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Data Dive - World Bank and DSDC

Data Dive - World Bank and DSDC

831046b797b2f467c4ca340b0f8a8868?s=128

Data Science DC

October 07, 2019
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  1. FINAL PRESENTATION

  2. GROUP # 1 MEMBERS (Twitter @datadrivenangel) - William Angel (Twitter

    @guynzeribe) - Guy Nzeribe (Github @thomasneil) - Neil Alex Github @nbroekman Nathaniel Broekman @avsolatorio - Aivin Solatorio Ryan Ritchey (Github @DoshiHarsh) - Harsh Doshi
  3. Conflict and Spending: Data is hard Focus- Asia. 5 countries

    that have cultural similarity and geographical proximity- Bangladesh, India, Sri Lanka, Nepal, Pakistan. • Fundamental Question - What is the relationship between conflict intensity and spending? Data: • The World Bank datasets (various indicators) • The Armed Conflict Location & Event Data Project (ACLED) -Conflict events, Conflict event types and fatality counts as a proxy for conflict intensity https://github.com/Nosferican/WorldBankDataDive2019ConflictSpendingAsia
  4. Political Stability vs Fatalities per million

  5. None
  6. Fatality related event trends and projections

  7. ThANKS! Current results- an aggregated dataset that pulls together data

    from several world bank sources, as well as per capita fatalities by event type.
  8. GROUP # 2 MEMBERS Smarter Lending Shijie Shi shishijie.vu@gmail.com Richard

    Johnson richard93johnson@gmail.com Jiawen Peng wstcagn@gmail.com Munkhjargal Tsogtsaikhan tsmj2013@gmail.com Max Kao KAOHAOTUN@GMAIL.COM Fernando Aguilar Islas f.aguislas@gmail.com Emefa Agodo e.Agodo@GMAIL.com
  9. Objective: Find risk factors for loan performance Challenge/Question: Is good

    governance related to lower risk of default? How do other factors affect the risk of default?
  10. How do other factors affect the risk of default?

  11. Is good governance related to lower risk of default?

  12. Is good governance related to lower risk of default?

  13. How do other factors affect the risk of default?

  14. How do other factors affect the risk of default?

  15. ThANK YOU!

  16. Group 3: Scaling up Financing for Human Capital Youyou Huang

    youyouh511@gmail.com Meron Asfaha masfaha@alumni.emory.edu Tarak Nandi tnnandi@gmail.com Nitin Gupta gupta.nitin1@gmail.com Ali Akbarpour aliakbarpour.mba@gmail.com rikhi bose rikhi004@gmail.com tigist wubneh tigistaws@gmail.com Bruno Aleonard bruno.aleonard@stanfordalumni.org Anubhuti Mishra anubhuti87@gmail.com Yarou Xu yx160@georgetown.edu Fernando Aguilar f.aguislas@gmail.com
  17. Group 3: Scaling up Financing for Human Capital • Correlation

    of 0.81
  18. None
  19. Group 3: Scaling up Financing for Human Capital

  20. ThANKS! Group 3: Scaling up Financing for Human Capital

  21. Human capital GROUP # 4 MEMBERS Joe MCALLISTER - mcallister.94@osu.edu

    Anna - a.vasylytsya@fraym.io Jerome - jerome.doe00@gmail.com Ru Sun - ru.smiln@gmail.com Liu Cui- yayavivien@gmail.com Boon Lim
  22. Summary Statistics 2007 2017 GDP Per Capita (constant 2010 US$)

    15,247 15,437 Life Expectancy in years 69.27 72.53 Internet Usage - % of Population 25.55 55.25 Urban - % of Population 57.54 60.60 Education Spending - % of GDP 4.406 4.173
  23. Factors for GDP Working population and internet usage are the

    two factors that most significantly affected GDP. - Multiple-year panel data - % working population and internet usage in 2007 vs GDP in 2017 Significant positive relationship between GDP and life expectancy.
  24. Internet usage growth and GDP growth 2006-2016 Trend between internet

    access increase and growth increase is surprisingly slightly negative
  25. ThANKS!

  26. Group 5: MaGic 5 sabrina.khan@live.com- Sabrina Khan av_m@hotmail.com - Ann

    Vroom @ashby_roger - Roger Ashby DataSpider13@gmail.com - Laura Cutrer
  27. Smarter Lending How can multilateral financial institutions and other creditors

    better understand and predict the existence and scale risks of their borrowers, during, and after they lend money? Is good governance related to lower risk of default? How do other factors affect the risk of default? Caveat: We looked proportions of loan being defaulted rather than actual risk because it took us a while to define ‘risk’.
  28. 2015 Country Political Stability and Absence of Violence/Terrorism Governance Index

    (-2.5 to +2.5) Sovereign Default Amounts - 2015 - Source: Bank of Canada Database of Sovereign Defaults
  29. Default amount: External debt stocks (long term) - Principal repayment

    long term Default %: Principal repayment/External debt stocks The countries that seem to default on majority of their loan (i.e high default %) are struggling to repay relatively “smaller amount”.
  30. None
  31. ThANKS!

  32. GROUP # 6 MEMBERS @www.linkedin.com/in/meron-asfaha- Meron asfaha @www.linkedin.com/in/melissacirtain/ - Melissa

    C @https://www.linkedin.com/in/hanahanfi/ -Hana HAnfi @https://www.linkedin.com/in/erik-hasse/ - Erik Hasse @www.linkedin.com/in/zhian-anita-wang/ - Anita Wang @https://www.linkedin.com/in/RKRAIG/ - ROBERT KRAIG @https://www.linkedin.com/in/dominickegan/ -Dominick Egan @Https://google.com -Evgenia Pugacheva
  33. Financing for Human Capital Objective: Identify relationships between human development

    and its benefit for countries Our finding: Investment in education and female school enrollment matters for development
  34. Outcome: What is the relationship between female school enrollment and

    GDP across countries? *As female secondary school enrollment , fertility rate *As female secondary school enrollment , MMR *GDP Per Capita (PPP) increases with increasing female secondary school enrollment
  35. Determinants of secondary school enrollment for women ➔ Women who

    have fewer children have more time to invest in their education ➔ Takeaway from regression analysis: If Government spending on education increases by 1%, female secondary school enrollment increases by 1.1% *High fertility is associated with low GDP
  36. Time to Act is Now! BIG PICTURE: -Government spending in

    education has remained stagnant over the years for majority of regions -Need to invest in the education sector -Investments in family planning → lower fertility → higher female school enrollment → higher GDP
  37. ThANKS!

  38. GROUP # 7 MEMBERS Parker Garrison Derek Burk - burkx031@umn.edu

  39. GROUP # 7 MEMBERS Parker Garrison Derek Burk Team: “One

    Thing Leads to Another”
  40. Complementarity Economy building is gradual -- one job can unlock

    others.
  41. Does job X unlock job Y, or vice versa? Need

    to determine if it is a cause or effect.
  42. Sequence Mining: Temporal DB Make use of the temporal database.

  43. Results 611 spurs 11 611 spurs 111 611 spurs 234

    611 spurs 912 612 spurs 11 612 spurs 111 612 spurs 234 612 spurs 912 613 spurs 11 613 spurs 111 613 spurs 114 613 spurs 234 613 spurs 912 614 spurs 111 614 spurs 234 615 spurs 11 615 spurs 111 615 spurs 234 615 spurs 912 ...
  44. Botswana 1996, 2001, 2007 Copyright retained by authors.

  45. None
  46. ThANKS!

  47. GROUP # 8 MEMBERS Elena Gillis Javier Gonzalez Jiahao Xu

    Dominique Duval-Diop Ancil Crayton Erik Friesenhahn
  48. Get to Work! Understanding the Underlying patterns of Jobs and

    Growth
  49. Descriptive visualization tool to explore Global Jobs Indicators Database http://jiahaoxu.com/WorldBankDataDive/index.html

  50. KMeans Clustering - Using Growth Categories

  51. Results of PCA Laplacian Embeddings - Using Decomposed Growth Rates

  52. ThANKS!

  53. Contact Us Jiahao Xu - http://jiahaoxu.com Ancil Crayton - https://www.linkedin.com/in/ancilcrayton

    Dominique Duval-Diop - https://www.linkedin.com/in/dominiqueduvaldiop Javier Gonzalez - https://www.linkedin.com/in/javiergcas Elena Gillis - https://www.linkedin.com/in/elena-gillis-2570a984
  54. ThANKS!

  55. GROUP # 9&10 Members HeYu1993@gmail.com - KEVIN H(Y) SHU @musse32

    - Hamza musse @mamata6 - mamata donkena @nextwavegit - Fusheng Wei @ -Khurshid Alam
  56. Time Series Tracking of Unemployment

  57. Rudimentary R Shiny Dashboard of Bivariate Relationships • No correlation

    between the lending rate and the proportion of non-agricultural workers in a given occupation • Continuing to explore!
  58. ThANKS!

  59. GROUP # 11 MEMBERS @XXXXXXX - Janusz Wasiolek @XXXXXXX -

    Steven Porter @XXXXXXX - Jonathan Giguere @XXXXXXX - Manisha Gupta @XXXXXXX - Douglas Ogata
  60. Political attention surrounding conflicts? (Conflicts & Spending)

  61. Projects being awarded frequency increase with relating to political interest?

    Conflict source: ACLED Budget source: IATI Nigeria
  62. Yemen No political interest prior to 2005?

  63. Spike in foreign aid in Nigeria ~ 2006 Types of

    fatalities in Nigeria - Violence against civilian correlate to increase in funding?
  64. The article does this with respect to the notion of

    an issue-attention cycle of political attention to policy issues and the manner in which these are played out. Several stages of the cycle are identified and related to the post September 11 aftermath. The cycle suggests that a five stage pattern of policy attention will be followed: pre-problem stage, alarmed discovery and euphoric enthusiasm, realisation of the cost of significant progress, gradual decline of intense public interest and the post-problem stage. The model suggests that current adoption of post September 11 security measures will likely cease to find political support once the perceived terrorist threat receives less attention in the media and, related to this, the voting public. - C. Michael Hall (2002) Travel Safety, Terrorism and the Media: The Significance of the Issue-Attention Cycle, Current Issues in Tourism, 5:5, 458-466, DOI: 10.1080/13683500208667935
  65. ThANKS!

  66. DATA DIVE 4 DEVELOPMENT #DATA4DEV