The Trade-off Between Inflation and Unemployment (joint with David Bell, University of Stirling) plus a diversion on Exploring the Pulse of the Nation (joint with Andrew Oswald, University of Warwick and IZA) World Bank, December 6 th 2011 1
The fixation with inflation is misplaced Arthur Okun characterised the negative effects of unemployment and inflation by the misery index -the sum of the unemployment and inflation rates. But the rapidly developing study of happiness (or well- being) means that a more direct approach can be taken to investigating how unemployment and inflation affect individual welfare. It turns out that qualitative data, especially consumer and dbusiness confidence such as the PMIs and deu surveys, collapsed well before output or employment fell in the Great Recession. They have turned down again. * * ICAEW/Grant Thornton Business Confidence Monitor 2
60 Chart 1a. Business and Consumer Confidence, 1985-2011 40 0 20-20 -60-40 Industry Services Consumer Retail -80 60 n-85 g-85 ar-86 ct-86 y-87 c-87 ul-88 b-89 p-89 pr-90 v-90 n-91 n-92 g-92 ar-93 ct-93 y-94 c-94 ul-95 b-96 p-96 pr-97 v-97 n-98 n-99 g-99 ar-00 ct-00 y-01 c-01 ul-02 b-03 p-03 pr-04 v-04 n-05 n-06 g-06 ar-07 ct-07 y-08 c-08 ul-09 b-10 p-10 pr-11 Retail Construction -100 Jan Aug Ma Oc May De Ju Feb Sep Ap Nov Jun Jan Aug Ma Oc May De Ju Feb Sep Ap Nov Jun Jan Aug Ma Oc May De Ju Feb Sep Ap Nov Jun Jan Aug Ma Oc May De Ju Feb Sep Ap
30 Chart 1b. Business and Consumer Confidence in the UK, 2007-2011 25 20 15 10 5 0-5 -10-15 -20-25 Industry -30 Services -35 Consumer -40-45 -50 Retail Construction -55-60 -65-70 -75-80
Happiness research Happiness can be defined as the degree to which an individual judges the quality of their life to be favourable Psychologists view it as natural that t a concept such as happiness should be studied by asking how people feel It turns out not to matter that much how the questions are asked one happiness equation is much like any other As a validation i of the answers to the recorded d levels l of happiness it turns out that answers to happiness questions are correlated with 5
Happiness correlates (1) Objective characteristics such as unemployment. Assessments of the person s happiness by friends and family members. Assessments of the person s happiness by his or her spouse. Heart rate and blood-pressure measures of response to stress. The risk of coronary heart disease. 6
Happiness correlates (2) Duration of authentic or so-called Duchenne smiles which occur when both the zygomatic major and obicularus orus facial muscles fire, and human beings identify these as genuine smiles Skin-resistance measures of response to stress. Electro-encephalogram encephalogram measures of prefrontal brain activity. Healing rates skin biopsies Life expectancy 7
Exploring the pulse of the nation David Blanchflower & Andrew Oswald 8
Validation of Happiness Could we use a physiological measure like heart rate as a measure of happiness or stress? Perhaps we could think of this as estimating a negative utility function That should get them worked up says Andrew! This is an attempt to study the macroeconomics of stress and pulse with an exogenous shock that acts as an experiment. 9
Biomarkers and pulse rates We make use of the Health Surveys of England from 1998-2009 (n=approx 90,000) Data are available on personal characteristics and each individual is also visited by a nurse who did a medical examination in the respondent s home and measured pulse rates and blood pressure reducing white coat effects. Three pulse measures are taken. We take the average of the three in most cases (88%). 10
Pulse rate characteristics* Mean SD Pulse average 70.92 12.28 Pulse 1 70.62 12.76 Pulse 2 70.91 12.57 Pulse 3 71.27 12.64 Male 69.40 13.08 Female 72.19 11.43 Asian 73.48 11.03 Black 72.01 11.24 Cigarette smoker 73.69 11.64 * Beats per minute 11
Pulse (resting heart rate) equations Controls are those used in most happiness and life satisfaction equations Pulse rates are higher among a) The young b) Blacks and Asians c) Women d) Smokers e) The unemployed f) Those with lower income g) Single, divorced, widowed and separated 12
Pulse and world events We find that pulse rates are raised by two major UK bad events The 7/7 bombings in July 2005 in London The autumn 2008 financial crisis And especially so in London and the South East We find no evidence for effects from 9/11 or the Iraq invasion. 13
Pulse equations Handout Table 1. (3) (4) (5) London & South East Financial crisis.8366 1.0992 2.0495 (1.81) (2.17) (2.57) 7/7 Bombings.8725 1.0651 2.140 (2.51) (2.81) (2.57) Log income - -.5058 -.6618 (7.32) (4.87) N 84,898 72,381 19,445 Notes: T-statistics in parentheses. Equations include, year, month, schooling and region dummies + controls. 14
Disaggregated pulse equations Handout Table 2. Financial crisis 7/7 bombings All 1.089* 1.061* London & S. East 2.046 2.123* Male.665 1.771* Female 1.4239*.444 Age 45-60 1.211 1.993* Working 1.372*.675 Unemployed.073 -.147 OLF 3.099* 2.481 White 1.220* 1.166* Notes: * t>2 15
Back to.happiness across countries Higher among Women Married people The highly hl educated d The healthy Those with high income The young and the old Lower among Newly divorced and separated people Adults in their mid to late 40s The unemployed and the disabled d Immigrants and minorities Those in poor health Commuters 16
Happiness research findings Richer people are happier and healthier Lottery winners experience better psychological health, but 10% less happy after a win Relative income seems to matter (Luttmer) Money buys happiness but life events give a lot of happiness such that it takes a lot of money to compensate for a loss of happiness e.g. from marriage or unemployment say Individuals have a lower tendency to report themselves as happy as inequality rises Married people happier than those who live together 17
Happiness across countries Little evidence that in developed countries life satisfaction has increased over time. This may be because a) Social comparisons (you compare your 3 BMWs to others who also have 3 BMWs) b) Habituation: people adapt to their current lifestyle c) Mistaken choices: people make incorrect predictions about the effect of important decisions on their happiness (e.g. long commutes and working hours). 18
Eurobarometer 10-step life satisfaction scores Country 2005 2009 2010 Austria 7.66 6.98 7.14 Bulgaria 4.87 4.38 4.51 Denmark 844 8.44 814 8.14 826 8.26 France 7.09 6.82 6.70 Germany 7.31 7.00 6.81 Greece 7.10 6.38 5.99 Ireland 7.64 7.41 7.36 Italy 6.76 6.48 6.61 Latvia 6.23 5.34 5.52 Lithuania 6.20 6.09 5.81 Netherlands 795 7.95 780 7.80 784 7.84 Portugal 6.33 5.59 5.40 Spain 7.47 6.94 6.98 Sweden 8.00 7.82 7.91 UK 7.54 7.41 7.21 19
Life satisfaction equations We estimate a series of life satisfaction equations based on data from 23 countries, in the Eurobarometer Surveys from 1975-2011 are asked "On the whole, are you very satisfied, fairly satisfied, not very satisfied, or not at all satisfied with the life you lead?" We include controls for individual characteristics including whether the individual is unemployed plus the annual linflation i rate and unemployment rate in the state/year cell. Standard errors are clustered at the state/year cell 22
Table 2 - Life satisfaction equations Life satisfaction equation looks similar to other equations such as financial position, standard of living etc Happiness is lower among the unemployed, men, the least educated, divorced and in Bulgaria and Romania and is U-shaped in age Happiness is highest among women, the most educated, married and in Denmark and Sweden 23
Most important problem Table 3 Unemployment Inflation U nemployment Inflation Austria 38 34 Italy 49 26 Belgium 44 20 Latvia 67 9 Bulgaria 53 22 Lithuania 60 28 Croatia 63 18 Luxembourg 42 28 Cyprus 40 24 Macedonia 63 14 Czech Republic 48 21 Malta 16 37 Denmark 37 3 Netherlands 19 9 Estonia 70 21 Northern Ireland 39 18 Finland 51 11 Poland 49 26 France 58 16 Portugal 62 32 Germany East 44 39 Romania 39 26 Germany West 39 23 Slovakia 64 22 Great Britain 31 12 Slovenia 51 19 Greece 44 25 Spain 72 10 Hungary 60 29 Sweden 57 3 Iceland 51 14 Turkey 68 12 Ireland 65 12 24
USA, Misery ratio Unemployment Inflation (U+I) Misery rate (%) rate (%) Ratio (U/I) 1948-19591959 4.58 2.2929 6.77 2.00 1960-1969 4.78 2.34 7.12 2.05 1970-1979 1979 6.22 7.09 13.31 0.88 1980-1989 7.27 5.56 12.83 1.31 1990-1999 5.76 3.01 8.77 1.92 2000-2010 5.91 2.49 8.40 2.37 1948-2010 5.72 3.73 9.45 1.53 Fb February 2011 890 8.90 211 2.11 11.01 422 4.22 25
European countries misery ratio 1975-1979 1980-1989 1990-1999 2000-2010 Belgium 0.76 2.46 4.26 4.34 Denmark 0.68 1.31 3.68 2.29 Finland 130 1.30 10.30 469 4.69 France 0.43 2.38 4.85 5.19 Germany 0.92 0.40 2.50 5.43 Greece 1.81 0.76 3.07 Ireland 0.66 1.03 5.10 1.80 Italy 0.44 0.30 2.57 3.84 Luxembourg 0.07 4.15 0.77 1.16 Nth Netherlands 078 0.78 054 0.54 238 2.38 135 1.35 Portugal 0.72 239 2.39 Spain 4.09 4.15 26
Life satisfaction Table 5 (%) Unemployment rate Inflation rate Mean 8.3 4.6 Standard deviation 37 3.7 45 4.5 Minimum 0.2-4.5 Maximum 24.2 24.5 These data imply a mean misery ratio at the macro level of 1.80. 27
Life satisfaction equations, 1975-2010 Table 5 (%) The country*year unemployment rate enters significantly and negative in column 1 with a coefficient of -.0111 (t=7.0) The country*year inflation rate enters significantly and negative in column 1 with a coefficient of -.0065 (t=4) Individual unemployment rate enters significantly and negative in column 1 with a coefficient of -.3633 (t=35) Standard errors are clustered by country*year 28
Misery ratio We calculate the impact of a one percentage point increase in unemployment compared with a one percentage point increase in inflation There are two unemployment unhappiness terms the indirect effect of the unemployment rate and the direct effect on the extra unemployed individuals From column 2 of Table 5 coefficients Unemployment rate =-.0113 Inflation rate =-.0061 Unemployment coefficient =-.3790 Misery ratio=2.47 ((-.0113+.0038)/.0061) 29
Disaggregated estimates of the misery ratio All with schooling (column 1) 227 2.27 All (column 2) 2.47 All Western Europe 2.51 Age<25 1.57 Age 65+ 663 6.63 Male 226 2.26 Female 2.68 ALS<16 4.79 ALS 16-19 2.10 ALS >=20 1.43 30
Conclusions (1) We discover that unemployment depresses well-being The northern European countries, especially the Danes, have generally higher happiness and life satisfaction scores than residents of Southern Europe, especially Portugal, Italy, Greece and Spain. Residents of former Eastern bloc countries have particularly low happiness scores. Unemployment lowers happiness of the unemployed but also the happiness of everyone else. 31
Conclusions (2) Unemployment lowers an individual s standards of living and makes it harder to make ends meet, but it also diminishes the quality of their family life. We estimate the unemployment/inflation trade-off as approximately two and a half. We find that the least educated and, somewhat surprisingly, the old put the highest weight on unemployment. Conversely, the young and the most educated put the greatest weight on inflation. Unemployment is more costly than inflation in terms of its impact on wellbeing. The misery ratio is closer to 2.5 than to 1. 32
The fixation with inflation is misplaced We discover that unemployment depresses well-being more than inflation. We characterise this wellbeing trade-off bt between unemployment and inflation using what we describe as the misery ratio. Our estimates with European data imply that a one percentage point rise in the unemployment rate lowers well being by two and a half times as much as a one percentage point increase in inflation. i Is unemployment more costly than inflation? The answer is unequivocally 'yes'. 33
End Thank you 34