In many contexts, events like earthquakes, epidemics and major weather catastrophes pose aggregate risks that affect not only the distribution but also the total amount of resources.
Systematic or aggregate risk arises from market structure or dynamics which produce shocks or uncertainty faced by all agents in the market; such shocks could arise from government policy, international economic forces, or acts of nature.
In some cases, aggregate risk exists due to institutional or other constraints on market completeness.
For countries or regions lacking access to broad hedging markets, events like earthquakes and adverse weather shocks can also act as costly aggregate risks.
Robert Shiller has found that, despite the globalization progress of recent decades, country-level aggregate income risks are still significant and could potentially be reduced through the creation of better global hedging markets (thereby potentially becoming idiosyncratic, rather than aggregate, risks).
[2] Specifically, Shiller advocated for the creation of macro futures markets.
The benefits of such a mechanism would depend on the degree to which macro conditions are correlated across countries.
Systematic risk plays an important role in portfolio allocation.
Over the long run, a well-diversified portfolio provides returns which correspond with its exposure to systematic risk; investors face a trade-off between expected returns and systematic risk.
Investors can only reduce a portfolio's exposure to systematic risk by sacrificing expected returns.
An important concept for evaluating an asset's exposure to systematic risk is beta.
On the other hand, an investor who invests all of his money in one industry whose returns are typically uncorrelated with broad market outcomes (beta close to zero) has limited his exposure to systematic risk but, due to lack of diversification, is highly vulnerable to idiosyncratic risk.
Fiscal, monetary, and regulatory policy can all be sources of aggregate risk.
In some cases, shocks from phenomena like weather and natural disaster can pose aggregate risks.
Small economies can also be subject to aggregate risks generated by international conditions such as terms of trade shocks.
Aggregate risk has potentially large implications for economic growth.
For example, in the presence of credit rationing, aggregate risk can cause bank failures and hinder capital accumulation.
[4] Banks may respond to increases in profitability-threatening aggregate risk by raising standards for quality and quantity credit rationing to reduce monitoring costs; but the practice of lending to small numbers of borrowers reduces the diversification of bank portfolios (concentration risk) while also denying credit to some potentially productive firms or industries.
As a result, capital accumulation and the overall productivity level of the economy can decline.
Modelers often incorporate aggregate risk through shocks to endowments (budget constraints), productivity, monetary policy, or external factors like terms of trade.
Idiosyncratic risks can be introduced through mechanisms like individual labor productivity shocks; if agents possess the ability to trade assets and lack borrowing constraints, the welfare effects of idiosyncratic risks are minor.
This can be the case in models with many agents and strategic complementarities;[5] situations with such characteristics include: innovation, search and trading, production in the presence of input complementarities, and information sharing.
[6] Consider a simple exchange economy with two identical agents, one (divisible) good, and two potential states of the world (which occur with some probability).
If allowed to do so, agents make trades such that their consumption is equal in either state of the world.
This is the well-known finance result that the contingent claim that delivers more resources in the state of low market returns has a higher price.
While the inclusion of aggregate risk is common in macroeconomic models, considerable challenges arise when researchers attempt to incorporate aggregate uncertainty into models with heterogeneous agents.
In this case, the entire distribution of allocational outcomes is a state variable which must be carried across periods.
One approach to the dilemma is to let agents ignore attributes of the aggregate distribution, justifying this assumption by referring to bounded rationality.
[7][8] Researchers should carefully consider the results of accuracy tests while choosing solution methods and pay particular attention to grid selection.
This is also known as inherent, planned, event or condition risk caused by known unknowns such as variability or ambiguity of impact but 100% probability of occurrence.