rafmacalaba/datause-encoder-data huggingface dataset:
Claessens, S., A. Demirguc-Kunt, and H. Huizinga. 2001. “How Does Foreign Entry Affect the Domestic Banking Markets? _Journal of Banking and Finance_ 25 (5): 891–911.

- Clarke, G. R., R. Cull, and Maria S. Martinez Peria. 2006. “Foreign Bank Participation and Access to Credit across Firms in Developing Countries.” _Journal of Comparative Economics_ 34 (4): 774–95.

- Cojocaru, L., S. Hoffman, and J. Miller. 2011. “Financial Development and Economic Growth in Transition Economies: Empirical Evidence from the CEE and CIS Countries.” Department of Economics Working Paper Series 22, University of Delaware, Wilmington.

- Cournede, B., and P. Slovik. 2011. “Macroeconomic Impact of BASEL III.” OECD Economics Department Working Papers 844, Organization for Economic Cooperation and Development, Paris.

- Cull, R., A. Demirguc-Kunt, and J. Morduch. 2011. “Does Regulatory Supervision Curtail Microfinance Profitability and Outreach?” _World Development_ 39 (6): 949–65.

- Cull, R., and L. Effron. 2005. “World Bank Lending and Financial Sector Development.” Policy Research Working Paper Series 3656, World Bank, Washington, DC.

- Curak, L. P. 2009. “Insurance Sector Development and Economic Growth in Transition Countries.” _Journal of International Research Publication: Economy & Business,_ 3, 99–112.

- Dabos, M. P., and E. R. Gantman. 2010. “The Fading Link? A New Empirical Analysis of the Relationship between Financial Development and Economic Growth.” Working Papers 2010-013, Becker Friedman Institute for Research in Economics, Chicago, IL.

- Das, U. S., M. Quintyn, and K. Chenard. 2004. “Does Regulatory Governance Matter for Financial System Stability? An Empirical Analysis.” IMF Working Papers 04/89, International Monetary Fund, Washington, DC.

- Davis, E. 2000. “Implications of the Growth of Institutional Investors for the Financial Sectors.” Technical report, Discussion Paper PI-0001, The Pensions Institute, London.

- Davis, E. and Y. Hu. 2008. “Does Funding of Pensions Stimulate Economic Growth?” _Journal of Pensions Economics and Finance_ 7 (2): 221–49.

- De Gregorio, J., and P. E. Guidotti. 1995. “Financial Development and Economic Growth.” _World Development_ 23 (3): 433–48.

- De Haan, J., and C. T. Shehzad. 2009. “Financial Reform and Banking Crisis.” CESifo Working Paper Series 2870, Center for Economic Studies and Ifo Institute, Munich.

- Demirguc-Kunt, A. and Detragiache, E. 1997. “The Determinants of Banking Crises: Evidence from Industrial and Developing Countries.” Policy Research Working Paper Series 1828, World Bank, Washington, DC.

- ———. 2002. “Does Deposit Insurance Increase Banking System Stability? An Empirical Investigation.” _Journal of Monetary Economics_ 49 (7): 1373–1406.

- ———. 2011. “Basel Core Principles and Bank Soundness: Does Compliance Matter?” _Journal of Financial Stability_ 7 (4): 179–90.

- Demirguc-Kunt, A., E. Detragiache, and T. Tressel. 2008. “Banking on the Principles:

31
from new employment opportunities. Meanwhile, the non-working or economically inactive poor gain from increased public and private transfers.

Figure 5. Welfare and the Labor Market: A Simple Framework <!-- Start of picture text --> Growth Opportunities<br>Country policies and<br>Country policies and nditions<br>: Education<br>Infrastructure<br>Labor Market Political economy<br>New Productivity - Public/Private Public/Private Redistribution of assets<br>Employment Employment E and wages mployment transfers transfers<br>Country policies and<br>Household and Conditions<br>group characteristics: : Education<br>Health, Education, Infrastructure<br>Gender, Political economy<br>Dependency Redistribution of assets<br>Outcomes for the Poor<br><!-- End of picture text --> Source: Adapted from “Pro-Poor Growth” (World Bank 2005).

Both access to these opportunities and their scale are mitigated by government policies, geographic location, gender and other demographic characteristics. Welfare outcomes at the individual level are also driven by the labor market activities of other members of individuals’ respective household. To understand changes in the welfare of the poor, it is critical to consider improvements or deteriorations in their wage levels, their employment opportunities, and the transfers they receive, along with changes in other mitigating factors. In BH case, we can also speculate on the role of recent changes in the first two channels (wage and employment opportunities), if any, in explaining recent poverty outcomes.

What do we know of the recent evolution of poverty? In BH, the poverty headcount is essentially unchanged between 2001 and 2004. The poverty headcount has fallen from 19.5 percent to 17.8 percent, although the reduction in poverty appears to be statistically insignificant. When we restrict the analysis to just the panel observations, the poverty headcount is essentially unchanged at 17.7 percent.

The unemployed generally face the highest incidence of poverty, compared to the employed and those out of the labor force, although it has decreased slightly over time (Figure 6). In particular, the incidence of poverty among the unemployed is 31 percent 14
(2017) and uses the average foreign-currency long-term sovereign debt rating by Fitch Ratings, Moody’s, and Standard and Poor’s. A dummy variable approach is used, where is set equal to one if the average rating at time _t_ is below investment grade and 0 otherwise. Consequently, the tt state-dependent impulse response function becomes a function of the dummy variable and the II endogenous variables: �αA,i,h + xi,tδA,h + shocki,tβA,h�+ yyrr,tt+h)�α= IIB,i,htt + xB,i,tδh + shocki,tβB,h�+ μ tt rr,tt+h **2.3 Modeling financial crisis probability** (1 −II Finally, the analysis explores how different U.S. interest rate shocks shape the probability of financial crises in EMDEs. To that end, it uses a logit model as in Kose et al. (2021) to assess the impact of different underlying shocks on the probability of crisis in EMDEs over the past 50 years. This is estimated using annual data from 1985 to 2018. Crisis events are based on Laeven and Valencia (2020) codified to 2017, and extended in Kose et al. (2021), and encompass sovereign debt, banking, and currency crises.

The model is estimated as: = β<sup>′</sup> + μ + ε where is a binary variable of banking, currency, or sovereign debt crises for country YYrr,tt XXrr,tt−1 rr rr,tt _i_ in year _t_ taking the value of 1 if a crisis occurred; is a vector of determinants of crisis including the rr,tt yy real, inflation, and reaction shocks as well as other control variables; μ captures unobserved rr,tt−1 country heterogeneity; and ε are the residuals. The baseline specification is a panel logit model XX rr with random effects, as the Hausmann test suggests that the random effects model is appropriate rr,tt for debt and banking crises. For robustness, the appendix presents results for a probit model with random effects (table A6) and logit model with fixed effects (table A7).

# **3.** **<u>Data</u>**

# **3.1 Identification of U.S interest rate shocks**

The data included in the VAR model used to decompose U.S. interest rate shocks are provided in table A1. The table indicates the transformation used in the model and the data source. The model includes four variables and is estimated on monthly data from February 1982 to September 2022. The variables include 2-year and 10-year yields on U.S. Treasury bonds at a constant maturity (figure 1A). Due to the secular decline in U.S. interest rates over the past four decades, the data are transformed to be stationary using first differences, as the focus is on shocks over the business cycle. Equity prices are measured by the S&P 500 composite index and transformed to percent 7
results show that deposit rates are not higher in countries with higher intermediation spreads. In contrast, nominal (and real) lending rates are. The wedge between nominal and real lending rates is also higher for countries with high spreads suggesting that they suffer from weaknesses in the macro-fiscal environment (Figure 5B, 5C, and 5D).

As expected, intermediation spreads are closely aligned with net interest margins. But the link is weaker in countries with higher spreads, perhaps due to developmental challenges which lead to risk mispricing and defaults (Figure 5B). The NIM is smaller in countries with higher spreads. For example, in the 5<sup>th</sup> quintile, spreads are almost twice as large as the NIM. Given that deposit rates are not significantly higher in the 5<sup>th</sup> quintile, this suggests that banks are not able to sustain adequate levels of interest income, possibly due to defaults or unsuccessful restructuring procedures.

# **<mark>Box 3: A Historical Perspective on High Interest Rates and Rate Spreads in Brazil</mark>**

Brazil is among one of the most developed emerging economies, having achieved a sound macroeconomic policy framework. However, its financial sector continues to face many challenges including high interest rates and spreads. Brazil has had a long history of high and volatile inflation. To contain inflation, Brazil implemented an inflation targeting regime in 1999 which significantly reduced it. Nonetheless, high lending interest rates and spreads persisted which concerns Brazilian policy makers. Notwithstanding their high levels, Brazilian interest rates have fallen from 78% on average in 1997 to 46% in 2017. Similarly, interest rate spreads have fallen from 54 percentage points to 36 percentage points in the same period.

## **What drives high interest rates and spreads?**

The literature on the drivers of interest rates and interest rate spreads in Brazil is mixed. Typically, the findings reflect macroeconomic and microeconomic determinants, with the importance of each varying by study.<sup>5</sup> The main drivers found in that literature are: <u>Macroeconomic factors: Brazil’s history of high and volatile inflation and macroeconomic fundamentals</u> (e.g., low savings and fiscal risk) are often cited as the major contributors to high interest rates. The low level of savings (consistently below 20%), combined with fiscal financing needs, have crowded out private credit markets. In addition, due to the history of high inflation, there is perhaps a tendency to overestimate medium-term inflation risk. This fosters the tendency to borrow at very high nominal rates which have made private financial intermediation mostly short term. This has constrained financing for longer-term capital investment and has led to high spreads.

> 5 Some studies such as De la Torre et al. (2006) and Afanasieff, Lhacer and Nakane (2002) find that macroeconomic factors are the main drivers of high interest rates and interest rates spread in Brazil, while Jorgensen and Apostolou, (2013) find that microeconomic factors are more important.

12
- 12* Marketing _Você faz alguma pesquisa para saber a satisfação dos clientes?_ Do you conduct customer satisfaction surveys?

- 13* Marketing _Você planeja ações para promover e divulgar seus produtos e serviços?_ Do you engage in marketing campaigns?

- 14 Marketing _Sua empresa oferta novos produtos/ serviços para seus clientes? (Observa critérios para escolha dos produtos e teste dos produtos novos)_ Do you offer new products or services to your clients (purposefully developing and testing new products)?

- 15* Marketing _Você avalia seus concorrentes para saber o que deve melhorar?_ Do you assess your competitors to find out how you can do better?

- 16 Strategic _Você planeja os objetivos que deseja alcançar, tendo alguma forma de registro de_ Planning _onde quer chegar?_ Do you strategically set and plan your goals?

- 17* Strategic _Você tem seus objetivos e metas escritos e bem definidos?_ Planning Are your objectives and goals written down and clearly defined?

- 18* Strategic _Você toma nota das decisões e resultados de seu planejamento, observando_ Planning _situações em que houve resultados diferentes dos que você queria, para aprimorar o que deu certo e não repetir erros do passado?_

- Do you keep track of decisions and results of your planning, paying attention to situations where the results were different than desired, to gauge what went well and which errors not to repeat?

- 19 Strategic _Existem ações com prazos definidos para que os objetivos planejados pela_ Planning _empresa para o futuro possam ser alcançados?_ Have you defined concrete actions with deadlines to help reach the firm’s goals?

- 20* Organization _Você possui um controle de quem são os fornecedores de seus produtos e prestadores de serviço, facilitando sua pesquisa de preços?_ Do you keep a register of suppliers and service providers for your products to help research prices?

- 21 Organization _Os documentos importantes de sua empresa e contas estão bem organizados?_ Are your important documents and accounts well organized?

- 22 Organization _As atividades realizadas regularmente possuem um procedimento escrito de como elas devem ser feitas?_

- Do you have written instructions for how frequently occurring tasks should be executed?

- 23 Organization _A organização da sua empresa permite que você trabalhe de maneira eficiente e ágil?_

28
||_Pan_|_el (c): Bene_|_fits by Emplo_|_yment Type_|||
|---|---|---|---|---|---|---|
|Go|vernment e<br>%|mployees|Private em<br>%|ployees|Casual w<br>%|orkers<br>|
|Un|weighted|Weighted<br>|Unweighted|Weighted|Unweighted|Weighted|
|Written|90.8|91.9|23.8|25.0|1.6|1.6|
|contract|||||||
|Verbal|4.6|5.0|48.7|48.2|54.4|51.3|
|Contract|||||||
|Sick leave|98.4|98.4|87.7|87.8|67.9|63.7|
|Casual leave|96.0|96.6|61.1|61.3|29.5|26.0|
|(paid|||||||
|vacation)|||||||
|Provident|91.5|92.9|12.3|12.7|0.0|0.0|
|Fund|||||||
|Termination|70.6|73.5|44.5|45.3|19.5|14.4|
|i|||||||
|notce||_Panel (d)_<br>MonthlyE|_: Monthly In_<br>arningsin 2016|_come_<br>Taka(USD i|nparentheses)||
|Employment Type|25%|percentile|50% p|ercentile|75% pe|rcentile|
||Unweighted|<br>Weighted|<br>Unweighted|Weighted|Unweighted|Weighted|
|Government|15,000|<br>15,000|<br>25,000|23,000|30,000|30,000|
|employee|(191)|(191)|(319)|(293)|(383)|(383)|
||6,000|6,913|8,000|9,000|15,000|15,000|
|Private employee|(77)|(88)|(102)|(115)|(191)|(191)|
||3,500|6,000|7,500|7,500|10,500|12,000|
|Casual worker|(45)|(77)|(96)|(96)|(134)|(153)|
|Self-employed|6,500|7,500|11,500|15,000|15,000|20,000|
|alone/with family|(83)|(96)|(147)|(191)|(191)|(255)|
|Self-employed (with|15,000|<br>15,000|<br>20,000|20,000|30,000|30,000|
|<br>non-family)|(191)|(191)|(255)|(255)|(383)|(383)|
||2,500|3,500|7,500|7,500|15,000|15,000|
|Familyworker|(32)|(45)|(96)|(96)|(191)|(191)|

_Source_ : Authors’ analysis based on survey data.

_Note_ : Summary statistics for individuals in survey. Results are shown with and without sampling weights. In Panel (c), we only include wage workers who were able to provide an answer. In Panel (d), if respondents did not provide an exact monthly income, but did indicate the bin into which their income fell, we used the median value from the bin for their income.

43
WPS3407

# **STATE OWNERSHIP: A RESIDUAL ROLE?**<sup>**1**</sup>

## **Enrico Perotti**

Univerity of Amsterdam

### World Bank Policy Research Working Paper 3407, September 2004

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

* The Global Corporate Governance Forum has commissioned a series of discussion papers that will help improve the understanding of corporate governance reform in developing countries. These papers discuss a number of issues raised by various regional corporate governance research network meetings organized by the Forum to support corporate governance research and policy discussion in developing countries. Comments on these papers are welcome and should be sent to the authors and copied to the Forum (cgsecretariat@worldbank.org). The full series of discussion papers can be found on the Forum’s website at http:www.gcgf.org.

1 I am grateful to Erik Feijen for excellent research assistance and Stijn Claessens for useful discussion.

- 1 -
22

# Table 7: PRICE AND QUALITY CHANCES: BILATERAL INDICES (Average Annual Orowth Ratee) US Weights

|||<br>P<br>|Tornqvi<br> <br>rles<br>Ind|_<br>t J<br>ex|Pr|Tornqv<br>ice Ind|ist<br>ex<br>2/|
|---|---|---|---|---|---|---|---|
||Pero0d<br>|<br>US|JAP|FRO|US|JAP|FRO|
|Rostrlctedk/<br>Commodities<br>(21Categorles)|R<br>U|.188<br>.009|.114<br>.06|.160<br>.01.|.140<br>.010|.172<br>.089|.188<br>-.030|
|All Co_inoditlesd<br>(26categories)|R<br>I<br>u<br>I|<br>.116<br> <br>.0o3|.180<br>.038|.116<br>.052|.121<br>.034|.169<br> <br>.013|<br>.162<br>.006|

* U a unrestricted period 19 R a restricted period

b/ categories restricted by the US OMA **(see** appendix for definition*) S/ all categories excluding parte, wood and cork, gaiters **(see** appendix for deflnitions) I/ Annual (calendar year) _gf_ Quarter 3 - quarter 2 year
across the country averages for the 54 countries that have at least one university present in all six rankings are also high, ranging from 0.61 to 0.91 (Table 3).

**Table 2 – Partial correlation across US universities (n=98)**

||Ov.<br>THE|Ov.<br>QS|RTC<br>ARW<br>U|Ov.<br>CWUR|Ov.<br>US<br>News|Ov.<br>UMR||RTC<br>THE|RTC<br>QS|RTC<br>ARW<br>U|Ov.<br>CWU<br>R|Ov.<br>US<br>News|RTC<br>UMR|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Overall<br>THE|1||||||RTC<br>THE|1||||||
|Overall<br>QS|0.9728|1|||||RTC<br>QS|0.9544|1|||||
|RTC<br>ARWU|0.8762|0.8895|1||||RTC<br>ARWU|0.8771|0.8735|1||||
|Overall<br>CWUR|0.9375|0.9492|0.9396|1|||Overall<br>CWUR|0.9384|0.9437|0.9396|1|||
|Overall<br>US<br>News|0.9395|0.9350|0.9381|0.9620|1||Overall<br>US<br>News|0.9386|0.9246|0.9381|0.9620|1||
|Overall<br>UMR|0.6886|0.7374|0.6486|0.7187|0.7274|1|RTC<br>UMR|0.7230|0.7666|0.6412|0.7246|0.7476|1|

**Table 3 – Partial correlation across country averages (n=54)**

||Ov.<br>THE|Ov.<br>QS|RTC<br>ARW<br>U|Ov.<br>CWUR|Ov.<br>US<br>News|Ov.<br>UMR||RTC<br>THE|RTC<br>QS|RTC<br>ARW<br>U|Ov.<br>CWU<br>R|Ov.<br>US<br>News|RTC<br>UMR|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Overall<br>THE|1||||||RTC<br>THE|1||||||
|Overall<br>QS|0.9044|1|||||RTC<br>QS|0.8833|1|||||
|RTC<br>ARWU|0.8514|0.8587|1||||RTC<br>ARWU|0.8436|0.8533|1||||
|Overall<br>CWUR|0.8741|0.8443|0.8461|1|||Overall<br>CWUR|0.8819|0.8427|0.8461|1|||
|Overall<br>US<br>News|0.9272|0.8220|0.7975|0.8961|1||Overall<br>US<br>News|0.9144|0.7962|0.7975|0.8961|1||
|Overall<br>UMR|0.7453|0.7711|0.6977|0.7122|0.6387|1|RTC<br>UMR|0.7354|0.7231|0.7210|0.7125|0.6138|1|

A positive correlation also exists between the quality scores and the income level of countries (see Figure 1). Singapore is ranked as the country with the highest quality score in the THE, QS and ARWU rankings, while for the CWUR ranking the highest ranked country is the Netherlands.

9
Eaton, J., and S. Kortum. 1999. “International Technology Diffusion: Theory and Measurement.” _International Economic Review_ 40 (3): 537–70.

Eaton, J., and S. Kortum. 2002. “Technology, Geography, and Trade.” _Econometrica_ 70 (5): 1741–79.

Feenstra, R., R. Lipsey, H. Deng, A. Ma, and H. Mo. 2005. “World Trade Flows: 1962– 2000.” NBER Working Paper 11040. Cambridge, Mass.: National Bureau of Economic Research.

Feenstra, R., and A. Rose. 2000. “Putting Things in Order: Trade Dynamics and Product Cycles.” _Review of Economics and Statistics_ 82 (3): 369–82.

Fieler, A.C. 2011. “Nonhomotheticity and Bilateral Export Trade: Evidence and a Quantitative Explanation.” _Econometrica_ 79 (4): 1069–101.

Foley, C.F., and W. Kerr. 2013. “Ethnic Innovation and U.S. Multinational Firm Activity.” _Management Science_ 59 (7): 1529–44.

Golub, S., and C. Hsieh. 2000. “Classical Ricardian Theory of Comparative Advantage Revisited.” _Review of International Economics_ 8 (2): 221–34.

Gould, D. 1994. “Immigrant Links to the Home Country: Empirical Implications for US Bilateral Trade Flows.” _Review of Economics and Statistics_ 76 (3): 500–18.

Hakobyan, S., and J. McLaren. 2016. “Looking for Local Labor Market Effects of NAFTA.” _Review of Economics and Statistics_ 98 (4): 728–41.

Hall, B., A. Jaffe, and M. Trajtenberg. 2001. “The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools.” NBER Working Paper 8498. Cambridge, Mass.: National Bureau of Economic Research.

Harrigan, J. 1997. “Technology, Factor Supplies, and International Specialization: Estimating the Neoclassical Model.” _American Economic Review_ 87 (4): 475–94.

Head, K., and J. Reis. 1998. “Immigration and Trade Creation: Econometric Evidence from Canada.” _Canadian Journal of Economics_ 31 (1): 47–62.

Helpman, E., and P. Krugman. 1985. _Market Structure and Foreign Trade._ Cambridge, Mass.: MIT Press.

Hummels, D., and P. Klenow. 2005. “The Variety and Quality of a Nation’s Exports.” _American Economic Review_ 95 (3): 704–23.

Hunt, J., and M. Gauthier-Loiselle. 2010. “How Much Does Immigration Boost Innovation?” _American Economic Journal: Macroeconomics_ 2 (2): 31–56.

Hunter, L. 1991. “The Contribution of Non-Homothetic Preferences to Trade.” _Journal of International Economics_ 30 (3): 345–58.

Hunter, L., and J. Markusen. 1988. “Per Capita Income as a Determinant of Trade.” in R. Feenstra, ed., _Empirical Methods for International Trade._ Cambridge, Mass.: MIT Press.

Irwin, D., and P. Klenow. 1994. “Learning by Doing Spillovers in the Semiconductor Industry.” _Journal of Political Economy_ 102: 1200–27.

Keller, W. 2002. “Geographic Localization of International Technology Diffusion.” _American Economic Review_ 92 (1): 120–42.

Kerr, W. 2008. “Ethnic Scientific Communities and International Technology Diffusion.” _Review of Economics and Statistics_ 90 (3): 518–37.

- ——— . 2007. “The Ethnic Composition of US Inventors.” HBS Working Paper 08-006.

- Boston, Mass.: Harvard Business School.