What is economics?

Human decisions as the outcome of preferences and restrictions

In his 1932 book An Essay on the Nature and Significance of Economic Science, Lionel Robbins famously defined economics as “the science which studies human behaviour as a relationship between ends and scarce means which have alternative uses”. This definition remains accurate today, even if contemporary economic terminology differs slightly: we typically use the term preferences for the “ends” and the term restric­tions (or constraints) for the “scarce means which have alternative uses” that Robbins identifies.

By focusing on humans’ behaviour, Robbins’s definition characterises economics as a social science. Indeed, present-day economics studies how humans make decisions in all areas of life: when they act as consumers, as employees, as employers, as managers, as investors, as parents, as members of society, as members of a team, or as political decision-makers, to provide just a few examples.

Restrictions are shaped not only by natural resources, but also by laws and their enforcement, social norms, available information, education and cognitive resources

Robbins’s definition captures that human behaviour is inevitably shaped by the available resources – the “scarce means which have alternative uses”. This includes not only physical resources but also the technology and knowledge to make use of physical resources: oil fields are of no use if you are unable to extract and transport the oil; similarly, machines and IT equipment are only useful if you know how to use them. As a consequence, political, societal and educational institutions play a crucial role in shaping the restrictions that economic actors face.

The economically relevant restrictions are also profoundly shaped by the legal system. In modern economies, this includes ownership of physical assets as well as norms regarding intellectual property and collected data. The rule of law is particularly important when it comes to investments: the transparency – or arbitrariness – of governmental decisions and the impartiality – or favouritism – of court rulings influence the anticipated returns to investments in both physical and human capital. Viewed more broadly, economic activity is shaped by both legal and social norms that generate trust: trust in not being taken advantage of by fellow human beings (an important concept in this context is that of “incomplete contracts”) and trust in the stability and fairness of the legal and political system.

Evidently, the legal and political environment is ever changing:

• Technological progress influences production technologies and employment opportunities.
• Institutions like the EU, currency unions and the World Trade Organization are established, change over time and may be dissolved.
• Free-trade agreements are signed or terminated.
• Worker rights are strengthened or weakened; migration is promoted or restricted; gender equality can be high up on the political agenda or absent from it.
• The design of social-security systems (e.g., health insurance, unemployment benefits) is put under scrutiny.
• Severe crises like wars, pandemics and climate change force people, political decision-makers and institutions to adapt.

This means that there are no “eternal truths” in economic analysis: as societies evolve, economics evolves. It also means that economists frequently incorporate insights from neighbouring disciplines into their analyses.

Focus on market economies

With its emphasis on human behaviour, economics focuses on market economies. Only when individuals and the companies that they establish are free to choose between alternative uses of their time, talents and capital does it make sense to investigate the motives and incentives behind their actions.

This does not rule out also addressing questions of socialism versus capitalism in class – but the vast majority of economic research and teaching is concerned with market economies.

Markets, market failure and policy failure

An fundamental characteristic of markets is that they generate prices for the traded goods. And an absolutely funda­mental characteristic of these prices is their role of signaling the relative scarcity of the traded resources and prod­ucts. Prices thereby have the crucial role of providing incentives for economic actors, for instance, to acquire par­tic­ular knowledge, to explore and develop new re­sources and to work in particular professions. 

Of course, not all markets function equally well, and their outcomes may be more or less desirable. Much of eco­nom­ics is devoted to analysing the causes of market imperfections – also called partial market failure – and to iden­ti­fy­ing potential remedies. In some cases, markets may fail to exist altogether; economists then speak of complete market failure or missing markets. Market failure can arise from market power, barriers to entry, incomplete information or externalities, and it provides a rationale for public policy to step in.

At the same time, regulatory interventions can pose risks to well-functioning markets. Policy interventions – particularly direct price restrictions in the form of price floors or caps – may prevent prices from fulfilling their fundamental role of signalling relative scarcity. This, in turn, can distort incentives and lead to inefficient market outcomes.

The ubiquity of externalities

A major obstacle to the efficient functioning of markets is the presence of externalities. An externality arises when­ever an action affects others without compensation being paid. Externalities, both positive and negative, are ubiq­ui­tous. Even sleeping in one’s own bed can generate a negative externality, if the sleeper’s snoring keeps someone else awake. At the same time, people continuously create positive externalities around the world by helping one another without demanding compensation. One might even argue that cooperating for the common good, and overcoming selfishness in the process, is the essence of civilisation and peaceful coexistence.

Externalities matter at the individual level and for economic activity at the societal level. Since externalities can accumulate, taking them into account is of first-order importance. Their relevance naturally varies across contexts. Examples of activities involving substantial externalities – and of selected policy remedies designed to “internalise” them – are:

• pollution in general, and greenhouse gas emissions in particular (motivating the creation of emissions trading systems);
• innovation and skill accumulation that lead to technological and knowledge spillovers which foster economic growth and prosperity (motivating publicly funded education and tax incentives for research and development);
• collaboration in teams;
• the effects of one country’s actions on the resources and prices faced by other countries (creating a role for international fiscal and monetary policy coordination);
• unpaid domestic care work, such as childcare and eldercare (creating a case for recognising care respon­si­bilities in the design of social-security systems);
• the transmission of infectious diseases (with vaccinations serving as both preventive and rapid-response counter­measures); and
• network effects, for instance of social-media platforms.

In addition to verbal arguments, economics relies heavily on diagrams and formal mathematical methods to analyse human behaviour and economic systems. There are several reasons for this:

Reason no. 1: Quantitative questions

Many questions in economics are of a quantitative nature. For instance, a government considering a change in tax rates will not only want to know whether tax revenues will go up or down in response to the envisioned change but also how much they will rise or decline. Similarly, a government that contemplates subsidising renewable energies will want to know how much energy production will change, because large changes may require investments into the power grid and other infrastructure.

Quantitative assessments are also key in the private sector. Any insurance company, for example, has to forecast both the magnitude and likelihood of claims to determine which policies it offers.

The inherently quantitative nature of many questions faced by economic actors and regulators is the first reason why economics relies strongly on formal mathematical models.^[1]

[1] Joseph Schumpeter (“The Common Sense of Econometrics”, Econometrica 1, no. 1, 1933: 5–12) considers eco­nom­ics as “the quantitative science” due to the very nature of its object of analysis: “There is … one sense in which eco­nom­ics is the most quantitative, not only of ‘social’ or ‘moral’ sciences, but of all sciences, physics not excluded. … Some of the most fundamental economic facts … present themselves to our observation as quantities made numerical by life itself. They carry meaning only by virtue of their numerical character. There would be movement even if we were unable to turn it into measurable quantity, but there cannot be prices independent of the numerical expression of every one of them, and of definite numerical relations among all of them.”

Reason no. 2: Empirical analysis

A second benefit of mathematical modelling is the ability to confront theoretical predictions with real-world data. Empirically testing theoretical predictions makes it necessary to collect data and calculate indicators of economic activity. Examples are a country’s gross domestic product (GDP), its trade balance, its inflation rate, its wage distribution and its unemployment rate. This requires precise definitions of how the respective indicators are constructed and how they relate to the theoretical quantities. Both necessitate the use of mathematics.

To assess the descriptive accuracy of theoretical models, economists employ a wide array of statistical methods to analyse empirical data. This branch of economics is called econometrics.^[2] Moreover, to establish causality between variables of interest, economists exploit natural ex­per­i­ments and quasi-experimental settings, which requires the use of advanced statistical methods. In addition to the analysis of field data, economists conduct randomised controlled trials (RCTs) in the form of lab, on­line, survey and field experiments. Experiments, of course, also rely on theory-driven hypothesising and on statistical analysis.

[2] Econometrics is the derivation of statistical models from sufficiently detailed theoretical models of economic phenomena and the application of these statistical models to suitable empirical data. See also Paul A. Samuelson, Tjalling C. Koopmans and John R. N. Stone (“Report of the Evaluative Committee for Econometrica”, Econometrica 22, no. 2, 1954: 141–146): “In these terms econometrics may be defined as the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference.”

Reason no. 3: Transparent modelling of restrictions, incentives and inter­dependencies between markets

The third reason why formal mathematical modelling plays an important role in economics has two components:

1. All economic decisions are made subject to restrictions – be it available physical resources, monetary budgets, time budgets or incomplete information.
2. Many questions in economics require the simultaneous analysis of multiple markets. The method most commonly used for this purpose is general-equilibrium analysis.

As an illustration of the two components, consider a change in a country’s tax system. Such a change will not only influence the country’s tax revenues but also its credit­worthi­ness and its government’s capacity to fund projects. As far as economic activity is concerned, the change in the tax system will influence the markets for both taxed and untaxed products. On the taxpayers’ side, it will alter their disposable income. Consequently, a change in the tax system shapes both labour supply and labour demand and, not least, investment opportunities. In short, the economy as a whole is impacted.

Meaningful economic analysis has to take such interdependencies between markets as well as between private and government activity into account. Obviously, it should do so in a manner that avoids contradictions and omissions. Using the language of mathematics helps us achieve exactly that. Economic analysis thereby specifies as clearly as possible the constraints that actors face and the incentives under which they operate.

Reason no. 4: Analysing strategic interaction

The fourth reason for the use of formal mathematical methods is the modelling of strategic interaction between individual economic agents. This branch of decision analysis is called game theory. (A pioneer in this field was Nobel laureate Reinhard Selten, a long-standing member of the Department of Economics at the University of Bonn.)

The agents under consideration can be coworkers, politicians competing for votes, companies, entire countries, labour unions or any other type of organisation. Strategic interaction arises, for instance, in settings where a limited number of agents competes for an exclusive opportunity (e.g., job promotions or spectrum auctions), where agents with only partially aligned interests interact (classical principal–agent problems, e.g., employer–employee or patient–clinician relationships), and where agents need to cooperate to achieve collective benefits in the presence of externalities (e.g., team production, pollution and greenhouse gas emissions).

Positive economics

One part of economic analysis concerns the – judgement-free – analysis of the consequences of decisions of economic actors. This branch of economics is often called positive economics or descriptive economics. It might, for instance, attempt to answer the question “What happens/will happen to wages, employment and product prices if the minimum wage is increased by 10%?” An important aspect in this endeavour is identifying situations in which individual incentives and the promotion of social welfare are misaligned.

Normative economics

Deeply interwoven with the descriptive analysis is a second branch of economic analysis that is often called normative economics. Normative economics investigates the conditions under which domestic and international markets work well, and it reflects on the question whether regulation is indicated to improve their functioning. Example questions are:

• “Does it make sense to tax emissions? And if so, what is an appropriate tax rate?”
• “Under which circumstances does a minimum wage make sense?”
• “How should we design social-security systems in view of their insurance function and incentive effects?”
• “Do we need mandatory health insurance?”
• “Should we subsidize particular sectors of our economy and levy tariffs on imported goods?”
• “Should we manage the economy via fiscal and/or monetary policy?”
• “Should we regulate financial markets?”
• “Should central banks be independent of the government?”

Informing democratic decision-making

Not only normative economics but also positive economics provides important input to shaping political views and democratic decision-making. It enables us to assess, ex ante, whether a proposed policy is likely to achieve its intended effects – regardless of whether we endorse the intention – and to evaluate, ex post, whether a policy has delivered on what policy-makers promised. More broadly, studying economics equips you to assess evidence and to formulate as well as evaluate justifications for political positions. It also fosters an appreciation of the value of reliable data for evidence-based policy-making and democratic decision-making, thereby underscoring the importance of statistical authorities that operate free from governmental interference.

Collaboration with neighbouring disciplines

To advance their methodological toolkit, researchers at the Department of Economics work with scholars from other quantitative disciplines, including

• mathematics,
• statistics and data science, and
• computer science.

In addition, reflecting the fact that economics is a social science, economists at our department collaborate with researchers from a wide range of related fields, such as

• business administration,
• history,
• political science,
• law,
• social and cognitive psychology, and
• neuroscience.

Two prominent examples: formation of beliefs and preferences

A core field of economic research in which insights from neighbouring disciplines are highly relevant is belief formation, often also referred to as expectations formation. Beliefs constitute a third central economic concept alongside preferences and restrictions. They describe the mental models economic actors hold about how the world works.

Beliefs are relevant whenever individuals – or firms or governments – interact with others and whenever uncertain future outcomes matter. In strategic interactions, one needs to anticipate what an opponent, collaborator or competitor will do. And in decisions involving future consequences, individuals must form expectations about the likelihood of different possible outcomes.

The latter category includes not only saving and investment decisions, but also choices related to education and health. In all these cases, individuals must form beliefs about how the probability of future outcomes depends on actions taken today. For example:

• “If I start saving and investing €10 per day now, how likely is it that I will enter retirement with at least €150,000 in my account?”
• “How much does my expected wage change if I study chemical engineering rather than economics?”
• “If my company spends an additional €5 million on research and development now, by how much can we expect profit to increase over the next 10 years?”
• “How do my food choices affect my likelihood of remaining healthy or developing cardiovascular disease?”
• “Should I allow my child to spend the next 30 minutes browsing social media rather than preparing for an upcoming exam?”

Economists studying how people form such expectations often draw on insights from psychology, sociology and political science, in particular regarding

• cognitive limitations and imperfect memory,
• the allocation of attention (see, for instance, the “rational inattention” approach in macroeconomics, pioneered by Nobel laureate Christopher Sims),
• the informational environment and
• emotional influences.

Similarly, research on preferences frequently incorporates insights from psychology, especially when it comes to how preferences are shaped or revised. Prominent examples include

• other-regarding preferences,
• social comparisons and attitudes towards inequality,
• preferences over uncertain outcomes, such as ambiguity aversion and loss aversion, as well as
• intertemporal preferences, where psychological concepts such as habituation and limited self-control as a source of present bias help explain patterns in human decision-making.