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Who Wants to be an AERC Millionaire

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Test your impact evlaution knowledge with our quiz from the Transfer Project Impact Evaluation Training with AERC in Nairobi in July 2019.

Published in: Government & Nonprofit
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Who Wants to be an AERC Millionaire

  1. 1. Who Wants To Be A AERC Millionaire?
  2. 2. Rules 1. There are 17 questions with 4 multiple choice options, you need to guess the correct answer 2. The questions will be read twice, then you have 30 seconds to record the correct answer 3. You must work with your group – each group has one judge/score keeper 4. No cheating, you cannot ask a trainer or ask another group what the correct answer is 5. The team with the most points at the end wins a prize (no, you cannot know what this is before the end of the game)
  3. 3. Example question
  4. 4. Where are the trainers from? A Germany, USA, Tanzania, Ghana B Ghana, Tanzania, Ecuador, Italy, USA C India, USA, Ghana, Tanzania, Spain, Peru’ D Italy, Ghana, Peru’, Tanzania Time’s Up!!!
  5. 5. Where are the trainers from? A Germany, USA, Tanzania, Ghana B Ghana, Tanzania, Ecuador, Italy, USA C India, USA, Ghana, Tanzania, Spain, Peru’ D Italy, Ghana, Peru’, Tanzania
  6. 6. Question 1
  7. 7. USD100,000
  8. 8. In impact evaluation, the counterfactual is… A The outcome of the control or comparison group B The outcome of the treatment group at baseline C The outcome of the treatment group in the absence of the program D The outcome of the control group had they received treatment Time’s Up!!!
  9. 9. In impact evaluation, the counterfactual is… A The outcome of the control or comparison group B The outcome of the treatment group at baseline CThe outcome of the treatment group in the absence of the program D The outcome of the control group had they received treatment
  10. 10. Question 2
  11. 11. USD100,000
  12. 12. Spillover is when… A You spill your tea onto the table B The controls obtain the treatment C The intervention affects the control group D A different program affects the treatment group Time’s Up!!!
  13. 13. Spillover is when… A You spill your tea onto the table B The controls obtain the treatment C The intervention affects the control group D A different program affects the treatment group
  14. 14. Question 3
  15. 15. USD100,000
  16. 16. Contamination is when… A The drinking water is dirty B The control obtains the treatment C When those assigned to treatment in practice do not receive it D You cough without covering your mouth Time’s Up!!!
  17. 17. Contamination is when… A The drinking water is dirty B The control obtains the treatment C When those assigned to treatment in practice do not receive it D You cough without covering your mouth
  18. 18. Question 4
  19. 19. USD100,000
  20. 20. External validity is… A When someone external to our organization tells you that your impact estimate is valid B The clothes you are wearing are appropriate for the occasion C The result is applicable to other settings D The outside temperature is good for field work Time’s Up!!!
  21. 21. External validity is… A When someone external to our organization tells you that your impact estimate is valid B The clothes you are wearing are appropriate for the occasion C The result is applicable to other settings D The outside temperature is good for field work
  22. 22. Question 5
  23. 23. USD200,000
  24. 24. In oversubscription randomization, intervention is given only to a subset of eligible participants because… A This approach ensures that a valid control group is present B It is a common knowledge that not everybody takes the intervention even when it is offered C Programs usually do not have enough resources to provide intervention to all eligible participants immediately D People who apply late do not deserve the program in the first place Time’s Up!!!
  25. 25. In oversubscription randomization, intervention is given only to a subset of eligible participants because… A This approach ensures that a valid control group is present B It is a common knowledge that not everybody takes the intervention even when it is offered C Programs usually do not have enough resources to provide intervention to all eligible participants immediately D People who apply late do not deserve the program in the first place
  26. 26. Question 6
  27. 27. USD200,000
  28. 28. In propensity score matching we assume that… A Program participation is determined by observables B Program participation is determined by unobservable C The region of common support is increasing as the propensity score increase D The likelihood of participating in the program increases as the score decreases Time’s Up!!!
  29. 29. In propensity score matching we assume that… A Program participation is determined by observables B Program participation is determined by unobservable C The region of common support is increasing as the propensity score increase D The likelihood of participating in the program increases as the score decreases
  30. 30. Question 7
  31. 31. USD200,000
  32. 32. The balancing property in PSM ensures that… A Sample observations of participants and nonparticipants are balanced in some predefined way B Allocation of project resources is balanced in different stages of the projects C Means of control variables are the same for participants and nonparticipants whose propensity scores are close D The sample sizes in the treatment and comparison groups are equal Time’s Up!!!
  33. 33. The balancing property in PSM ensures that… A Sample observations of participants and nonparticipants are balanced in some predefined way B Allocation of project resources is balanced in different stages of the projects C Means of control variables are the same for participants and nonparticipants whose propensity scores are close D The sample sizes in the treatment and comparison groups are equal
  34. 34. Question 8
  35. 35. USD200,000
  36. 36. When can we use Regression Discontinuity Analysis (RDA)? A When you get married B When the slopes of the functional for are linear C When there is a discontinuity between outcome and score/rating variable D When the cut-off point is exogenous Time’s Up!!!
  37. 37. When can we use Regression Discontinuity Analysis (RDA)? A When you get married B When the slopes of the functional for are linear C When there is a discontinuity between outcome and score/rating variable D When the cut-off point is exogenous
  38. 38. Question 9
  39. 39. USD400,000
  40. 40. “Timing of effects” is a potential threat to validity that refers to… A The year when the program started B The year when you conduct the evaluation C The time needed to run an impact model in Stata D The time needed for the intervention to affect the outcome Time’s Up!!!
  41. 41. “Timing of effects” is a potential threat to validity that refers to… A The year when the program started B The year when you conduct the evaluation C The time needed to run an impact model in Stata D The time needed for the intervention to affect the outcome
  42. 42. Question 10
  43. 43. USD400,000
  44. 44. The main reason for using a longitudinal data model in impact evaluation is… A To use data the program has been accumulating in its routine information system over time B Because it is more sexy C To deal with potential endogeneity of the program variable D To increase the precision of your impact estimates Time’s Up!!!
  45. 45. The main reason for using a longitudinal data model in impact evaluation is… A To use data the program has been accumulating in its routine information system over time B Because it is more sexy C To deal with potential endogeneity of the program variable D To increase the precision of your impact estimates
  46. 46. Question 11
  47. 47. USD400,000
  48. 48. A difference-in-differences with fixed effects model is useful to address… A Endogeneity bias that comes from large standard errors B Endogeneity bias that comes from unobserved factors that changed between baseline and endline C Lack of precision that comes from small sample size D Endogeneity bias that comes from unobserved factors that do not change between baseline and endline Time’s Up!!!
  49. 49. A difference-in-differences with fixed effects model is useful to address… A Endogeneity bias that comes from large standard errors B Endogeneity bias that comes from unobserved factors that changed between baseline and endline C Lack of precision that comes from small sample size D Endogeneity bias that comes from unobserved factors that do not change between baseline and endline
  50. 50. Question 12
  51. 51. USD400,000
  52. 52. The design effect due to clustering is given by: DE= 1+ρ(m-1). What does the m in the design effect equation represent? A The total number of cluster B The average cluster size C The Intra-cluster correlation coefficient D The minimum detectable difference Time’s Up!!!
  53. 53. The design effect due to clustering is given by: DE= 1+ρ(m-1). What does the m in the design effect equation represent? A The total number of cluster B The average cluster size C The Intra-cluster correlation coefficient D The minimum detectable difference
  54. 54. Question 13
  55. 55. USD800,000
  56. 56. Which of these is NOT a criticism of RCTs? A They are expensive to execute B They often lack external validity C They are unethical D They cannot be easily understood Time’s Up!!!
  57. 57. Which of these is NOT a criticism of RCTs? A They are expensive to execute B They often lack external validity C They are unethical D They cannot be easily understood
  58. 58. Question 14
  59. 59. USD800,000
  60. 60. A 50-50 split of treatment and control is recommended because… A It is the most ethical design B It reduces the bias of the treatment effect C It reduces the variance of the treatment effect D It mitigates the effects of cluster-based sampling Time’s Up!!!
  61. 61. A 50-50 split of treatment and control is recommended because… A It is the most ethical design B It reduces the bias of the treatment effect C It reduces the variance of the treatment effect D It mitigates the effects of cluster-based sampling
  62. 62. Question 15
  63. 63. USD800,000
  64. 64. Adding covariates (additional X variables) to your regression… A Can improve the efficiency (variance) of your estimate B Can reduce the bias of your estimate if X is correlated with T C Can increase the bias of your estimate if T affects X D All of the above Time’s Up!!!
  65. 65. Adding covariates (additional X variables) to your regression… A Can improve the efficiency (variance) of your estimate B Can reduce the bias of your estimate if X is uncorrelated with T C Can increase the bias of your estimate if T affects X D All of the above
  66. 66. Question 16
  67. 67. USD800,000
  68. 68. What is the meaning of this expression: E(Y1/P=1) – E(Y0/P=1) ? A The selection bias B The counterfactual C The ATT D A measure of endogeneity Time’s Up!!!
  69. 69. What is the meaning of this expression: E(Y1/P=1) – E(Y0/P=1) ? A The selection bias B The counterfactual C The ATT D A measure of endogeneity
  70. 70. JACKPOT
  71. 71. USD1,000,000
  72. 72. What is the meaning of this expression: E(Y0/P=0) – E(Y0/P=1) ? A The selection bias B The counterfactual C The ATT D A measure of endogeneity Time’s Up!!!
  73. 73. What is the meaning of this expression: E(Y0/P=0) – E(Y0/P=1) ? A The selection bias B The counterfactual C The ATT D A measure of endogeneity
  74. 74. And the winner is: Drum roll. . .

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