rafmacalaba/data-use-mentions-extended huggingface dataset:
world. This changing nature of innovation implies that discovery activity would be more frequent at lower levels of development when countries are farther from the global technological frontier, but decline and eventually be overtaken by on-the-frontier innovation as incomes rise.

The second reason why expected levels of discovery activity would depend on the level of income is the recently-uncovered pattern of the stages of productive diversification across levels of development. Imbs and Wacziarg (2003) analyze how productive diversification behaves across income levels, and found that although there are theoretical arguments supporting both a positive and a negative monotonic relationship between diversification and growth, the evidence shows that neither view is correct. There is, in fact, a robust pattern whereby as countries develop, production is diversified until reaching a relatively high level of GDP per capita, between $13,000 and $14,600 1996 US dollars, after which point economies become increasingly specialized.

Although Imbs and Wacziarg (2003) used domestic production and labor data in their analysis of the stages of diversification, the same result can be found in export data. We construct a Herfindahl index ( _H_ ) of exports for each country in every year with reported exports between 1992 and 2003, and estimate the following equation using a fixed-effects estimator:<sup>4</sup> The results, summarized in Table 1, indicate that, similar to the pattern in domestic production data, a country’s export basket becomes more diversified as income rises until a relatively high level, at which point the process reverses itself and specialization occurs. This happens in the export basket at a higher transition point than that found by Imbs and Wacziarg (2003) in domestic production data ($22,500 in 2000 US dollars, PPP adjusted, compared to $14,600 in 1996 US dollars), but these results support the view that the pattern of economic diversification is related to patterns of international trade.

# _<Insert Table 1 here>_

This robust pattern in both domestic production and export data suggests a
commodity prices, and short-term interest rates. The fact that inflation rises following a demand shock but falls with a supply shock allows us to disentangle one type of shock from the other.

A global monetary shock – i.e., an expansionary shift in global monetary policy – increases output, inflation, and commodity prices, but reduces the short term interest rate on impact. This latter sign allows us to distinguish demand from monetary shocks. Finally, a global commodity shock, understood as a decline in global excess demand for commodities, is assumed to increase global output and to reduce inflation and commodity prices on impact. Note how the opposing impacts on commodity prices allow us to disentangle a commodity price shock from a (noncommodity) supply shock. In both cases, we leave the response of the interest rate unrestricted.

It is important to stress that sign restrictions, unlike conventional parametric (zero) restrictions, only achieve what has been termed set identification. That is, they help identify a set of models, rather than a single model, consistent with the assumed restrictions (see, e.g., Fry and Pagan 2011). Below we describe how we deal with this issue when reporting the empirical results.

# **3. Empirical implementation**

The empirical sample is dictated by data availability. We take all countries with complete GDP data in PWT 8.1 over the period 1970-2011. After dropping countries with anomalous observations, high-income, and very small economies, we are left with 82 developing and emerging countries. In terms of the World Bank 2014 classification, 79 belong to the ‘middle income’ category, and 3 are low- income countries. They are listed in table A1 in the Appendix.<sup>11</sup>

> 11 From the overall sample of 167 countries, we retain only those with complete GDP data over the period 1970‐ 2011. Next, we drop 11 countries exhibiting anomalous and/or possibly erroneous observations, as well as 24 countries with
# **Figure 10 Change in STRI between 2008-11 and 2016 by economy**

<!-- Start of picture text --> Sector: Commercial banking<br>THA<br>URY<br>BGD<br>EGY<br>VNM<br>PHL<br>IDN<br>PRT<br>PAK<br>ECU<br>CHL<br>CRI<br>RUS<br>MYS<br>PER<br>UKR<br>NGA<br>BRA<br>IND<br>CAN<br>GBR<br>JPN<br>FRA<br>ITA<br>KEN<br>MEX<br>KAZ<br>OMN<br>DEU<br>POL<br>AUS<br>AUT<br>LKA<br>COL<br>HUN<br>LTU<br>ZAF<br>BEL<br>KOR<br>TUR<br>-30 -20 -10 0 10<br>Note: Change in WB-WTO STRI scores.<br>Negative values denote lower scores in 2016 compared to 2008.<br><!-- End of picture text --> Digging deeper into the policy data on commercial banking services reveals certain patterns worth noting. We see convergence of policies related to entry – with most liberalization already undertaken by 2008 – but in the context of reinforced scrutiny of foreign service suppliers, for prudential or even security reasons. As a result of gradual trade liberalization, a large majority of economies allow entry into their markets through the acquisition and control of domestic entities, through the establishment of wholly-owned subsidiaries and through direct branching (Figure 11). The preferred avenue is the acquisition of already licensed institutions, which may be explained by the host regulators' wish to recapitalize local institutions (notably after the 2008-2009 crisis) while maintaining the existing market structure and therefore current intensity of competition. Both fullyowned subsidiaries and
# **G RD Plot with Fitted Local-quadratic Polynomial**

Figure G.1. RD Plot with Fitted Local-quadratic Polynomial <!-- Start of picture text -->
-200 -150 -100 -50 0 50 100 150 200<br>Arrival (days from June 8, 2018)<br>Sample average within bin Polynomial fit of order 2<br>1<br>.75<br>.5<br>PEP [=1]<br>.25<br>0<br><!-- End of picture text -->

_Notes:_ The figure illustrates the discontinuity in treatment probability 200 days around June 8, 2018, when the RAMV census closed.

66
br>18% 18%<br>4% 15% 5% 10%2% 2%9% 5% 7% 12%4% 3% 14% 3% 7% 4% 2% 8% 8%<br>1995-96 2003/04 2010/11 2014/15 1995-96 2003/04 2010/11 2014/15 1995-96 2003/04 2010/11 2014/15 1995-96 2003/04 2010/11<br>Computer Heaters Car Washing Machine<br>21% 21%<br>5% 2% 3%0% 4% 7% 12% 1% 2% 3% 3% 0% 0% 2% 3% 3%0%<br>1995-96 2003/04 2010/11 2014/15 1995-96 2003/04 2010/11 1995-96 2003/04 2010/11 2014/15 1995-96 2003/04 2010/11 2014/15<br><!-- End of picture text --> Source: World Bank Staff Calculation based on Nepal Living Standard Surveys 1995/96, 2003/04, and 2010/11. Question on computer ownership was not available in 1995/96. 2014/15 estimates are added when data is available in the 2014/15 Annual Household Survey.

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# **GREEN GROWTH, TECHNOLOGY AND INNOVATION**

**Mark A. Dutz and Siddharth Sharma**<sup>**1**</sup>

> 1 PRMED, The World Bank. The paper benefited from helpful feedback from Natalia Agapitova, Paulo Correa, Marianne Fay, Stephane Hallegatte, Stefano Negri and Michael Toman. We gratefully acknowledge the valuable contributions from Yasin Kursat Onder on the USPTO data and from Ravi Gupta on innovation technology and policy case studies.
measured as the average height of the city’s buildings within 5 kms of the highest point in the city.<sup>9</sup> Similar analysis is conducted using the average over the whole urban extent as defined by GHSL, or using quantiles over the whole distribution. Several specifications are reported in Table 5 adding regional dummies as additional controls and replacing city income by its Nighttime Light proxy or its equivalent at the country level.<sup>10</sup> Using the cross-section data for almost 400 cities, the following specification is estimated for all cities c: ln Average Height ln Income + β<sup>he</sup> ln Population cc<sup>eehtt</sup> (4)<sup>eehtt</sup> cc,2000 cc,2000 As city population doubles, the average height increases by 25% when keeping income constant. Such = αα+ γ<sup>he</sup> cc vertical growth adds up to the horizontal built-up growth previously measured. This elasticity is consistent + RRa eeooPP FFssI eeaass+ εε across the different specifications presented in Table 8.

As city income doubles, the average height increases by 18% when keeping population constant. While the population elasticity is lower for height than for built-up, the income elasticity is higher for height. Income is associated with a larger impact on vertical growth relatively to its impact on horizontal growth. This can be rationalized through different economic channels. As households get richer, more of them want to live close to where jobs are to reduce the time spent on commuting and can afford higher rents. Richer cities also tend to produce more tradable services which are intensive in knowledge workers and

> 8 The subsample of 400 cities was built to be as representative as possible at the global level of the GHSL sample of cities. As a first check, the same regression is run using both the universe and the subsample. The within-estimator of the income and population elasticities of built-up is obtained for
Policy Research Working Paper 9920

# **Abstract**

More than 20 developing countries do not publish any data on their sovereign debt. In those that do disclose data, public debt statistics usually do not comply with international standards in terms of coverage and definitions. Some information can be deduced through indirect disclosure of debt statistics to external agents, such as the World Bank and the International Monetary Fund, and this can help minimize data gaps. This paper has two main objectives. First, it measures the extent of transparency in direct reporting and identifies the factors that promote it. The results show that debt transparency is fostered by standardized recording and reporting systems, high levels of external scrutiny (for example, Eurobond issuance and ratings), and the presence of highly skilled staff at the local debt office. Second, the paper describes the reporting ecosystem in which two type of channels (direct and indirect) coexist and provides novel estimates of the data gaps across the two. Cross-comparison of direct reporting and the World Bank– International Monetary Fund Debt Sustainability Analysis shows that deviations in public debt stocks can represent up to 30 percent of national gross domestic product. Based on these results, the paper puts forward a call for action to (i) improve debt transparency by focusing on those factors that best promote transparency; (ii) shifting the focus of multilateral development banks’ operations and technical assistance from indirect to direct reporting; (iii) introducing minimum but enforceable international standards for direct reporting; and (iv) promoting the use of modern and integrated debt recording and reporting systems.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. 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://www.worldbank.org/prwp. The author may be contacted at drivetti@worldbank.org.

_The Policy Research Working
examines which borrower and loan characteristics predict whether the client was interested in the course. These characteristics all come from Partner’s client database.

Table 1 shows three specifications, one with demographic characteristics alone, the next one adding loan characteristics, and the final one with Partner branch fixed effects. All specifications show that women were about 13 percent less likely to be interested in participating in the training.<sup>7</sup> In addition, clients who had been late on at least one of their loan payments (during the course of the loan) were 5 percent more likely to be interested in training. On average, almost 60 percent of clients had made a loan payment at least one day late, but the median number of days late was relatively small (i.e. two days). This last result is promising in that people who were late on payments perceive business and financial education as being valuable.

None of the other variables show a statistically significant correlation with being interested in training. Most notably, neither the client’s age, nor the loan amount, predicts whether the client is interested in participating in the business and financial education course.

In our study, we only include clients who were interested in the training. This implies that we measure the impact of training only on the population of interested clients. For policy

> 7 About 35 percent of the clients who met all selection criteria were women.

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Policy Research Working Paper 7992

# **Abstract**

This paper looks at the structural marginalization of ethnic, religious, and sexual minorities in six pilot economies (Bulgaria, Mexico, Morocco, the Netherlands, Tanzania, and Vietnam) and proposes a new methodology for collecting cross-country comparable data on antidiscrimination legal frameworks. The data cover six areas of law, addressed by six indicators: (a) access to institutions, (b) access to education, (c) access to the labor market, (d) access to property, (e) access to public services and social protection, and (f) protection from hate crimes and hate speech. The laws, policies, and regulations presented fall under one of these indicators. For each, the paper attempts to identify the minority gap, the difference between the legal treatment of the ruling majority and that of the minority. Data were collected through two sources: first, standardized surveys submitted to ombudsman institutions, lawyers, academics, and civil society organizations; second, public government records on laws and regulations and data from international legal databases and human rights organizations.

The idea driving the study is that institutional measures that hamper the access of ethnic, religious, and sexual minorities to the labor market and financial systems directly affect their economic performance and, as a consequence, represent a cost for the economy. Among the findings of the study is that antidiscrimination labor legislation is well developed in all six pilot economies, but many gaps still exist in access to property and in access to public goods and social services. The study also found that, of the three groups covered by the study, the least protected under the law are the sexual minorities. Although data from six economies cannot provide statistical evidence, findings suggest the need for further research. The authors hope to encourage a wider debate on the consequences of systematic discrimination against minorities and to help governments critically review their legal frameworks to ensure equal opportunities for all citizens, regardless of religion, ethnicity, gender identity
<!-- Start of picture text --> Egypt,Arab Republic of<br>Chad<br>a<br>a<br>Densityper Km2per Km2 Km2<br>( “4<br>4-10<br>vsea . 1045050= 10050= 100= 100 100<br>@ 100-500<br>@ > 500<br>) Daniger<br>a<br>Sudan<br>Central African Republic 4 tig MALAKAL Ethiopia Areaof Map<br>J a eene SN<br><!-- End of picture text --> <!-- Start of picture text --> Densityper Km2per Km2 Km2<br>“4<br>4-10<br>. 1045050= 10050= 100= 100 100<br>@ 100-500<br>@ > 500<br><!-- End of picture text -->
# **6 Discussion**

The development of the IRENCGE-DF model represents an example of a new regional and environmental CGE model and constitutes a novelty in the comparative literature. IRENCGE-DF is dynamic and, using the neo-classical growth specification, treats labor growth as exogenous and capital accumulation as the result of savings and investment decisions. The vintage structure for capital allows for putty/semi-putty assumptions with sluggish mobility of installed capital. The model grows on the ground of a regionalized SAM that we described account by account in Section 3. The Italian regional SAM represents our input data, and its main strength is the easy procedure we implemented to update data and calibrate them.

In this solid framework, it is possible to create a picture of the Italian economic and fiscal system so that we can run simulations. The actual debates in Italy are directed at improving the regional economic outcomes through a possible modification of IRAP (the business tax). This framework justifies our proposed application. In Section 4, we simulated three different scenarios on IRAP: abolition, tax shift with IRES (corporate income tax), and tax shift with VAT (value added tax). This exercise represents an example of how the IRENCGE-DF model can be used and, more in general, how CGE models can help simulate economic-fiscal shocks in a specific regionalized economy.

In the first scenario (IRAP abolition), we allow the government to compensate for its loss with a higher public deficit. The impact on GDP is positive (+0.35% in 2018) and the highest if we compare it with the other scenarios. In regional terms, the abolition of IRAP causes adverse effects on regional value added for _Sardegna, Valle D’Aosta, Basilicata_ , and _Trentino Alto Adige_ . On the contrary, _Lazio, Lombardia_ , and _Marche_ would benefit most from this scenario. Looking at the welfare effects in terms of households’ monetary utility functions, the abolition of IRAP would positively affect all regions (i.e., the households would benefit from IRAP
firms also tend to have few assets that can be foreclosed in the event of breaches of contract, and their transactions are so small that the monetary and time costs <u>associated with court actions would not be justified in any case.</u> The business environment also impacts on how firms do business. Widespread market failures imply that firms face a lot of “holes” in important markets, such as those for insurance and credit. This is especially pronounced for the smallest firms. Fafchamps (2001) identifies two types of responses that aim to reduce the resulting transaction costs, namely development of relationships and the sharing of information within networks. Essentially, when search and verification costs are high, it makes sense to try to establish long-term relationships and share information with other market participants, in order to economize on such costs. The firm data have been extensively used to shed light on these mechanisms.

Trade credit is a good example of how supplier relationships can be utilized to fill in some of the holes in the formal credit market. Fisman (2001) argues that trade credit plays an important role in firm financing in Africa, mainly by enabling firms to manage raw material inventories more efficiently and by reducing the likelihood of raw material shortages. Trade credit may therefore contribute to higher productive efficiency. Fisman analyses these issues using the first waves of RPED data from 17
398|0.321|0.624|0.138|

_Notes:_ *** _p <_ 0.01, ** _p <_ 0.05, * _p <_ 0.10. OLS estimates at the target child-level are presented using outcomes reported by the caregiver at endline. Standard errors clustered at the community level are shown in parentheses. All regressions include district fixed effects. Westfall and Young (1993) _p_ -values are shown in square brackets, where 10,000 replications were used. Estimates are weighted to give each community an equal weight in the analysis. Covariates are not included in the regressions.

its Family Care Indicator (Hamadani et al., 2010; Kariger et al., 2012). Our evidence indicates that parents in treated communities provide a more stimulating environment for their children. Parents were more actively involved in stimulating their children (scoring 17.1% of standard deviation higher than parents in the control group; _p <_ 0 _._ 01) and the children of the treated communities participated more in play at home (7.7% of a standard deviation higher than in control households; _p <_ 0 _._ 1).

Second, we find that parents of target children have greater engagement with the child’s primary school. It is important to note that the parental education component of the DICIPE program promoted communication between parents and their _preschool_ . What we find here is that parents’ greater involvement with educators spills over to the primary school environment. These results are shown in Table 7. Column (1) shows that parents and other household members in treated communities were 6.7 percentage points more likely to meet with the child’s primary school principal in the past year relative to control communities ( _p <_ 0 _._ 01). Compared to a control mean of 21.2%, this is a sizeable 32% increase. Column (2) shows that parents and other
vignette:||||||
|Correct diagnosis|0.315|0.017|0.135|0.395|2095|
|Proportion of history taking|0.336|-0.022|0.117*|0.066|2095|
|Proportion of exam procedures|0.373|-0.088|0.132**|0.040|2095|
|<br>High cardiovascular risk vignette:||||||
|<br>Correct diagnosis|0.230|0.034|0.265**|0.021|2095|
|Proportion of history taking|0.385|-0.016|0.089*|0.079|2095|
|Proportion of exam procedures|0.371|-0.112|0.142**|0.011|2095|

Note: data from interviews of health providers in both rural health centers and health houses. All regressions are the difference-in-differences specification with facility fixed effects. Standard errors are clustered at the district and survey round level with wild bootstrapping. All regressions include controls for facility type, exposure to the collaborative quality improvement and citizen scorecards interventions, age and gender of providers, position, a binary indicator for experience of over 20 years and an indicator for being born in the district. Standard errors are clustered at the district and survey round level with wild bootstrapping. a Proportion of categories about which providers reported to be satisfied. The individual categories are listed in Appendix Table A4. b The definition of all the indicators related to the clinical vignettes indicators are specified in Appendix 5. Level of statistical significance: *p<0.10; **p<0.05; ***p<0.01 26
expenditures analyzed in this work represent 33.7 percent of total government expenditures and 42.9 percent of social protection expenditures. A brief description of government expenditures is presented below.

Column 6 of Table II-2 presents the ratio between total government expenditures that are obtained with the household survey and the amount reported in the administrative data. This ratio differs from 100 percent since the household survey is not representative of each social program or transfers analyzed in this document, so the number of beneficiaries differs from that of the administrative records. Consequently, the total resources transferred likewise vary by the program. However, in the case of large programs, such as _Más Familias en Acción_ and in-kind transfers for education and health, it is possible to have a better approximation of the total values. An additional reason why the survey data do not align with administrative records is the non-existence of a municipality variable. That is, a domain variable is available for the 38 municipalities that are representative of the survey and the department variable, but, in many cases, a municipality is necessary to be able to perform a better allocation of the transfer.<sup>8</sup>

> 6 For more details on how personal income tax and social security contributions operate, as well as how they were processed for inclusion in the incidence analysis, see annex I in Nuñez et, al. (2019).

> 7 For more detailed information see annex III, in Nuñez et, al. (2019).

> 8 For more information see annexes II, IV, V, and VI, in Nuñez et, al. (2019).

6