Chapter 2: Economic Theories, Data, and Graphs – Study Notes

Economic Theories, Data, and Graphs

Positive and Normative Statements

Economists distinguish between two types of statements: positive and normative. This distinction is fundamental for understanding economic analysis and policy debates.

• Positive statements: Concerned with facts and can be tested or validated. They describe what is, was, or will be.

• Normative statements: Involve value judgments and prescribe what ought to be. They cannot be evaluated solely by recourse to facts.

• Example: "The unemployment rate is 6%." (positive) vs. "The government should reduce unemployment." (normative)

Disagreements Among Economists

Economists often disagree in public discussions, largely due to the distinction between positive and normative statements.

• Many disagreements are rooted in whether statements are factual (positive) or value-based (normative).

• Responsible economists clarify which parts of their advice are based on facts and which reflect value judgments.

Where Economists Work

Economists' skills are in demand across various sectors, reflecting the broad applicability of economic analysis.

• Governments and public institutions (e.g., ministries of finance, competition policy agencies)

• International organizations (e.g., World Bank, IMF, OECD)

• Private businesses

• Non-profit organizations

• Post-secondary schools

• Example: Economists may design regulatory frameworks, evaluate government policies, and contribute to policy coordination.

Building and Testing Economic Theories

What Are Theories?

Economic theories are abstractions from reality, designed to explain and predict economic phenomena.

• Variables: Quantities that can take on different values.

• Endogenous (dependent) variables: Explained within the theory.

• Exogenous (independent) variables: Determined outside the theory.

• Assumptions: Simplifying conditions to make analysis tractable.

• Predictions: Testable implications derived from the theory.

Testing Theories

Theories are tested by comparing their predictions with empirical evidence.

• If a theory conflicts with facts, it is amended or replaced.

• The scientific approach is central: hypotheses are confronted with data.

Interaction Between Theory and Empirical Observation

The process of theory development and testing is iterative, involving continual refinement based on empirical results.

• Theories generate predictions.

• Empirical observation tests these predictions.

• Theories are revised if predictions do not match observed data.

Statistical Analysis

Statistical techniques are essential for analyzing economic data and testing hypotheses.

• Hypotheses such as "if X occurs, then Y will also happen" are tested using data.

• Economists often rely on "uncontrolled" experiments in the marketplace.

• Complex statistical methods are required due to the simultaneous influence of many variables.

Correlation versus Causation

Understanding the difference between correlation and causation is crucial in economics.

• Positive correlation: X and Y move together in the same direction.

• Negative correlation: X and Y move in opposite directions.

• Correlation does not imply causation; advanced statistical techniques are needed to establish causality.

• Example: Spurious correlations (e.g., pool drownings and Nicolas Cage films) illustrate the need for careful analysis.

Controlled Experiments in Economics

Economists are interested in causal relationships but often cannot conduct controlled experiments.

• Randomized controlled trials (RCTs) are increasingly used to determine causality among economic variables.

• Example: RCTs in development economics to test the impact of policy interventions.

Economic Data

Index Numbers

Index numbers are used to measure changes in economic variables over time, relative to a base period.

• An index number expresses the value of a variable relative to a base period (assigned the value 100).

• The Consumer Price Index (CPI) is a common example, measuring the average price of a typical basket of goods and services.

Constructing Index Numbers

Index numbers are calculated using the following formula:

• $\text{Index} = \left( \frac{\text{Value in given year}}{\text{Value in base year}} \right) \times 100$

• Example: If steel output in 2024 is 22.5% greater than in 2014, the index number for 2024 is 122.5.

Year	Steel Procedure	Steel Index	Newsprint Procedure	Newsprint Index
2014	10000/10000 × 100	100.0	8000/8000 × 100	100.0
2015	10500/10000 × 100	105.0	7500/8000 × 100	93.8
2024	12250/10000 × 100	122.5	7500/8000 × 100	93.8
Additional info:	Other years follow the same calculation method.

Graphing Economic Data

Economic data can be represented in various graphical forms to reveal patterns and relationships.

• Cross-sectional data: Observations at a single point in time across different units (e.g., provinces).

• Time-series data: Observations of a variable over time.

• Scatter diagrams: Graphs showing two variables, each measured on one axis; each point represents a unit of observation.

• Example: Bar graph of average house prices across Canadian provinces (cross-sectional), line graph of unemployment rate over time (time-series).

Graphing Economic Theories

Functions in Economics

Economic relationships are often expressed as functions, showing how one variable depends on another.

• If Y depends on X, we write $Y = f(X)$.

• Functions can be expressed verbally, in tables, mathematically, or graphically.

Example: Income and Consumption

Consumption is a function of wage income. The relationship can be expressed as:

• $C = f(W)$

• If wage income $W$ is zero, consumption $C$ is $800. For every extra $1 of wage income, consumption increases by $0.80:

• $C = 800 + 0.8W$

Wage Income (W)	Consumption (C)	Reference Letter
0	800	p
2,500	2,800	q
5,000	4,800	r
7,500	6,800	s
10,000	8,800	t

Graphing Functions

Functions can be graphed to visualize relationships between variables.

• Positively related: Variables move in the same direction.

• Negatively related: Variables move in opposite directions.

• If the graph is a straight line, the relationship is linear; otherwise, it is non-linear.

The Slope of a Straight Line

The slope measures the rate at which one variable changes in response to another.

• The slope of a straight line is calculated as:

$\text{Slope} = \frac{\Delta Y}{\Delta X}$

• Example: If reducing pollution by 1,000 tonnes ($\Delta X$) costs $2,000 ($\Delta Y$), the slope is$-0.5$.

Non-linear Functions

For non-linear functions, the slope changes as X changes, illustrating concepts like diminishing marginal response.

• Example: Pollution reduction may show diminishing returns; marginal response decreases as more pollution is reduced.

Functions with a Minimum or Maximum

Some economic functions have a minimum or maximum point, important for optimization problems.

• Maximum: Profits as a function of output may reach a peak before declining.

• Minimum: Average fuel consumption as a function of speed may reach a minimum at an optimal speed.

A Final Word

Economists develop theories to understand real-world events, test these theories against data, and use graphs to illustrate and communicate their findings. The continual process of empirical testing and refinement is central to economic analysis.