Misery index (economics) explained

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)

President	Time Period	Average	Low	High	Start	End	Change
	1948 - 1952	7.88	03.45  - Dec 1952	13.63  - Jan 1948	13.63	3.45	-10.18
	1953 - 1960	9.26	02.97  - Jul 1953	10.98  - Apr 1958	3.28	9.96	+5.68
	1961 - 1963	7.14	06.40  - Jul 1962	08.38  - Jul 1961	8.31	6.82	-1.49
	1963 - 1968	6.77	05.70  - Nov 1965	08.19  - Jul 1968	7.02	8.12	+1.10
	1969 - 1974	10.57	07.80  - Jan 1969	17.01  - Jul 1974	7.80	17.01	+9.21
	1974 - 1976	16.00	12.66  - Dec 1976	19.90  - Jan 1975	16.36	12.66	-3.70
	1977 - 1980	16.26	12.60  - Apr 1978	21.98  - Jun 1980	12.72	19.72	+7.00
	1981 - 1988	12.19	07.70  - Dec 1986	19.33  - Jan 1981	19.33	9.72	-9.61
	1989 - 1992	10.68	09.64  - Sep 1989	14.47  - Nov 1990	10.07	10.30	+0.23
	1993 - 2000	7.80	05.74  - Apr 1998	10.56  - Jan 1993	10.56	7.29	-3.27
	2001 - 2008	8.11	05.71  - Oct 2006	11.47  - Aug 2008	7.93	7.39	-0.54
	2009 - 2016	8.83	05.06  - Sep 2015	12.87  - Sep 2011	7.83	6.77	-1.06
	2017 - 2020	6.91	05.21  - Sep 2019	15.03  - Apr 2020	7.30	8.06	+0.76
	2021 - 2023	10.16	06.79  - Feb 2024	11.29  - Jun 2021	7.70	6.79	-0.91

^[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]

In 2013 Hanke 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).

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 Misery Index

Ranked from worst to best

Country/Territory	2020^[7]	2022^[8]
			style=text-align:left		3827.6	330.8
style=text-align:left		547.0	414.7
style=text-align:left		N/A	225.4
style=text-align:left		N/A	116.2
style=text-align:left		N/A	86.8
style=text-align:left		N/A	31.5
style=text-align:left		193.9	176.1
style=text-align:left		177.1	190.337
style=text-align:left		145.3	80.5
style=text-align:left		105.7	60.3
style=text-align:left		95.0	156.192
style=text-align:left		92.1	73.3
style=text-align:left		60.6	93.518
style=text-align:left		60.4	63.6
style=text-align:left		53.4	61.785
style=text-align:left		49.3	83.492
style=text-align:left		48.9	95.4
style=text-align:left		47.1	40.977
style=text-align:left		45.6	47.2
style=text-align:left		42.7	63.1
style=text-align:left		42.4	51.6
style=text-align:left		42.2	34.835
style=text-align:left		41.6	32
style=text-align:left		41.2	176.1
style=text-align:left		41.2	101.601
style=text-align:left		40.7	55.7
style=text-align:left		40.5	62.4
style=text-align:left		40.3	61.5
style=text-align:left		39.7	64.023
style=text-align:left		39.5	42.3
style=text-align:left		39.3	62.3
style=text-align:left		39.1	26.32
style=text-align:left		38.6	41
style=text-align:left		37.9	63.5
style=text-align:left		37.9	56.3
style=text-align:left		36.8	38.9
style=text-align:left		36.7	30.296
style=text-align:left		36.7	33.7
style=text-align:left		36.2	52.653
style=text-align:left		36.1	46.905
style=text-align:left		36.1	61
style=text-align:left		35.8	42.2
style=text-align:left		35.8	22.58
style=text-align:left		35.7	19.21
style=text-align:left		35.4	44.531
style=text-align:left		35.4	42.98
style=text-align:left		34.8	52.5
style=text-align:left		34.1	44.4
style=text-align:left		34.0	27.2
style=text-align:left		33.5	110.003
style=text-align:left		33.1	24.603
style=text-align:left		32.7	50.2
style=text-align:left		32.5	52.6
style=text-align:left		32.4	37.077
style=text-align:left		32.0	43.7
style=text-align:left		31.5	21.98
style=text-align:left		31.3	31.128
style=text-align:left		30.4	29.884
style=text-align:left		30.2	41.2
style=text-align:left		29.9	26.3
style=text-align:left		29.9	18.9
style=text-align:left		29.5	43.854
style=text-align:left		29.3	26.3
style=text-align:left		28.7	41
style=text-align:left		28.3	19.552
style=text-align:left		28.2	38.131
style=text-align:left		28.2	28.16
style=text-align:left		28.1	50.4
style=text-align:left		27.8
style=text-align:left		27.4	38.64
style=text-align:left		27.1	31.8
style=text-align:left		26.2	37.1
style=text-align:left		26.2	50.4
style=text-align:left		26.0	28.4
style=text-align:left		25.8	36.9
style=text-align:left		25.7	18.725
style=text-align:left		25.6	20.3
style=text-align:left		24.3	99.634
style=text-align:left		23.9	36.846
style=text-align:left		23.8	25.6
style=text-align:left		23.8	75.9
style=text-align:left		23.5	21.525
style=text-align:left		23.3	17.5
style=text-align:left		23.2	17.5
style=text-align:left		23.2	45.4
style=text-align:left		22.8	36.565
style=text-align:left		22.2	22.441
style=text-align:left		22.0	39.2
style=text-align:left		22.0	26.451
style=text-align:left		21.6	11.3
style=text-align:left		22.5	17.659
style=text-align:left		20.9	41.832
style=text-align:left		20.9	21.727
style=text-align:left		20.8	29.264
style=text-align:left		20.4	18.3
style=text-align:left		20.3	8.6
style=text-align:left		20.1	18
style=text-align:left		19.9	33.202
style=text-align:left		19.9	37.18
style=text-align:left		18.5	32.271
style=text-align:left		18.4	41.138
style=text-align:left		18.4	19.935
style=text-align:left		18.3	25.5
style=text-align:left		18.2	18.191
style=text-align:left		18.1	20.676
style=text-align:left		18.0	11.062
style=text-align:left		18.0	18.615
style=text-align:left		17.6	35.235
style=text-align:left		17.5	32.7
style=text-align:left		17.1	34.692
style=text-align:left		17.1	35.49
style=text-align:left		17.0	19.919
style=text-align:left		16.7	16.882
style=text-align:left		16.4	52.9
style=text-align:left		16.3	20.6
style=text-align:left		16.2	32.051
style=text-align:left		16.0	24.6
style=text-align:left		16.0	52.16
style=text-align:left		15.9	20.059
style=text-align:left		15.9	26.3
style=text-align:left		15.8	102
style=text-align:left		15.7	22.2
style=text-align:left		15.5	19
style=text-align:left		15.4	20.608
style=text-align:left		14.8	40.242
style=text-align:left		14.6	15.986
style=text-align:left		14.5	17.063
style=text-align:left		14.5	32.87
style=text-align:left		14.5	9.075
style=text-align:left		14.4	17.2
style=text-align:left		14.4	12.384
style=text-align:left		14.3	18.316
style=text-align:left		14.0	20.107
style=text-align:left		13.9	33.761
style=text-align:left		13.4	14.839
style=text-align:left		13.2	22.2
style=text-align:left		13.2	35.4
style=text-align:left		13.0	14.973
style=text-align:left		12.9	8.602
style=text-align:left		12.8	21.629
style=text-align:left		12.8	13.542
style=text-align:left		12.7	29.198
style=text-align:left		12.6	10.219
style=text-align:left		11.8	15.785
style=text-align:left		11.8	13
style=text-align:left		11.6	25.132
style=text-align:left		11.6	23.34
style=text-align:left		11.4	88.1
style=text-align:left		10.9	16.381
style=text-align:left		10.8	11.622
style=text-align:left		10.6	69.192
style=text-align:left		10.5	9.77
style=text-align:left		9.5	10.95
style=text-align:left		8.6	8.518
style=text-align:left		8.3	12.515
style=text-align:left		8.3	13.1
style=text-align:left		8.1	9.071
style=text-align:left		5.3	13.591
style=text-align:left		3.8	9.399
style=text-align:left		−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."^[9]

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.^[10] 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

• Elder Index

External links

• The current and historical Misery Index
• The Misery Index by President
• The Misery Index By Year
• Cato Publications Commentary
• Correlations of Misery Index and Consumer Sentiment

Notes and References

1. Web site: The US Misery Index. Inflationdata.com.
2. Web site: US Misery Index by President .
3. News: Reagan Vs. Clinton: Who's The Economic Champ?. https://web.archive.org/web/20121022195246/http://www.businessweek.com/stories/1999-02-21/reagan-vs-dot-clinton-whos-the-economic-champ. October 22, 2012. Robert J. Barro . Bloomberg. 22 February 1999 .
4. Web site: Misery in MENA. Steve H. Hanke. March 2011. Cato Institute: appeared in Globe Asia.
5. Web site: Measuring Misery around the World. Steve H. Hanke. May 2014. Cato Institute: appeared in Globe Asia.
6. Book: Capital as Power: A Study of Order and Creorder . Nitzan, Jonathan . Bichler, Shimshon . 2009. 384–386. Routledge. RIPE Series in Global Political Economy.
7. Web site: Hanke . Steve H. . 14 April 2021 . Hanke's 2020 Misery Index: Who's Miserable and Who's Happy? . 23 March 2022 . National Review.
8. Web site: Hanke’s 2022 Misery Index . May 18, 2023 . STEVE H. . HANKE .
9. Di Tella, Rafael . MacCulloch, Robert J. . . 2001. Preferences over Inflation and Unemployment: Evidence from Surveys of Happiness. American Economic Review. 91. 1. 335–341, 340. 10.1257/aer.91.1.335. 14823969 .
10. New evidence from the misery index in the crime function. Tang, Chor Foon . Lean, Hooi Hooi . Economics Letters. 2009. Hooi Hooi Lean. 102. 2. 112–115. 10.1016/j.econlet.2008.11.026.