IEBE Final Exam

What is economics?

the study of how people and society end up choosing to employ scarce productive resources that could have alternative uses, to produce various ccommodities and distribute them from consumpiton among various persons and groups in society. Economics analyses the costs and benefits of improving patterns of resource use.

Multidisciplinary Nature of Econ

• Queen of Social Sciences: phsycology, political science, sociology history

• Pshycohology: behaviour economics

• Political Science: policy

• Sociology: social issues like poverty and inequality

• Mathematical/Engineering approaches

Economics as a Science vs as an art

Science: systematically studies economic behaviour and phenomena using theories, nomdels and empirical evidence to explain relationships and test hypothesis

• Develops theories and models to explain phenomena: mdels simplify complex reality so that erlationships can be studied

• Empirical evidience: data, stats, experiments to make predictions —> Frisch and Tinbergen

• Test explanations and improves knowledge

Normative and Positive

Art: involves applying economics knowledge and judgment to pratical problems such as choosing policies to reduce unemployment or inflation. Requires deciding how to use knowledge in particular circumstances

• Economics knowlegde must be applied to real world problems

• Policy decisions involve judgment

• Economic advice depends on context and objectives

One vs the other would be an example of a doctor and medicine.

Methods to Econ

• Mathematical reasoning

• Statistical analysis

• Modeling

• Experimental method

  • Case study

Explain how Samuelson’s discussion of “theoretical spectacles” is mirrored by Kuhn’s concept of scientific “paradigms”.

Paradigm shift: fundamental change in basic conceps, assumptions and practices of a science discipline. Demonstrates how science moves through stages rather than linear development. eg. Industrial rev

Theatrical spectacles: preexisting knowledge infleinces that way people approach present issues. By using knowledge of past perspectives, economists filter their interpretations and adapt their knowledge (gestalt theory)

Link: Both of these concepts use precedented patterns where shared concepts are used as a framework towards future solutions.

• Theatrical spectacles: previous knowledge shapes the persons perspective on something so they will consider it when looking towards a future solution.

• Paradigm shift: if scientists' theoretical frameworks influence how they see reality, changing the framework can change how they see that same reality. The paradigm shift is essentially a change in the “spectacles” through which scientists view the world.

Samuelson’s aspects of reasoning, methods, and tools used in economics

• Historical perspective: understanding economic and social phenomena requires considering their historical development.

• Statistics and probability: importance in applying economic theory to real-world problems.

• Mathematics: mathematics plays a role in economics, particularly in more advanced theoretical work

Main Differences Between normal-science/textbook problems and wicked problems

Normal-science textbook problems:

• clearly defined

• possible solution

• Eg: Calculate the profit-maximising output of a firm given its demand and cost functions.

Wicked problems

• Ambiguous: The problem itself may be difficult to define.

• no definitive formulation or universally correct solution

• no enumerable set of solution

• tradeoffs

• Eg: Reduce income inequality, which involves conflicting interests, political choices, social values and potentially unintended consequences.

Post-Hoc Fallacy

Due to identification limitation our quantative economic knowledge is far from complete

• Logiacal error where you assume that beacuse one event followed another, first event caused second

• EG: A government imposes import tariffs, and consumer prices rise soon after. Concluding that the tariffs were the sole cause of inflation ignores global oil price surges or post-pandemic supply chain crunches

Tyranny of Words

different words but similar meaning or vise versa creates a confusion/misunderstanding. this is why scientifc discussion is needed to remove misunderstanding

Fallacy of Composition

error made in reasoning stating that even though one thing might be application to one exampke, does not mean it is true to everything put together as a whole.

• true for one account but not necessarity true for all

• Eg. company lays off workers or lowers wages to cut costs. If all companies do this, overall consumer purchanisng power collapses, hurting sales across businesses.

Positive, normative and Art

• Positive: description and explanations of economic data and results. “what is”. objective facts and empirical dimensions

• Normative: value judgment about economic policies and outcomes. "what ought to be" involving subjective opinions and beliefs.

• Art: bridges positive and normative economics. action/application oriented taking facts from positive and desired goals of normative to apply a model to a policy “how it do it”

Business Cycle

• used as a method of observation of how events influence the economy at a specific time.

• Demonstrates observation in economics: find the underlying mechanism and then see how to control it, explain it and mathematize it

Econometrics

advancement of economic theory in its relation to statistics and math

started with explicit aim of being a science

objective: theoretical-quantative and exmpirical quantatic approach to economic problems

Allais Paradox

Rational people violate the axioms of expected utility (people make irrational choices)

Behavioral economics: study of economics that includes psychology to understand why people often make irrational or non-optimal economics choices)

War Economies

• government is in a budget deifict due to spending for war

• taxes are higher to fund the war

• Represented by Keynesian theory with government involvement

How did McCarthyism influence economy

McCarthyism influenced the development of economics by creating a political climate of anti-communism and fear during the Cold War. Economists and academics suspected of communist sympathies risked losing their jobs or facing professional exclusion. This restricted academic freedom and made some economic perspectives, particularly Marxist and radical approaches, more difficult to teach and develop. It also created pressure on economists working on controversial questions about government intervention and economic power.

McCarthyism has also been linked to the mathematization of economics, as some scholars argue that mathematical models provided a more politically neutral way to express economic ideas. However, this causal relationship is disputed: Weintraub argues that the mathematization of economics was driven primarily by broader scientific and methodological developments rather than by McCarthyism itself.

Economics as Laboratory Science

RCTS: a study design that randomly assigns participants into an experimental group or a control group. As the study is conducted, the only expected difference between the control and experiemental group in an RCT is the outcome variable being studied. This is how to study variables and their signficance in a policy or model.

Economics as Engineering

• Shift from verbal and philosphical study of the economy to a more technical discipline that uses mathematics, statistics, modelling and data to strengthen theoretical arguments.

• precision of representation of economic qorld, quantitative investigation, exact analysis

• Introduction of maths doesn’t replace human judgment but gies human tools to exercise judgements and strenghten claim.

• Economists increasingly acted as “operators” and “designers” as they were managing the economy through policy or designing institutions and incentives to shape behaviour (in control of economy)

Measuring the economy

• new methods like index numbers, statistics, correlation, regression made measuring things like prices, output and business cycles possible

• Wars and GD gave more data for economists to analyse —> peaks and troughs of business cycle

• statistics like correlation and regression important to test relationships and explain causes

Mathemizing Economics

• introduced through marginal utilities

• indroduction shaped the way that theorizing was carried out and concepts weere defined. altered questions considered relevant towards study'

• mathematical theorizing radically changed the objects of study in economics and kind of truth economists sought

• distiguished economy theory to realities

Modelling and Tool Based Economics

• Modelling provides a simple and mathematical represnatation of the complexity of the real economy

• formed basis for statistical descirption of actual historical and strutucal relations embdded in the data of the real economy

• Business cycles example: models like Tinbergen’s gave mathematical representation by attaching data to provide measurements of the parameters involved in teh relationships.

Logical Positivism

20th century philosophical movemnet that asserts a statement is meaningful only if it can be verified empirically or logically (science-based policy).

aim to demarcate scientific knowledge, to distinguish science from pseudo-science and to remove any kind of metaphysical or imagined content from scientific knowledge

accept only analytic and synthetic a posteriori propositions as scientific knowledge

Analytic statement

true by definition. does not expand knowledge

Eg.

• A square has 4 equal sides

• All bachelors are unmarried

• Vixens are female foxes

Synthetic a priori

a statement adds new information to our knowledge and can be known or justified through reason alone.

Eg.

• f=ma

• 7+5=12 (The concept of "12" is not analytically contained inside the individual concepts of "7", "+", or "5". If you just analyze the definitions of 7, 5, and addition, you do not automatically discover 12 until you synthesize them together.)

• The sum of the angles in a triangle is 180 degrees.

• There exists no synthetic a priori statements

Synthetic A posteriori

A statement that tells you something new about the wolrd and requires sensory experience or empirical evidence to prove

• Eg. “The cat is sleeping”

• There exists no unicorns

• In the long run, the economy moves to potential GDP.

• If inflation becomes expected by the public, the price-adjustment schedule is shifted upward by the amount of the expected inflation.

Demarcation between science and pseudo-science

• Science: builds models through observation, experiment and peer review. seeks falsifiability. analytic and synthetic a posteriori

  • Pseudo-science: a collection of theories that are claimed to be scientific but do not use proper scientific methods or empirial evidence (synthetic a priori)

Verification vs Falsifiability

Verification: claims that a statement is meaningful only if it can be empirically verified by observation or is true by definition (analytic). Its goal is to prove theories true using inductive reasoning. uses sense data or instruments

Falsification: developed by philosopher Karl Popper as a critique of verificationism, falsificationism argues that a theory is scientific only if it is falsifiable—meaning it makes risky predictions that could be proven false by an observation or experiment. Instead of trying to prove a theory true, science progresses by trying to refute or disprove it.

Operationalism

to verify a statement, all its terms should correspond to observational counterparts

if you can’t measure or observe something with clear physical action operationalism says it doesn’t have real meaning

Eg. Unemployment. Operationalisation is turning the abstract concept of being “unemployed” into clear, measurable variables for research or data collection.

Explanation

• an answer to a why-question

• non-scientific answers need a deductive-nomological model or a “covering-law” model

• explanan: set of statements or reasons that do explaining

• explanandum: event that needs to be explained

Rule of Modus Ponen

a fundamental deductive argument form and rule of inference in logic (also known as affirming the ancedent)

If A → B; A; therefore B

Example:

• Premise 1: If it rains, then the ground is wet.

• Premise 2: It is raining.

• Conclusion: Therefore, the ground is wet.

Modus tollens: If A → B; not B; therefore not A

Fallacy that can be added into this is the Affirming the consequent: If A → B; B; therefore A. Affirming the consequent is a logical fallacy because it assumes that if the consequence (B) occurs, the original condition (A) must have occurred. However, B could have other possible causes. A conditional statement only establishes that A is sufficient for B, not that A is the only possible cause of B.

logical positivist’s requirements for a scientific explanation

• Logical Consequence: The phenomenon being explained (the explanandum) must be a logically valid consequence of the explanatory premises (the explanans).

• Inclusion of Laws: The premises must contain at least one general, universal law of nature that is strictly necessary for the deduction to work.

• Empirical Content and Validity: The premises must have empirical import, meaning they must be testable by observation or experiment.

Theories and Evidence of Logical Positivists

• distinction made between context of discovery and context of justification: difference to how a theory was discovered and the context of its justification.

• for logical positivists, context was not important. biographical and historical data about lives should have no place in any serious history of subject

Criticique of logical positivist program

• to logial positivists, witohut laws then there are no scientific explanations and no scientific predictions and science can only provide descriptions of diniviudal phenomena

• problem of induction: laws deduced by observations and sense data may not be fully accurate since they are unable to use full population as experiment. Challenges eviential support for laws

  • no univseral laws that can be based on sense data implying that laws should be removed from science

• Response:

  • Instrumentalism: laws are useful instruments whose value is measured by how effectively they explain and predict phenomena

  • Confirmationalism: probabalistic knowledge (most likely true)

Symmetry of Explanation and Prediction

go both ways

Explanation —> prediction: if you have an adequate explanation you could use that arguement to predict it and vice versa

Explanation in Economics (Rationality Principle)

Agent A is in sitution of type C. The rational deicision is E. Agents always action rationally so Agent A did E.

Formalism

school of thought stating that mathematical statements and proffs are simply rules for manipulating physcial or abstract symbols rather than descirptions of an objective.

(ignores content, emotional expression, historical context and external meaning)

Keynes-Tinbergen Debate

• Tinbergen wanted to make economics more quantative and scientific.

• His approach was to build a simplified model of economy, estimate relationship and how strongly variables influence economic activity and use model to determine future policies.

• Keynes argued that regression analysis requires a certain degree of uniformity. Statistical technqiues can not mechanically uncover economic laws and theory is needed to idenify causal relationships.

• Regression treates differences in time and space as irrelevant (time lags and invariance). Some variables can affect each other (simultaneity). Omitted and unmeasurable factors cannot easily be quantified.

• 70 econometricians

Measurement without theory debate

NBER approach: extensive empirical measurement of business cycles was done without relying heavily on economic theory.

Haavelmo and Koopmans: argued that economics can never isolate variables and theory was needed to know what causal influences are relevant. Assumptions are needed

Vinings challenge to Koopmans:

1) economic theory isn’t developed enough, data can help discover theories, should empirical research be evaluated from point of social usefulness

Cowle’s Commision and Friedman’s instrumentalism

• Cowle’s commission: empirical framework for economic forecasting and policy analysis that relies on simultanoues equations. Aim was to build increasingly comprehensible models to improve predictability.

• Friedman’s critique: models focused too much on constructing complicated formal models rather than determining if the model actually helped explain or predict real world problems

• Friedman’s approach (instrumentalism): you don’t need to completely describe economy before making useful economic predictions. unrealistic assumptions do not automatically make the theory bad. anti-realitsiticness

Samuelson’s Descriptivism

Descriptivism came as criqtiue to Milton’s approach: f-twish —→ unrealistic assumptions do not automatically make the theory bad. Truth can be deduced by false theory or the truth value of a theory is irrelevant for truth value of its consequences.

If we only accept statemnets that can be empirically verified, we run into the problem of induction so we cannot observe all possible cases.

Descripitivism: we cannot completely verify a universal so so if we reject them entirely, science can mainly give us accurate descriptions of what has been oberserved rather than universal causal laws.

Economic behaviour is generally explained by the incentives at play. What is the underlying rationality principle that is often used?

Economic behaviour is commonly explained through rational choice theory (RCT), which is based on the principle of instrumental rationality (means–ends rationality).

Rational choice theory assumes that individuals are rational decision-makers who respond to incentives by choosing the option that best serves their preferences and objectives. Individuals are assumed to weigh the expected costs and benefits of different alternatives and select the one that maximises their utility, given their available resources, information and constraints. Similarly, firms are assumed to make decisions that maximise their profits. The underlying principle of instrumental rationality means that individuals choose the most effective means to achieve their given ends. In other words, their goals are taken as given, and rationality concerns how efficiently they pursue those goals rather than whether the goals themselves are desirable.

Example: If the price of a product increases, consumers may reduce their consumption and switch to cheaper alternatives. This is because they respond to the changed financial incentive by adjusting their choices to maximise their utility within their budget constraint.

Standard View of Science

objective obersvations combined with correct reasoning produce reliable scientific knowledge, however, observations can be interpreted differently, reasoning can be affected by biases and scientific concepts can contain hidden values

Logical Reasoning

follows rules that determine whether a conclusion follows from given premisies. Modus ponens is a basic logical rule

Rational Reasoning

• unemotional, unbiased and objective

  • concerns whether reasoning or deicisions meet standarsd of rational judgement

Heuristics and Biases

Heuristics: a rule of thumb/mental shortcuts to make difficult judgments about probablilities and predictions. They simplify complex decisions and are useful but create systematic errors

Base rate fallacy

Part of representative heuristic

When people neglect how common or rare something is in the population and focus to heavily on other information.

• Probability of a evidence given a condition is different to the probability of the condition given the evidence

  • The Scenario: A quiet, shy person who loves reading and working alone is described to you. You are asked to guess their profession: librarian or teacher.

    The Fallacy: You immediately guess "librarian" because the description fits the stereotype of a librarian.

    The Reality: You ignored the base rate—there are vastly more teachers in the population than librarians, making it statistically more likely that a shy book-lover is a teacher.

Hume’s guillotine

you cannot logically derive an ought statemnet from an is statement alone.

Eg.

Fact: unemployment is high —> conclusion: the government should increase spending.

illegitimate derivation = ‘naturalistic fallacy’

Gunnar Myrdal: implicit values

• social sciences can never be entirely free of values.

• Science may aim for objectivity, but the choice of research questions, concepts and evaluation ciriteria can involve values

Observation and theory-ladenness

seeing = retinal impressions + inetepretation

Same data can support different interpretations because people approach observations with different theories and assumptions

To be able to settle a question nterpretation and expert evaluation is needed. Evidence alone does not suffice.

Science as a consensus

Normal science: shared paradigm, researchers solve accepted puzzles, agreed methods and standards

Scientific crisis: disagreement over paradigm

need for synthesis in economics

Falsification

According to popper:

• Scientific tests should attempt to falsify theories, rather than merely confirm them

• A theory cannot be refuted by any possible event is not scientific.

Eg. “it either rains in utrecht or it doesn’t” provides no meaning for empircal test while “it does not rain in utrecht” is falsiable

Immunizing strategy: protects a theory from being falsified

Eg all swans are white

Open Society

allows people to criticise rulers and institutions because human knowledge is fallibe.

Contrasts w/platos idea of the philospher-king

Merton’s CUDO

norms describing how science should operate

Communalism

Univeralism

Disinterestedness

Organized skepticism

Logos Pathos and Ethos

Logos: (logic) internal consitency and effective reasoning. —> rigor

• rigor vs relevance

Pathos: emotions and imagination —> audiences background knowledge

• can lead to strawman account

Ethos: (evidence) credibility of speaker

• can lead to inappropriate appeal to authority

Representativeness Heuristic

Definition: People judge the probability that something belongs to a category by how closely it resembles their stereotype of that category, rather than by considering actual probabilities.

In simple terms: If something looks like what I expect, I assume it is likely to be that thing.

Main biases to remember

• Neglect of base rates: Ignoring how common a category actually is. eg. librarian

• Insensitivity to sample size: Ignoring that small samples vary more than large samples. eg. hospital, red and blue ball

• Misconceptions of chance: Expecting random sequences to look balanced or representative in the short run. eg. HHHHHH

• Insensitivity of predictibility: neglect how reliable the description is and how accurately it can predict future performance. eg, company, student teachers

• Illusion of validity: Being overly confident in a prediction because the evidence fits a stereotype or pattern. eg student with 6 As over student with averaging between B and C

• Failure to account for regression toward the mean: Mistaking natural changes in extreme performance for the effects of rewards or punishments.

Availability Heuristic

People judge how frequent or likely an event is by how easily examples come to mind or how easily they can imagine it happening.

In simple terms: If I can remember or imagine it easily, I assume it happens often.

Main Biases

• Ease of recall: Memorable examples are mistaken for frequent examples. eg. risk of a heart attack among middle-aged people by recalling cases among their friends or acquaintances

• Ease of imagination: Easily imagined scenarios are judged more likely. eg. business venture will fail, Risk of an expedition, Imagining committees

• Search-set bias: People overestimate what is easier to search for mentally, such as words beginning with a particular letter. eg. words beginning with R, Famous men and women, Abstract versus concrete words

• Illusory correlation: People overestimate the frequency of two events occurring together because they are strongly associated in their minds. eg. hypothetical mental patients' diagnoses and drawings

• Recency and salience: Recent or vivid events have a disproportionate influence on judgments. eg A burning house and a car accident

Adjustment and Anchoring

People make an estimate by starting with an initial value (the anchor) and adjusting it to reach a final answer. The adjustment is often insufficient, so the final estimate remains biased toward the starting value.

In simple terms: The first number I see influences my answer, even when that number is arbitrary.

Main Biases

• Insufficient adjustment: People do not move far enough away from their starting value. eg. multiplication problem, planning projects; complex systems and failure; confidence intervals and stock-market estimates

• Arbitrary numerical anchors: Irrelevant numbers influence later estimates. eg. Africa nations and wheel of fortune, two methods of estimating uncertainty

• Overconfidence: Confidence intervals become too narrow because people do not adjust far enough from their best estimate. Confidence intervals and stock-market estimates

• Compound-event errors: People overestimate the probability that every step in a sequence succeeds and underestimate the probability that at least one component in a complex system fails. Eg. Planning projects; complex systems and failure

Economics in terms of political management

The economy is something that governments can measure, manage and influence through economic policies.

The economy is viewed as something that policymakers can actively intervene in to achieve particular economic and social objectives. This perspective became particularly prominent with the development of Keynesian economics, which emphasised the role of government intervention in stabilising the economy.

Governments use economic indicators, such as GDP, unemployment, inflation and government debt, to identify economic problems and determine appropriate policy responses.

eg.

• Unemployment: Governments may increase public spending to stimulate aggregate demand and create jobs.

• Inflation: Central banks may increase interest rates to reduce borrowing and spending.

• Economic growth: Governments may invest in infrastructure, education and innovation to increase productive capacity

Economics in terms of aggregates

The economy is understood through combined or total economic measurements rather than looking at every individual economic decision separately.

Aggregates combine the economic activities of individuals, households and firms into larger measurements that describe the overall economy.

This is particularly important in macroeconomics, where economists examine indicators such as:

- GDP: The total value of final goods and services produced within an economy.

- National income: The total income earned within an economy.

- Aggregate consumption: Total household consumption expenditure.

- Aggregate investment: Total investment expenditure across the economy.

These aggregates allow economists to simplify a complex economy into measurable indicators, making it easier to identify broad economic trends and compare economic performance over time or between countries.

Limitation: Aggregation hides individual differences.

Economics in terms of macro-behaviour

The economy is understood through the collective behaviour and interactions of economic actors, rather than simply adding up individual decisions.

Macroeconomic behaviour examines how the decisions of households, firms, governments and financial institutions interact to produce outcomes at the level of the entire economy.

The important distinction here is that the behaviour of the economy as a whole cannot always be understood by looking at individuals in isolation.

Individual decisions can produce unexpected collective outcomes.

Limitation: Macroeconomic models simplify the interactions between individuals and institutions. They may overlook differences in individual behaviour, expectations, social structures and institutional conditions.

fallacy of composition: assuming that something true for an individual must also be true for the economy as a whole.

What would a legal definition of an economy be?

A legal definition views the economy in terms of laws, regulations, property rights and legally recognised transactions.

It focuses on the formal rules that determine how economic activities are organised and conducted within society.

This includes:

- Property ownership and property rights.

- Contracts and agreements between individuals and businesses.

- Employment laws and labour regulations.

- Taxation and government regulations.

- Legally recognised markets and business activities.

Example: A company selling products, employing workers and paying taxes operates within the legal framework of the economy. Illegal activities, such as selling prohibited goods, may still involve economic transactions but fall outside the legally permitted economy.

Key limitation: A legal definition may exclude or overlook economic activities that are not formally recognised or regulated, such as unpaid household work, informal labour and illegal markets

What would a moral definition of an economy be?

A moral definition views the economy in terms of ethical values, social welfare and what is considered desirable or fair for society.

Rather than focusing on whether an economic activity is legally permitted, it asks whether that activity contributes positively to human well-being and serves society's interests.

It focuses on:

- Fairness and equality in the distribution of resources.

- Human welfare and living standards.

- Fair wages and working conditions.

- Social responsibility and environmental sustainability.

- Whether economic activities contribute to the common good.

Example: A company may legally pay workers the minimum wage, but a moral perspective might question whether that wage provides workers with a decent standard of living.

For example, in Michael Sandel's discussion of the moral limits of markets, selling a kidney raises moral questions about whether market exchanges can be exploitative or undermine the value of human life.

Key limitation: Moral definitions are subjective because individuals and societies may disagree about what is fair, ethical or desirable.

In what ways can the complexity of a economic be simplified in a model?

Complexity can be simplified by constructing a model that leaves out unnecessary details while retaining the features that are important for understanding the economic phenomenon being studied.

• abstraction

• idealisation

• assumptions

• aggregationg

• ceterus paribus

A good model does not need to represent reality in every detail. It needs to simplify reality in a way that is useful for answering the particular research question.

Market Libertarianism and invisible hand

Market liberatarainism: applies strict individual-liberty principles to the regulation and organization of markets.

• institutions emerge as unintended results of individual actions rather than through deliberate design (God’s plan)

• spontanous order is assumed to be best order

Invisible hand: individuals purpsuing their own interests can sometime be unintentionally benefit society (critique of market externalities)

How the definition of economics has changed

trad: economics focuses on economic growth, income, employment, production as indicators of development

broader: developement also involves human wellbeing, social progress, health, edu, enrivonmental sustainability

Measuring the Economy: GDP

• measurement of value of goods and servies produced within a country over a given period

• Activities excludede: unpaid household actvities, natural resouces like air water raw materials. This shows GDP doesn’t capture all activities that contribute to people’s livelihoods and wellbeing

• Welfare also influenced by health, family situations, employment satisfaction, wars, epidemics, natural disasters and inventions.

HDI, MDGs, SDGs

provides broader measure of development than GDP alone

CBA

evaluates a policy or project by comparing its expected benefits with its costs (opportunity cost)

Developments in Economic Theory

Economics became increasingly mathematical, formalised and focused on individual decision-making.

• Econometrics: combines economic theory with mathematics and statistics to analyse economic relationships using data.

• Mathematical modelling: economic models simplify reality into formal relationships that can be analysed and tested.

• Microfoundations: macroeconomic theories are built on the behaviour of individual agents, such as households and firms.

• Rational choice: individuals are assumed to make rational decisions, often by maximising utility, while firms are assumed to maximise profits.

• Human capital: education, training and health are treated as investments in people that can increase their productivity.

• Game theory: analyses strategic interactions in which the decisions of one agent affect others.

• Market design: uses economic theory to design rules and institutions that help markets achieve particular objectives.

Developments in applied economics

• Empirical research: using surveys, administrative records and other data to investigate actual economic behaviour.

• Modern econometrics: using statistical methods to estimate relationships and assess economic hypotheses.

• Behavioural economics: investigating how actual human behaviour may differ from the assumptions of perfect rationality.

• Experimental and quasi-experimental methods: using controlled experiments or naturally occurring circumstances to identify the effects of particular factors.

• Big data and computation: analysing larger datasets and using computational methods to investigate complex problems.

• Policy relevance: applying economic research to issues such as inequality, employment, migration, health, crime and education.

Historical Development

1) Before WW2: Empirical

2) 1950s-1960s: Age of economic theorist

• neoclassical theory dominant

• mathematical models of utility-maximising consumers and profit-maziming firms gained prestige

3) 1970-1980s: transition

• theory was disconnected from reality and gov demand for applied economics for policy grew

• new econometric techniques expanded research possibilities

4) 1990-2000s: applied economics gains prominence

• Quasi-experimental methods allowed identification of causal effects without always specifying complete economic model

Causes for economics to change

• New research methods, more data and computing technology

• Policy demand, new institutions and funding, changing professional standards

• Data and computing revolution were necessary enablers but political priorities, funding, institutions and economists choices shaped how new opportunities were used.

Quasi-Experimental Approach

a quantitative research methodology used to evaluate a cause-and-effect relationship between an intervention and an outcome when true random assignment is either unethical or unfeasible.

Unlike a true randomized controlled trial (RCT), participants are not randomly assigned to treatment and comparison groups. Instead, researchers rely on pre-existing groups, self-selection, or administrative thresholds.

became especially influential in applied microeconomics during 90s

Patrons and Clients in Applied Economics

Applied economics grew partly because institutions needed economic expertise to solve practical problems

Patrons: economists Clients: gov, central bank, business firms, research funders

• Governments: Used economic analysis to design, regulate and evaluate policies.

• Central banks and international organizations: Expanded their employment of economists and their research departments.

• Businesses and technology firms: Used economic expertise to understand markets and design strategies.

• Research funders: Increasingly expected researchers to demonstrate the practical or policy benefits of their work.

Type of Explanations

Covering-law: states that to explain a particular event or phenomenon is to deductively subsume it under a general law.

• eg. students leave a lecture room when the class ends according to the timetable.

  
  

Rationality: Explains behaviour by examining how individuals choose actions to achieve their objectives.

• eg. a student attends lectures to improve their chances of passing an exam.

Path-Dependency: Explains current outcomes through the influence of past decisions and events. Earlier choices can constrain later options and create patterns that persist over time.

• easy: the idea that where you end up is heavily shaped by what happened in the past, even if better or more efficient options are available today

• eg. Lectures even though they are not the most effecient matter of learning

Narrative: a structured account of connected events, choices, and conditions that explains how or why something happened by placing it within a meaningful story

Case study: as an empirical research methodology to investigate real-world economic phenomena and as a pedagogical tool in the classroom

Which type of explanation would be most suitable to explain a social phenomenon. Explain why.

• A path-dependency explanation is particularly suitable for explaining complex social phenomena because social outcomes are often shaped by historical events, institutions and previous decisions. These influences can create patterns that persist even when alternative arrangements become possible.

  • For example, a university's teaching structure may reflect historical decisions and established routines. These arrangements can continue to influence how teaching is organised today, even if they are no longer the most efficient option.

• However, the most suitable explanation depends on the phenomenon being studied.

  • Rationality explanations are useful for understanding individual choices, while covering-law explanations are suitable when reliable general patterns exist.

  • A narrated explanation or case study can also be useful when a phenomenon requires detailed attention to its historical and social context.