption, voice and accountability, political stability, government effectiveness and regulatory quality. Further, we use the Heritage Foundation _Index of Barriers to Economic Freedom_ - an average of ten sub-indices including

> 14 We do not include the financial sector indicators in the regressions, since unlike for the other variables, there is a strong case for bi-directional causality, which might bias the OLS coefficients and renders interpretation problematic.

> 15 This interpretation has to be taken with a grain of salt since the correlations might also indicate that sectors that provide greater outreach are more competitive and therefore margins are lower as a result.

> 16 Only when we control for communication infrastructure (Table IX), does economic size turn insignificant.

> 17 For an overview of the importance of legal institutions for financial development, see Beck and Levine (2005).

16
<!-- Start of picture text --> Middle East and North Africa<br>ick Te ese Gub-Saharan Africa<br>8<br>a oO eee<br>{Woe _. em Asia-Pacific<br>3 me central and Eastern Europe<br>é<br>5 North America<br>3<br>1<br>iNe<br>10 —<—<br>2007 2012<br><!-- End of picture text -->
women who have inordinately liberal attitudes to gender equality in education – both for their children and within their own marriages. When seen together with the low educational attainment of women in Sylhet this presents itself as a sort of “yearning for education” among women. But Chittagong defies explanation. It is next to Sylhet in the perception of conservatism and in terms of low levels of educational attainment of girls, and also comes across as the region with the most conservative attitudes to educational equality among girls and boys.<sup>2</sup>

# **CONCLUSION**

Our results show that the far-reaching changes in Bangladesh in terms of female education seem to have had equally far-reaching impacts on the value of girls’ education relative to boys. Education for women thus explains these liberal attitudes towards their children’s education. But in terms of their attitudes to their marriages, Bangladeshi women are still very conservative and education has done little to change that. We predict for the future that as female education expands, the demand for girls’ education will grow even more robust. Also, as more wives are equal or better educated than their husbands, the value of equality in marriages, too, will grow.

> 2 These observations are further supported by the data on gross enrollment rates of boys and girls by level and region presented earlier (see Table 1), especially for lower and higher secondary.

21
# 1. **Introduction**

Indoor air pollution from burning wood, animal dung and other biofuels is a major cause of acute respiratory infections (ARI), which constitute the most important cause of death for young children in developing countries (Murray and Lopez, 1996). Acute lower respiratory infection (ALRI), the most serious type of ARI, is often associated with pneumonia (Kirkwood et al., 1995). ALRI accounts for 20% of the estimated 12 million annual deaths of children under five, and about 10% of perinatal deaths (WHO, 2001; Bruce, 1999). Nearly all of these deaths occur in developing countries, with the heaviest losses in Asia (42% of total deaths) and Africa (28%) (Murray and Lopez, 1996). Through its effect on respiratory infections, indoor air pollution (IAP) is estimated to cause between 1.6 and 2 million deaths per year in developing countries (Smith, 2000). Most of the dead are in poor households and approximately 1 million are children (Smith, 1993; Smith, et al., 1993; Smith and Mehta, 2000). Table 1 provides estimates of health damage from IAP by region.

**Table 1:  Annual Disease Burden From Indoor Air Pollution (Early 1990’s)**

|Region|Deaths<br>(‘000)|Illness<br>Incidence<br>(‘000,000)|DALYs<sup>~~1~~</sup><br>(‘000,000)|
|---|---|---|---|
|China|516.5|209.7|9.3|
|India|496.1|448.4|16.0|
|Sub-Saharan Africa|429.0|350.7|14.3|
|Other Asia & Pacific Islands|210.7|306.4|6.6|
|Mid-East and North Africa|165.8|64.2|5.6|
|Latin America & Caribbean|29.0|58.2|0.9|
|Total|1,800.0|1,400 .0|53.0|

Source: World Bank (2002), drawing on Smith and Mehta (2000) and Von Schrinding, et al., (2001) The size of IAP’s estimated impact has prompted the World Bank (2001) and other international development institutions to identify reduction of indoor air pollution as a critical objective for the coming decade. The current scientific consensus is that most respiratory health damage comes from

> 1  DALYs, or disability-adjusted life years, combine life-years lost from premature death and fractional years of healthy life lost from illness and disability (Murray and Lopez 1996).

3
SPEcIAL ToPic **1: PROJECTING** AIDS MORTALITY **btvil** <!-- Start of picture text --> Figure S4. Life Expectancy Cyears)<br>Sekharan Africa, 198-220<br>63<br>62<br>61<br>s0<br>59<br>so<br>57<br>58<br>54<br>53<br>52<br>15-90 1990-9S 19500 2000-05 2005-10 2010-15 2015-20<br>0 No AIDS + AIDS<br><!-- End of picture text --> Figure S5. Annual Deaths Cmillions) <!-- Start of picture text --> Su.C-Satirrsn Africa. 1985-2020<br>11<br>10<br>9<br>a<br>7<br>4<br>lIeS-S0 1990-95 1995-00 2000-05 2005-10 2010-15 2015-20<br><!-- End of picture text -->
Table A2: Profile of the poor across urban versus rural areas

||||**Poor b**|**y DOU**|||**Po**|**or by D**|**B**||
|---|---|---|---|---|---|---|---|---|---|---|
||All<br>(1)|Urban <br>(2)|center <br>(3)|Urban <br> cluster <br>(4)|Urban<br> Rural <br>(5)|Urban <br>(6)|Core <br>(7)|Suburb <br>(8)|Town <br>(9)|Other<br> Rural<br>(10)|
|**Demographic:**|||||||||||
|Household size|6.55|7.05|6.97|7.09|7.50|7.49|7.56|6.95|8.07|7.06|
|Age of household head|40.31|42.15|42.82|41.87|40.20|40.40|41.12|36.56|44.26|41.62|
|Household head is male|0.78|0.74|0.69|0.77|0.81|0.79|0.75|0.80|0.82|0.79|
|No education|0.37|0.29|0.25|0.30|0.49|0.44|0.37|0.40|0.55|0.40|
|Primary complete or incomplete|0.39|0.55|0.54|0.56|0.44|0.46|0.47|0.51|0.38|0.51|
|Secondary complete or incomplete|0.18|0.15|0.19|0.13|0.07|0.09|0.14|0.07|0.07|0.08|
|Tertiary complete or incomplete|0.06|0.02|0.02|0.01|0.00|0.01|0.02|0.01|0.00|0.00|
|**Employment (of household head):**|||||||||||
|Not in labor force|0.12|0.16|0.19|0.14|0.14|0.14|0.14|0.14|0.13|0.17|
|Unemployed|0.03|0.05|0.09|0.03|0.02|0.03|0.05|0.02|0.02|0.03|
|Employed in Agriculture|0.52|0.49|0.19|0.61|0.73|0.64|0.49|0.70|0.73|0.68|
|Employed in Industry|0.08|0.08|0.12|0.06|0.04|0.05|0.08|0.04|0.04|0.04|
|Employed in Services|0.26|0.23|0.40|0.16|0.07|0.14|0.24|0.10|0.07|0.08|
|**Access to basic services**|||||||||||
|Improved water|0.69|0.77|0.86|0.73|0.59|0.65|0.74|0.61|0.59|0.63|
|Improved sanitation facility|0.24|0.25|0.32|0.21|0.16|0.18|0.23|0.14|0.17|0.20|
|Access to electricity|0.48|0.37|0.56|0.29|0.20|0.26|0.35|0.22|0.23|0.20|

Source: International Urban Poverty Database. Note: WorldPop 250m is used for the DOU and DB methods. Poverty is measured using the $2.15 poverty line.

42
# **Exhibit A.3 – MSCI investible market indices for selected countries, January 1**<sup>**st**</sup> **2003-June 20**<sup>**th**</sup> **2008**

_Denominated in local currencies_ <!-- Start of picture text --> 2000<br>1800<br>1600<br>Egypt<br>1400<br>Abu Dabhi<br>1200<br>1000 Amman<br>800<br>Casablanca<br>600<br>Kuwait<br>400<br>200 Manama<br>0<br>Muscat<br>Qatar<br>01/02/2003 07/02/2003 01/02/2004 07/02/2004 01/02/2005 07/02/2005 01/02/2006 07/02/2006 01/02/2007 07/02/2007 01/02/2008 07/02/2008<br><!-- End of picture text --> _Source: Bloomberg_

**Exhibit A.4 – Number of firms simultaneously covered by Bloomberg, January 1**<sup>**st**</sup> **2003June 20**<sup>**th**</sup> **2008**

<!-- Start of picture text --> Number of<br>stocks, %<br>250 Egypt<br>Abu Dabhi<br>200 Amman<br>Casablanca<br>150 Kuwait<br>Manama<br>100 Muscat<br>Qatar<br>50<br>0<br>1/2/2003 5/2/2003 9/2/2003 1/2/2004 5/2/2004 9/2/2004 1/2/2005 5/2/2005 9/2/2005 1/2/2006 5/2/2006 9/2/2006 1/2/2007 5/2/2007 9/2/2007 1/2/2008 5/2/2008<br><!-- End of picture text --> _Source: Bloomberg_ 38
# Mass Media and Public Policy:

# Global Evidence from Agricultural Policies

_Alessandro Olper and Johan Swinnen_<sup>_1_</sup>

## **JEL classification:** D72, D83, Q18

**Keywords:** Mass Media; Information; Agricultural Protection; Political Economy

**Sector Board:** Public Sector Governance (PSM)

1 Alessandro Olper is an associate professor at the University of Milano, Italy, and a researcher at Centre for Institution and Economic Performance; his email address is <u>alessandro.olper@unimi.it. Jo Swinnen is a professor of economics and director of Centre</u> for Institution and Economic Performance at the University of Leuven, Belgium, and visiting professor at Stanford University, United States. His email address is <u>Jo.Swinnen@econ.kuleuven.be.</u> This work was supported by the KU Leuven Research Council (Methusalem project). The authors would like to thank the participants in several conferences and meetings, the editor, and three anonymous referees for the _World Bank Economic Review_ for useful comments and suggestions.
Nevertheless, rigorous validation strategies must be developed. At a minimum, in-sample validation techniques should be used.<sup>18</sup> The potential for out-of-sample validation remains unknown, but access to longer CDR data series, which include more than one household survey, could help address this concern.

## **_Privacy_**

Data privacy is a sensitive and often controversial issue, and certain precautions must be taken before analyzing CDR data. Identifiers should be obscured before records are exported from MNO systems, so that cell phone numbers or similar fields do not remain in the output data. This process is referred to as “pseudonymization.” In general, pseudonymization should ensure that the same pseudonym is applied to a given user’s entire call history.

Research suggests that simple pseudonymization can be reversed by a determined individual armed with relatively easy-to-obtain auxiliary information, such as a person’s home and work addresses and one or two other locations that they are known to visit at particular times.<sup>19</sup> Therefore, additional technical and institutional measures are necessary to restrict access to the data. This has generally entailed nondisclosure agreements between MNOs and researchers, and the research, development and MNO communities are striving to streamline this process.

In addition, any final data produced as a result of the CDR analysis should not compromise individuals’ privacy. Similar precautions to those used when releasing tabulations from traditional survey data can reinforce the privacy of CDR data. These measures may include grouping data where cell sizes fall below some fixed number of people (e.g. 5 or 10), or top- and bottom-coding variables in cases where extreme values could be revealing.

# **Other Promising Applications of CDR Analytics**

CDRs offer a rich dataset for studying populations, and numerous applications are emerging in areas beyond poverty measurement. Two applications of particular relevance to the World Bank’s work in Guatemala and the Latin America region are described below.<sup>20</sup>

## **_Transportation Analysis_**

> 18 In-sample validation techniques include holdout test sets or leave-one-out cross validation. 19 De Montjoye (2013).

> 20 A more complete review is provided in Blondel (2015).

**19**