Bob Barsky Miles Kimball Noah Smith

1. Bob Barsky Miles Kimball Noah Smith

2. Two Polar Views of Consumer Confidence in Macroeconomics • Information • Animal Spirits • Issues in Cognitive Psychology • Effect of affect on judgment • Degree of persistence in “happiness shocks”

3. Confidence shocks reflect genuine news about relevant future variables Link between confidence and economic behavior not causal

4. “Animal Spirits” View • Important movements in confidence that are exogenous to the macroeconomy • “Confidence shocks” have causal effects on economy

5. Do changes in measured confidence reflect information or fluctuations in pure sentiment? • Is the relationship between confidence and subsequent economic outcomes causal? • What might “explain” variation in confidence? • Time-series variation • Cross-sectional variation at a point in time • Individual innovations in panel data

6. The Index of Consumer Sentiment • Pago: “Would you say that you (and your family living there) are better off or worse off financially than a year ago?” • Pexp: “Do you think that a year from now you (and your family living there) will be better off financially, or worse off, or just about the same as now?” • Bus12: “Do you think that during the next 12 months we’ll have good times financially, or bad times, or what?” • Bus5: “Which would you say is more likely – that in the country as a whole we’ll have continuous good times during the next 5 years or so, or that we will have periods of widespread unemployment and depression, or what?” • Dur: “Generally speaking, do you think now is a good time or a bad time for people to buy major household items?”

7. Three Dimensions • National vs. Personal • Expectations vs. Judgments about the Past and Present • Clearly Defined or Not

8. “Now turning to business conditions in the country as a whole: Do you think that over the next five years we will have mostly good times, or mostly bad times with periods of widespread unemployment and depression, or what?”

9. Time series co-variation in happiness measures and the responses to the various confidence questions How is variation in confidence answers across individuals related to the happiness individual effect? How do changes in each individual’s answer to the confidence questions between the initial interview and the reinterview covary with happiness?

10. Now think about the past week and the feelings you have experienced. Please tell me if each of the following was true for you much of the time this past week: • Much of the time during past week, you felt you were happy. (Would you say yes or no?) • (Much of the time during the past the week,) you felt sad. (Would you say yes or no?) • (Much of the time during the past week,) you enjoyed life. (Would you say yes or no?) • (Much of the time during the past week,) you felt depressed. ( Would you say yes or no?) (average survey time=36 seconds)

11. Negligible Serial Persistence in Daily Average Happiness note: some days have only 1 obs

14. (Green is Happiness)

16. Negligible variation even over this long period Strikingly, national mood was not depressed during 1970s “malaise” period nor ebullient in late 1980s or 1990 Celebrated relationship between happiness and inflation, unemployment apparently not first order

17. Interpretation:

18. To get intuition about the likely size of causal effects of changes in expectations on happiness at the 6 month frequency, let’s look at the effect of objective circumstances on happiness at the 6 month frequency. Effect of household income on happiness

20. National News

21. Personal News

22. Econometric Issues for Later • Discreteness of the components of the happiness index. • Differential sensitivity of the components of the happiness index to the underlying latent variable. • Plan: Use an approach similar to Kimball, Sahm and Shapiro, “Imputing Risk Tolerance from Survey Responses” JASA (forthcoming) and NBER 13337

23. Measurement Model

25. Component Impulse Responses (National News)

26. Component Impulse Responses (Personal News)

27. Measurement Model

28. Structural Model

29. Structural Model: Comments

30. Measurement Model for Happiness Index

31. Measurement Model for Average Daily Happiness Index of Others NOTE: All components depend on the date because the set of “others” depends on the date.

32. Identifying N

33. Identifying N

34. Persistence of national happiness

35. Persistence of national happiness

36. Effect of national happiness

37. Identifying P 1=1st obs date, 2=2d obs date; cross-question covariance: rq

38. Identifying P

39. Identifying P

40. Identifying P

41. The Correction Factor for P since and

42. Covariances of Happiness Responses across Contact Dates [Average of All]/[Average off Diagonal] = 1.07

43. Identifying T 1=1st obs date, 2=2d obs date

44. Identifying T 1=1st obs date, 2=2d obs date; cross-question covariance: rq

45. Identifying T

46. Identifying T

47. The Correction Factor for T since and

48. Covariances of 6-month changes in individual responses to happiness questions Average on Diagonal/Average off Diagonal = 1.400 (Omitting ENJOYLIFE: 1.421)

49. Bus5 (national, future, ρ=.446)“Which would you say is more likely – that in the country as a whole we’ll have continuous good times during the next 5 years or so, or that we will have periods of widespread unemployment and depression, or what?” Persistent Effect: .396 (t=11.26) Transitory Effect: .011 (t=0.57) Bus12 (national, future, ρ=.422)“Do you think that during the next 12 months we’ll have good times financially, or bad times, or what?” Persistent Effect: .243 (t=6.91) Transitory Effect: .066 (t=3.24)