rafmacalaba/datause-encoder-data huggingface dataset:
other side arguing that the 2011 prices were ‘too low,’<sup>6</sup> the results of the comparison of the 2011 ICP PPPs with the counterfactual PPPs acquires considerable interest. Since a key distinctive feature of the alternative methodology proposed here to calculate PPP is that it dispenses with the need for price information, the present results acquire significance in the context of this debate on the quality of the price information used in the ICP PPPs. Moreover, it addresses a significant practical issue, namely, that in the case of most developing countries the required price information is missing or is of suspect quality.

Another distinctive feature of this exercise is the use of the Indian rupee as the numeraire currency instead of the US dollar. This is much more than a simple change of the base country, from USA to India, since while interest in all the existing PPP applications in ‘real expenditure comparisons’ centers on the question of whether the world is ‘richer’ or ‘poorer’ in relation to the USA, the counterfactual PPPs and their implied real expenditure comparisons presented here are with respect to India. While the 2011 ICP PPPs suggest that the world has suddenly become a lot ‘richer’, or more accurately ‘less poor’, with respect to the USA when compared with the 2005 ICP PPPs, a distinctive finding of this study is that the 2011 ICP PPPs make much of the developing world look ‘richer’ or ‘less poor’ with respect to India as well, but the comparison here is with the alternative set of 2011 non ICP PPPs, not with a previous set of ICP PPPs. The move to India is justified by the fact that India occupies a unique position in sharing the features of a developing economy in terms of its poverty rates and per capita expenditure, yet it offers a market and the size of its aggregate economy that dwarf many of the developed economies. If the often made comparisons between the 2005 and 2011 ICP PPPs suggest a downward bias in the 2011 ICP PPPs, vis a vis the US dollar, the counterfactual exercise of the present study extends that finding vis a vis the Indian rupee.

# **Organization**

The rest of the paper is organized as follows. Section 2 proposes a non-homothetic preference based analytical framework that yields propositions on the relationship between (a) PPP and exchange rates, (b) PPP and consumption patterns, (c) PPP and factor endowments, and (d) PPP and inequality. Section 3 presents the empirical evidence on non-homothetic preferences

> 6 See Ravallion (2014) and Jolliffe and Prydz (2015) for alternative, indeed contradictory, comparative assessments of the price information collected in ICP 2005 and ICP 2011. While Ravallion (2014) finds issues with ICP 2011, Jolliffe and Prydz (2015) are critical of the price information collected in ICP 2005. Inklaar and Rao (2015) attempt at reconciling the PPPs from ICP 2005 and ICP 2011, and argue that “relying on a single benchmark for country figures is hazardous”.

7
within-sector productivity and the lower employment rate have had a negative impact on growth. The contribution of demographic changes is, however, much larger in this period. We also note some distinctive features with respect to sectoral growth contributions. The contribution of agriculture to static structural change turned positive. All major sectors posted negative productivity growth. Altogether, unlike the period 1998-2005 when structural change and “within” gains together accounted for almost all of growth, they explained only 30 percent of per capita growth in 2005-2014.

**Table 6. Burkina Faso: Sectoral contributions to inter-sectoral shifts**

||**1998-2014**<br>||
|---|---|---|
||Direction of<br>employment<br>share shift|Contribution to<br>inter-sectoral<br>shifts (%)|
|Agriculture|-|18.53|
|Mining|+|7.25|
|Manufacturing|+|10.64|
|Utilities|-|-1.83|
|Construction|+|10.75|
|Transport|+|7.24|
|Commerce|+|17.05|
|Finance|-|-1.16|
|Other services|+|31.52|
|_Total_||_100_|

Source: Author’s estimation based on data described in Section 2.

In the case of Côte d’Ivoire, the very small per capita growth in 2002-2014 was due to the higher employment rate and, to a much lesser extent, structural change, while persistent decline in “within” productivity reduced growth. Of the 0.9 percent annual average growth in output per capita, acceleration in the employment rate contributed around 1.46 ppts while structural change made up 0.45 ppts. The substantial contribution of the employment rate, combined with the strongly negative productivity growth, suggests that increased production in Côte d’Ivoire since the early 2000s was not based on productivity increases but instead on increased accumulation of factors such as labor. The within component, however, made a significant negative contribution, offsetting almost all of the gains due to the employment rate and structural change.

**Table 7. Côte d’Ivoire: Sectoral decomposition of GDP per capita growth: 2002-2014 (Annual percentage changes)**

|||% C<br>|ontributio|n of<br>|||
|---|---|---|---|---|---|---|
||Within-sector|Employment||Inter-sectoral||Total|
||productivity|rate|Static|Dynamic|total|(%)|
|Agriculture|-0.08|-0.07|0.49|0.06|0.56|0.41|
|Mining|-0.03|0.01|0.08|0.00|0.08|0.06|
|Utilities|-0.28|0.05|-0.04|-0.01|-0.04|-0.27|
|Manufacturing|0.33|-0.01|-0.09|0.00|-0.08|0.24|
|Construction|-0.15|0.05|0.03|0.00|0.03|-0.06|
|Transport|-0.19|0.08|0.10|0.00|0.09|-0.02|
|Commerce|-0.81|0.98|-0.24|0.06|-0.19|-0.01|
|Finance|0.08|-0.01|-0.16|0.00|-0.16|-0.09|
|Other services|-0.06|0.37|0.16|0.00|0.15|0.46|
|Subtotals|**-1.19**|**1.46**|**0.35**|**0.11**|**0.45**|**0.73**|
|Demographic co|mponent|||||**0.17**|
|Annual % chang<br>Source: Author’s est|e in GVA per cap<br>imation based on da|ita<br>ta described in Sect|ion 2.|||**0.896**|

Agriculture accounted for most of the growth attributed to structural change, while the higher employment rate could be largely explained by changes in commerce and ‘other services’. In addition, 20
|P146287|2014|2017|8/4/2016|5 Active|Mali|
|---|---|---|---|---|---|
|P146287|2014|2017|3/9/2017|6 Active|Mali|
|P146287|2014|2018|10/31/2017|7 Active|Mali|
|P146287|2014|2018|6/5/2018|8 Active|Mali|
|P146287|2014|2019|12/20/2018|9 Active|Mali|
|P146287|2014|2019|4/30/2019|10 Active|Mali|
|P146287|2014|2020|11/26/2019|11 Active|Mali|
|P146287|2014|2020|5/13/2020|12 Active|Mali|
|P146294|2015|2016|12/3/2015|1 Closed|Togo|
|P146294|2015|2016|6/9/2016|2 Closed|Togo|
|P146294|2015|2017|12/19/2016|3 Closed|Togo|
|P146294|2015|2017|6/28/2017|4 Closed|Togo|
|P146294|2015|2018|12/27/2017|5 Closed|Togo|
|P146294|2015|2018|6/28/2018|6 Closed|Togo|
|P146294|2015|2019|12/31/2018|7 Closed|Togo|
|P146294|2015|2019|6/13/2019|8 Closed|Togo|
|P146294|2015|2020|9/27/2019|9 Closed|Togo|
|P146312|2014|2014|5/20/2014|1 Closed|Yemen,Republic of|
|P146312|2014|2015|11/3/2014|2 Closed|Yemen,Republic of|
|P146312|2014|2015|6/13/2015|3 Closed|Yemen,Republic of|
|P146312|2014|2016|12/17/2015|4 Closed|Yemen,Republic of|
|P146312|2014|2016|6/21/2016<br>|5 Closed|Yemen,Republic of|
|P146312|2014|2017|12/12/2016|6 Closed|Yemen,Republic of|
|P146314|2014|2015|9/29/2014|1 Active|Sri Lanka|
|P146314|2014|2015|4/2/2015|2 Active|Sri Lanka|
|P146314|2014|2016|8/26/2015|3 Active|Sri Lanka|
|P146314|2014|2016|5/16/2016|4 Active|Sri Lanka|
|P146314|2014|2017|12/19/2016|5 Active|Sri Lanka|
|P146314|2014|2017|6/22/2017|6 Active|Sri Lanka|
|P146314|2014|2018|12/15/2017|7 Active|Sri Lanka|
|P146314|2014|2018|6/27/2018|8 Active|Sri Lanka|
|P146314|2014|2019|12/23/2018|9 Active|Sri Lanka|
|P146314|2014|2019|6/26/2019|10 Active|Sri Lanka|
|P146314|2014|2020|12/31/2019|11 Active|Sri Lanka|
|P146314|2014|2020|6/29/2020|12 Active|Sri Lanka|
|P146318|2014|2015|7/4/2014|1 Active|Armenia|
|P146318|2014|2015|1/30/2015|2 Active|Armenia|
|P146318|2014|2016|8/14/2015|3 Active|Armenia|
|P146318|2014|2016|2/17/2016|4 Active|Armenia|
|P146318|2014|2017|9/24/2016|5 Active|Armenia|
|P146318|2014|2017|12/22/2016|6 Active|Armenia|
|P146318|2014|2018|11/7/2017|7 Active|Armenia|
|P146318|2014|2018|6/29/2018|8 Active|Armenia|
|P146318|2014|2019|12/19/2018|9 Active|Armenia|
|P146318|2014|2020|7/17/2019|10 Active|Armenia|
|P146318|2014|2020|2/5/2020|11 Active|Armenia|
|P146318|2014|2020|6/22/2020|12 Active|Armenia|
MALI’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE and 2001 but fell by 0.5 percent of population per year between 2001 and 2006, during which the use of wells and boreholes increased by 2.4 percent of population per year.

**Table 8.  Expansion of safest water and sanitation technologies**

|a.Water|Population g<br>(per y|aining access<br>ear, %)|b. Sanitation|Population<br>(per|gaining access<br>year, %)|
|---|---|---|---|---|---|
||1996–2001|2001–2006||1996–2001|2001–2006|
|Piped water|0.79|0.55|Flush toilets|1.04|–0.57|
|Standposts|2.05|–0.51|Improved latrines|1.36|2.28|
|Wells/boreholes|–1.20|2.34|Traditional latrines|0.50|0.25|
|Surface water|0.24|–0.05|Open defecation|–1.18|0.32|

Source: WHO–Joint Monitoring Programme 2010, from Demographic and Health Surveys for 1987,1996, 2001 and 2006 Between late 1900s and early 2000s, the patterns from providing access to sanitation modalities have shifted from flush toilets to improved latrines. Population gaining access to flush toilets increased by 1 percent per year between 1996–2001 while during 2001–06 fell by –0.6 percent. During the same periods, the percentage of the population gaining access to improved latrines each year increased by 60 percent from 1.4 to 2.2 percent (table 8b). Although population using open defecation decreased at a 1.2 percent per year during 1996–01, for 2001–06 every year 0.3 percent of the population regained use of open defecation.

Urban water is provided by EDM (Energie du Mali) a multiservice utility that provides access to both water and to electricity. EDM has been instrumental in Mali’s achievements in provision of improved water and sanitation services in urban areas, managing to keep up with population growth and urbanization rates. The share of the population that EDM serves through private residential connections in EDM service areas went from 18.6 percent in 2000 to 29.0 percent in 2007. Over that same period, the number of household connections rose from 54,688 to 103,286—an increase of about 90 percent. Similarly, the number of community standpipes almost doubled from around 1,000 in 2001 to 2,400 in 2005, corresponding to an increase in access via standpost from 20 percent to 34 percent.

EDM’s improvements in providing access can be traced to its 2000 award of a concession to a private consortium composed of SAUR International, a member of the French group Bouygues (table 9). The concession was later cancelled owing to financial strain but left a track record of improved standard operational efficiency indicators: nonrevenue water fell from 36 percent in the early 2000s to 26 percent in 2008; connections per employee rose from 189 in 2005 to 210 in 2007; and revenue per cubic meter of water consumed increased from $0.57 in 2000 to $0.66 in 2007.

21
# WPS3619

## **State Bank Transformation in Brazil – Choices and**

## **Consequences**

### **Thorsten Beck, Juan Miguel Crivelli and William Summerhill**

**Abstract:** This paper analyzes the different options – liquidation, federalization, privatization and restructuring – that the Brazilian state government had for the transformation of state banks under the Programa de Incentivo á Redução do Setor Público Estadual na Atividade Bancária (PROES) in the late 1990s. Specifically, the paper explores (i) the factors behind the states’ choices and (ii) the effects of the transformation process on bank performance and efficiency. We find that states that were more dependent on federal transfers, whose banks were already under federal intervention and that established development agencies were more likely to relinquish control over their banks and transformation processes. We find that privatized banks improved their performance, while restructured banks did not.

#### Keywords:  Bank privatization; Brazil; bank performance

JEL Classification: G21 ; G28 ; H77

#### World Bank Policy Research Working Paper 3619, June 2005

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ Beck and Crivelli: World Bank; Summerhill: University of California at Los Angeles. We are grateful to Fernando Blanco, Robert Cull, George Clarke, Phil Keefer, Anjali Kumar, Marcio Nakane, Alvaro Vivanco, and an anonymous referee for useful suggestions and discussions, and to Duillo Pighi for excellent research and editorial assistance. We also benefited from comments by participants at the World Bank Conference on Bank Privatization and ISNIE 2004.
earlier: -0.5, -1.0, and -1.8.<sup>15</sup> With the survey data, poverty falls from 39 percent in 2002 to 35 percent in 2015. With the elasticity approach, in the most favorable case (an elasticity of -1.8), poverty falls from 42.3 percent in 2002 to 26.1 percent in 2015. However, with a partial elasticity of -0.5 (which is close to the estimate provided by Christiansen, Demery, and Paternostro (2003) for Ethiopia, as noted earlier), the poverty rate falls from 43.7 percent to only 38.4 percent. Thus, whether a significant and sustained reduction in poverty can be achieved in Ethiopia may depend crucially on the country’s ability to improve its growth performance. We now turn to an examination of these issues, with a focus on the impact of foreign aid and public investment.

# **IV. POLICY EXPERIMENTS**

We now examine four types of policy experiments: changes in the level and composition of foreign aid (which imply also changes in the level of public investment), changes in the composition of public spending coupled with a reallocation of public investment (for a given level of foreign aid), and an evaluation of the level of aid needed by Ethiopia to achieve a 50 percent reduction in poverty between 2003 and 2015. All results are displayed as percentage changes (for variables in levels) or absolute differences (for variables in percentage form) from baseline values.

# **1.  Change in the Level of Foreign Aid**

Our first experiment consists of a permanent increase in the aid-GDP ratio by one percentage point relative to the baseline scenario. This implies that both categories of aid increase in the same proportion, given that the shares of food and nonfood aid remain constant.

> 15Note that these calculations do not account for the possibility of asymmetric effects in the relationship between growth and poverty—an issue discussed at length in Agénor (2004 _c_ ). These effects could actually make the prospect for poverty reduction worse than it appears.

35
Policy Research Working Paper 7364

# **Abstract**

Using manufacturing plant-level census data, this paper demonstrates that minimum wage increases in Indonesia reduced gender wage gaps among production workers, with heterogeneous impacts by level of education and position of the firm in the wage distribution. Paradoxically, educated women appear to have benefitted the most, particularly in the lower half of the firm average earnings distribution. By contrast, women who did not complete primary education did not benefit on average, and even lost ground in the upper end of the earnings distribution. Minimum wage increases were thus associated with exacerbated gender pay gaps among the least educated, and reduced gender gaps among the best educated production workers. Unconditional quantile regression analysis attests to wage compression and lighthouse effects. Changes in relative employment prospects were limited.

This paper is a product of the Trade and International Integration Team, Development Research Group. 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 brijkers@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
country also has comparative advantage. The closer an item is to the origin, the more capabilities that a country has for that particular product. All the figures in this section are based on UN Comtrade SITC rev. 2 4-digit data for 1995, 2000, and 2006 and 6-digit level data for Penang. To foreshadow the results, the analysis reveals that capabilities in Penang are increasing; however, such increases are seen mainly in those products that Penang already exports and where it has a comparative advantage. For other products that Penang does not export or in which Penang does not have comparative advantage, there is no evidence from the test conducted that Penang is accumulating necessary capabilities to upgrade or diversify. This suggests that Penang is becoming more specialized in certain export commodities, mainly electronics. Opportunities for Penang to upgrade or diversify remain, of course, but they will be harder to grasp. We explain in detail, the evolution of Penang’s capabilities using product space analysis.

Figure 1 shows the graphical representation of product-space for Penang in 2007. Each point in the graph is a commodity exported by all the countries in the world. Therefore, these points include products that are exported by Penang and others that are not. The coordinates of these points were calculated using the export basket of Penang. From the graph it appears that not many products in Penang are high density (i.e. easier to diversify into) and upscale. The scope for diversification and upgrading is significantly narrower than for Malaysia as a whole, or for China (see Figure 2 and Figure 3).

**Table 5: Changes in Average Sophistication of Penang’s Exports**

|Year<br>EXPY|
|---|
|1995<br>11,073.01|
|2000<br>11,004.57|
|2006<br>13,768.47|

Source: Authors’ calculation 9
Table 4: Autonomy Measures

|Dependent Variable|Consults on HH<br>decisions|Need<br>Permission|Permission to<br>buy for Self|Composite<br>Autonomy|
|---|---|---|---|---|
|Estimation Method|Ordered Probit|Ordered Probit|Probit|OLS|
||(1)|(2)|(3)|(4)|
||_Panel A: Average_|_Effects of Work_|||
|Work|0.216**|0.415***|0.128***|0.590***|
||[0.087]|[0.095]|[0.032]|[0.115]|
|Observations|1,284|1,321|1,321|1,284|
||_Panel B: Interaction w_|_ith Age at Marriage_|||
|Work|-0.100|0.404|0.215|0.659|
||[0.462]|[0.516]|[0.203]|[0.791]|
|Age First Marriage|0.020|0.016|0.011*|0.038*|
||[0.014]|[0.013]|[0.006]|[0.019]|
|Work X Age First Marriage|0.018|0.000|-0.006|-0.005|
||[0.027]|[0.030]|[0.014]|[0.046]|
|Observations|1,284|1,321|1,321|1,284|
||_Panel C: Interactio_|_n with Education_|||
|Work|0.140|0.545***|0.151***|0.748***|
||[0.108]|[0.129]|[0.043]|[0.151]|
|Education|0.040***|0.044***|0.020***|0.079***|
||[0.010]|[0.011]|[0.005]|[0.015]|
|Work X Education|0.011|-0.035**|-0.009|-0.047**|
||[0.020]|[0.016]|[0.008]|[0.020]|
|Observations|1,284|1,321|1,321|1,284|

_Consults on HH decisions: 0 = never; 1 = sometimes; 2 = often; 3 = always Need permission: 0 = need permission for a purchase of even 100 taka_ _1 = need permission for a purchase of 300 taka but not 100 taka_ _2 = do not need permission even for purchases over 300 taka Permission to buy for self: 0 = yes; 1 = no_ _Composite autonomy: first principal component taken from principal component analysis that includes all three autonomy variables, where categorical variables converted into a series of dummies (e.g. consults on hh decisions at least sometimes; consults on hh decisions at least often; consults on hh decisions always)_
# **TABLE A19:  International Research & Exchanges Board (MSI)**

## **A19: Media Sustainability Index (MSI)**

http://www.irex.org The International Research & Exchanges Board (IREX) is an international nonprofit organization specializing in education, independent media, Internet development, and civil society programs. Through training, partnerships, education, research, and grant programs, IREX develops the capacity of individuals and institutions to contribute to their societies.

Through the financial assistance of USAID, IREX introduced in 2002 the Media Sustainability Index, a tool designed to inform media development practitioners, public officials, scholars and others concerned about the region’s media. The MSI analyzes issues such as freedom of speech, plurality of media available to citizens, professional journalism standards, business sustainability of media, and the efficacy of institutions that support independent media.

In the table below we list the variables included in each of the governance indicators. We use data from the 2002-2005 Reports

|**Table A19: Media Sustainability I**|2<br>**ndex(19 developing**|24<br>**cou**|2<br>**ntries**|22<br>**)**|2|1|1|
|---|---|---|---|---|---|---|---|
||005|00|003|00|000|998|996|
|**Voice and Accountability**||||||||
|Media Sustainability Index|X|X|X|X|..|..|..|
|**Political Stability and Lack of Violence**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|NA|..|..|..|..|..|..|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

69