rafmacalaba/datause-encoder-data huggingface dataset:
unconditional cash transfers and conditional cash transfer schemes which do not condition on MCH service use or employ soft conditions or co-responsibilities.

In terms of _outcomes_ , this review focuses on six indicators that either represent the official and supplemental RMCH indicators of the Millennium Development Goals (MDGs)<sup>11</sup> or are intermediate indicators critical to their achievement, namely the shares of (1) women of fertile age who use modern contraceptives, (2) pregnancies with four or more antenatal care checks, (3) pregnant women receiving tetanus vaccination, (4) births occurring in health facilities, (5) births with postnatal care, and (6) children receiving the full course of vaccinations recommended for the first year of life. Importantly, we only include impact estimates of outcomes whose provision is financially incentivized by the interventions under study. This incentivization may be direct, e.g. a fee the health facility receives for each birth taking place in it, or it may be indirect – e.g. maternal tetanus vaccination being incentivized in a CCT which rewards pregnant women for antenatal care visits during which maternal tetanus vaccinations are carried out. By contrast, we exclude impact estimates of outcomes without financial incentivization, e.g. those measuring an intervention’s unintended consequences. Finally, we only include impact estimates from samples representing the entire population of program beneficiaries – for instance, impacts on antenatal care content are included if based on a sample of all pregnancies and excluded if they come from the subsample of antenatal care users.

_Methodologically_ , we only include evidence from household survey data because of sample selectivity and reporting bias concerns in health facility and administrative data sets from LMICs.<sup>12-15</sup> Regarding study design, we include randomized controlled trials (RCTs) as well as evaluations of non-randomized interventions which identify impacts using regression discontinuity (RD), instrumental variables (IV), or double difference (DD) and triple difference (DDD) models. The parameter of interest in this review is a program’s intention-to-treat (ITT) effect – the impact on its full target population which consists of both compliers and noncompliers. We thus exclude effects estimated only for compliers, e.g. for enrollees of a CCT scheme, as opposed to its entire target group. As a requirement for meta-analysis, we only include impact estimates if they are presented with a measure of statistical uncertainty.

To identify relevant references, in September 2016, we searched the Cinhal, Cochrane Library, Econlit, Embase, Medline, Popline, and Scopus databases as well as Google Scholar for 3
shows that such negative impact arises from the observations with above-median (but not extreme) poverty rates. Indeed, the indirect impact is negligible when poverty is below the median, and it even turns positive at extremely high levels of poverty. Importantly, these empirical findings are fully consistent with the analytical model sketched in Section II.

# **VI. Conclusions**

This paper has examined two issues that have received limited attention in the otherwise extensive empirical literature of growth, inequality and poverty. First, the paper provides an empirical assessment of the impact of poverty on growth, building on the earlier work by López and Servén (2009). Second, as a byproduct, the paper also highlights the indirect effect of inequality on growth accruing through poverty.

To guide its empirical work, the paper uses a simple analytical model in which growth is driven by aggregate investment, but poor consumers lack the resources to save and invest. In the model, the impact of poverty on growth is unambiguously negative, and its magnitude increases with the extent of poverty. In contrast, the impact of inequality on growth can go either way, as it combines two different effects that may be mutually opposing. The first one is the indirect impact of inequality on growth accruing through poverty, which is uniformly negative except when extremely high poverty is coupled with very low levels of inequality. The second is due to the impact of inequality on the aggregate investment of non-poor individuals, which is also shown to be ambiguous.

To test these predictions, the paper uses a large panel data set including 804 observations covering 158 countries and spanning the years 1960-2010. The empirical strategy involves including inequality and poverty indicators among the explanatory variables in an otherwise standard empirical growth equation.

On the whole, the results reveal a consistently negative and strongly significant correlation of poverty with subsequent growth. Its magnitude is economically significant too: a 10 percentagepoint decrease in the headcount poverty rate is associated with a rise in annual per capita real growth of 0.5% to 1.8%, depending on the precise specification of the empirical model. However, further analysis reveals that the magnitude and significance of the effect depend on the prevailing level of poverty. Specifically, when the level of poverty is low (below the sample median), the growth effect of poverty is not statistically significant. In contrast, when the level of poverty is high, changes in the poverty headcount rate show a significantly negative association with subsequent growth – i.e., 25
- (c) _Regulation on its own (R)_ . In the absence of other policy changes, the introduction of regulation, as used in countries where there is private sector participation and competition, would be expected to have a negligible effect on the performance of an SOE. The regulator would essentially be duplicating the control of whichever government department was responsible for the actions of the SOE. Regulation makes sense when there has been unbundling and some private sector entry into the sector. The greater the market power of the private participants in the market the greater the need for an independent regulator who can control excess profit making and ensure some efficiency gains are passed on to consumers.

- (d) _Introduction of competition on its own (C)_ . In the presence of a single state-owned utility, it is impossible to introduce competition in the market. Competition in the market requires unbundling and privatization, permitting the presence of several firms, each with an incentive to increase its profits at the expense of the others. Competition for the market would be possible even without unbundling-–it corresponds to the privatization of the entire SOE as a single entity from some form of auction. Competition can be between generators (wholesale) and between distributors (retail).

This simple discussion makes it clear that certain policies, if applied on their own, would be expected to have little or no effect on sector performance–instead, policies need to be combined. However, most of the econometric studies reviewed below do not recognize this aspect of reform and test whether each policy component contributes separately to improved performance whether or not other policies are in place. The discussion above suggests that the policy combinations that could be expected to improve performance substantially are (U+P), (U+R+P), and (U+R+P+C). The last corresponds to the full policy reform implementation, while the former two do not attempt to create a competitive environment in the sector. Other combinations are expected to make little or no impact on sector performance, but they may act as stepping stones to the full policy implementation–hence some countries may exhibit the implementation of partial reform policies, with little effect on performance.

The survey of reform steps undertaken by developing countries (World Bank 2017b) provides insights on combinations of policies adopted that can be regarded as incomplete and unlikely to be effective unless further reforms are undertaken. The percentages of the 88 developing countries surveyed exhibiting various different ineffective reform combinations in 2015 are shown in table 4. The percentage of countries that have some private sector participation without having undertaken any unbundling is very high (34%). Quite a few have created an independent regulator in the absence of any PSP (12%) with a similar value allowing competition in the absence of an independent regulator (12%).

13
A depressed state of investment is arguably one of the primary factors keeping the Afghan economy from growing given the vast empirical literature documenting the strong correlation between economic growth and the investment share of GDP (Figure 2).<sup>5</sup> More importantly, though, this relationship between investment and growth remains robust to the inclusion of other variables considered important for growth (Levine and Renelt (1992), Xala-i-Martin (1997)). Through its effect on economic growth, a healthy investment environment is potentially also important in delivering the development goals of poverty reduction and boosting shared prosperity as well. A pertinent question then is what causes such huge variation in investment rates across countries and what can be done to boost investment in economies that are plagued by low investment. The role of financial underdevelopment has been explored in various settings over the past few decades. Theoretical studies have argued that access to finance provides real services via reducing information frictions and transaction costs. Relatedly, empirical research has found evidence linking growth and financial development. A key mechanism highlighted in this context is the easing of financial constraints leading to eradication of barriers to firm growth and expansion.<sup>6</sup> Uncertainty is another factor that has been examined in the literature. Yet, there does not exist a sound prediction about the nature of the relationship between uncertainty and investment due to opposing forces created by risk aversion, adjustment costs, production technology etc. (Caballero (1991), Dixit and Pindyck (1994), Abel and Eberly (1996) etc.). Though not entirely unanimous, the bulk of empirical investigations has found evidence of a negative relationship between the two (Serven and Solimano (1993), Aizenman and Marion (1996), Hausmann and Gavin (1998), Serven (1998) etc.).

**Figure 2: Gross Fixed Capital Formation (percent of GDP)**<sup>**7**</sup>

<!-- Start of picture text --> 25<br>20<br>15<br>10<br>5<br>0<br>2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br><!-- End of picture text -->

> 5 This literature includes studies that have considered cross-sectional data (Mankiw, Weil and Romer (1992), Barro and Sala-iMartin (1995) etc.) as well as panel studies (Caselli, Esquivel and Lefort (1996), Bond, Hoeffler and Temple (2001) etc.). 6 See Levine (2005) for a survey of both the theoretical and the empirical literature. 7 Source: World Development Indicators.

3
- 10-

of the 1980s, Argentina was no exception to this rule as the potential VAT base'<sup>3</sup> was estimated at 52.2 percent of GDP, much lower than the potential VAT base in Europe averaging 60 percent during the 1980s. Over the last two years, the legal coverage of the VAT was increased dramatically by a series of legal actions including the elimination of exemptions for combustibles and foodstuffs in February 1990, improved controls of the industrial promotion regime in April 90 (and a further tightening in December 92), and the inclusion in the VAT base of most services in November 1990. Previously, the VAT had been applicable only to those services specifically listed in the law; the new law contains the few exemptions. Finally, the potential VAT base was extended to water supply services in March 1991 and to insurance services in February 1992. Overall, VAT coverage is estimated to have increased from 52.2 percent in 1989 to almost 80 percent of GDP in 1992.

# **_Tax Evasion_**

The Menem Administration fought with strong sanctions and a larger tax administration capacity tax evasion. Tax penalties were increased through the reactivation of existing and newly created legal capacities to enforce compliance. A new penal law (February 1990) strengthened the hand of the authorities in prosecuting tax evasion and fraud, mainly by reducing the burden of evidence required before the Government can proceed with penalties. The General Ahx Board (DGI) has been granted the authority to close temporarily the premises of enterprises that fail to register for the VAT or to issue invoices. As a result, business closures, which had never been used in Argentina in a systematic way until two years ago, rose fror 751 in 1990 to 5,021 in the first 9 months of 1991.

To increase the capacity of the tax administration, the strategy was to enhance simultaneously computerization and human resources development. The administration reactivated its managerial capacities through actions in the areas of **collection management, audits and** internal **control,** and **personnel policy.** The effort of increasing the number of audits, closures and detentions are summarized in Table 4.

The primary functions of tax administration--facilitating and monitoring taxpayer compliance and preventing taxpayer non-compliance--have until recently operated very 13 Source: World Bank (1990) and defined as the share in GDP of the economic sectors not exempted from payment of VAT.
Table A.2: Average Cost Shares and Variations

||Pre-|WTO|Post-|WTO|Percent|Change (%)|
|---|---|---|---|---|---|---|
||_α_<sup>_l_</sup><br>_it_<br>(1)|_α_<sup>_m_</sup><br>_it_<br>(2)|_α_<sup>_l_</sup><br>_it_<br>(3)|_α_<sup>_m_</sup><br>_it_<br>(4)|_α_<sup>_l_</sup><br>_it_<br>(5)|_α_<sup>_m_</sup><br>_it_<br>(6)|
|31 Food|0.1012|0.6368|0.1042|0.6538|2.97|2.66|
|32 Textiles|0.1728|0.5436|0.1203|0.6287|-30.38|15.66|
|33 Wood|0.1993|0.5057|0.1753|0.4731|-12.03|-6.43|
|38 Metals|0.1646|0.5722|0.1280|0.6109|-22.24|6.77|

**_Source:_** Data for the study comes from the World Bank Regional Project on Enterprise Development (RPED) and Ghana Manufacturing Survey (GMES) from 1992 to 2003.The surveys were conducted by the Centre for the Study of African Economies (CSAE) at the University of Oxford, University of Ghana, and Ghana Statistical Service. **_Note:_** Columns (1) & (2) report sector-level input shares on labor and materials respectively for _exante_ trade liberalization period, whilst Columns (3) & (4) report that of ex-post trade liberalization. WTO is an acronymon for Wolrd Trade Organization.

# **B Appendix: Monopsony Incidence Selection Equation**

Table B.3: Average Monopsony Incidence

|Sector|Pre-WTO|Post-WTO|Diferences|Variation|(%) P-Value|
|---|---|---|---|---|---|
|31 Food|0.464706|0.6751592|0.2104533|45.29|0.000|
|32 Textiles|0.434524|0.655914|0.2213902|50.95|0.000|
|33 Wood|0.251282|0.3529412|0.1016591|40.46|0.014|
|38 Metals|0.315508|0.6105263|0.2950183|93.51|0.000|

**_Source:_** Data for the study comes from the World Bank Regional Project on Enterprise Development (RPED) and Ghana Manufacturing Survey (GMES) from 1992 to 2003.The surveys were conducted by the Centre for the Study of African Economies (CSAE) at the University of Oxford, University of Ghana, and Ghana Statistical Service. **_Note:_** The table presents average incidence of monopsony power between _ex-ante_ (Pre-WTO) and _expost_ (Pre-WTO) trade liberalization periods. The table also test whether differences in the monopsony power between the two periods are statistically significant.

37
- Jones, Benjamin F. “The Human Capital Stock: A Generalized Approach.” _American Economic Review_ 104, no.11 (2014): 3752-77.

- Jones, Benjamin F. “The Human Capital Stock: A Generalized Approach: Reply.” _American Economic Review_ 109, no. 3 (2019): 1175-95.

- Klenow, Peter J., and Andres Rodriquez-Clare. _The neoclassical revival in growth economics: has it gone too far?_ ” NBER Macroeconomics Annual, MIT Press, Cambridge, MA (1997): 83–103.

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43
Policy Research Working Paper 7627

# **Abstract**

Many countries in Africa suffer high rates of underemployment or low rates of productive employment; many also anticipate large numbers of people to enter the workforce in the near future. This paper asks the question: Are African firms creating fewer jobs than those located elsewhere? And, if so, why? One reason may be that weak business environments slow the growth of firms and distort the allocation of resources away from better-performing firms, hence reducing their potential for job creation. The paper uses data from 41,000 firms across 119 countries to examine the drivers of firm growth, with a special focus on African firms. African firms, at any age, tend to be 20–24 percent smaller than firms in other regions of the world. The poor business environment, driven by limited access to finance, and the lack of availability of electricity, land, and unskilled labor have some value in explaining this difference. Foreign ownership, the export status of the firm, and the size of the market are also significant determinants of firm size. However, even after controlling for the business environment and for characteristics of firms and markets, about 60 percent of the size gap between African and non-African firms remains unexplained.

This paper is a product of the Innovation, Technology and Entrepreneurship Global Practice, Financial and Private Sector Development. 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 Liacovone@worldbank.org and vramachandran@cgdev.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
calculations for electricity, and 2014-2015 for the case of water. In the case of EEU, the utility company also provided information on capital cost shares of electricity generation, transmission, and distribution. In the case of AAWSA, the provided information helped us to separate the costs for providing water from those for providing sewerage services. Table 4 summarizes the total average unit costs calculated for water and electricity.<sup>21</sup>

**Table 4: Summary of Average Unit Costs for Water And Electricity** **<u>(Addis Ababa, 2015/2016)</u>**

|**Electricity**<br>**( USD / KWh)**|**Water**<br>**(USD / m3)**|
|---|---|
|**Cost component by type of cost**||
|**Operation and Maintenance**<br>0.004|0.19|
|**Capital cost**<br>0.088|0.70|
|**Total Cost**<br>0.092|0.89|
|**Cost component by production step**||
|**Distribution**<br>0.023||
|**Transmission**<br>0.014||
|**Generation**<br>0.055||
|**Total Cost**<br>0.092||

Authors calculation based on primary data collected from the utility company (1 US Dollar = 20.68 Bir)

# **5. Results**

# **_Description of sample households_**

Our subsample of households with private water and electricity connections for the exclusive use of household members represent about 39% of households in Addis Ababa. Households in this subsample are wealthier than those with shared water or electricity connections (or both) or without a water connection. The mean household income of our 366-household subsample is approximately

> 21 Appendix B presents further details, including the assumptions underlying our estimates for average unit costs of water delivery in Addis Ababa. Details regarding our estimates for average unit costs of electricity delivery are given in Cardenas and Whittington (2019).

14
3 Japan, Hong Kong SAR, China; Taiwan, China; Singapore; and South Korea have all gone on to become high-income economies with steady and positive economic growth that has persisted over five decades. Can aspiring countries in Southeast Asia hope to experience the same success? The track-record so far is not promising. Malaysia, Indonesia, Thailand and the Philippines also experienced rapid growth in the 1980s and early 1990s, but that growth rate was insufficient to advance these economies to high-income status. Since the 1997 East Asian crisis, their growth rates have stagnated, or even contracted for a period of time (Figure 1).

This paper focuses on Malaysia and Thailand because they appear to be on the ‘cusp’ of sustained growth as the two most prosperous Southeast Asian economies (Figure 1). The latest data shows that Malaysia’s per capita income was $4987 while Thailand’s was $2604 in constant 2000 US dollars in 2010. They have surpassed the income per capital of countries like Indonesia and the Philippines with which they were once comparable. But they still lag high-income economies like Japan and South Korea and do not seem to be catching up with them.

<!-- Start of picture text --> Figure 1:<br>45000 GNI per capita, constant 2000 US$<br>40000<br>35000<br>30000 Japan<br>25000 United States<br>Korea, Rep.<br>20000<br>Malaysia<br>15000<br>Thailand<br>10000 Philippines<br>5000 Indonesia<br>0<br>Year<br><!-- End of picture text --> Source: World Development Indicators The secret to sustained growth is elusive (Easterly 2001a).<sup>2</sup> Kharas and Kohli (2011) argue that they key for middle-income countries to escape this income status is to rely on growth of a capital- and skill-intensive manufacturing sector and growth of a high-productivity service industry. Non-tradable services such as house cleaning or hair cutting have little room for productivity improvements and market expansion, but sophisticated financial, consulting, health and environmental services do contribute to productivity growth.