Solar Activity and Perturbations in Economy and Society


Our research aims to propose a consistent theory explaining the empirically observed impact of the cyclical fluctuations in the solar activity on economy and society. Unemployment increases, consumer and business confidence drops, and recessions in the US and G7 countries occur more frequently in the years around and after the solar maximums. This is consistent with the findings of the Russian scientist Alexander Chizhevsky, who in the early XX century claimed that the cyclical maximums in the solar activity affect human behavior and well-being. In particular, they increase the occurrence of revolutions, riots, and mass movements and lead to intensification of political life. Apart from producing direct negative impact on the economies of the affected countries, such commotions increase uncertainty, which hampers consumer and business confidence, weakens economic activity and, ultimately, triggers recessions. Also, the negative impact of the sun-induced fluctuations in the geomagnetic field on human health and well-being can affect consumer demand, labor productivity, and consumer confidence.




One more look at the solar activity and its impact on earth


For the last hundred years or more, the primary index of solar activity has been the sunspot number (often denoted Rz). It has a prominent 11-year cycle, named after German astronomer Samuel Heinrich Schwabe, who discovered it in 1843 with less than 11 years of data. The cycles are numbered since 1750 (cycle 1 = 1755 minimum to 1766 minimum). In recent years, many other solar indices were established (notably the 2800MHz, 10.7cm radio emission flux, denoted as F10, recorded since 1947). All these show an 11-year cycle, except that during sunspot minimum when sunspot numbers almost reach zero, most of the other indices reach a minimum nonzero level (Kane, 2002). In cycle 18, data for very few indices were available. Thereafter, the number has increased considerably from one cycle to the next. Table 1 lists the indices considered for cycles 18–23, in the order of their approximate altitude of origin in the solar atmosphere, starting from solar radio emissions in solar corona and ending with sunspots at the photosphere. Since all solar indices attain their maxima near sunspot maximum and minima near sunspot minimum, the long-term correlation between all indices is very high.


A curious feature of the long-term activity is the evolution of sunspot numbers near sunspot maximum. In some cycles, Rz rose rapidly to a maximum and fell thereafter rapidly, giving the impression of a sharp peak. In some other cycles, the rise of Rz from the sunspot minimum halted after a few years, the level remained almost steady for the next few years, giving the impression of a plateau, and then there was a sharp fall up to the next sunspot minimum. Whereas most of the other indices of solar activity had coinciding sharp maxima, in some cases, further evolution was not similar to the sunspot number (Kane, 2002).


Moreover, solar activity modulates intensity and energy spectrum of the galactic cosmic rays reaching earth (Gupta et al., 2006). For most of the years, cosmic ray intensity correlates negatively with sunspot number. However, poor correlations are observed during the high and low solar activity years. Also, cosmic rays correlate negatively with geomagnetic activity (Tiwari et al. 2011).


And it has long been recognized that the solar activity is at the origin of the geomagnetic activity. The latter is the result of variable current systems formed in the magnetosphere and ionosphere as a consequence of the interaction of the solar wind with the magnetosphere and is described quantitatively by means of so-called geomagnetic indices. Among the indices designed to provide a global picture of the degree of disturbance level, the aa index covers the longest time span (the time series starts in 1868) and is well suited as a proxy of geomagnetic activity in long-term studies. This index has been compiled from the range of variations of the geomagnetic field over periods of 3 hours (the K index) at two near-antipodal observatories in England and Australia. The long-term behavior of the geomagnetic activity and its resemblance to the long cycle in the solar activity, as well as peculiarities of the 11-year cycle of aa, such as the second peak in the declining phase of the sunspot cycle and the increase of the minimum values during the twentieth century, have been discussed by several authors. Their main conclusion was that the upward drift in geomagnetic activity is caused by heliospheric conditions, represented by the interplanetary magnetic field (IMF) strength, the solar wind speed, and the solar wind density (Demetrescu, 2008).


The impact of solar activity on the climate on earth is a subject of much debate. Broadly speaking, changes in the amount of radiation emitted by the sun and in its spectral distribution over years could have had an impact on climate, but strictly proving it is difficult for the lack of detailed data on climate and sun activity going so deep in history. For example, the so-called Maunder Minimum of the solar activity from about 1645 to 1715 coincided with the middle (and coldest) part of the so-called Little Ice Age, during which Europe and North America were subjected to bitterly cold winters. However, changes in solar brightness were too weak to explain recent climate changes, including the global warming. Solar irradiance has been measured from satellites since 1979, which covered about three solar cycles. During this period, solar irradiance varied by approximately 0.1 percent peak-to-trough from solar maximum to solar minimum during the 11-year sunspot cycle. A recent NASA study of the earth’s energy imbalance underscored that greenhouse gases generated by human activity are the primary force driving global warming, though changes in solar activity also played a role (Hansen et al., 2011).


Figures plotting sunspot number, 10.7cm radio emission flux, solar flares, geomagnetic field indicator (Ap), cosmic rays, and solar irradiance


Solar and geomagnetic activity indices, 1991-2012

Sunspot numbers and solar flares, 1965-2009

Smoothed monthly sunspot numbers for cycles 0-23

Solar irradiance fluctuations



List of solar indices


Literature references


Demetrescu, Crisan, Venera Dobrica, 2008: “Signature of Hale and Gleissberg solar cycles in the geomagnetic activity,” — Journal of Geophysical Research, Vol. 113, 2008.


Gupta, Meera, V. K. Mishra, A.P.Mishra, 2006: “Study of cosmic ray intensity variations in relation to solar activity for sunspot cycles 19 to 23,” — Indian Journal of Radio & Space Physics, Vol.35, June 2006, pp. 167-173.


Hansen, J., Mki. Sato, P. Kharecha, and K. von Schuckmann, 2011: “Earth's energy imbalance and implications,” — Atmos. Chem. Phys., 11, 13421-13449, doi:10.5194/acp-11-13421-2011.


Kane, R. P., 2002: “Evolutions of various solar indices around sunspot maximum and sunspot minimum years,” — Annales Geophysicae (2002) 20: 741–755.


Tiwari, Rakesh Kumar, Achyut Pandey, Pankaj K. Shrivstava, Sushil Kumar Srivastava, 2011: “Relationship of cosmic rays with solar and geomagnetic activity,” — Indian Journal of Scientific & Industrial Research 2(4) : 15-19, 2011.



Here Comes Solar Maximum

Carrington-class CME Narrowly Misses Earth

Solar Storm




Impact of the solar activity on the frequency and intensity of historical events


In the early XX century, Russian scientist Alexander Chizhevsky compared sunspot records to riots, revolutions, battles and wars in Russia and seventy-one other countries for the period 500 BC to 1922. He discovered that when the sunspot activity approached its maximum, the number of important mass historical events was increasing as well, and decreased during the times of the sunspot minimums. This led him to believe that the periods around sunspot maximums are generally associated with intensification of human activity. During such periods, revolutions, insurrections, expeditions, mass migrations, and formation of new states occurred much more frequently than usual. Many of these events were so important that they virtually heralded new historical epochs in the life of humanity (Chizhevsky, 1924).


Consequently, Chizhevsky proposed to divide the eleven-year solar cycle into four periods according to the degree of the “mass excitability” associated with it: (1) a 3-year period of minimum activity (around the solar minimum) characterized by passivity and autocratic rule; (2) a 2-year period during which people “begin to organize” under new leaders and one theme; (3) a 3-year period (around the solar maximum) of “maximum excitability”, revolutions and wars; (4) a 3-year period of gradual decrease in “excitability”, until the people are apathetic. Based on his studies, Chizhevsky claimed that as much as 60 percent of the most important historical events occur in the 3-year period associated with maximum solar activity, and only 5 percent of such events occur in the 3-year period around the sunspot minimum.


Russian scientist A. Putilov empirically tested Chizhevsky’s hypothesis of the solar cycles’ impact on the historical process. He analyzed samples of near 13 thousand and 4.6 thousand events mentioned in Chronology sections of two largest Soviet historical handbooks. Events were classified into 4 groups on the basis of their "strength" and "social contradictions meaning", called tolerance and polarity: tolerant--intolerant (e.g., riot-reform) and polar-neutral (e.g., civil war-external war). It was found that frequency and polarity of historical events increased in maximum of sunspot cycle and in the next year after it, particularly when compared with the years of minimum and before minimum. The probability of revolution (the most polar and intolerant of historical event) is the highest in maximum and the lowest in the year before minimum. Intolerance of polar events increased and neutral events decreased in maximum. All these relations were highly significant (P < 0.001). It was concluded that the solar activity does impact historic events, particularly in the years of sunspot maximums (Putilov, 1992).


Our own research, though not so fundamental, confirmed a positive correlation between solar activity and revolutions. We compared annual (and monthly) series for sunspot observations with time series reflecting frequency of particular historical events during each year (and month) over 1749-2011. For this, we constructed time series for frequency of world most important revolutions and rebellions; most important political events; dates celebrated by countries as their national foundation days; and for the dates of formation of the currently existing sovereign states (counting also important changes in governance, including births of current form of government and acquisition of sovereignty). For all these four series of historical events linked to revolution and political instability, we obtained positive and statistically significant correlations with the sunspot numbers. For the annual data, the pairwise correlation ranged from 0.15 – 0.27, and were all statistically significant at 1 percent level or above (table). It is interesting to note that the bilateral correlations between thus constructed historical time series were also positive and highly statistically significant, ranging from 0.38 – 0.82. This confirmed significant overlap and mutual consistency of those series, the raw data for which came from different source, and also indirectly confirmed robustness of our results.


For those historical series where monthly data were available, the pairwise correlation with the sunspot number remained positive and statistically significant. The sunspots correlation with the series for most important political events; dates celebrated by countries as their national foundation days; and for the dates of formation of the currently existing sovereign states ranged from [0.09 – 0.10]. These correlations remained highly significant, at 1 percent or above, as they were calculated on the monthly data that provided 12 times more observation points, and the significance threshold was lower than for the annual data.


Chizhevsky’s hypothesis of the solar cycles’ impact on the mass movement and revolutions finds support from anecdotal data as well. The most important European revolutions of the XIX and XX century overlapped closely with the sunspot maximums. Remarkably, both the Great October Socialist Revolution of 1917 in the Russian Empire and the collapse of Soviet Union in 1991, which could be considered the two most important revolutions of the XX century, both occurred exactly in the years of solar maximums. In France, all the greatest revolutions of the modern times including the Great French Revolution of 1789, the revolutions of 1830 and 1849, and “Paris Commune” in 1871 overlapped very closely with the solar maximums. In America, the secession of the 13 southern US states in 1861 that triggered the bloodiest civil war in the continent’s history occurred in the year of solar maximum. Most recently, the cyclical increase in the solar activity in the currently unfolding 24th solar cycle overlapped closely with the “Arab Spring”, a series of revolutions in the Arab countries in 2010-13, and with revolution in Ukraine in 2013-14.




Division of solar cycle into four periods (by Chizhevsky)

Advent and demise of communism

French Republic timeline, 1785-1975

World revolutions, 1785-2012

Frequency of revolutions in the years of solar cycle, 1775-1995



Properties of four periods in the solar cycle

Correlation between sunspot numbers and historical events series, 1749-2011



Literature references


Chizhevsky, Alexander, 1924: "Physical Factors of the Historical Process," — Kaluga, 1924. (In Russian: А.Чижевский. «Физические факторы исторического процесса.» Калуга, 1-я Гостиполитография, 1924).


Putilov A. A., 1992: “Unevenness of distribution of historical events throughout an 11-year solar cycle”, Biofizika. 1992 Jul-Aug; 37(4):629-35. (In Russian: А.А. Путилов, «Неравномерность распределения исторических событий в пределах 11-летнего солнечного цикла», Биофизика, том 32, вып. 4, 1992).


Smelyakov, S.V., 2006: “Tchijevsky's Disclosure: How the Solar cycles Modulate the History,” — mimeo available at http://www.astrotheos.com/Page5.htm .




Solar activity hazards for human health


In his studies of the influence of the solar activity upon the terrestrial processes, Alexander Chizhevsky devoted much attention to the questions of medical geography and epidemiology. He compared the data on the epidemics and infectious disease outbreaks ranging from XIV century with the sunspot records.Chizhevsky considered both global and local Russian records for cholera, typhus, anthrax, plague, diphtheria, cerebral fever, influenza, and other diseases. He observed that the diseases intensified and the epidemics occurred more frequently around the periods of sunspot maximums than in the years of minimums. This led him to conclusion that the solar activity facilitates epidemics, somehow regulating their timing and strength.


Chizhevsky considered solar flares as a medium propagating the impact of the solar activity on earth. The frequency of flares varies in direct proportion to the number of sunspots. Actually, the flares occur in active regions around sunspots, where intense magnetic fields penetrate the sun’s photosphere to link the corona to the solar interior. The flares produce radiation across the electromagnetic spectrum at all wavelengths, from radio waves to gamma rays. Moreover, they can produce streams of highly energetic particles in the solar wind, known as a solar proton event, or "coronal mass ejection". These particles impact the earth's magnetosphere, trigger geomagnetic storms, and present an immediate radiation hazards to spacecraft and astronauts. Furthermore, Chizhevsky hypothesized that the solar flares can change ionization of the earth atmosphere, which can be either positive or harmful for humans depending on its properties.


The debates about the possible impact of conditions on the sun and in the earth’s magnetosphere on human health at the earth’s surface have intensified in the last decade. The available research and data confirm that variations of geomagnetic activity can affect human cardiovascular health. The studies suggest that geomagnetic effects are more pronounced at higher magnetic latitudes, that extremely high as well as extremely low values of geomagnetic activity seem to have adverse health effects, and that a subset of the population (10–15 percent) is predisposed to adverse health due to geomagnetic variations (Palmer et al., 2006):


A group of scientist investigated whether the sunspot periodicity correlated with the incidence of the cervical epithelial histopathologies and human physiologic functions. From January 1983 through December 2003, monthly averages were obtained for six infectious, premalignant and malignant changes in the cervical epithelium from 1,182,421 consecutive screening; and six human physiologic functions of a healthy man, which were measured about 5 times per day during about 34,500 self-measurement sessions. All six annually rhythmic infectious, premalignant and malignant cervical epithelial pathologies showed strong 10-year cycles, broadly matching solar cycle, as did all six self-measured physiologic functions. The phases (maxima) for the sixhistopathologic findings and five of six physiologic measurements were very near, or within, the first two quarters following the cyclical solar maxima (Hrushesky et al., 2011). These findings added to the growing evidence that solar magnetic storm periodicities are mirrored by cyclic rhythms of similar periods in human physiology and pathophysiology (Table).


Evidence from 6 large population-based studies in Europe and Australasia confirmed that geomagnetic storms can trigger stroke. The authors used a time-stratified case-crossover study design to analyze individual participant and daily geomagnetic activity (as measured by Ap Index) data from several large population-based stroke incidence studies (with information on 11,453 patients with stroke collected during 16,031,764 person-years of observation) in New Zealand, Australia, United Kingdom, France, and Sweden conducted between 1981 and 2004. Overall, geomagnetic storms (Ap Index 60+) were associated with 19% increase in the risk of stroke occurrence. The triggering effect of geomagnetic storms was most evident across the combined group of all strokes in those aged less than 65 years, increasing stroke risk by more than 50%. Moderate geomagnetic storms (60–99 Ap Index) were associated with a 27% increased risk of stroke occurrence, strong geomagnetic storms (100–149 Ap Index) with a 52% increased risk, and severe/extreme geomagnetic storms (Ap Index 150+) with a 52% increased risk (Feigin et al, 2014).


Most recently, a research published in January 2015 found that the life spans of people born in Norway during a solar maximum period were about five years shorter than those of people born in a solar minimum period. Using data on temporal variation in sunspot numbers and individual-based demographic data (N = 8662 births) from Norway between 1676 and 1878, while controlling for maternal effects, socioeconomic status, cohort and ecology, the research showed that solar activity (total solar irradiance) at birth decreased the probability of survival to adulthood for both men and women. On average, the lifespans of individuals born in a solar maximum period were 5.2 years shorter than those born in a solar minimum period. In addition, fertility and lifetime reproductive success (LRS) were reduced among low-status women born in years with high solar activity. The proximate explanation for the relationship between solar activity and infant mortality may be an effect of folate degradation during pregnancy caused by ultraviolet radiation (UVR). It can suppress essential molecular and cellular mechanisms during early development in living organisms and variations in solar activity during early development may thus influence their health and reproduction (Skjćrvř et al, 2015).



Summary of the conclusions


Literature references


Chizhevsky, Alexander, 1938, “Les Epidemies et les perturbations electro-magnetiques du milieu exterieur,” — Paris, Hippocrate, 1938.


Chizhevsky, Alexander, 1976: “The Terrestrial Echo of Solar Storms,” — (In Russian: А.Л.Чижевский. «Земное эхо солнечных бурь.»  Москва, Издательство «Мысль», 1976).


Feigin, Valery L., Priya G. Parmar, Suzanne Barker-Collo, Derrick A. Bennett, Craig S. Anderson, Amanda G. Thrift, Birgitta Stegmayr, Peter M. Rothwell, Maurice Giroud, Yannick Bejot, Phillip Carvil, Rita Krishnamurthi and Nikola Kasabov, 2014: “Geomagnetic Storms Can Trigger Stroke: Evidence From 6 Large Population-Based Studies in Europe and Australasia,” – Stroke, Journal of American Heart Association,  published online April 22, 2014.


Hrushesky, William J.M., Robert B. Sothern, Jovelyn Du-Quiton, Dinah Faith T. Quiton, Wop Rietveld, Mathilde E. Boon, 2011: “Sunspot Dynamics Are Reflected in Human Physiology and Pathophysiology,” — ASTROBIOLOGY,Volume 11, Number 2, 2011.


Otsu A., Chinami M., Morgenthale S., Kaneko Y., Fujita D., Shirakawa T., 2006: “Correlations for number of sunspots, unemployment rate, and suicide mortality in Japan.” — Percept Mot Skills, 2006 Apr; 102(2):603-8.


Palmer, S. J., M. J. Rycroft, M. Cermack, 2006: “Solar and geomagnetic activity, extremely low frequency magnetic and electric fields and human health at the Earth's surface,” — Surveys in Geophysics, Volume 27, Issue 5, pp.557-595.


Skjćrvř, Gine Roll; Frode Fossřy; Eivin Rřskaft, 2015: “Solar activity at birth predicted infant survival and women's fertility in historical Norway,” — Proc. R. Soc. B 2015 282 20142032; DOI: 10.1098/rspb.2014.2032. Published 7 January 2015.



Impact of uncertainty on economic conditions


Uncertainty, because it increases the value of waiting for new information, retards the current rate of investment. The nature of investor's optimal reactions to events whose implications are resolved over time is a possible explanation of the instability of aggregate investment over the business cycle (Bernanke, 1983).


Uncertainty appears to jump up after major political shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock, and the 9/11 terrorist attacks. This occurs because higher uncertainty causes firms to temporarily pause their investment and hiring. Productivity growth also falls because this pause in activity freezes reallocation across units. In the medium term the increased volatility from the shock induces an overshoot in output, employment, and productivity. Thus, uncertainty shocks generate recessions and recoveries (Bloom, 2009). Uncertainty shocks could drive business cycles (Bloom et al, 2012). First, microeconomic uncertainty is robustly countercyclical, rising sharply during recessions. Second, reasonably calibrated uncertainty shocks can explain drops and rebounds in GDP of around 3 percent in a DSGE model. Third, increased uncertainty alters the relative impact of government policies, making them initially less effective and then subsequently more effective.


But what is the causal relationship between uncertainty and growth? Does rising uncertainty drive recessions, or is uncertainty just an outcome of economic slowdowns? To determine the direction of causality, a recent study performed a simulation in which a modeled economy undergoes shocks to business conditions, and tested the effects of these shocks (Baker and Bloom, 2012). The authors built a panel of indicators for natural disasters, terrorist attacks, political shocks and revolutions. They reported that both first and second moment shocks are highly significant in driving business cycles. Specifically, their regressions revealed that the impact of revolutions on economic growth was particularly strong and highly statistically significant (Table). At the same time, their results confirmed that the economic variables cannot forecast revolutions and other factors that induce uncertainty, which confirms their exogenous status (Table).




Economic variables cannot forecast revolutions

Revolutions, volatility, returns and GDP growth



Literature references


Baker, Scott R., and Nicholas Bloom, 2012: “Does Uncertainty Reduce Growth? Using Disasters as Natural Experiments,” — draft available at http://www.stanford.edu/~nbloom/BakerBloom.pdf.


Bernanke, Ben, 1983: "Irreversibility, Uncertainty and Cyclical Investment", Quarterly Journal of Economics, 98, 85-106.


Bloom, Nicholas, 2009: “The Impact of Uncertainty Shocks,” — Econometrica, 2009.


Bloom, Nicholas, Max Floetotto, Nir Jaimovich, Itay Saporta and Stephen Terry, 2012: “Really Uncertain Business Cycles” — mimeo available at http://www.stanford.edu/~nbloom/RUBC_DRAFT.pdf.




Explanation of the empirically observed impact of the solar activity on the economy


The “physical” influence of solar activity and “space weather” on earth and human activity has long been recognized. Modern society depends heavily on a variety of technologies that are susceptible to the extremes of space weather—severe disturbances of the upper atmosphere and of the near-earth space environment that are driven by the magnetic activity of the sun. Strong auroral currents can disrupt and damage modern electric power grids and may contribute to the corrosion of oil and gas pipelines. Magnetic storm-driven ionospheric density disturbances interfere with high-frequency (HF) radio communications and navigation signals from Global Positioning System (GPS) satellites, while polar cap absorption (PCA) events can degrade—and, during severe events, completely black out—HF communications along transpolar aviation routes, requiring aircraft flying these routes to be diverted to lower latitudes. Exposure of spacecraft to energetic particles during solar energetic particle events and radiation belt enhancements can cause temporary operational anomalies, damage critical electronics, degrade solar arrays, and blind optical systems such as imagers and star trackers (National Research Council, 2008).


The effects of space weather on modern technological systems are well documented in both the technical literature and popular accounts.

1.    Most often cited perhaps is the collapse within 90 seconds of northeastern Canada’s Hydro-Quebec power grid during the great geomagnetic storm of March 1989, which left millions of people without electricity for up to 9 hours, with the damage estimates ranging widely from $4 billion to $10 billion.

2.    The outage in January 1994 of two Canadian telecommunications satellites during a period of enhanced energetic electron fluxes at geosynchronous orbit, disrupting communications services nationwide. The first satellite recovered in a few hours; recovery of the second satellite took 6 months and cost $50 million to $70 million.

3.    The diversion of 26 United Airlines flights to non-polar or less-than-optimum polar routes during several days of disturbed space weather in January 2005. The flights were diverted to avoid the risk of HF radio black- outs during PCA events. The increased flight time and extra landings and takeoffs required by such route changes increase fuel consumption and raise cost, while the delays disrupt connections to other flights.

4.    Disabling of the Federal Aviation Administration’s recently implemented GPS-based Wide Area Augmentation System (WAAS) for 30 hours during the severe space weather events of October-November 2003.

These events exemplify the dramatic impact that extreme space weather can have on a technology upon which modern society in all of its manifold and interconnected activities and functions critically depends. At the same time, the immediate economic damage produced by these events appears miniscule compared with the overall size of the world economy.


In the second half of the XIX century, British economist and statistician William Stanley Jevons developed the theory of solar variation as the explanation of the period of the trade cycle (Jevons, 1875, 1878). In his own lifetime, the commercial crises had occurred at intervals of 10-11 years (1825, 1836-39, 1847, 1857, 1866). In his paper, Jevons carried back the history of commercial crises at 10-11 intervals almost to the beginning of the XVIII century. He produced considerable evidence for the view that commercial crises had occurred at intervals of about 10˝ years, which broadly matched the solar cycle length. This" beautiful coincidence," as he called it, produced in him an unduly strong conviction of causal nexus. He linked the crisis first to harvests in Europe, and subsequently to Indian harvests, which, he argued, transmitted prosperity to Europe through the greater margin of purchasing power available to the Indian peasant to buy imported goods. But he devoted far too little attention to the exact dating of deficient harvests in relation to the dating of commercial crises, which was a necessary first step to tracing the intermediate links. Thus the details of his inductive argument were flimsy, and subsequent studies did not confirm robustness of his calculations. It is now generally agreed that, even if a harvest period can be found associated with the solar period or with more complex meteorological phenomena, this cannot afford a complete explanation of the trade cycle. Nevertheless, Jevons's notion, that meteorological phenomena play a part in harvest fluctuations and that harvest fluctuations play a part (though more important formerly than today) in the trade cycle, is not to be lightly dismissed (Keynes, 1936). In his book, Russian scientist Alexander Chizhevsky provided evidence in support of the solar variation on agricultural harvests (Chizhevsky, 1976). Chizhevsky listed the impact on harvest among about 27 series that exhibited fluctuations broadly following cyclical changes in the solar activity. However, subsequent studies did not confirm the influence of the solar activity on harvests (Garcia-Mata and Shaffner, 1934).


Curiously, even morning sunshine can have a tangible impact on economy. A research examined the relation between morning sunshine at a country’s leading stock exchange and stock returns that day at 26 stock exchanges internationally from 1982-97. It found out that the sunshine is strongly significantly correlated with daily stock returns, and hypothesized that the sunny weather was associated with upbeat mood on the trading floor (Hirshleiferand Shumway, 2001).


Moreover, another research documented the impact of geomagnetic storms on daily stock market returns. The research found strong empirical support in favor of a geomagnetic-storm effect in stock returns after controlling for market seasonals and other environmental and behavioral factors. Unusually high levels of geomagnetic activity have a negative, statistically and economically significant effect on the following week’s stock returns for all U.S. stock market indices. Finally, there is evidence of substantially higher returns around the world during periods of quiet geomagnetic activity (Krivelyova andRobotti, 2003). This research builds upon a large body of psychological literature that has shown that geomagnetic storms have a profound effect on people’s moods, and, in turn, people’s moods relate to human behavior, judgments and decisions about risk. An important finding of this literature is that people often attribute their feelings and emotions to the wrong source, leading to incorrect judgments. Specifically, people affected by geomagnetic storms may be more inclined to sell stocks on stormy days because they incorrectly attribute their bad mood to negative economic prospects rather than bad environmental conditions. Misattribution of mood and pessimistic choices can translate into a relatively higher demand for riskless assets, causing the price of risky assets to fall or to rise less quickly than otherwise.



Literature references


Belkin, Vladimir Alexeevich, 2017: “Oil and Solar Cycles: Statistics of Strong Ties (1970–2016 Years),” – Chelyabinsk Humanitarian, 2017, No. 1 (38), pages 17-27.


Belkin, Vladimir Alexeevich, 2015: “Cycles of Oil Prices and Magnetic Storms: Mechanism and Facts of Strong Ties (1861-2015 Years),” – Chelyabinsk humanities, 2015, No. 3 (32), pages 17-31.


Belkin, Vladimir Alexeevich, 2015: “Macroeconomic Indicators and Solar Activity Cycles: Mechanism and Facts of Strong Ties (1867-2014 Years),” – Chelyabinsk humanities, 2015, №2 (31), pages 17-27.


Chizhevsky, Alexander, 1938, “Les Epidemies et les perturbations electro-magnetiques du milieu exterieur,” — Paris, Hippocrate, 1938.


Chizhevsky, Alexander, 1976: “The Terrestrial Echo of Solar Storms,” — (In Russian: А.Л.Чижевский. «Земное эхо солнечных бурь.»  Москва, Издательство «Мысль», 1976).


Dewey, Edward, 1968: “Economic and Sociological Phenomena Related to Solar Activity and Influence,” — “Cycles Magazine,” 1968, Volume 19 Number Nine (1968V19_9Sep), page 201.


Garcia-Mata, Carlo, and Felix I. Shaffner, 1934: “Solar and Economic Relationships: A Preliminary Report,” — The Quarterly Journal of Economics, Vol. 49, No. 1, Nov., 1934.


Hirshleifer, David, and Tyler Shumway, 2001: “Good Day Sunshine: Stock Returns and the Weather,” — mimeo available at http://www-personal.umich.edu/~shumway/papers.dir/weather.pdf.


Keynes, John Maynard, 1936: “William Stanley Jevons 1835-1882: A Centenary Allocution on his Life and Work as Economist and Statistician,” — Journal of the Royal Statistical Society, Vol. 99, No. 3 (1936), pp. 516-555.


Krivelyova, Anna, and Cesare Robotti, 2003: “Playing the Field: Geomagnetic Storms and the Stock Market,” — Federal Reserve Bank of Atlanta, Working Paper 2003-5b, October 2003.


National Research Council, 2008: “Severe Space Weather Events—Understanding Societal and Economic Impacts: A Workshop Report,” — Committee on the Societal and Economic Impacts of Severe Space Weather Events: A Workshop, The National Academies Press, Washington, DC.


Jevons, William Stanley, 1875: “Influence of the Sun-Spot Period on the Price of Corn,” — A paper read at the meeting of the British Association, Bristol, 1875.


Jevons, William Stanley, 1878: “Commercial crises and sun-spots,” — “Nature,” Volume xix, November 14, 1878, pp. 33-37.


Jevons, William Stanley, 1879: “Sun-Spots and Commercial Crises,” — “Nature,” Volume xix, April 24, 1879, pp. 588-590.


Jevons, William Stanley, 1882: “The Solar-Commercial Cycle,” — “Nature,” Volume xxvi, July 6, 1882, pp. 226-228.


Poluyakhtov, S., and V. Belkin, 2011: “Solar Activity Cycles as the Foundation of the Bank Interest Rate Cycle.” (In Russian:  С. А.Полуяхтов, В. А. Белкин. «Циклы солнечной активности как основа циклов банковской процентной ставки». Вестник Челябинского государственного университета. 2011. № 6 (221). Экономика, Вып. 31, с.39–43.).


Poluyakhtov, S., and V. Belkin, 2011: “Non-traditional Theories of Periodicity: Solar System Cycle and Economy Development Cycle  (In Russian: Белкин В.А., Полуяхтов С.А. «Нетрадиционные теории цикличности: цикличность солнечной активности и цикличность развития экономики» — Научный вестник Уральской академии государственной службы, Выпуск №2(15), июнь 2011г.).


Walsh, Bryan, 1993: “Economic Cycles and Changes in the Earth's Geomagnetic Field,” — “Cycles Magazine”, 1993, Volume 44 Number two (1993 V44_2 May).








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