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Martin Berlin

Postdoktor

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Arbetar vid Institutet för social forskning
E-post martin.berlin@sofi.su.se
Besöksadress Universitetsvägen 10 F
Rum F884
Postadress Institutet för social forskning 106 91 Stockholm

Om mig

Jag är forskare i nationalekonomi vid Institutet för social forskning (SOFI).

Publikationer

I urval från Stockholms universitets publikationsdatabas
  • 2015. Martin Berlin. Nationalekonomi för miljöintresserade
  • Artikel Beyond Income
    2015. Martin Berlin, Niklas Kaunitz. Journal of Happiness Studies 16 (6), 1557-1573

    We study how life satisfaction among adult Swedes is influenced by having access to a cash margin, i.e. a moderate amount of money that could be acquired on short notice either through own savings, by loan from family or friends, or by other means. We find that cash margin is a strong and robust predictor of life satisfaction, also when controlling for individual fixed-effects and socio-economic conditions, including income. Since it shows not to matter whether cash margin comes from own savings or with help from family members, this measure captures something beyond wealth.

  • 2017. Martin Berlin, Markus Jäntti, Andrew Clark.

    This thesis consists of four self-contained essays in economics, all concerned with different aspects of subjective well-being. The abstracts of the four studies are as follows.

    Beyond Income: The Importance for Life Satisfaction of Having Access to a Cash Margin. We study how life satisfaction among adult Swedes is influenced by having access to a cash margin, i.e. a moderate amount of money that could be acquired on short notice either through own savings, by loan from family or friends, or by other means. We find that cash margin is a strong and robust predictor of life satisfaction, also when controlling for individual fixed effects and socio-economic conditions, including income.

    Decomposing Variation in Daily Feelings: The Role of Time Use and Individual Characteristics. I explore the potential of using time-use data for understanding variation in affective well-being. Using the Princeton Affect and Time Survey, I decompose variation in daily affect into explained and unexplained within- and between person variation. Time use is found to mostly account for within-variation. Hence, its explanatory power is largely additive to that of individual characteristics. The explanatory power of time use is small, however. Activities only account for 1–7% of the total variation and this is not increased much by adding contextual variables.

    The Association Between Life Satisfaction and Affective Well-Being. We estimate the correlation between life satisfaction and affect — two conceptually distinct dimensions of subjective well-being. We propose a simple model that distinguishes between a stable and a transitory component of affect, and which also accounts for measurement error in self-reports of both variables, including current-mood bias effects on life satisfaction judgments. The model is estimated using momentarily measured well-being data, from an experience sampling survey that we conducted on a population sample of Swedes aged 18–50 (n=252). Our main estimates of the correlation between life satisfaction and long-run affective well-being range between 0.78 and 0.91, indicating a stronger convergence between these variables than many previous studies that do not account for measurement issues.

    Do OLS and Ordinal Happiness Regressions Yield Different Results? A Quantitative Assessment. Self-reported subjective well-being scores are often viewed as ordinal variables, but the conventional wisdom has it that OLS and ordered regression models (e.g. ordered probit) produce similar results when applied to such data. This claim has rarely been assessed formally, however, in particular with respect to quantifying the differences. I shed light on this issue by comparing the results from OLS and different ordered regression models, in terms of both statistical and economic significance, and across data sets with different response scales for measuring life satisfaction. The results are mixed. The differences between OLS, probit and logit estimates are typically small when the response scale has few categories, but larger, though not huge, when an 11-point scale is used. Moreover, when the error term is assumed to follow a skewed distribution, larger discrepancies are found throughout. I find a similar pattern in simulations, in which I assess how different methods perform with respect to the true parameters of interest, rather than to each other.

  • 2017. Martin Berlin. Nationalekonomins frågor
Visa alla publikationer av Martin Berlin vid Stockholms universitet

Senast uppdaterad: 10 september 2018

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