What Is Applied Economics?

Applied economics applies the conclusions drawn from economic theories and empirical studies to real-world situations with the desired aim of informing economic decisions and predicting possible outcomes. The purpose of applied economics is to improve the quality of practice in business, public policy, and daily life by thinking rigorously about costs and benefits, incentives, and human behavior. Applied economics can involve the use of case studies and econometrics, which is the application of real-world data to statistical models and comparing the results against the theories being tested.

Understanding Applied Economics

Applied economics is the application of economic theory to determine the likely outcomes associated with various possible courses of action in the real world. By better understanding the likely consequences of choices made by individuals, businesses, and policy makers, we can help them make better choices. If economics is the science of studying how people use various, limited means available to them to achieve given ends, then applied economics is the tool to help choose the best means to reach those ends. As a result, applied economics can lead to “to do” lists for steps that can be taken to increase the probability of positive outcomes in real-world events.

The use of applied economics may first involve exploring economic theories to develop questions about a circumstance or situation and then draw upon data resources and other frames of reference to form a plausible answer to that question. The idea is to establish a hypothetical outcome based on the specific ongoing circumstances, drawn from the known implications of general economic laws and models.

Applied Economics Relevance in the Real World

Applied economics can illustrate the potential outcomes of financial choices made by individuals. For example, if a consumer desires to own a luxury good but has limited financial resources, an assessment of the cost and long-term impact such a purchase would have on assets can compare them to the expected benefit of the good. This can help determine if such an expense is worthwhile. Beyond finances, understanding the meaning of the economic theories of rational choice, game theory, or the findings of behavioral economics and evolutionary economics can help a person make better decisions and plan for success in their personal life and even relationships. For example, a person who wants to quit smoking might recognize that they are prone to hyperbolic discounting and might choose to employ precommitment strategies to support their long-term preference to quit over more powerful short-term preferences to smoke. Or a group of friends sharing a large bowl of popcorn might explicitly or implicitly agree to limits or shares on how much popcorn each will take in order to avoid a tragedy of the commons situation.

Applied economics can also help businesses make better decisions. Understanding the implications of economic laws of supply and demand combined with past sales data and marketing research regarding their target market can help a business with pricing and production decisions. Awareness of economic leading indicators and their relationship to a firm’s industry and markets can help with operational planning and business strategy. Understanding economic ideas such as principal-agent problems, transaction costs, and the theory of the firm can help businesses design better compensation schemes, contracts, and corporate strategies. 

Applied economics is an invaluable tool for public policy makers. Many economists are employed to predict both the macro- and microeconomic consequences of various policy proposals or to evaluate the effects of ongoing policy. Applied macroeconomic modeling is routinely used to project changes in unemployment, economic growth, and inflation at the national, regional, and state level. Understanding the way the economic incentives and compensating behaviors created by public policy impact real-world trends in things like job growth, migration, and crime rates is critical to implementing effective policy and avoiding unintended consequences. For example, understanding what the application of the laws of supply and demand imply about the effects of price floors, along with case studies and empirical research, can inform better policy regarding minimum wage laws.

What Is an Anomaly?

In economics and finance, an anomaly is when the actual result under a given set of assumptions is different from the expected result predicted by a model. An anomaly provides evidence that a given assumption or model does not hold up in practice. The model can either be a relatively new or older model.

Understanding Anomalies

In finance, two common types of anomalies are market anomalies and pricing anomalies. Market anomalies are distortions in returns that contradict the efficient market hypothesis (EMH). Pricing anomalies are when something—for example, a stock—is priced differently than how a model predicts it will be priced.

Common market anomalies include the small-cap effect and the January effect. The small-cap effect refers to the small company effect, where smaller companies tend to outperform larger ones over time. The January effect refers to the tendency of stocks to return much more in the month of January than in others.

Anomalies also often occur with respect to asset pricing models, in particular, the capital asset pricing model (CAPM). Although the CAPM was derived by using innovative assumptions and theories, it often does a poor job of predicting stock returns. The numerous market anomalies that were observed after the formation of the CAPM helped form the basis for those wishing to disprove the model. Although the model may not hold up in empirical and practical tests, it still does hold some utility.

Anomalies tend to be few and far between. In fact, once anomalies become publicly known, they tend to quickly disappear as arbitragers seek out and eliminate any such opportunity from occurring again.

Types of Market Anomalies

In financial markets, any opportunity to earn excess profits undermines the assumptions of market efficiency, which states that prices already reflect all relevant information and so cannot be arbitraged.

January Effect

The January effect is a rather well-known anomaly. According to the January effect, stocks that underperformed in the fourth quarter of the prior year tend to outperform the markets in January. The reason for the January effect is so logical that it is almost hard to call it an anomaly. Investors will often look to jettison underperforming stocks late in the year so that they can use their losses to offset capital gains taxes (or to take the small deduction that the IRS allows if there is a net capital loss for the year). Many people call this event tax-loss harvesting.

As selling pressure is sometimes independent of the company’s actual fundamentals or valuation, this “tax selling” can push these stocks to levels where they become attractive to buyers in January.

Likewise, investors will often avoid buying underperforming stocks in the fourth quarter and wait until January to avoid getting caught up in the tax-loss selling. As a result, there is excess selling pressure before January and excess buying pressure after Jan. 1, leading to this effect.

September Effect

The September effect refers to historically weak stock market returns for the month of September. There is a statistical case for the September effect depending on the period analyzed, but much of the theory is anecdotal. It is generally believed that investors return from summer vacation in September ready to lock in gains as well as tax losses before the end of the year.

There is also a belief that individual investors liquidate stocks going into September to offset schooling costs for children. As with many other calendar effects, the September effect is considered a historical quirk in the data rather than an effect with any causal relationship. 

Days of the Week Anomalies

Efficient market supporters hate the “Days of the Week” anomaly because it not only appears to be true, but it also makes no sense. Research has shown that stocks tend to move more on Fridays than Mondays and that there is a bias toward positive market performance on Fridays. It is not a huge discrepancy, but it is a persistent one.

The Monday effect is a theory which states that returns on the stock market on Mondays will follow the prevailing trend from the previous Friday. Therefore, if the market was up on Friday, it should continue through the weekend and, come Monday, resume its rise. The Monday effect is also known as the “weekend effect.”

On a fundamental level, there is no particular reason that this should be true. Some psychological factors could be at work. Perhaps an end-of-week optimism permeates the market as traders and investors look forward to the weekend. Alternatively, perhaps the weekend gives investors a chance to catch up on their reading, stew and fret about the market, and develop pessimism going into Monday.

Superstitious Indicators

Aside from calendar anomalies, there are some non-market signals that some people believe will accurately indicate the direction of the market. Here is a short list of superstitious market indicators:

• The Super Bowl Indicator: When a team from the old American Football League wins the game, the market will close lower for the year. When an old National Football League team wins, the market will end the year higher. Silly as it may seem, the Super Bowl indicator was correct almost three-quarters of the time over a 53-year period ending in 2021. However, the indicator has one limitation: It contains no allowance for an expansion-team victory!
• The Hemline Indicator: The market rises and falls with the length of skirts. Sometimes this indicator is referred to as the “bare knees, bull market” theory. To its merit, the hemline indicator was accurate in 1987, when designers switched from miniskirts to floor-length skirts just before the market crashed. A similar change also took place in 1929, but many argue as to which came first, the crash or the hemline shifts.
• The Aspirin Indicator: Stock prices and aspirin production are inversely related. This indicator suggests that when the market is rising, fewer people need aspirin to heal market-induced headaches. Lower aspirin sales should indicate a rising market.

What Is Asymmetric Information?

Asymmetric information, also known as “information failure,” occurs when one party to an economic transaction possesses greater material knowledge than the other party. This typically manifests when the seller of a good or service possesses greater knowledge than the buyer; however, the reverse dynamic is also possible. Almost all economic transactions involve information asymmetries.

Understanding Asymmetric Information

Asymmetric information exists in certain deals with a seller and a buyer whereby one party is able to take advantage of another. This is usually the case in the sale of an item. For example, if a homeowner wanted to sell their house, they would have more information about the house than the buyer. They might know some floorboards are creaky, the home gets too cold in winter, or that the neighbors are too loud; information that the buyer would not know until after they purchased the house. The buyer, then, might feel they paid too much for the house or would not have purchased it at all if they had this information beforehand.

Asymmetric information can also be viewed as the specialization and division of knowledge, as applied to any economic trade. For example, doctors typically know more about medical practices than their patients. After all, physicians have extensive medical school educational backgrounds that their patients generally don’t have. This principle equally applies to architects, teachers, police officers, attorneys, engineers, fitness instructors, and other trained professionals. Asymmetric information, therefore, is most often beneficial to an economy and a society in increasing efficiency.

Advantages and Disadvantages of Asymmetric Information

Advantages

Asymmetric information isn’t necessarily a bad thing. In fact, growing asymmetrical information is the desired outcome of a healthy market economy. As workers strive to become increasingly specialized in their chosen fields, they become more productive, and can consequently provide greater value to workers in other fields.

For example, a stockbroker’s knowledge is more valuable to a non-investment professional, such as a farmer, who may be interested in confidently trading stocks to prepare for retirement. On the flip side, the stockbroker does not need to know how to grow crops or tend to livestock to feed themself, but rather can purchase the items from a grocery store that are provided by the farmer.

In each of their respective trades, both the farmer and the stockbroker hold superior knowledge over the other, but both benefit from the trade and the division of labor.

One alternative to ever-expanding asymmetric information is for workers to study all fields, rather than specialize in fields where they can provide the most value. However, this is an impractical solution, with high opportunity costs and potentially lower aggregate outputs, which would lower standards of living.

Disadvantages

In some circumstances, asymmetric information may have near fraudulent consequences, such as adverse selection, which describes a phenomenon where an insurance company encounters the probability of extreme loss due to a risk that was not divulged at the time of a policy’s sale.

For example, if the insured hides the fact that they’re a heavy smoker and frequently engage in dangerous recreational activities, this asymmetrical flow of information constitutes adverse selection and could raise insurance premiums for all customers, forcing the healthy to withdraw. The solution is for life insurance providers to perform thorough actuarial work and conduct detailed health screenings, and then charge different premiums to customers based on their honestly disclosed risk profiles.

Special Considerations

To prevent abuse of customers or clients by finance specialists, financial markets often rely on reputation mechanisms. Financial advisors and fund companies that prove to be the most honest and effective stewards of their clients’ assets tend to gain clients, while dishonest or ineffective agents tend to lose clients, face legal damages, or both.