rafmacalaba/data-use-mentions-extended huggingface dataset:
enabling assessment of a wide range of its PRSP achievements.<sup>24</sup> However, despite the prominence of citizen empowerment, the action plan’s detailing of ten critical areas of information gathering and analysis includes little mention of empowerment indicators or measurement. In addition, recent work undertaken for the World Bank’s forthcoming Ethiopia Poverty Assessment demonstrated that direct indicators of empowerment are extremely hard to find. Where information is available, it is scattered and largely anecdotal.

To address this problem, which Ethiopia has in common with many other PRSP countries, a draft empowerment module has been developed for partial integration into other household survey instruments or use “as is” at the national level. The full draft of the module can be found in 5. This represents an early and as yet untested effort to develop an instrument that can either stand alone as a national household survey, or have selected components modified to become an integral part of an LSMS or other national survey.<sup>25</sup> The draft survey module contains two sections. The first describes tools for institutional mapping at a local level. The second contains a questionnaire. At present, the questionnaire is lengthy and is regarded as providing a set of base questions that can be added to or subtracted from in different countries and contexts.

# 2.3.1 Agency and Opportunity Structure

Many intermediate indicators of empowerment, especially indicators referring to a person’s agency, are already generated by well-honed and tested questions in tools such as the LSMS and social capital survey tools.<sup>26</sup> Rather than generating new indicators or survey questions, the draft module utilizes indicators and questions that have already been developed. In both cases, existing sources of information or survey questions are identified. In addition to recognizing the contributions of existing instruments, this approach reduces possibilities of duplication—where surveys are already undertaken in countries—and enhances opportunities to easily integrate parts of the empowerment module into other national-level survey activities
transfers and income support programs; (b) local government support and community development programs investing in e.g. health care, infrastructure, education, labor markets, agricultural productivity and micro finance; (c) food-and-cash for work programs; (d) fund raising and donor coordination; and (e) evaluation of country strategies, and the monitoring of progress towards millennium development goals (MDGs).

To take full advantage of the poverty maps, in particular of their policy relevance, it is key that they are accessible to a wide range of policy makers that include local entities as well as high level officials. It is not uncommon that public institutions, many of which may be potential users, are left largely unaware of the results from the poverty mapping exercise and their potential applications. Also important is that outdated estimates are replaced with up-to-date estimates of poverty and inequality.

23
Policy Research Working Paper 9670

# **Abstract**

This paper analyzes the relationship between financial structure and innovation. Analysis of cross-country micro data over 2009–18 shows that a firm’s financial sources matter for the choice to innovate and the extent to which a firm innovates. The relationship is stronger for firms relying on non-bank financial intermediaries and for firms in low-technology sectors. Moreover, the use of external sources of finance is associated with improved prospects of innovation, especially in more financially developed countries. These findings suggest that developing the financial sector can bring benefits in terms of innovation.

This paper is a product of the Office of the Chief Economist, East Asia and the Pacific 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://www.worldbank.org/prwp. The authors may be contacted at dmare@worldbank.org, fdenicola@worldbank.org, and fmiguelliriano@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 the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
254)|
|∆FDI_export_L|-1.172|-0.180|0.685|1.147**|0.570**|
||(1.153)|(0.819)|(0.548)|(0.544)|(0.229)|
|Observations|609|609|609|609|609|
|R-squared|0.558|0.581|0.494|0.818|0.735|
|Prov-Year FE|Y|Y|Y|Y|Y|
|Lagged city characteristics|Y|Y|Y|Y|Y|
|SOE reform|Y|Y|Y|Y|Y|
|Tariff shocks|Y|Y|Y|Y|Y|
|Excludingmigrants|Y|Y|Y|Y|Y|

Note: This table shows the heterogenous effects of FDI on city level structural transformation and school enrollment by export intensity of FDI. Standard errors are clustered at the city level. *** p<0.01, ** p<0.05, * p<0.1.

# 6.2 FDI shock by skill intensity

Li (2018) shows that high-skill export shocks raise both high school and college enrollments, while low-skill export shocks depress both. By the same token, the effect of FDI shock could also vary by the skill intensity associated with FDI. We construct high-skill FDI shock and low-skill FDI shock in a similar way as high export intensity and low export intensity shocks. We first calculate the share of employees with at least a college degree in each 3-digit manufacturing industry based on the 2000 population census. We then divide industries into high-skill and low-skill based on whether the college employee share is above the median of all manufacturing industries. Next, we calculate high-skill and low-skill FDI shocks as the interaction between each city’s initial industry employment share and predicted national FDI employment share changes at the
age) and early child development tests (children 36-59 months old) among the children of study participants, as well as a survey and biomarker data collection among their husbands.

The household surveys at each round consisted of a multi-topic questionnaire administered to the households in which the core respondents resided during the data collection period. They consisted of two parts: one that was administered to the head of the household and the other administered to the core respondent. The former collected information on the household roster, dwelling characteristics, household assets and durables, shocks, and consumption. The survey administered to the core respondent collected detailed information about her family background, schooling status, health, dating patterns, sexual behavior, fertility, marriage, labor market outcomes, and empowerment. In addition to the household survey administered to the core respondent (and to her parents/guardian if she still lived with them), the Round 4 survey included a similar module administered to the husbands of married study participants.

The Round 4 household survey also consisted of a test to measure basic labor market skills of the core respondent, which we termed “competencies.” It included reading and following instructions to apply fertilizer; making correct change during a hypothetical market transaction; sending a text message and using a calculator on a mobile phone, and calculating profits for a hypothetical business scenario. As Round 4 was focused more on the transition into adulthood and labor markets, as opposed to the school attainment and learning focus in Round 3, this test was designed to replace the reading comprehension, math, and cognitive skills tests utilized in Round 3, and serve as a measure of a more practical set of skills that might be influenced by increased schooling and needed in the labor market.

Home-based voluntary counseling and testing for HIV (for core respondents during Rounds 2-4, and their husbands in Round 4) was conducted by Malawian nurses and counselors certified 12
13 that is those living in sampled towns as of 1981. Unfortunately, the 1991 census does not provide information about past place of residence. We thus proxy the town of residence as of 1981 with town of birth<sup>13</sup> . The evidence discussed in the previous section suggests, however, that geographic mobility is not a relevant issue in our specific sample.

The proportion of youths exempt before eligibility who completed high school by 1991 is higher by 2.3 percentage points than among similar non exempt ones (row D). The p-value of the unconditional difference is 0.088 and compares with the much lower levels of significance and point estimates close to zero detected for the other long run outcomes and for all observable circumstances of the older cohort. In particular, there is no statistically relevant difference in the proportion of males enrolled in formal education or participating in the labor market as of 1986 (rows E-F) and as of 1991 (rows G-H). Also, as of 1991 there is no difference in the proportion of those who had completed college between exempt and non exempt youths in both cohorts (row I), consistently with the idea that individuals whose behavior was changed by the exemption are those at risk of high school dropout, thus unlikely to pursue a college education. To put the difference in high school completion rates in context, it implies that in the entire quake region over 3,000 youths who would have otherwise dropped out managed to complete high school and around 200 in the sample of towns under investigation.

Finally, the last three rows of table (1) compare the probability of dying between 1991 and 2001. We recover this measure by combining the information on the initial population at risk in cohort c born in town j (Nc,j) from the 1991 population census with that obtained from the individual death data. For each death, we observe the date of the event and a variety of individual characteristics including town and year of birth. We recover
Nitsch, V., 2009, “Die Another Day: Duration in German Import Trade,” Review of World Economics 145(1), 133–154.

- Nunn, N., 2007, “Relationship-Specificity, Incomplete Contracts, and the Pattern of Trade,” Quarterly Journal of Economics 122(2), 569-600.

- Paravisini, D., V. Rappoport, P. Schnabl, and D. Wolfenzon, 2015, “Dissecting the Effect of Credit Supply on Trade: Evidence from Matched Credit–Export Data,” Review of Economic Studies 82, 333–359.

- Raddatz, C., 2006, “Liquidity Needs and Vulnerability to Financial Underdevelopment,” Journal of Financial Economics 80(3), 677-722.

- Rajan, R.G., and L. Zingales, 1998, “Financial Dependence and Growth,” American Economic Review 88(3), 559-586.

- Rampini, A.A., and S. Viswanathan, 2010,“Collateral, Risk Management, and the Distribution of Debt Capacity,” Journal of Finance 65(6), 2293-2322.

- Romalis, J., 2004, “Factor Proportions and the Structure of Commodity Trade,” American Economic Review 94(1), 67-97.

- Shen, C.-H., and C.-C. Lee, 2006, “Same Financial Development yet Different Economic Growth - Why?” Journal of Money, Credit, and Banking 38(7), 1907-1944.

- Shleifer, A., and R.W. Vishny, 1992, “Liquidation Values and Debt Capacity: A Market Equilibrium Approach,” Journal of Finance 47(4), 1343-1366.

- Song, F., and A.V. Thakor, 2010, “Financial System Architecture and the Co-Evolution of Banks and Capital Markets,” Economic Journal 120, 1021-1055.

- Strieborny, M., and M. Kukenova, 2016, “Investment in Relationship-Specific Assets: Does Finance Matter
completed responses have been met in each governorate aside from the island of Soccatra. The number of minimum responses per governorate are determined by the governorate’s share of the total population. The number of respondents surveyed each month is approximately 2400.<sup>8</sup> The survey is a rolling panel, where the call center acquired a list of 2400 phone numbers that answered the survey in the initial month via random digit dialing, subject to the governoratelevel targets mentioned above. In the second month, the same 2400 phone numbers are contacted for an identical survey. Of these 2400, approximately 400 on average will not be able to be reached and will have to be replaced with a household from the same governorate via random digit dialing, and approximately 200 will not respond for two months in a row. However, those that are not reached will continue to be listed in the bank of possible phone numbers to be tried each month and will only be dropped from the survey completely if they have been tried to be contacted and not completed a survey for three straight rounds.<sup>9</sup> Every month, the survey collects information necessary to construct the Food Consumption Score (FCS)<sup>10</sup> , information on food coping strategies necessary to construct the Reduced Coping Strategy Index (rCSI)<sup>11</sup> , information on whether the household received food assistance in the past month, and information on the location of households (governorate and district). Other survey modules have been inserted in a subset of monthly surveys, including modules on displacement status and the type of housing in which the household lives.<sup>12</sup> Although the survey reaches 2400 households each month, the household-level data is not publicly available. However, the WFP publicly shares each month the governorate-level averages and confidence intervals of all key variables collected<sup>13</sup> , and these monthly governorate-level estimates are used in the empirical
costs associated with trading a particular security. This variable helps determine the barriers to efficiency in the market. All these indicators are constructed by compiling and statistically processing firm-level data from a variety of market sources.

# _3.4. Financial Stability_

Last, but not the least, financial stability is an important feature of the financial sector. There is a vast literature specifically on measuring systemic risk, stress tests, and other tools for financial stability. Because of the importance of financial stability for broader macroeconomic stability, the topic is sometimes treated as a separate one.<sup>6</sup> But financial stability is a part of the broader financial development process. To illustrate this, imagine a country where banks‘ lending standards become very loose, with banks providing loans left and right, without proper risk management and loan monitoring. On the surface, one could observe the rapid growth as a sign of deepening and increased access to finance. Also on surface, the financial sector can seem efficient, for some period of time: without the loan approval process, such banks would be able

> 6 For example, many central banks around the world publish reports focused almost exclusively on financial stability. Similarly, the IMF‘s _Global Financial Stability Report_ has a clear stability focus. There are, however, many complementarities between financial stability, depth, access, and efficiency, as emphasized for instance in the World Bank-IMF‘s Financial Sector Assessment Program.
# **Figure 10: Job content of exports across macro sectors, South Africa 2011**

<!-- Start of picture text --> Manufacturing<br>Mining and Energy<br>Other commercial services<br>Agriculture<br>Transport and communication<br>Trade, sales and accomodation<br>Public services<br>Financial services<br>Electricity, gas and water<br>Real estate, renting<br>Construction<br>0 500 1,000 1,500 2,000<br>Thousands<br>Direct JOBX Indirect JOBX<br><!-- End of picture text --> _Source:_ Authors’ elaboration based on LACEX.

The intensity with which manufacturing exports support jobs is instead lower than agriculture as well as most services sectors. Figure 11 shows the direct and indirect jobs per $1 million of gross exports for 2011. Aside from real estate and renting, manufacturing has the lowest direct job intensity of exports, with 6 jobs directly supported per $1 million in exports. The indirect job intensity of exports is instead higher than all other sectors, at 22 jobs indirectly supported per $1 million in exports. Overall, the total job intensity of exports is about average, but below agriculture and other services sectors. The job intensity of mining and energy, on the other hand, is among the lowest.

18
<!-- Start of picture text --> Figure 2: Quantity and Quality of Education Data<br>Panel A: Expected Years of School By Age 18<br>Expected Years of School<br>BDI MWISLEMOZCODMDGGNBCOMTGOETHGINGMBHTIAFGZWEUGABENKIRTLSSLBYEMNPLTZASENLSOCMRVUTKENTJKBGDKHMSTPTUVKGZGHAMHLZMBCIVPNGSDNCOGPSEHNDNICPAKMDANGATONWSMINDVNMMMRLAOBOLCPVGTMGUYPHLMARJAMAGOBTNSWZSLVFJIBLZPRYARMUZBXKXUKRGEOVCTDMAJORLCAEGYTUNIDNECUBIHLKANAMCUBALBPERMNGZAFGRDNRUCOLDZAIRQLBNBRADOMMKDSRBCHNVENSURGABBRBTHAPLWCRIAZEMNEBWAMEXIRNBLRBGRMUSARGTURURYPANCHLBHSATGROUTKMRUSHRVKAZMYSLVAGRCSYCPOLVGBHUNPRTESTLTUCYPTTOSVKSVNCZEISRMLTPRINZLESPJPNITAKORABWOMNFRAFINGBRBHRCANAUSTWNBEDNKDEUSWEISAUTSAUNLDHKGUSA L SMRBMUCHEKWTIRLBRNNORARESGPMACLUX QAT<br>CAF BFARWA MRTSYR<br>NER MLI DJI<br>TCD<br>LBR SSD<br>6 8 10 12<br>Log Real GDP Per Capita at PPP<br>Note: Dataset version 21 Sept 2018<br>Panel B: Harmonized Test Scores<br>Harmonized Test Scores<br>SGP<br>JPNKORTWNHKG<br>VNM CUBSRBBGRRUSHRVKAZLVAPOLHUNESTPRTLTUCYPSVKSVNCZEISRNZLESPITAFRAFINGBRCANAUSBELDNKDEUSWEISLAUTNLDUSACHEIRLNOR MACLUX<br>UKR<br>BDI KENTJKKHMKGZ MDAMMRSWZARMGEOECUBIHALBMNGCOLCHNVENGABTHAAZECRIMNEMEXIRNMUSARGTURURYCHLROUMYSGRCSYCTTOMLTOMNBHR ARE QAT<br>LBRMWISLEMOZCODMDGCOMTGOETHGINGMBHTIBFARWATCDAFGSSDZWEUGABENKIRTLSSLBYEMNPLTZASENLSOCMRVUTBGDMRTTUVZMBCIVPNGSDNSYRCOGPSEHNDNICPAKNGATONINDLAOGTMGUYPHLMARJAMAGOSLVPRYXKXJORTUNEGYIDNLKANAMPERZAFDZAIRQLBNBRAMKDDOMBWAPAN SAUKWT<br>NER MLI GHA<br>6 8 10 12<br>Log Real GDP Per Capita at PPP<br>Note: Dataset version 21 Sept 2018<br>14<br>12<br>10<br>Years<br>8<br>6<br>4<br>600<br>500<br>Test Scores<br>400<br>300<br><!-- End of picture text --> Notes: Expected years of school are calculated using repetition‐adjusted enrollment rates by school level to proxy for age‐specific enrollment rates up to age 18. Enrollment rates are taken from the UNESCO Institute for Statistics, and extensively revised/updated/expanded with estimates provided by World Bank staff. Harmonized test scores are taken from Patrinos and Angrist (2018) and are measured in TIMSS‐equivalent units, i.e. a mean of 500 and a standard deviation of 100 across students in OECD countries. Real GDP per capita adjusted for differences in purchasing power parity is taken from the Penn World Tables (Feenstra et. al. (2015)) , with missing countries filled using data from World Bank estimates of GDP at PPP. Graph shows the most recent
WPS3723

# **Determinants of City Growth in Brazil**

Daniel da Mata<sup>*</sup> , Uwe Deichmann<sup>†</sup> , J. Vernon Henderson<sup>‡</sup> , Somik V. Lall<sup>†</sup> , and Hyoung Gun Wang<sup>‡</sup>

* DIRUR, Instituto de Pesquisa Econômica Aplicada (IPEA), Brasilia † Development Research Group, The World Bank, Washington  DC

‡ Department of Economics, Brown University, Providence, RI

# **Abstract**

In this paper, we examine the determinants of Brazilian city growth between 1970 and 2000. We consider a model of a city, which combines aspects of standard urban economics and the new economic geography literatures. For the empirical analysis, we constructed a dataset of 123 Brazilian agglomerations, and estimate aspects of the demand and supply side as well as a reduced form specification that describes city sizes and their growth. Our main findings are that increases in rural population supply, improvements in inter-regional transport connectivity and education attainment of the labor force have strong impacts on city growth. We also find that local crime and violence, measured by homicide rates, impinge on growth. In contrast, a higher share of private sector industrial capital in the local economy stimulates growth. Using the residuals from the growth estimation, we also find that cities that better administer local land use and zoning laws have higher growth. Finally, our policy simulations show that diverting transport investments from large cities toward secondary cities does not provide significant gains in terms of national urban performance.

World Bank Policy Research Working Paper 3723, September 2005 _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,
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|---|---|---|---|---|---|---|--
malnutrition, stunting and wasting rates for children under the age of 5. According to the Nepal Living Standard Survey 2010/11, 46.7 percent of children under the age of 5 are stunted, 15.1 percent are wasted, and 36.3 percent are underweight. Moreover, pregnant mothers have sub-optimal weight gain during pregnancy. The consequences are significant and long-term, ranging from increased neonatal mortality and morbidity to irreversible adverse physical and cognitive outcomes that harm health, productivity and economic growth (Pelletier, Frongillo Jr, Schroeder, and Habicht, 1995; Strupp and Levitsky, 1995; Alderman, Hoddinott, and Kinsey, 2006). The economic costs of – malnutrition are very high an estimated 2-3 percent of GDP (US$250 million 1