rafmacalaba/data-use-mentions-extended huggingface dataset:
represents the proportion of households in the full estimation sample considered to be adequate. Pairwise correlations of the seven adequacy dimensions are reported in Annex 3.

**Table 1: Summary Statistics of the Seven Adequacy Dimensions in 64 Economies**

|**Adequacy Dimension**|**Number**<br>**of**<br>**Observations**|**Mean**|**Std. dev**|
|---|---|---|---|
|Access to Water|2,461,605|.941|.235|
|Access to Sanitation|2,460,289|.575|.499|
|Adequate Living Space|2,395,203|.657|.475|
|Durable Material Good Structural Quality|2,145,454|.520|.519|
|Security of Tenure|2,453,341|.782|.109|
|Access to Electricity|2,463,409|.876|.330|
|Access to Clean Cooking|2,249,519|.443|.497|

**Note** :  Summary statistics of adequacy dimensions across 64 emerging economies. Missing data within countries are imputed as presented in section 3.4. Country specific statistics are presented in Annex 3.

Across the board, access to safe cooking fuel is most commonly absent in emerging economies’ HHs. This is particularly acute in Sub-Saharan African economies, where the overarching majority of HHs does not have access to clean cooking and where HH air pollution stemming mostly from cooking smoke is a serious health hazard. This avoidable first-order public health crisis disproportionately harms women and children (cf. World Bank et al. 2014). Moreover, cooking with inadequate cooking fuels such as wood, charcoal, crop waste, dung, coal, or kerosene, also has a wide range of negative environmental and climate change effects.

Durable material
below the 1980 benchmark.<sup>24</sup> The lost decade adage applied to the majority of emerging and developing economies, many of which were coping with _conglomerate_ crises. During this period, reality consistently disappointed expectations, successive downward revisions to economic growth projections were legion.

The experience of the 1980s suggests caution is warranted in projections of post-COVID-19 economic growth, particularly for countries that are already experiencing some variants of financial stress. The October 2020 WEO projections show that by 2025, 29 percent of EMDEs will have per capita incomes below what they were in 2019 (the comparable share for EMDEs is 94 percent in 2020). This is only slightly higher than the share in any “normal” year and spectacularly better than the track record of the 1980s. It is difficult to reconcile this GDP path with the prevalent expectation that there will be a higher incidence of sovereign debt and financial sector problems in the period ahead.

Inflation in some EMDEs may also surprise on the upside. At present, the substantial contraction in aggregate demand acts to dampen inflationary pressures. However, a frequent component of the _composite_ crises that I have described involves inflation, a point stressed in Reinhart and Rogoff (2009). A country losing access to external capital markets relies more on domestic funding sources to meet the government’s financing needs. For many developing countries, the scope for internal financing is limited and governments turn more to the revenue for money creation and, in many cases, government arrears.

I am not suggesting a full-blown reversion to the 1980s, when more than half of the EMDEs had double-digit inflation (Figure 2) and inflation targeting was still limited to a handful of advanced economies. The share of countries with double-digit inflation rates has dropped precipitously since then, possibly hitting a low point in 2014 (7 percent of EMDEs registered double-digit inflation that year). In 2020 that share is about 14 percent. But not surprisingly, the re-

> 24 In any given random year, anywhere between 16 and
E. Strahan. 2001. “The division of spoils: rent-sharing and discrimination in a regulated industry.” _American Economic Review_ 91(4), 814-831.

- Niels, B., M. van Praag, R. Thurik, G. de Wit. 2004. “The value of human and social capital investments for the business performance of startups.” _Small Business Economics_ 23, 22736.

Bouchard Jr., G., J.C. Loehlin. 2001. “Genes, evolution, and personality.” _Behavior Genetics_ 31(3), 243-273.

Bruch, C. 1992. “Research on women business owners: Past trends, a new perspective and future directions.” _Entrepreneurship Theory and Practice_ 16(4): 5-30.

- Buchan, N., R.T. Croson, S. Solnick. 2008. “Trust and gender: an examination of behavior and beliefs in the investment game.” _Journal of Economic Behavior and Organization_ 68(3), 466-76.

- Cai, H., H. Fang, and L.C. Xu. 2011. “Eat, Drink, Firms, Government: An Investigation of Corruption from Entertainment and Travel Costs of Chinese Firms.” _Journal of Law and Economics_ , 54, 55-78.

Cassar, A., F. Wordofa, Y. J. Zhang. 2016. “Competing for the benefit of offspring eliminates the gender gap in competitiveness.” PNAS 113(19), 5201-05.

Cattan, S. 2014. “Psychological traits and the gender wage gap.” Unpublished.

Chattopadhyay, R., E. Duflo. 2004. “Women as policy makers: Evidence from a randomized policy experiment in India.” _Econometrica_ 72(5), 1409-43.

Clarke, G., L.C. Xu. 2004. “Privatization, Competition, and Corruption: How Characteristics of Bribe Takers and Payers Affect Bribe Payments to Utilities,” _Journal of Public Economics_ 88 (9-10), 2067-97.
employment may have been overstated. First, since the medical benefits program in Mexico, as elsewhere, covers a worker's entire family, the marginal value of benefits to the second formal sector worker in a family is zero. Second, administrative overhead costs are high and the benefits may be of low value given their cost. In his interviews with Guadalajaran workers, Roberts (1989, p. _50)_ found that "many informants cited the deduction made for welfare as a disadvantage of formal employment, particularly since the services they received were poor." Third, rapid rates of turnover mean that leaving does not necessarily imply the loss of nominally very generous separation benefits and pensions since as Balan et. al (1973, p. 212) found in their extensive surveys of worker career trajectories in Monterrey, "many change enterprises quite often and thus they cannot benefit from the seniority accumulated in each of them." In each case, the value to workers of formal sector benefits is below their value on paper, and what, in the absence of a binding minimum wage, workers implicitly pay.'<sup>4</sup> In sum, earning differentials do not offer compelling evidence in favor of the segmentation hypothesis in Mexico and, given the difficulty of quantifying the unobservables, are unlikely ever to be convincing tests.

# IV. Patterns of Mobility

In contrast, the patterns of worker transitions can offer additional information on the validity of the dualistic view. Ideally, a model of the behavior for each of the four sectors and workers' choices to enter them would be postulated and held up against the evidence. However, this is a vast

**"Bell** (1994) argues that the minimum wage has virtually no impact on the distribution of average wages reported by **firms** in Mexico and little evidence of non-compliance since few firms paid wages below the

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in the literature as being important for trade in general, or for GVC trade in particular.<sup>1</sup> We focus on widely-used measures of backward GVC participation, mainly drawing on the EORA database, which capture the import content of exports, that is, how much imported materials are used in countries’exports. We consider seven broad types of determinants emphasized in the trade literature: (i) factor endowments, (ii) geography, (iii) domestic industrial capacity, (iv) trade policy and foreign direct investment (FDI), (v) institutional quality, (vi) connectivity, and (vii) macroeconomic factors.

However, establishing causality is challenging in the cross-country setting as some of the potential determinants, such as tari¤s and FDI in‡ows, are endogenous to GVC participation. To this end, we rely on instrumental variables (IVs) estimation in the cross-country regressions, and a di¤erence-in-di¤erence framework following Rajan and Zingales (1998) in the cross-country cross-sector regressions. The use of IVs also mitigates biases in the construction of the GVC participation variables, which hinges on the use of international input-output tables that may have measurement problems. Our IV selections are guided by existing trade theories and strong empirical evidence.

The results from our cross-country decadal panel and our cross-country IV regressions show that the key determinants of backward GVC participation are, in order of importance, factor endowments, geographical location, political stability, tari¤s and FDI in‡ows, and domestic industrial capacity. We show that our IVs have the expected coe¢ cients and signi...cant explanatory power with high ...rst-stage F-statistics. Our second-stage IV coe¢ cient estimates are larger in magnitude than the corresponding least squares coe¢ cient estimates suggesting that measurement errors and reverse causality are important in biasing the least squares results. Our ...ndings are robust to the inclusion of alternative determinants and controls. Moreover, broad sector analysis suggests that the overall
a positive and significant effect on SWF investments. The introduction of country and SWF characteristics captured by _Xj_ and _Yi_ allows us to examine if there exists cultural bias for SWF investments in Africa, and if the drivers of these investments are financial rather than political. Indeed, Chhaoccharia and Laeven (2009) found that cultural bias is more pronounced for SWFs and they tend to invest in countries with similar cultural traits. Most importantly, they showed that religious closeness is positively and significantly related to SWF investments. Knill et _et al._ (2012) find that political relations are important in why SWFs invest. However, for Avendano and Santiso (2009), SWF investments do not exhibit political bias, and their investments are not different from Mutual Fund investments. Our dependent variable is the logarithm of one plus the share of each investment in terms of total capitalization for 26 SWFs in Africa over the period 1985-2013.

In order to estimate the empirical model, we use the following proxies. We first calculate the excess return using the average GDP growth rate over the period 1985-2013 taken from the new Penn-World Table 8.0 of Feenstra _et al._ (2013). The United States is used as a proxy in terms of investment in a risk-free asset, _Rf_ . The expression _Rj_ , which denotes the expected return in African country _j_ , is measured as the average per-worker GDP growth rate.<sup>6</sup> To measure the risk of investments in Africa, we use the standard deviation of the average per-worker GDP growth rate over the period 1985-2013. Our networking variables _Xj_ and _Yi_ are proxied by religion and political fund, respectively. Specifically, Bortolotti _et al._ (2015) use the question 11 of Truman (2008): “Are decisions on specific investments made by the Managers?” to construct the index of political fund. They classify all funds with managerial independence score of less than 1 as “political funds” and all others as “non political funds.” They then
Policy Research Working Paper 6121

# **Abstract**

This paper presents new global evidence on the key determinants of public-private partnership investment in electricity transmission and distribution, based on a panel data analysis of 105 developing countries over a period of 16 years from 1993 to 2008. It aims to identify the key factors affecting the private investor’s decision to enter electricity transmission and distribution, through a probit analysis and the amount of investment sunk in this market segment, based on Heckman’s sample selection analysis. One of the key results of the analysis is that sector regulatory governance affects only the entry of private investors in electricity transmission and distribution. It is not significantly linked to higher investment in transmission and distribution. The result implies that the power of the incentive has not been so strong as to affect the volume of investment. Similarly, economy-wide governance factors, including control for corruption and degree of political competition, are factored in by private investors only in the initial stage of the game when the decision to enter into the transmission and distribution market is taken. This reinforces the expectation that private investors seem to be adequately protected against risks, so that once they have entered the market, they can accommodate the governance environment. Finally, the introduction of renewables in the power system enhanced overall public-private partnership investment in transmission and distribution. Renewable-based energy also requires technical and regulatory certainty about the availability of renewable-ready transmission resources.

This paper is a product of the Energy Unit, Sustainable Energy Department. 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 mvagliasindi@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
specific scale parameters that are employed. Our results are robust to different measures of poverty, income expectations, reference groups, functional forms, and various other specifications.

This paper consists of seven sections. We briefly review the literature in the next section, before discussing our empirical strategy in Section 3. We subsequently describe the data in section 4, and present estimation results in section 5. We offer a wide range of robustness checks and further extensions in Section 6 before finally concluding in Section 7.

# **2. Brief Literature Review**

A number of studies estimate equivalence scales using panel subjective well-being data, but these studies mostly investigate data on life and income satisfaction and focus on richer countries that have panel data such as Germany or the United Kingdom (Charlier, 2002; Schwarze, 2003; Falter, 2006; Bollinger _et al._ , 2012; Biewen and Juhasz, 2017; Borah _et al.,_ 2018). Our brief overview of these studies, shown in Table A.1, Appendix A, offers several findings. First, although the magnitude of the estimated equivalence parameters differs considerably across studies, all the four studies for Germany find a lower weight for children than that of an additional adult. Only one study by Bollinger _et al._ (2012) finds that children in the United Kingdom are associated with diseconomies, but this result mostly applies to the first child. Second, although most studies suggest larger returns to scale than the (old or modified) OECD equivalence scales, non-parametric scales recently estimated for Germany by Biewen and Juhasz (2017) are fairly close to “squareroot” equivalence scales.<sup>5</sup> Third, equivalence parameters depend on the types of subjective data/questions used for analysis. For example, analyzing life satisfaction or minimum income data

> 5 The old OECD scale assigns a value of 1 to the first household member, 0.7 to each additional adult, and 0.5 to each child. The corresponding
Figure 3: Change in sales/worker vs. ICT use <!-- Start of picture text --> Low competition with China High competition with China<br>−1.5 −1 −.5 0 .5 1 −1 0 1 2<br>Change in computers−per−worker Change in computers−per−worker<br>−1 −.5 0 .5 1 −1 −.5 0 .5 1<br>Change in the share of labor with internet Change in the share of labor with internet<br>−1 −.5 0 .5 1 −1 −.5 0 .5 1<br>Change in the share of labor with computer Change in the share of labor with computer<br>10 4<br>2<br>5<br>0<br>0<br>−2<br>−5 −4<br>Conditional ln(sales/worker) Conditional ln(sales/worker)<br>−6<br>−10<br>10 4<br>2<br>5<br>0<br>0<br>−2<br>−5 −4<br>Conditional ln(sales/worker) Conditional ln(sales/worker)<br>−6<br>−10<br>10 4<br>2<br>5<br>0<br>0<br>−2<br>−5 −4<br>Conditional ln(sales/worker) Conditional ln(sales/worker)<br>−6<br>−10<br><!-- End of picture text --> Source: Authors’ calculations with data from ENTIC 2009 and 2013, INEGI Note: For conditional ln(sales/worker) we use the residuals of a regression of ln(sales/worker) over size dummies
and _Com_PubRafj_ are defined similarly, indicating assignment to the commitment treatment _and_ either the private or the public raffle treatment condition. These indicators are essentially interactions of _Ordinaryj_ and _Commitmentj_ , respectively, with variables indicating assignment to the private or public raffle treatment conditions. **_S_** is a vector that includes stratification cell dummies. _ε_ is a mean-zero error and ij _ij_ because the unit of randomization is the club, standard errors are clustered at this level (Moulton 1986).

Coefficients _α_ 1 and _α_ 4 measure the difference in means of the dependent variable between

> 12 60 clubs in two locations had to be excluded from the sample because of serious implementation irregularities. Clubs in Kasungu Central were discovered to contain substantial numbers of “ghost” (nonexistent) club members and served as vehicles for larger landowners to fraudulently obtain very large loans from our partner institution; survey data collected for these individuals is thus likely to be fictitious. Clubs in Mndolera were excluded because of clerical and communications errors that led to ambiguity in treatment assignment. In the two locations subject to these issues, we excluded all clubs (amounting to three stratification cells) from the sample. Because entire stratification cells were excluded, inference among the remaining stratification cells yields internally valid results.

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restructuring is not necessarily beneficial to the shareholders; firms that resolve financial distress out-of-court are more likely to remain highly-leveraged and more likely, with a likelihood of 33%, to experience further financial distress.

Several papers have examined the effect of corporate ownership on the resolution of financial distress. Japanese firm-level data have been used to examine the main-bank system, which implies both an ownership and lending relationship between a bank and a commercial firm. Hoshi et al. (1990b) find that a bank relationship improves a firm's access to capital and promotes corporate investment in a sample of Japanese firms. In addition, Hoshi, et al. (1990a) show that bank-affiliated firms can more easily renegotiate their terms of credit to reduce the costs of financial distress. Consequently, bank-related firms recover more quickly from financial distress than other firms, and without necessarily using formal reorganization or bankruptcy procedures. This finding is explained in Aoki (1990) and Prowse (1992), who describe the involvement of Japanese banks in management decisions as a form of monitoring and resolution of principal-agent and information problems between the lender and borrower.

Weinstein and Yafeh (1998), however, find that although ties to a bank improve access to capital, they do so at a higher cost; i.e., although bank-controlled firms have access to more capital, the benefits are offset by the rents extracted by the banks. Johnson et al. (1998) estimate excess stock market returns for a cross-section of emerging markets, including the East Asian countries in our sample. They find that weaknesses in corporate governance - defined as the existence of strong links between banks and corporations and non-transparent cross-holdings between corporations - cause larger discounts in asset prices.

6
I). For services, there are recent estimations by Hoekman and Shepherd (2019). The estimated AVEs of NTMs on services are much higher than on goods (Figure 5). This might be related to the techniques used to estimate the AVE, but also to the fact that as tariffs are not imposed on services, protection through NTMs is higher. The most protected services sectors in RCEP are Public administration and defense, Construction, Trade, Tourist services, and Communications.

In the comparison of AVEs of NTMs on goods estimated by Cadot et al. (2018) and Kee and Nicita (2017), we find significant differences. In most sectors, the estimations by Cadot et al. are higher, except for two specific sectors, i.e., Other manufactures and Metals, where estimates by Kee and Nicita are higher. Both studies find a higher protection level on agriculture and food sectors, especially in Meat products and Food and beverages. In this study, we use the estimates by Cadot et al. (2018), which we found to have a more comprehensive coverage of the countries of interest and more intuitive estimates at the sectoral level, but we run a sensitivity analysis with the estimates by Kee and Nicita, presented in Appendix II. Using the database by Kee and Nicita results in slightly higher impacts on real income for RCEP as a whole, with heterogeneity of country and sectoral results. However, the results are broadly consistent across the two NTM data sets.
# **Box 3 Key Indicators from the Doing Business Report**

|<br>Starting a business: all procedures that are officially required for an entrepreneur to start up and<br>formally operate an industrial or commercial business.|
|---|
|`o`<br>Procedure is defined as any interaction of the company founders with external parties (for<br>example, government agencies, lawyers, auditors or notaries).|
|`o`<br>Time is recorded in calendar days. The measure captures the median duration that<br>incorporation lawyers indicate is necessary to complete a procedure with minimum follow-<br>up with government agencies and no extra payments.|
|`o`<br>Cost is recorded as a percentage of the economy’s income per capita. It includes all official<br>fees and fees for legal or professional services if such services are required by law.|
|`o`<br>The paid-in minimum capital requirement reflects the amount that the entrepreneur needs to<br>deposit in a bank or with a notary before registration and up to 3 months following<br>incorporation and is recorded as a percentage of the economy’s income per capita.|
|<br>Getting Credit: the legal rights of borrowers and lenders with respect to secured transactions<br>through one set of indicators and the sharing of credit information through another.|
|`o`<br>The strength of legal rights index measures the degree to which collateral and bankruptcy<br>laws protect the rights of borrowers and lenders and thus facilitate lending.|
|`o`<br>The depth of credit information index measures rules and practices affecting the coverage,<br>scope and accessibility of credit information available through either a public credit registry<br>or a private credit bureau. The public credit registry coverage indicator reports the number<br>of individuals and firms