rafmacalaba/data-use-mentions-extended huggingface dataset:
during the harvest season when prices are lowest. We discuss the role of search costs as a part of this framework.

We begin by describing maize traders and the farm-gate buying process in the first section. The second section presents our conceptual framework. It is followed by sections presenting the data used and a quantitative analysis using household budget survey data<sup>4</sup> , before briefly concluding.

> 2 Proximity of markets, formal and informal rules governing buying and marketplaces and transaction costs such as search and transport all affect this choice.

> 3 Field interviews with farmers and mills owners revealed that this maize is stored throughout the year, and milled into flour at the local “ _posho_ ” mill at a high cost: approximately 15 to 30 percent of the value of the maize

> 4 As a part of the research for this paper, field work was conducted in two major maize producing regions in Tanzania, namely Iringa (Southern) and Arusha (Northern) and in Dar es Salaam, the major urban trading centre for

2
In column 3, in which we control fully for country-specific and sector-specific sources of variation, the estimates suggest that over a 7-year period, the expected value of M&A inflow is on average about $2.2bn lower in

> less detailed than in the M&A data and often defined differently, so that including greenfield flows into the dataset would substantially limit our ability to exploit the cross-sectoral variation in restrictiveness. 32  Air transportation and maritime shipping are excluded because both services are traded primarily crossborder rather than by establishing commercial presence; in addition, in both sectors, alliances and networks dwarf mergers or acquisitions as a means of reaching foreign markets.

> 33  We also experimented with other sets of variables, but there seemed to be the strongest a priori justification for including the set shown in Table 5.

> 34 In keeping with recent advances in estimating (trade) flow variables, results in Table 5 are obtained using Poisson estimation, which addresses concerns about heterogeneity arising from log-linearizing the model and, in addition, allows us to retain zero investment flow observations.

38
The survey provides information on a wide range of firm characteristics and firm performance measures. It also reports on firm’s experience with various aspects of the business climate such as infrastructure availability, access to finance, corruption, tax rates, inspections by government officials and tax administration. We complement these data with country level data from various sources including World Development Indicators (World Bank) and Heritage Foundation (discussed below).

A formal definition of all the variables used in the regressions is provided in Table 1. Summary statistics of all the variables is contained in Table 2 and the correlation between the explanatory variables is provided in Table 3A and Table 3B. All regression results discussed below are based on Huber-White robust standard errors and clustered on the country. For estimation, we use the ordinary least squares, ordered logit and instrumental variables regression methods.

# **2.1** _Dependent variable_

Our dependent variable is a measure of the quality of tax administration as experienced by the firms. In one question in the survey, firms were asked how severe tax administration is as an obstacle to their current operations. Response of firms was recorded on a 0-4 scale: no obstacle (0), minor obstacle (1), moderate obstacle (2), major obstacle (3) and very severe obstacle (4). These responses constitute our dependent variable, _Tax Administration_ . Note that higher values of the dependent variable imply worse (more burdensome to firms) tax administration.

The mean value of the dependent variable equals 1.4 and the standard deviation is 1.3. In terms of the distribution, about 33 percent of the firms selected no obstacle, 22 percent selected 7
**Inquiry about Progress.** Investment organizations provide evaluation templates to investors to facilitate their assessment of competence by assessing the growth potential of early-stage startups in the absence of a history of startup performance (Cohen et al. 2019b, Gompers et al. 2020). However, evaluating potential can disadvantage female candidates. For example, in a retail organization, evaluating “potential” for leadership did not result in promotions for equally-performing female candidates. If the organization had promoted based on current job performance, it would have reduced disparities (Benson et al. 2022). Whereas performance ratings are backward-looking and based on demonstrable achievements, potential ratings are based on an evaluator’s forecast of a worker's future performance and contribution. This makes rating “potential” fundamentally more subjective and uncertain, which could increase reliance on ascriptive characteristics such as gender (Ridgeway and Correll 2004, Correll and Benard 2006, Botelho and Abraham 2017, Snellman and Solal 2023).

How investment organizations might assess performance is complicated, given the lack of organizational performance data on startups (e.g., <mark>Stinchcombe 1965, Aldrich and Fiol 1994, Cohen et al. 2019a). However, some organizations assess short-term</mark> signals of performance during hiring processes. For example, the classic Goldin and Rouse study (2000) demonstrates that when orchestra hiring managers evaluated candidates’ performance through blind auditions, this resulted in hiring more female performers. This suggests that investors may be able to assess competence differently – inquiring about and assessing short-term signs of performance during the selection process.

In fact, some investors already do so. For example, program managers in Vilcap shared that progress made during the three-month program is important to investment decisions: “[We] invest in people that make the most progress during the program”. A VC investor, Mark Suster, (2010) blogged:

> “The first time I meet you, you are a single data point... Because I have no observation
Policy Research Working Paper 6158

# **Abstract**

This paper addresses the conditions under which donor and non-state actor service provision is likely to undermine or strengthen citizens' legitimating beliefs. On the one hand, citizens may be less likely to support their government with quasi-voluntary compliance when they credit non-state actors or donors for service provision. On the other hand, the provision of goods and services by donors and non-state actors might strengthen citizens' confidence in their government and their willingness to defer to governmental laws and regulations if citizens believe that the government is essential to leveraging and managing these resources. The author assesses these competing hypotheses using multi-level analyses of Afrobarometer survey data. The sample, drawn from a continuum of developing societies in Africa, allows for analysis of associations between donor and non-state actor service provision and the sense of obligation to comply with the tax authorities, the police and courts. The findings yield support for the hypothesis that the provision of services by donors and non-state actors is strengthening, rather than undermining, the relationship between citizens and the state.

This paper is a product of the Poverty Reduction and Economic Management Departyment, Africa Region. 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 asacks@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
that can be used in the function. An example of this structure are the technologies used in fabrication processes. Those at the bottom of the tree (manual processes and machines controlled by operators) have a clear vertical relationship. The rest of technologies in the function (machines controlled by computers, robots, additive manufacturing, and other advanced manufacturing processes), also have a vertical relationship with respect to the first two (as once present, they make irrelevant manual processes and machines controlled by operators). But, for the fours technologies with higher sophistication, it is possible to find tasks for which each of them most effective. Hence, the horizontal relationship between them. These four structures characterize all the relationships between the technologies in the functions covered in the FAT survey.<sup>57</sup> In Table B.1, we provide the technology structure of each business function. We first show whether each business function is under general vs. sector specific business functions

> 57Another possible structure that we do not observe in the business functions in FAT is an inverted tree structure where at the bottom we have a horizontal relationship, and then a ladder of technologies that are technologically more sophisticated than those in the horizontal portion.

64
2023a) and the lack of housing is one of the main factors, if not the main factor, of urban poverty (UN Habitat, 2020).

Today, satellite imagery and computer technology allow us to map and analyze the physical form, compactness, and built-up density of settlements in 3D based on a measurement of their horizontal extent and/or vertical extent (Angel et al., 2012; Mahtta et al., 2019; Angel et al., 2021; Blei and Angel, 2021; Jedwab et al., 2021b; Frolking et al., 2022). This is especially important for developing country municipalities that do not have the administrative capacity to generate and maintain cadasters, despite how essential these are for urban planning and development (Erba and Piumetto, 2016). Recently, Esch et al. (2022), Li et al. (2022), Pesaresi and Politis (2022) and Zhou et al. (2022) generated global 3D data of the built environment that provides insights into the worldwide patterns of built-up heights and volumes. However, despite this recent progress, there is still a lack of sufficient data and knowledge at the global scale related to three issues.

Firstly, existing 3D studies still only reflect the morphological characteristics of the built-up area in general (buildings but also roads and other paved areas). For many applications, the key information needed is precise and consistent knowledge about the building stock in 3D (e.g., for estimating economic production, population distribution, or energy consumption).

Secondly, to our knowledge, most of the globally available key figures on 3D settlement morphology are currently derived from input data or analysis kernels with coarse geometric resolutions of 500m-1000m (Frolking et al., 2022; Li et al., 2022; Zhou et al., 2022).
members, ranging from an average of 4.6 in Zimbabwe to 6 in Zambia.

Informal Sector Enterprise Surveys also enable the study of the link between the informal sector and migration that has been extensively investigated (e.g., Harris and Todaro, 1970; Mazumdar, 1976; Banerjee, 1983; Elgina and Oyvatb, 2013). Informal businesses are often viewed in the literature as temporary means of subsistence for new rural migrants to the city as they seek employment in a modern sector of the economy. However, this view of the informal sector as a mere waypoint on the path to formal sector employment has conflicted with decades of persistently low rates of formalization despite rising urbanization (Kanbur, 2017). Informal Sector Enterprise

> 12 Interestingly, about 72% of micro-enterprises were started by owners primarily due to the lack of adequate income from elsewhere. On the other hand, micro-enterprise owners are more likely than informal owners to have paid employment elsewhere. This contrasts sharply with the image of small businesses owners in developed countries who voluntarily quit their salaried jobs in the search of more independence and outlets for entrepreneurial self-expression (Watson et al, 1998).

13
The “servicification” of manufacturing is particularly important in the context of the internationalization of production.

Figure 18 shows that about 40 different types of services are involved when a manufacturing firm internationalizes its production (National Board of Trade, 2010). Recent trade in value-added data also suggest that services represent about 30% of the share of value-added in manufacture trade (OECD, 2013a – see Figure 19). Thus, a country cannot be competitive and join GVCs, even in the manufacturing sector, if it does not have efficient domestic services or is closed to the importation of such services. Managing the complexity of the chain and preserving the production standards throughout the chain require a strong coordination that relies on efficient services (e.g., auditors, lawyers, and managers) and the movement of key personnel across borders.

**Table 5. Improving domestic services, infrastructure, and market structure: Policy objectives and performance indicators**

||**Policy objectives**|**Performance indicators**|
|---|---|---|
|**Imp**|**roving access to finance**|•<br>Banking GATS commitment index (USITC, WTI 1.14)<br>•<br>Export credit – insured exposures (WTI 4.5)|
|•|Reforms of the financial sector, including micro-finance, to increase<br>affordability and availability of financial services|•<br>Indicators of financial structure, development and soundness (IMF)<br>•<br>Access to finance (WDI)|
|•|Export credit and trade finance|•<br>Enabling Trade and Global competitiveness indexes<br>–<br>financial market development (WEF GCI 8.01-8.08);|
|**Imp**|**roving other domestic infrastructure, including storage and energy**|•<br>Procedures and time to build a warehouse
The contribution of this paper to the existing literature is fivefold. First, it offers a cross-country approach and employs a harmonized definition that ensures comparability using the new World Bank’s Businesses of the State (BOS) database (Dall'Olio, et al., 2022). Second, it studies the differences in firm performance by the type of sector and potential opportunity costs of state ownership in sectors where the economic rationale is less clear by implementing the World Bank BOS sector taxonomy (Dall'Olio, et al., 2022b). Thus, we differentiate the role of state ownership in competitive sectors such as the manufacturing of textiles or accommodation services vis-à-vis natural monopolies (e.g., electricity transmission) and partially contestable sectors (e.g., extraction of gas). Third, this study shows how performance differential varies by the level of state participation and how mixed and private ownership can explain better financial and operational outcomes vis-à-vis cases where the state is the sole owner. Fourth, this paper unveils performance differentials between directly and indirectly owned BOS and explores to what extent a higher degree of separation or autonomy from the state can drive better operational and financial results. Finally, we explore how POEs and BOSs respond to economic shocks in the short-term (e.g., COVID-19).

The remainder of the paper is organized as follows. Section 1 discusses the analytical framework of principal-agent theory to understand the role of state ownership in firms’ operational and financial performance. Section 2 presents the review of the existing literature. Section 3 presents the data sources followed by some descriptive statistics in section 4. Section 5 describes the empirical methodology. Our empirical results are presented and examined in Section 6, followed by Section 7, which discusses policy implications and concludes.

**1. PRINCIPAL-AGENT THEORY TO UNDERSTAND THE ROLE STATE OWNERSHIP IN FIRMS’ PERFORMANCE**

The principal-agent problem proposed by Jensen & Meckling (1976) underscores potential issues that can arise when one or more principals engage an agent to perform
, this effect is smaller than the nationalaccounts-based adjustment in Lakner and Milanovic (2016) (shown in Figure 1). Regarding the time trend, Anand and Segal also find a fall in the most recent period (between 2002 and 2005 in their data), although the level remains marginally higher in 2005 than in 1988 (72.7% and 72.6%, respectively).

> 7 According to the review by Anand and Segal (2015), methodologies differ primarily in their (1) use of GDP per capita or average incomes from household surveys, (2) adjustments for differences between income and consumption surveys, and (3) PPP exchange rates. Bourguignon (2016), who rescales survey incomes to GDP per capita, finds a faster decline than what is presented in Figure 1, beginning in the early 1990s.

> 8 I use an alternative measure of inequality because the Gini index cannot be decomposed in this manner.

5
households, recent research suggests that poorer, credit-constrained households may not benefit as fully from migrant opportunities as middle-income households (de Brauw and Giles 2018; Du et al. 2005).

Section 4 reviews evidence on the effects of migration on household earnings, consumption, and poverty alleviation. One credible study based on data from China’s poor counties finds household income per capita increases from 8.5 to 13.1 percent after sending a migrant (Du et al. 2005). Research also suggests that increased migration from villages also contributed to average increases in household consumption within villages, including those without a migrant household member. One study attributes 65 percent of the consumption growth experienced by a panel of households from villages surveyed from 1988 to 2002 to increases in rural-to-urban migration (de Brauw and Giles, 2018).

The opportunity to diversify household earnings through migrant work lowers the risk of falling into poverty, even for households not currently engaged in migrant work. The option to find migrant work and diversify income sources after experiencing agricultural shocks affects precautionary savings behavior, poverty risk, and household investment decisions. As out-migration from a village increases, the risk of falling into poverty declines: a 1 percent increase in migration from the village is associated with a 3.2 percent decline in the risk of falling into poverty (Giles and Murtazashvili, 2013). Facing lower consumption-risk, households make higher return risky investments in tea, fruit trees, and animal husbandry when migration becomes easier, yielding earning increases of 12 to 22 percent for animal husbandry and 5 percent for fruit production (Kinnan et al. 2018).

As China enters its third decade of rural-urban migration, some areas of concern discussed in Section 5 warrant additional research and policy attention. In other countries, out-migration with urbanization has often led to a collapse in public goods provision, negatively impacting infrastructure maintenance and the provision of health and education services (Moretti, 2012). In rural China, a negative correlation exists between the scale of out-migration and village-level public
# **_Medium-term credit cycle versus GDP growth_**

In the next step for analyzing the relation between the credit cycles and GDP growth, we visualize the medium-term credit versus the GDP growth in Figure III-3. For the oil-exporters, we report the graphs for the medium-term credit cycles and short-term non-oil GDP growth, in the appendix. According to these data, there is no clear correlation between the fluctuations of credit cycles and those of GDP cycles for MENA countries (oil and non-oil exporting), while there is a clear correlation after every local peak in a medium-term credit cycle as there is a drop in the GDP growth.

# **Figure III-3: Medium-term Credit Cycle and GDP Growth**

<!-- Start of picture text --> Saudi Arabia: Mediuterm Credit Cycle and GDP growth Egypt: Medium-term Credit Cycle and GDP Growth<br>(in percent) (in percent)<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br> Medium-term credit cycle GDP Growth Medium-term credit cycle GDP Growth<br>60 20<br>40 10<br>20 0<br>0 -10<br>-20 -20<br><!-- End of picture text --> <!-- Start of picture text --> USA: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term credit cycle GDP Growth<br>10<br>5<br>0<br>-5<br><!-- End of picture text --> 16
# **4.2 Data**

To implement (8), we augment the FAI dataset with additional information on tax rates and macroeconomic conditions. Statutory tax rates are headline corporation tax rates drawn from the IMF World Tax Rate Database. Data on _KF_ - _METR_ s are from the Oxford University Centre for Business Taxation Database;<sup>34</sup> these, however, are available only for a subset of 46 out of 187 parent countries and for 28 of the 32 host countries in our dataset.<sup>35</sup> The FAS data provide useful information, at the bilateral host-parent level, on several further aspects of foreign affiliate activity, including sales, exports, number of workers, and value-added. Additional macroeconomic indicators are taken from the World Bank’s _World Development Indicators_ . Bilateral gravity variables are from CEPII;<sup>36</sup> we also control for standard gravity variables such as the physical distance between two countries, and common language or colonial ties that may shape cross-border investment. When estimating the effect of the host country _KF_ - _METR_ , and therefore, unable to include effects _aht_ , we instead include year fixed effects and several additional control variables, varying over both parent and host countries, which have been found to be important determinants of cross-border investment. These include country-level GDP, capital account openness, trade openness, exchange rate, inflation, and government expenditure.<sup>37</sup> We of course control for macroeconomic variables of parent countries when we include _aht_ .

Table 1 reports the descriptive statistics for the main variables used in the empirical analysis.<sup>38</sup> It remains to specify the weights used in constructing the rate differential term, ∆ _hp_ .

> 34At: https://oxfordtax.sbs.ox.ac.uk/cbt-tax-database.

> 35The exceptions are Cyprus, Malta, Latvia, and Lithuania.

> 36Centre d’Etudes Prospectives et d’Informations Internationales, see