rafmacalaba/datause-encoder-data huggingface dataset:
# _Rules-Based Indicators of Governance_

Several well-known examples of rules-based indicators of governance are noted in Table 1, including the Doing Business project of the World Bank, which reports detailed information on the legal and regulatory environment in a large set of countries; the Database of Political Institutions constructed by World Bank researchers, and also, the POLITY-IV database of the University of Maryland that both report detailed factual information on the features of countries' political systems; and the Global Integrity Index which provides detailed information on the legal framework governing public sector accountability and transparency in a sample of 41 mostly developing countries.

At first glance, one of the main virtues of indicators of rules is their clarity. It is straightforward to ascertain whether a country has a presidential or a parliamentary system of government, or whether a country has a legally-independent anticorruption commission. In principle it is also straightforward to document details of the legal and regulatory environment, such as how many distinct legal steps are required to register a business or to fire a worker. This clarity also implies that it is straightforward to measure progress on such indicators: Has an anticorruption commission been established? Have business entry regulations been streamlined? Has a legal requirement for disclosure of budget documents been passed? This clarity has made such indicators very appealing to aid donors interested in linking aid with performance indicators in recipient countries, and in monitoring progress on such indicators.

Set against these advantages are what we see as three main drawbacks. First, it is easy to overstate the clarity and objectivity of rules-based measures of governance. In practice there is a good deal of subjective judgment involved in codifying all but the most basic and obvious features of countries' constitutional, legal, and regulatory environments. After all, it is no accident that the views of lawyers -- on which many of these indicators are based -- are commonly referred to as "opinions". For example, in Kenya at the time of writing, a constitutional right to access to information may be undermined or offset entirely by an official secrecy act and by pending approval and implementation of the Freedom of Information Act, so that codifying even the legal right to access to information requires careful judgment as to the net effect of potentially conflicting laws. Of course, this drawback of ambiguity is hardly unique to rules-based 8
assembly who had received the investment grant had 0.4 days fewer school absences per month and 16 percent higher school expenditures. The two-year impacts on school investment of the interactions between beneficiaries and leaders who had received the investment grant are at least as large as the impacts during the program implementation (Macours and Vakis 2016).

# **Table 2.  Social interaction effects on human capital investments and aspirations two years after the Nicaragua CCT program ended**

||**Control**|**Intent-to-**<br>**treat effect**|**Intent-to-treat interacted**<br>**with percentage of leaders**<br>**with the investment grant**|
|---|---|---|---|
|**_Human capital investments_**||||
|Percent attending school (7–18-year-<br>olds)|0.777|-0.008|0.045|
|Number of days absent from school (7–<br>18-year-olds)|6.341|0.197|-1.506*|
|School expenditures (7–18-year-olds)|493.4|-68.8|310.9***|
|Share of food expenditures for vegetables<br>and fruit|0.0581|0.001|0.022***|
|**_Education and aspirations_**||||
|Years of education attained by 2008|3.12|-0.171|0.7***|
|Desired years of education|13.29|-0.09|0.946**|
|Desired professional occupation|0.5|-0.015|0.115*|
|Expected professional occupation|0.023|0.002|0.035**|

_Note_ : This is based on intent--to-treat estimators from Table 2 of Macours and Vakis (2016). The share of leaders measures the share of female leaders with the productive investment package over all female leaders in a beneficiary's registration assembly. The data for school attendance and school expenditures are individual-level data for all children of age 7-18 years in a household. The data for food expenditures are household-level data. Excluded from the data are households with female leaders. Highest and lowest 0.5 percent of outliers in expenditures are trimmed. Robust standard errors in parentheses, corrected for clustering at the community level. _*** p_ <0.01, _** p_ <0.05, _* p_ <0.1 37
# **5.2 Effects on business practices and performance**

While the effect of the information sheet on use of SEBRAE services was small in absolute magnitude and temporary, firms may have relied on other mechanisms to improve their business practices. First, firms may have sought out business development services from providers other than SEBRAE. Panel A of table 3 show that, during the follow-up survey, 15.4 percent of control firms reported using services from other providers. This number was not statistically significantly different in the treatment group, indicating that the intervention did not cause firms to seek out business development services from other sources.

Second, firms may have improved their business practices without help from SEBRAE or other service providers. Some of the actions listed on the information sheet were concrete and can in principle be implemented without help, such as “keep a register of suppliers” or “conduct a customer satisfaction survey.” However, column 2 in table 3 shows no effect of receiving an information sheet on business practices.

Given that the information sheet had no effect on business practices, we do not expect it to affect business performance. Indeed, columns 3 through 6 in table 3 show no robust effect of the intervention on business performance, measured using follow-up survey variables (sales and profits), as well as administrative data on the number of employees and business closures.

# **5.3 Reasons for not using SEBRAE services**

During the follow-up survey, we asked firms that had not used a SEBRAE service during the months between the intervention and follow-up survey why they did not use these services. The most given reason was lack of time, with about 60 percent of firms giving this reason (table 4). The second most given reason was that the firm was happy with their business performance: 28.6 percent of control firms gave this reason, dropping to only 15.8 percent of treatment firms. Our interpretation of this effect is that the information sheet made firms realize that they were not using best business practices. At the same time, firms report being time constrained, which also aligns with the finding from section 5.1 that even the firms that sought out SEBRAE services predominantly accessed light touch services.

Since table 4 only includes firms that did not use SEBRAE services, the finding that treatment firms are less likely to be happy with their business performance than control firms may be driven by differential selection in the treatment and control groups. However, the results in table A5 suggest that the effect on being happy with the firm’s performance is not only due to selection. Table A5 shows the answers to the related question: “what prevents you from adopting additional business practices?” that was posed to all firms that participated in the follow-up survey. As in table 4, treatment firms are 12
# **Figure 18**

# **Evolution of Turnover Fixed Effects**

This figure presents the evolution of the coefficients obtained from the regression of the Grinblatt et al. (1995) turnover statistic at the PFAtime-fundtype level on PFA, time, and fund type fixed effects. This figure considers the entire sample period (July 1996 to December 2005). The zero-mean time fixed effects are presented in the figure. Coefficients that are statistically significant at the ten-percent level are marked on the figure. T-tests are two-tailed. Significant events that occurred during this period of time are also highlighted on the figure: the Asian crisis (July 1997), the Russian crisis (August 1998), the introduction of Fund E and the widening of the minimum return band (October 1999), and the establishment of the multi-fund regime (September 2002). Numbers represent percentages (results are multiplied by 100).

<!-- Start of picture text --> 40<br>Grinblatt et al.<br>35<br>Significant at ten percent<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>-5<br>Asian Crisis Russian Crisis Fund E Multi-Fund<br>-10<br>Jul-96 Mar-97 Nov-97 Jul-98 Mar-99 Nov-99 Jul-00 Mar-01 Nov-01 Jul-02 Mar-03 Nov-03 Jul-04 Mar-05 Nov-05<br> Time Fixed Effects from Turnover Regression<br><!-- End of picture text -->
On the role of services in economic development, Hoekman and Mattoo (2008) review the literature, focusing on channels through which openness to trade in services may increase the productivity of a firm, an industry and an economy as a whole. The existing studies show that access to low-cost and high-quality producer services can promote economic growth. Based on an industry-level analysis of the U.S., Amit and Wei (2009a) find that services offshoring by highincome countries tends to raise their manufacturing sectors’ productivity. While services offshoring has both positive and negative effects on domestic employment, Amiti and Wei (2009b) show that, at least for the case of the United States, it tends to enhance domestic employment on average. Arnold, Javorcik, and Mattoo (2011), using firm-level data from the Czech Republic for the period 1998-2003, find a positive effect of services sector reforms on the productivity of domestic firms in downstream manufacturing. The manufacturing-services linkage is measured using information on the degree to which manufacturing firms rely on intermediate inputs from services industries. Arnold et al. (2012) use a similar methodology to show that services reforms had significant and positive effects on the productivity of manufacturing firms in India. Fernandes and Paunov (2012), using the annual manufacturing survey of Chilean firms, find a positive effect of substantial FDI inflows in producer services sectors on the total factor productivity (TFP) of Chilean manufacturing firms. Their findings also suggest that services FDI fosters innovation activities in manufacturing and offers opportunities for laggard firms to catch up with industry leaders. Debaere et al. (2013) find that greater availability of services increases manufacturing firms’ foreign sourcing of materials, which may in turn enhance manufacturing productivity. Using Swedish firm-level data, Lodefalk (2014) shows that in-house and outsourced services help to increase export intensity measured by the share of merchandise exports in total sales. Finally, a recent paper by Bamieh et al. (2017) shows that more intensive use of producer services appears to be positively associated with resilience to greater import competition.

In this paper, we study particularly the roles of financial services and business services in manufacturing production. On financial services, Rajan and Zingales (1998) and a number of follow-up studies find that industries that are particularly dependent on financing grow relatively faster in countries with more developed financial markets.<sup>5</sup> Our approach differs from Rajan and

> 5 Based on a non-parametric estimation, however, Shen (2013) shows that the effect is even stronger for financially underdeveloped countries than financially developed countries due to diminishing returns.

6
ETHIOPIA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# The continental perspective

The Africa Infrastructure Country Diagnostic (AICD) has collected and analyzed extensive infrastructure data for more than 40 Sub-Saharan countries, including Ethiopia. The results are presented in reports on various infrastructure sectors—ICT, irrigation, power, transport, water and sanitation—and policy areas, including investment needs, fiscal costs, and sector performance.

This country report presents the key AICD findings for Ethiopia. This will allow its infrastructure situation to be benchmarked against that of other African nations that, like Ethiopia, are low-income countries, with particular emphasis on immediate regional neighbors in East Africa.

Several methodological issues should be borne in mind. First, the cross country nature of the data collection creates an inevitable time lag. The period covered by the AICD runs from 2001 to 2006. Most technical data are presented for 2006 (or the most recent year available), while financial data typically are averaged over the available period to smooth out the effect of short term fluctuations. Second, cross country comparisons require standardization of the indicators and the analysis to ensure consistency. Therefore, some of the indicators may be slightly different from those that are routinely reported and discussed at the country level.

# Why infrastructure matters

During the 2000s, Ethiopia’s annual economic growth has averaged 4.8 percent, compared with only 0.5 percent in the previous decade. Notwithstanding this improvement, current annual growth levels still fall short of the sustained 7 percent needed to meet the Millennium Development Goals. Improved structural and stabilization policies generated an estimated 4.2 percent of Ethiopia’s improved per capita growth performance during the 2000s, and improvements in the country’s infrastructure platform over that period contributed up to 0.6 percentage points to growth. This was due almost entirely to the introduction of mobile telephony in Ethiopia. Simulations suggest that if Ethiopia’s infrastructure platform could be improved to the level of the African leader, Mauritius, annual per capita growth rates could increase by 3.8 percent. This potential impact would come equally from improvements to transport, power, and ICT infrastructure (figure 1).

Evidence from enterprise surveys suggests that infrastructure constraints are responsible for an estimated 50 percent of the productivity handicap faced by Ethiopian firms. The remainder is caused by governance, red tape, and financing constraints. Power is by far the infrastructure constraint that weighs most heavily on Ethiopian firms (figure 2).

2
Policy Research Working Paper 7189

# **Abstract**

Previous research on sex-selective abortions has ignored the interactions between fertility, birth spacing, and sex selection, despite both fertility and birth spacing being important considerations for parents when deciding on the use of sex selection. This paper presents a novel approach that jointly estimates the determinants of sex-selective abortions, fertility, and birth spacing, using data on Hindu women from India’s National Family and Health Surveys. Women with eight or more years of education in urban and rural areas are the main users of sex-selective abortions and they also have the lowest fertility. Predicted lifetime fertility for these women declined 11 percent between the 1985–1994 and 1995–2006 periods, which correspond to the periods of time before and after sex selection became illegal. Fertility is now around replacement level. This decrease in fertility has been accompanied by a 6 percent increase in the predicted number of abortions during the childbearing years between the two periods, and sex selection is increasingly used for earlier parities. Hence, the legal steps taken to combat sex selection have been unable to reverse its use. Women with fewer than eight years of education have substantially higher fertility and do not appear to use sex selection.

This paper is a product of the Poverty and Inequality 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 author may be contacted at work@clausportner.com.

_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
_- 50 -_ reasonably well capitalized as shown in Table 15 .21 However, the current practice of loan classification and loan loss provisioning may not provide an accurate picture of potential as opposed to actual loan losses in the banking system. The current loan loss classification system is largely based on the number of days a loan is past due for principal. The problem with this is that deteriorating credits are likely to be provisioned later than they should be. By the time borrowers are unable to meet principal payments, there is a large probability that the loan will be a loss to the bank.

One sign of the existence of larger than reported credit risks is that credit to the private sector appeared to have grown very fast. Commercial banks' claim on the private sector grew in real terms by 44% in 1995 (which might to a large extent reflected making up for the sharp contraction of 32% in lending to the private sector in 1994 ), 28% in 1996, and 22% in 1997. Thus the growth in bank credit to the private sector exceeded by a wide margin the already rapid growth of GNP. The credit growth rates were very high as compared to other large capital importers. The nature of such lending is not clear (in terms of sectoral concentration, etc), but it is noteworthy that consumer lending has assumed increasing importance. Though consumer credits have been only a small part of the total lending (about 9% as of end 1997), the volume of consumer credits have been growing very fast - from US$1.9 billion as of end 1996 to US$2.9 billion as of end 1997 (a growth rate of 53%). Such a high credit growth rate may not augur well for credit quality. Turkish banks may be subject to large credit losses if economic activity slows down, for example, due to business cycle reasons.

**Table** 27

**Turkey: Growth of Bank Credit to the Private Sector**

||**Relative to the**|**Growth of GNP**||
|---|---|---|---|
|Year|Real Credit Growth|Real GNP Growth|Difference|
|1992|14.3%|6.4%|7.9%|
|1993|15.3%|8.1%|7.2%|
|1994|-32.0%|-6.1%|-25.9%|
|1995|44.0%|8.0%|36.0%|
|1996|27.7%|7.1%|20.6%|
|1997|22.5%|8.0%|14.5%|

Source: own calculation based on IFS.

21 The level of non-performing loans was reported to have increased sharply during 1998, as a consequence of adverse economic conditions.
WPS4048

# **Services Inputs and Firm Productivity in Sub-Saharan Africa** Evidence from Firm-Level Data

### Jens Matthias Arnold<sup>*</sup> Aaditya Mattoo<sup>**</sup> Gaia Narciso<sup>***</sup>

### **Abstract**

This paper investigates the relationship between the productivity of African manufacturing firms and their access to services inputs. We use data from the World Bank Enterprise Survey for over 1,000 firms in 10 Sub-Saharan African countries to calculate the total factor productivity of firms. The Enterprise Surveys also contain unique measures of firms' access to communications, electricity and financial services. The availability of these measures at the firm level, both as subjective and objective indicators, allows us to exploit the variation in services performance at the sub-national regional level. Furthermore, by using the regional variation in services performance, we are also able to address concerns about the possible endogeneity of the services variables. Our results show a significant and positive relationship between firm productivity and service performance in all three services sectors analyzed. The paper thus provides support for the argument that improvements in services industries contribute to enhancing the performance of downstream economic activities, and thus are an essential element of a strategy for promoting growth and reducing poverty.

Keywords: services liberalization, productivity JEL Codes: L8, F2, D24 World Bank Policy Research Working Paper 4048, November 2006 _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._

## _________________________

*Organisation for Economic Co-operation and Development, 2, rue Andre Pascal, 75116 Paris, France. Email: jens.arnold@oecd.org. **World Bank, 1818 H Street, NW; MSN MC3-303; Washington, DC, 20433. Email: amattoo@worldbank.org. *** Bocconi University, Via Sarfatti 25, Milano, Italy. Email: gaia.narciso@unibocconi.it. This paper is part of the World Bank’s research program on trade in services, which is supported in part by the United Kingdom’s Department for International Development.
# _a. Scope of competition laws_

The responses show that in the majority of countries lawmakers granted exemptions to certain economic sectors. Some exemptions are permanent while others are temporary. According to the responses, the latter are justified as being a concession granted to industries that need to adjust to a liberalization process. Unfortunately, no information was provided on the length of temporary exemptions. Competition laws include temporary and permanent exemptions in the three regions. Some of the exempted sectors are: <u>Permanent: agriculture, labor market, financial markets, state-owned monopolies, water and</u> sanitation, land passenger transport, electricity.

<u>Temporary: telecommunications, postal sector, railways, air transport.</u> <!-- Start of picture text --> Figure 1<br>Any sector exempted from competition laws?<br>8<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>Yes No Yes No Yes No<br>ECA LAC EAP<br><!-- End of picture text --> Countries in LAC tend to have competition laws that apply to all sectors. This result differs from ECA and EAP where half of the countries that responded the questionnaire have some sectors excluded from the application of competition laws.

5