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The Dynamics of Happiness: Evidence from Daily Panel Data

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1 The Dynamics of Happiness: Evidence from Daily Panel Data
Miles Kimball, Fumio Ohtake and Yoshiro Tsutsui RA’s: Yuki Kosaka and Noah Smith

2 Two Meanings of “Happiness”
The grand meaning: the greatest good for an individual, as viewed by that individual. The narrow meaning: feeling happy.

3 The Big Question: Connection Between These Two Meanings?
Why it matters: The greatest good for an individual as viewed by that individual is closely related to welfare concepts in economics. Data on how happy people say they feel is abundant.

4 The relationship between long-run happiness and economic welfare concepts is controversial.
Choices that do not maximize happiness e.g., commuting further: bigger house and yard more pay aggravating commute that dominates the effect of this choice on happiness Easterlin Paradox: strong upward trend in income, no trend in happiness

5 The Easterlin Paradox

6 So, we focus on the short-run responses of happiness to news.
Theory from Kimball and Willis (2007) “Utility and Happiness”: Happiness and News After good news about anything, measured happiness will temporarily spike up. After bad news about anything, measured happiness will temporarily dip down. Economic Definition of Good and Bad News Good news is anything that raises expected lifetime utility. Bad news is anything that lowers expected lifetime utility.

7 USA: The Happiness Index on the Reuters/UM Surveys of Consumers
“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 the past week, you felt you were happy. (Would you say yes or no)? (Much of the time during the past 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?)”

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10 Japan: The Osaka University Panel Study of Happiness Dynamics
71 Osaka University Undergraduates 49 male, 22 female Answered daily web survey for 273 days (so far). Often used web-capable cell-phones High response rates Total of person-day observations

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12 Top of the First Page of the Paper Version

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14 Personal News

15 National News

16 Histogram of Average Happiness (averaged across individuals)

17 Histogram of Average Personal News Ratings

18 Histogram of Average National News Ratings

19 Scatterplot of Happiness vs. Same-Day Personal News

20 Scatterplot of Happiness vs. Same-Day National News

21 Average Happiness vs. Average Personal News Rating

22 Average Happiness vs. Average National News Rating

23 Empirical Strategy Estimate the time series effect of innovations in personal and national news on happiness. Allow for individual fixed effects Regress personal news ratings on their own lags and treat the residuals from this regression as true personal news innovations (“whitened personal news”) Do the same for national news ratings to construct “whitened national news.” Check for nonlinearities in the relationship between news ratings and happiness.

24 News Ratings vs. Lifetime Utility Innovations
Our theoretical concept of “news” is innovations in information about lifetime utility. These innovations should be unpredictable. However, the ordinary language meaning of “good news” and “bad news” may be somewhat predictable. We will purge the component of the news ratings that are predictable by past news ratings. We expect some remaining predictability of news ratings as today’s information is sometimes treated as “tomorrow’s expected news.” The theory then implies that today’s reported happiness should be correlated with tomorrow’s news ratings even after controlling for current and past news ratings.

25 Daily Happiness vs. Daily Personal News

26 Increments (Personal)

27 Cumulative Increments (Personal)

28 Daily Happiness and Daily National News

29 Increments (National)

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31 Whitening (Personal)

32 Whitening (National)

33 Impulse Response (Personal & National)

34 Impulse Response (Personal)

35 Impulse Response (National)

36 Component Impulse Responses (Personal News)

37 Component Impulse Responses (National News)

38 Impulse Response + Neg. Sensitivity (Personal)

39 Impulse Response + Neg. Sensitivity (National)

40 Overshadowing (Personal)

41 Overshadowing (Personal)


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