The Comparative Approach in Political Science

Chapter 1: The Comparative Approach: An Introduction

Learning Objectives

  • Distinguish between scientific and non-scientific questions.
  • Understand some of the major questions of comparative politics.
  • Differentiate between empirical and normative arguments.
  • Understand the characteristics of good and bad concepts in social science.
  • Explain the relationship between conceptualization and measurement.
  • Explain the use of cases and other forms of evidence in the testing of hypotheses.
  • Demonstrate the basic features of several forms of comparative design, including the most-similar-systems (MSS) design and the most-different-systems (MDS) design, as well as comparative checking and within-case comparison.

Empirical Versus Normative Questions and Arguments

  • Causal questions lead to empirical arguments:
    • These are drawn from observations of facts in the world.
    • They provide explanations about why the world is the way it is.
    • In Comparative Politics, we primarily ask causal questions.
  • This is distinct from normative questions and moral arguments:
    • These are concerned with what is moral or ethical.
    • They are arguments about how the world ought to be.

Causal Questions in Comparative Politics

  • Comparative politics focuses on asking causal questions such as:
    • Why did modern states emerge and grow?
    • Why are some countries rich and others poor?
    • Why are some countries democracies and others not?
    • What are the effects of different institutions?
    • Why do revolutions happen?
    • Why do identities and beliefs matter?
    • Why do ideology and religion affect modern politics?
  • Ways to ask causal questions in Comparative Politics include:
    • What are the consequences of different kinds of institutions for policy? (e.g., presidential vs. parliamentary systems for education policy)
    • Under what conditions will democracies emerge and consolidate?
    • How do major social revolutions affect subsequent political developments in given countries?
  • Assessing the value/utility of questions:
    • Broad questions: "Why are some countries democratic and others not?" is a useful starting point but often too broad for a single study.
    • Specific, single-case questions: "Why is India a democracy?" or "What caused the 1959 Cuban Revolution?" are less useful for comparative politics because they don't involve comparison, though they might be part of an in-depth case study within a comparative framework.
    • Comparative questions: "Why is Ghana a democracy and Togo not?" is a good comparative question.
    • Temporally broad questions: "If we consider all country-years from 1950 to 2020, what explains democracy vs. nondemocracy?" offers a broader scope for comparison over time and across many cases.

Concepts

  • Definition: Concepts are ideas that comparativists use to think about the processes they study. They are mental constructs comprising a combination of characteristics.
  • Sartori's ladder of abstraction:
    • Illustrates how concepts can be more or less abstract.
    • Up the ladder of abstraction: REGIME $\rightarrow$ Civilian regime $\rightarrow$ Competitive regime $\rightarrow$ Democracy $\rightarrow$ Parliamentary democracy.
    • Down the ladder of abstraction: Two-party parliamentary democracy $\rightarrow$ Parliamentary democracy $\rightarrow$ Democracy $\rightarrow$ Competitive regime $\rightarrow$ Civilian regime $\rightarrow$ REGIME.
  • Characteristics of good concepts:
    • Clear and coherent: A good definition leaves no ambiguity.
      • Bad example: "all good things that happen when a society changes" (too vague).
      • Good example: "process by which rights and liberties are extended to all adults in a country" (specific and measurable).
    • Consistent: If a concept like "democracy" is defined as a "set of institutions," then "democratization" should consistently refer to changes in those institutions, not just "values."
    • Useful for measuring variables: A concept should be defined in a way that allows for clear distinction and measurement (e.g., some places have it, others do not).
  • Operationalization: The process of making basic concepts measurable.
    • Importance: Measurable concepts become "variables."
    • Variable: An element or factor that can change, or vary, from case to case.
  • Examples of operational definitions of democracy:
    • A country holds a free and fair multiparty election.
    • Free and fair elections are held, and constitutional law guarantees freedom of speech, press, assembly, and religion.
    • Two turnovers of government at the ballot box have occurred, in which the ruling party loses an election and peacefully steps down from power.
    • There is no verifiable suppression of political participation and expression.
    • More than two-thirds of citizens in a survey express values that reject authoritarian rule.

Empirical Evidence

  • Definition: Evidence consists of facts supporting an argument and information that has implications for a theory or hypothesis.
  • Characteristics of strong evidence:
    • Relevance: Evidence must be directly relevant to the issue at hand.
      • Example: If measuring democracy in Saudi Arabia, discussing religion (Islam) or economy (oil exporter) is not directly relevant to the measure of democracy, though these factors might cause or prevent democracy.
    • Operates at the same level of analysis as the claim:
      • Example: If claiming Saudi Arabia (a country) has poor gender relations, talking about the beliefs of a few men (individuals) is insufficient evidence for a country-level claim.
  • Evaluating evidence (Examples provided):
    • Student 1 (Strong Evidence):
      • Claim: Saudi Arabia is not democratic.
      • Evidence: Saudi Arabia has not held free and fair elections for its national government. Women do not have the same political and social rights as men.
      • Assessment: Claim is strong, facts are correct, evidence is strong (directly addresses institutional aspects of democracy and lack of rights).
    • Student 2 (Weak Evidence):
      • Claim: Saudi Arabia is not democratic.
      • Evidence: Saudi Arabia is an Islamic country whose economy is based on exporting oil. It is a long-time ally of the United States and is led by King Salman and a large royal family.
      • Assessment: Claim is strong, facts are correct, evidence is weak (these facts don't directly measure or demonstrate a lack of democracy, though they might be associated with it).
  • Common pitfalls in evaluating evidence:
    • Generalizing from specific instances: "Protests against the U.S. invasion of Iraq in 2003 show overall public opposition." This assumes widespread public opinion from specific protests.
    • Generalizing from a non-representative sample: "Many Flagstaff residents who post on Nextdoor complain about Airbnbs, demonstrating Flagstaff opposes short-term rentals." Nextdoor users are not necessarily representative of all Flagstaff residents.
    • Ecological fallacy: This occurs when one infers about individuals based on aggregate data.
      • Example: "Bilingual individuals tend to be better at math. Therefore, since you are bilingual, you must be good at math." This is a fallacy because a general trend for a group does not guarantee it for any single individual within that group.

Cases and Case Studies

  • Case: The unit of analysis in comparative politics, an example of the phenomenon to be studied.
  • Examples of cases:
    • A country (e.g., France, China, Ghana, Togo).
    • A country for a specific period of time (e.g., French government before and after the Revolution).
    • An event or a set of events (e.g., U.S. Civil Rights movement in the mid-20th century, compared with the Women’s suffrage movement of the early 20th century).
    • A certain group (e.g., majority Catholics in Southern Europe and majority Protestants in Northern Europe).
    • Other geographic units (e.g., social history in Texas and California).
  • Example scenario: Student protests of Israeli Policy in Gaza (2023-2024 academic year)
    • Research Question (specificity): What explains the variation in protest activity and university administration responses across U.S. universities?
    • Case: Individual universities in the U.S. (or specific protests at those universities).
    • Important Concepts: "Protest activity," "university administration response."
    • Operationalization: For "protest activity," one could measure the number of students participating, duration of protest, types of tactics used (e.g., encampments, sit-ins), or level of disruption. For "university administration response," one could measure the speed of response, use of police, level of negotiation, disciplinary actions, etc.

Variables and Comparison

  • Comparative politics examines cases to see how variables interact within them, focusing on causes and effects.
  • Causal arguments use different vocabulary:
    • Cause $\rightarrow$ Effect
    • Independent variable $\rightarrow$ Dependent variable
    • ExpXlanatory variable $\rightarrow$ Outcome
    • X variable $\rightarrow$ Y variable
  • Example (Ghana and Togo):
    • A research question could be: Why is Ghana democratic (Case 2) while Togo is authoritarian (Case 1)?
    • "Regime Type" (democratic vs. authoritarian) is the dependent variable (Y variable, Outcome).
    • Researchers then look for causes (X variables) in these cases that explain the variation in regime type.

The Comparative Method

  • Most-Similar-Systems (MSS) Design:
    • Goal: To find cases that are similar in many respects but differ on the outcome (dependent variable).
    • Logic: If two similar cases have different outcomes, then the differentiating factor(s) (independent variables) are likely the causes of the outcome.
    • Example: Why do contiguous countries in Africa (Togo and Ghana) have different regime types?
      • Similarities: Climate (Hot), Income (Low), Ethnic Demography (Heterogeneous), Largest Religion (Christian), Other Religions (Islam, Traditional).
      • Outcome: Togo (Authoritarian), Ghana (Democratic).
      • Hypothesized Cause (X variable): Colonizer (Togo: France, Ghana: United Kingdom).
      • Purpose of similarities: By holding confounding variables constant (like climate, income), researchers can isolate the impact of different independent variables (like colonizer) on the outcome.
  • Most-Different-Systems (MDS) Design:
    • Goal: To find cases that are very different in many respects but share the same outcome (dependent variable).
    • Logic: If different cases have the same outcome, then the shared factor(s) across these diverse cases are likely the causes of the outcome.
    • Example: Why do major social revolutions occur?
      • Differences: France (1780s) vs. China (1940s) differ significantly in Continent, Population, Century, and Regime.
      • Outcome (common): Both experienced Social Revolution (Yes).
      • Hypothesized Cause (X variable): The researcher would then propose a shared factor despite all the differences (e.g., profound economic crisis, state weakness, widespread peasant discontent, etc.) that explains why both experienced a revolution.
      • Purpose of differences: By demonstrating the outcome occurs despite vast differences, researchers can identify factors that are common and potentially crucial.
  • Comparative Checking:
    • An extension of MSS or MDS, adding more cases to strengthen or refine findings.
    • Example: Adding Benin to the Togo/Ghana comparison.
      • Togo: Authoritarian, Colonizer: France.
      • Ghana: Democratic, Colonizer: UK.
      • Benin: Democratic, Colonizer: France.
      • What adding Benin does: If the hypothesis was that French colonialism always leads to authoritarianism, Benin (a former French colony that is democratic) disproves this simple hypothesis. It suggests that while colonialism may be a factor, it's not the sole or deterministic cause, or other variables are at play here.
  • Within-Case Comparison:
    • Comparative analysis of variation over time or in distinct parts of a single case.
    • Involves digging deep into one case to better understand the evidence.
    • Across-time example: Comparing Russia in 1905 (massive uprisings) with Russia in 1917 (full revolution) to understand why a full revolution occurred in one period but not the other, despite similar underlying conditions, or how conditions changed.

Coming Up with Variables

  • The selection of independent and control variables depends directly on the research question (i.e., the dependent variable).
  • Variables are chosen primarily based on existing scholarly literature.
    • Researchers must read extensively to understand what variables scholars have already identified as important potential causes for the phenomenon being studied.
    • For example, when asking "why do revolutions happen?" one must consult literature on past revolutions to identify established causal factors.

Is Politics a Science? Limits of the Comparative Method

  • Political science rarely results in "proofs":
    • Findings typically "support" hypotheses and theories, rather than definitively proving them.
  • Exceptions and probabilities: Most social science findings have exceptions, and relationships between variables are about probability and likelihood, not deterministic "laws" like in some natural sciences.
  • Lack of controlled experiments:
    • Unlike the physical and natural sciences, social sciences usually cannot make use of true controlled experiments (where there is random assignment to treatment and control groups).
    • Note: Field experiments in Political Science are an exception, involving real-world random assignment, but are less common for broad comparative questions.
  • Reliance on observational research: This is the most common approach in the social sciences.
    • While not experimental, methods like MSS and MDS (and statistical analysis) attempt to implicitly hold certain variables constant or account for their influence, allowing for more rigorous comparison and inference about causality.
  • The comparative method is a tool to mimic experimental control by carefully selecting cases that isolate certain variables, despite the inability to manipulate conditions in a lab setting.