rafmacalaba/data-use-mentions-extended huggingface dataset:
as well as the restructuring terms. We also expand that dataset forward, by 50 years, adding monthly price quotations for external sovereign bonds trading on the LSE from 1930 to 1980, as provided by The Economist and the Financial Times.

Importantly, for the interwar period and post-WW2, we are the first to code and integrate into the analysis a large dataset of prices and returns for external sovereign bonds on the NYSE, which became the main trading platform for foreign sovereigns after 1914. Specifically, we coded NYSE sovereign bond price data from the Bank and Quotation Section of the Commercial Financial Chronicle (1905–27 and 1954– 78) and from the Bank and Quotation Record (from 1927–54). Taken together, the historical bond price sample spans the period from 1815 until 1980 and includes more than 900 external sovereign bonds.

For the modern (post-1990) period, we build on the extensive emerging market bond price collection by JP Morgan as part of their EMBI Global indices. EMBI data have been very widely used in the sovereign

> 31 Their dataset is hosted on the website of the International Center for Finance at Yale. A large literature has used their data and, more generally, data from the Investor’ Monthly Manual, for example, Ferguson and Schularick (2006), Mauro, Sussman, and Yafeh (2002), or Mitchener and Weidenmier (2010).

16
section. The same applies for column (5) when baseline community wealth – as measured by the median of the household wealth index – is added on top of the baseline electricity access variable. The results are consistent and in fact stronger. One noticeable change that can be observed in the results presented in columns (4) and (5) is that the effect of unimproved sanitation on school enrollment becomes significant for children ages 8–9 years after the inclusion of the two additional covariates. The effect was previously insignificant. For example, if both community electricity access and wealth at baseline are included in the model as additional covariates, the exposure to unimproved sanitation reduces the likelihood of school enrollment by 6 percentage points for all children ages 8–9 years, about twice the size of the estimated effect when community electricity access and wealth at baseline are not accounted for in our preferred specifications. The findings also suggest that the estimated coefficients for both community electricity access and community wealth variables are barely significant or insignificant, predicting school enrollment significantly for two to three subgroups but counterintuitively in the wrong direction – suggesting that the effect of unimproved sanitation on school enrollment is indeed more robust and meaningful than those two variables.

_(ii) Coefficient Stability_ While the discussion above addresses potential omitted variable biases that could arise due to general living conditions confounding our results, other omitted variable bias may underlie our preferred specifications. Our findings in Table 8 address these issues.

Table 8 further examines the robustness of the negative effects of children’s exposure to unimproved sanitation at baseline on school enrollment at the time of the survey, found in Tables 4, 5, and 6. This follows the bounding method introduced in Oster (2019) as well as Altonji, et al. (2005), who developed a method to investigate the coefficients’ sensitivity to potential omitted variable bias. The estimates reported here are calculated using the Stata module _psacalc_ introduced in Oster (2019). Since the bounding method can only be implemented on linear models
_Source:_ World Bank staff calculations based on _Doing Business_ , World Economic Forum, World Development Indicators, Eurostat.

# **6. Conclusion**

Using a panel of micro-data on firms from 12 EU countries<sup>43</sup> from 2003 to 2008, this paper addresses the confusing proliferation of suggested determinants of productivity growth and seeks to provide clear policy implications. The literature has generated theories attributing growth to country, industry, firm, and even product characteristics. Studies have thus far found support for each of these, but have failed to determine which among the many correlates are most critical for growth. We specify a model incorporating initial conditions, firm age, size, international affiliation, business environment indices, and FDI to assess the relative importance of each in explaining growth in labor productivity. We divide our sample into two groups, New Europe and Old, and obtain results for each.

In the economies of the EU12, country-level variables dominate—the most important of which are the stock of inward FDI, business regulations facilitating foreign investment, and the availability of private credit. The most important firm-level characteristic is international affiliation, either as headquarters of a multinational corporation or as subsidiary of a foreign firm. These results suggest that accession to the EU has been beneficial for new members because the ease with which foreign firms may now penetrate these new markets has facilitated the transfer of technology and the diffusion of best practices. The clear policy implication is that developing countries may realize significant productivity gains by taking the relatively easy steps of improving their regulatory regimes and creating environments attractive to inward FDI before addressing the more costly requirements of improving infrastructure and better educating their workforces.

With the EU15, firm-level characteristics dominate. Among these, the most critical are international affiliation and firm size. The most important country-level factor is outward FDI. Taken together, these results argue strongly for the role played by multinational corporations in driving productivity growth in developed countries. Thus, it is not surprising that firm size contributes to
are identified using the GTI index, which is based on ISCO-08 task statements (described in section 3.A). For the purpose of this discussion, occupations are classified into three categories: Zero GTI (occupations without any green tasks), Low GTI (occupations with less than 30% of their tasks being green), and High GTI (occupations with 30% or more of their tasks being green). It is important to note that, due to the inherent biases of the OV data, only high-skilled occupations with at least 30 job posts in the database are considered for application #2.<sup>62</sup> Project management skills are particularly crucial for high-skilled occupations that involve green tasks. On average, 60% of job advertisements for high GTI occupations require at least one project management skill, which is 10% higher compared to occupations without green tasks (Figure 4.3). Specifically, jobs in high GTI occupations typically require an average of 2.19 management skills. Examples of in-demand project management skills for these occupations include quality assurance and control, planning, people development, and compliance management (Table 4.1). There is a high demand for these skills in green occupations compared to non-green occupations. For instance, the skill of quality assurance appears 4.2 times more frequently in green jobs than in non-green jobs.

Similarly, jobs in high GTI occupations are more likely to require cognitive skills and specific field expertise. Table 4.1 illustrates the relative importance of these skills in high GTI occupations compared to occupations without green tasks (column 5). Skills such as fiber optics, research, occupational health and safety, and environmental management are particularly relevant to jobs that involve green tasks.

**Figure 4.3. Average share of posts with at least one skill demanded in a skill group, by GTI index**

<!-- Start of picture text --> 0 10 20 30 40 50 60<br>Cognitive (
institutions. Informal businesses are thus more vulnerable in terms of both being able to convince the customers that their side of the transaction will be fulfilled and ensuring that customers fulfill their side of the transaction as well (e.g., pay as much as agreed and on time). To investigate informal businesses’ relations with their customers, the Informal Sector Enterprise Surveys ask whether the businesses’ typical customer is someone known as a repeated customer, someone known personally, or someone unfamiliar. Figure 9 shows the shares of businesses’ typical customers in each country (panel A) and sector (panel B). Except for Mozambique, the least common type of customer for each country is someone unfamiliar, suggesting that impersonal market exchanges comprise a minority of business transactions for informal businesses in these countries.

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therefore likely to result in an overallocation of resources to municipal services in some jurisdictions, and an underallocation of resources to municipal services in others. While central governments could, in principle, vary the tax rates they impose in different jurisdictions to match the preferences of local taxpayers, in practice they are in a poor position to do so. Local governments would appear to have a clear comparative advantage in discerning the preferences of their constituencies.

Local control over tax rates is, however, largely limited to industrial countries. In most developing countries, central governmernts control local tax rates, either directly or in the form of ceiling on maximum rates. In rare cases, this control may be justified by central government's need to control the instruments of macroeconomic policy. Given the property tax's small role in public sector resource mobilizationz5/ this argument is not persuasive.

III. TAX REFORM PROGRAMS: DESIGN AND IMPLEMENTATION Efforts to improve property taxation rarely begin with a tabula rasa. Almost all market-economy countries have some form of property taxation already in place. The job of reform is to improve the performance of an existing system. The process of reform must begin with a careful diagnosis of the weaknesses of the present system. Beyond this, specifics will vary. Experience with property tax reform in LDCs nevertheless provides some broad guidelines for the process.

15/ Based on data from 55 developing countries, the IMF reports that recurrent taxes on imuovable property constitute an average of 1.3 percent of total public sector taxation.
within sector growth has been broad-based-including in agriculture as well as manufacturing, trade, transport and finance services, while the between-sector productivity gains mainly reflected a move out of agriculture into services. In particular, the share of workers employed in agriculture fell from about 70 percent in 1975 to about 30 percent in 2018. In LICs, between-sector productivity gains in LICs reflected a broad-based shift out of agriculture into services such as trade, transport and finance. During the 2010s, the contribution of between-sector slowed down due to small movement to higher productivity sectors such as manufacturing and trade.

Figure 4 shows that contributions of the between-sector effect have been non-negligible in the East Asia and Pacific (EAP), European and Central Asia (ECA), South Asia (SAR) and Sub-Saharan Africa (SSA) regions whereas those in Latin America and Caribbean (LAC) and Middle East and North Africa (MENA) have been small.

# **3.2 Baseline regression**

# **3.2.1 Aggregate convergence**

Table 1 and Figure 5 show the results with three different balanced panel datasets: 60 countries in 1975-2018, 60 countries in 1975-1995, and 91 countries in 1995-2018. At the aggregate level, regression (2) shows there has been weak unconditional convergence prior to 1995. However, since the late 1990s aggregate convergence emerges (Table 1 and Figure 5, World Bank (2020)). Over this period, countries with lower initial levels of productivity have begun to catch up to high-productivity economies. Nonetheless, at the estimated rate of convergence it would take about 140 years for countries at the bottom 10 percent of the productivity distribution to reach the level of the top 10 percent.<sup>8</sup>

# **3.2.2 Decomposing within and between sector convergence**

Even though many sectors are not converging to the frontier, the reallocation of labor to other sectors with higher productivity levels could be an important engine of aggregate convergence. Estimating the decomposition of aggregate
Table 6 Descriptive statistics of the CCR efficiency index (Normal and Bias-Corrected) by Industry and country <u>(year 2005).</u>

|**Country/industry**|**Be**|**verages**||**Food**|**Ga**|**rments**|**Metals**|**and machinery**|
|---|---|---|---|---|---|---|---|---|
|**CCR efficiency**<br>**index**<br>|**Normal**|**Bias Corrected**<br>|**Normal**|**Bias Corrected**<br>|**Normal**|**Bias Corrected**<br>|**Normal**|**Bias Corrected**|
|Bulgaria|0.781|0.658|0.977|0.866|0.811|0.682|0.780|0.718|
|Czech Republic|0.611|0.554|0.536|0.504|0.554|0.518|0.687|0.656|
|Estonia|0.547|0.492|0.503|0.430|0.609|0.566|0.777|0.722|
|Hungary|0.752|0.653|0.763|0.681|0.719|0.628|0.700|0.656|
|Latvia|0.784|0.627|||0.790|0.627|0.769|0.693|
|Lithuania|0.751|0.645|||0
One issue is the lack of fiscal institutions to save during good times, reduce debt, and establish greater credibility of debt repayment during bad times. The federal system with important subnational expenditure responsibilities but limited subnational revenue responsibilities also hampered incentives for fiscal probity at the subnational level.<sup>30</sup> Federalism and national politics interacted through the use of regional distribution of funds and/or regional pattern of reforms to secure support from small, over-represented provinces to establish coalitions for reform (Gibson and Calvo, 2000; Calvo and Murillo, 2008).

On the side of monetary policies, as the situation deteriorated in 2001, the government may have “doubled its bets” on the convertibility plan, but it also sent mixed signals as it tweaked the currency board at the margin (“fiscal” devaluation and introduction of the euro) and tinkered with the institutional arrangements (questionable dismissal of the Central Bank president). One issue that is often under-emphasized in the “post-mortems” of the crisis is the double digit unemployment rate that emerged in the mid-1990s and persisted even during the post-Tequila crisis growth period. As established in a classic paper,<sup>31</sup> signaling a tough stance on an exchange rate peg can actually lower the future credibility of that pledge in the face of persistently high unemployment.

What would a credible policy package have looked like to avoid the crisis? It is not at all clear. Recall the three criteria laid out in the introduction: (i) the policy has internal logic and rationale and appears to have the right magnitude to achieve its goals; (ii) the policy is based on reliable data and trusted institutions; and (iii) the policy is consistent with a longer-term vision or strategic direction. On the fiscal policy front, there was great uncertainty as to whether a fiscal contraction could create a confidence shock sufficiently large to reassure the private sector. Some argued that a fiscal expansion might have worked; however, given the soaring bond spreads and declining
ACGMS 2019 provides a comparison of the average characteristics of the MFI client households and those for rural households in Latur and Nanded districts. It is nonetheless surprising that households that are officially classified as being VG appear not to be too dissimilar from non-VG households in terms of their economic status. This suggests that the MFI is good at targeting the most needy households and that it manages to serve households possibly mis-classified as being non-VG.

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age, which reflects children‘s development relative to a reference population of wellnourished children (WHO 2006).<sup>5</sup> Because children‘s weight at birth influences their health and prospects for survival (Rosenzweig and Shultz 1982), a key variable for this study is the data on children‘s weight at birth in the survey. The NFHS collects information on weight at birth in addition to weight at the time of the survey and asks mothers to categorize the weight of their children at birth as large, average, or small.<sup>6</sup> The sample of children with weight measured at birth is much smaller than the sample of children whose weight was assessed by their mother (table A1 in the appendix). The study relies mainly on these subjective assessments as a proxy for health endowments at birth. The weight of about 20–25 percent of children was lower than average according to their mothers‘ assessments (see table A1), a figure not out of keeping with the rate of low birth weight children in India.

The data show that average height-for-age has risen over time for both boys and girls, with z-scores rising from –1.91 in 1992 to –1.55 in 2005 for boys and from –1.86 to –1.53 for girls. Correspondingly, stunting declined from 72 percent of boys and 70 percent of girls in 1995 to 65 percent for both sexes by 2005. Despite these improvements, malnutrition remains prevalent in India.

Deaths around the time of birth (neonatal) are high in all rounds of the NFHS (table 1). Boys accounted for about 56 percent of all deaths in the immediate postnatal period. However, beyond age 6 months, the share of deaths is higher for girls than for boys. A plot of the cumulative mortality hazard by gender for the three rounds of the NFHS again shows that more than half the deaths in children under age 36 months occur in the first month after
result is driven by Southern SSA countries who appear to have deindustrilized when examining manufacturing output shares. This section investigates two specification issues in an attempt to understand the nature of SSA’s manufacturing experience. First, we augment the set of covariates beyond the population size and per capita income in equation (2). In particular, we include other potential correlates of deindustrialization such as the levels of remittances and foreign direct investments (FDI) (Lartey, Mandelman & Acosta 2012). Second, we also conduct our analysis by limiting the sample to countries for which we have non-oil GDP data. Recall that we have a subsample of SSA countries for which we have non-oil GDP data spanning 2004-2016 (see Section 2 for details). Our objective is to examine whether there other channels 21
**Figure 3. 8  Location of cashing pay checks**

<!-- Start of picture text --> 100%<br>90% 83%<br>80%<br>70%<br>60% 53%<br>47%<br>50%<br>40%<br>30%<br>20% 13%<br>10% 1% 5%<br>0%<br>Cash it in a bank Other Deposit in account<br>Banked Unbanked<br>%<br><!-- End of picture text --> _Source DANE household study of Bogotá, 2003_ 15. **The unbanked are also disadvantaged when making payments.** Colombian banks process payments for public services (water, sanitation, electrical energy, garbage collection, telephones etc.) for both deposit holders and non-deposit holders. Banked individuals can make payments using traditional means such as check or cash, or instruments such as ATM, debit, credit cards, internet and telephone payments. Public utility payments can also be made with debit, credit and ATM cards using data phones at a wide variety of places such as supermarkets, video stores and malls. However, the unbanked who need to pay in cash are obliged to travel to Administrative Centers of Services<sup>44</sup> . Commercial banks only accept payments in cash for public utilities at specified hours and days. In addition, only one line is available for the unbanked to make payments in banks and processing late or overdue payments bears additional costs.

16. **Both the banked and unbanked receive income from remittances.** Approximately 6% of Bogotá’s population receives remittances from other cities (3.2%) and from abroad (2.4%). Of these, 58% of recipients are banked, while 42% are unbanked. When receiving domestic remittances, 60% of the banked rely on
(11.876)<br>Socialist Legal Origin<br>-13.27<br>-13.756<br>(17.112)<br>(19.851)<br>Constant<br>-18.81<br>-55.130**<br>-43.738<br>-138.177***<br>-121.617***<br>(14.303)<br>(27.507)<br>(30.971)<br>(25.783)<br>(28.812)<br>Dep. Var.: EFNX<br>Predicted EFNX<br>1.188***<br>1.181***<br>1.104***<br>1.038***<br>1.047***<br>(0.184)<br>(0.189)<br>(0.216)<br>(0.175)<br>(0.212)<br>Observations<br>96<br>96<br>96<br>96<br>96<br>**_Panel A: Second Stage_**<br>**_Panel B: First Stage_**<br>Notes: Robust standard errors in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%; Dependent<br>variable,_Private Credit/GDP_is credit to the private sector by banks and other financial institutions as a share of GDP;<br>_EFNX_is the external finance need of exports;_Log(Trade/GDP)_is log of exports and imports as a share of GDP;<br>_Log(Income)_is log of PPP-adjusted real per capita income from Penn World Tables;_French
Source: World Bank staff estimates based on the Changing Wealth of Nations 2021._ When we limit this to just nonrenewable natural assets, seven countries had the largest share (more than 50%) of total wealth in assets including oil, natural gas, coal or metals and minerals. By 2014, five of these countries still had most of its total wealth concentrated in nonrenewable natural resources. These countries were: Central African Republic, Democratic Republic of Congo, Gabon, Guinea, Liberia, Mali and Chad.

According to the Growth Commission: “Strong enduring growth requires high rates of investment. If the sustained, high-growth cases are any guide, it appears overall investment rates of 25 percent GDP or above are needed, counting both public and private investment.

We can examine this in terms of investment in physical capital (gross fixed capital formation), human capital (such as educational expenditures). First, we examine the investment rate over the period, defining investment as the sum of physical capital investment (the traditional definition of the investment rate) and the investments made into human capital (i.e. health and education spending).

From the 22 resource-rich countries with non-missing data, only 10 exceeded 25% during the boom. However, this measure excludes health and education as it does in national accounts. The Growth Commission report notes than health and education spending should 36
highest on Hofstede‟s (1980) masculinity index, suggesting that differences between genders would be starker in those cultures. Indeed, Gneezy et al. (2009) show that gender differences are subject to cultural forces.

Banuri and Eckel (2012b) implement an ABA design using the same game as above in the US and Pakistan. The study the long-term impacts of a short term policy shock on bribing behavior by conducting 10 rounds with no punishment, 10 rounds with punishment, and then 10 rounds without punishment. As in their previous experiment, subjects are matched once at the beginning of the session, and then keep their roles throughout the session. Their punishment between-subjects results are largely replicated. They show, however, that bribing behavior

> 17 This is not true for bribe acceptances, however.  They find that a significantly lower percentage of women accept bribes in the neutral frame, but not in the loaded frame.

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-|62%|
|Kenya|116|407<br>|290<br>-|29%|
|Sudan|62|207|144<br>-|30%|
|DRC|52|56|4<br>-|93%|
|Uganda|42|89|47<br>-|47%|
|Niger|32|106|74<br>-|31%|
|Ecuador|26|789|763<br>-|3%|
|Colombia|21|2,083<br>|2,062<br>-|1%|
|South Africa|17|2,094|2,077<br>-|1%|
|Pakistan|9|363|355<br>-|2%|
|Egypt|7|401<br>|394<br>-|2%|
|India|3|406<br>|402<br>-|1%|
|Peru|3|1,578|1,576<br>-|0%|
|Chad|2|110|107<br>-|2%|
|Iran|2|691|689<br>-|0%|
|Mexico|0|1,923|1,923<br>-|0%|
|Brazil|0|2,548<br>|2,548<br>-|0%|

# _Source: REFD (2024)_

Key Fact 10: ODA for refugee education in LICs and MICs is primarily allocated to Syrian refugees Further disaggregation of ODA for refugee education in LICs and MICs reveals that not only is financing skewed towards specific countries, but towards one specific crisis.

Figure M uses country of origin data for each of the 25 largest refugee hosting countries to create an estimate of financing for refugee education by crisis.<sup>29<