Misery Index
  Misery Index
  Unemployment rate
  Inflation rate CPI

The misery index is an economic indicator, created by economist Arthur Okun. The index helps determine how the average citizen is doing economically and is calculated by adding the seasonally adjusted unemployment rate to the annual inflation rate. It is assumed that both a higher rate of unemployment and a worsening of inflation create economic and social costs for a country.[1]

Misery index by US presidential administration

Index = Unemployment rate + Inflation rate (lower number is better)
PresidentTime PeriodAverageLowHighStartEndChange
Harry Truman194819527.883.45 Dec 195213.63 Jan 194813.633.45-10.18
Dwight D. Eisenhower195319609.262.97 Jul 195310.98 Apr 19583.289.96+5.68
John F. Kennedy196119637.146.40 Jul 19628.38 Jul 19618.316.82-1.49
Lyndon B. Johnson196319686.775.70 Nov 19658.19 Jul 19687.028.12+1.10
Richard Nixon1969197410.577.80 Jan 196917.01 Jul 19747.8017.01+9.21
Gerald Ford1974197616.0012.66 Dec 197619.90 Jan 197516.3612.66-3.70
Jimmy Carter1977198016.2612.60 Apr 197821.98 Jun 198012.7219.72+7.00
Ronald Reagan1981198812.197.70 Dec 198619.33 Jan 198119.339.72-9.61
George H. W. Bush1989199210.689.64 Sep 198914.47 Nov 199010.0710.30+0.23
Bill Clinton199320007.805.74 Apr 199810.56 Jan 199310.567.29-3.27
George W. Bush200120088.115.71 Oct 200611.47 Aug 20087.937.39-0.54
Barack Obama200920168.835.06 Sep 2015
12.87 Sep 20117.836.77-1.06
Donald Trump201720206.915.21 Sep 2019
15.03 Apr 20207.308.06+0.76
Joe Biden2021202310.167.47 Aug 2023
11.29 Jun 20217.707.47-0.23

[2]

Variations

Harvard Economist Robert Barro created what he dubbed the "Barro Misery Index" (BMI), in 1999.[3] The BMI takes the sum of the inflation and unemployment rates, and adds to that the interest rate, plus (minus) the shortfall (surplus) between the actual and trend rate of GDP growth.

In the late 2000s, Johns Hopkins economist Steve Hanke built upon Barro's misery index and began applying it to countries beyond the United States. His modified misery index is the sum of the interest, inflation, and unemployment rates, minus the year-over-year percent change in per-capita GDP growth.[4]

Hanke has recently constructed a World Table of Misery Index Scores by exclusively relying on data reported by the Economist Intelligence Unit.[5] This table includes a list of 89 countries, ranked from worst to best, with data as of December 31, 2013 (see table below).

World Table of Misery Index Scores as of December 31, 2013.

Political economists Jonathan Nitzan and Shimshon Bichler found a negative correlation between a similar "stagflation index" and corporate amalgamation (i.e. mergers and acquisitions) in the United States since the 1930s. In their theory, stagflation is a form of political economic sabotage employed by corporations to achieve differential accumulation, in this case as an alternative to amalgamation when merger and acquisition opportunities have run out.[6]

Hanke's 2020 Misery Index

Ranked from worst to best[7]
Country/Territory 2020 2022
 Venezuela3827.6330.8
 Zimbabwe547.0414.7
 SyriaN/A225.4
 YemenN/A116.2
 GhanaN/A86.8
 BarbadosN/A31.5
 Sudan193.9176.1
 Lebanon177.1190.337
 Suriname145.380.5
 Libya105.760.3
 Argentina95.0156.192
 Iran92.173.3
 Angola60.693.518
 Madagascar60.463.6
 Brazil53.461.785
 South Africa49.383.492
 Haiti48.995.4
 Kyrgyzstan47.140.977
 Nigeria45.647.2
 Eswatini42.763.1
 Lesotho42.451.6
 Peru42.234.835
 Zambia41.632
 South Sudan41.2176.1
 Turkey41.2101.601
 Namibia40.755.7
 Gabon40.562.4
 Congo40.361.5
 Botswana39.764.023
 Iraq39.542.3
 São Tomé and Príncipe39.362.3
 Liberia39.126.32
 Jamaica38.641
 Malawi37.963.5
 Jordan37.956.3
 Guinea36.838.9
 Uruguay36.730.296
 Armenia36.733.7
 Montenegro36.252.653
 Tunisia36.146.905
 Ethiopia36.161
 Honduras35.842.2
 India35.822.58
 Panama35.719.21
 Colombia35.444.531
 Mongolia35.442.98
 Georgia34.852.5
 Uzbekistan34.144.4
 Dominican Republic34.027.2
 Ukraine33.5110.003
 Saudi Arabia33.124.603
 Algeria32.750.2
 Pakistan32.552.6
 Costa Rica32.437.077
 Paraguay32.043.7
 Trinidad and Tobago31.521.98
 Greece31.331.128
 Mauritius30.429.884
 Gambia30.241.2
 Cape Verde29.926.3
 Bolivia29.918.9
 Kazakhstan29.543.854
 Guatemala29.326.3
 Burundi28.741
 Philippines28.319.552
 Azerbaijan28.238.131
 Spain28.228.16
 North Macedonia28.150.4
 Belize27.8
 Democratic Republic of the Congo27.438.64
 Equatorial Guinea27.131.8
 Comoros26.237.1
 Myanmar26.250.4
 El Salvador26.028.4
 Mozambique25.836.9
 Nicaragua25.718.725
 Mexico25.620.3
 Sri Lanka24.399.634
 Chile23.936.846
 Albania23.825.6
 Bosnia and Herzegovina23.875.9
 Iceland23.521.525
 Ecuador23.317.5
 Fiji23.217.5
 Mauritania23.245.4
 Morocco22.836.565
 New Zealand22.222.441
 Belarus22.039.2
 Italy22.026.451
 Oman21.611.3
 United Kingdom22.517.659
 Egypt20.941.832
 Indonesia20.921.727
 Kenya20.829.264
 Vanuatu20.418.3
 Kuwait20.38.6
 Papua New Guinea20.118
 Russia19.933.202
   Nepal19.937.18
 Romania18.532.271
 Serbia18.441.138
 France18.419.935
 Croatia18.325.5
 Hong Kong18.218.191
 Canada18.120.676
 Malta18.011.062
 Portugal18.018.615
 Uganda17.635.235
 Mali17.532.7
 Estonia17.134.692
 Latvia17.135.49
 Slovenia17.019.919
 United States16.716.882
 Moldova16.452.9
 Cyprus16.320.6
 Slovakia16.232.051
 Bulgaria16.024.6
 Laos16.052.16
 Australia15.920.059
 Burkina Faso15.926.3
 Cuba15.8102
 Czech Republic15.722.2
 Cameroon15.519
 Belgium15.420.608
 Hungary14.840.242
 Singapore14.615.986
 Austria14.517.063
 Lithuania14.532.87
 Malaysia14.59.075
 Guinea-Bissau14.417.2
 Israel14.412.384
 Luxembourg14.318.316
 Bangladesh14.020.107
 Poland13.933.761
 Vietnam13.414.839
 Bahrain13.222.2
 Central African Republic13.235.4
 Netherlands13.014.973
 Ireland12.98.602
 Finland12.821.629
 Norway12.813.542
 Sweden12.729.198
 Thailand12.610.219
 Denmark11.815.785
 United Arab Emirates11.813
 Tanzania11.625.132
 Chad11.623.34
 Tonga11.488.1
 Germany10.916.381
 Côte d'Ivoire10.811.622
 Rwanda10.669.192
 Niger10.59.77
 Togo9.510.95
  Switzerland8.68.518
 South Korea8.312.515
 China8.313.1
 Japan8.19.071
 Qatar5.313.591
 Taiwan3.89.399
 Guyana−3.3

Criticism

A 2001 paper looking at large-scale surveys in Europe and the United States concluded that unemployment more heavily influences unhappiness than inflation. This implies that the basic misery index underweights the unhappiness attributable to the unemployment rate: "the estimates suggest that people would trade off a 1-percentage-point increase in the employment rate for a 1.7-percentage-point increase in the inflation rate."[8]

Misery and crime

Some economists, such as Hooi Hooi Lean, posit that the components of the Misery Index drive the crime rate to a degree. Using data from 1960 to 2005, they have found that the Misery Index and the crime rate correlate strongly and that the Misery Index seems to lead the crime rate by a year or so.[9] In fact, the correlation is so strong that the two can be said to be cointegrated, and stronger than correlation with either the unemployment rate or inflation rate alone.

Data sources

The data for the misery index is obtained from unemployment data published by the U.S. Department of Labor (U3) and the Inflation Rate (CPI-U) from the Bureau of Labor Statistics. The exact methods used for measuring unemployment and inflation have changed over time, although past data is usually normalized so that past and future metrics are comparable.

See also

References

  1. "The US Misery Index". Inflationdata.com.
  2. "US Misery Index by President".
  3. Robert J. Barro (22 February 1999). "Reagan Vs. Clinton: Who's The Economic Champ?". Bloomberg. Archived from the original on October 22, 2012.
  4. Steve H. Hanke (March 2011). "Misery in MENA". Cato Institute: appeared in Globe Asia.
  5. Steve H. Hanke (May 2014). "Measuring Misery around the World". Cato Institute: appeared in Globe Asia.
  6. Nitzan, Jonathan; Bichler, Shimshon (2009). Capital as Power: A Study of Order and Creorder. RIPE Series in Global Political Economy. Routledge. pp. 384–386.
  7. Hanke, Steve H. (14 April 2021). "Hanke's 2020 Misery Index: Who's Miserable and Who's Happy?". National Review. Retrieved 23 March 2022.
  8. Di Tella, Rafael; MacCulloch, Robert J.; Oswald, Andrew (2001). "Preferences over Inflation and Unemployment: Evidence from Surveys of Happiness" (PDF). American Economic Review. 91 (1): 335–341, 340. doi:10.1257/aer.91.1.335. S2CID 14823969.
  9. Tang, Chor Foon; Lean, Hooi Hooi (2009). "New evidence from the misery index in the crime function". Economics Letters. 102 (2): 112–115. doi:10.1016/j.econlet.2008.11.026.
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