2.2: Four Approaches to Research

Learning Objectives

By the end of this section, you will be able to:

• Identify, and distinguish between, the four different approaches to research.
• Consider the advantages and disadvantages of each research approach.
• Compare and contrast the four approaches to research.
• Identify best practices for when and how to use case studies.

Introduction

In empirical research, there are four basic approaches: the experimental method, the statistical method, the case study method, and the comparative method. Each involves research questions, the use of theories to inform our understanding of the research problem, hypothesis testing, and/or hypothesis generation. Further, each method attempts to understand the relationship between two or more variables, whether that relation is correlational or causal.

The Experimental Method

What is an Experiment? An experiment is defined by McDermott (2002) as “laboratory studies in which investigators retain control over the recruitment, assignment to random conditions, treatment, and measurement of subjects” (pg. 32). Thus, experimental designs involve “standardization, randomization, between-subjects versus within-subject design, and experimental bias” (McDermott, 2002, pg, 33). This methodology assists in reducing bias in research, and for some scholars holds great promise for research in political science (Druckman, et. al. 2011). Political science experimentation almost always involves statistical tools to discern causality.

An experiment is used whenever the researcher seeks to answer causal questions (cause and effect) or is looking for causal inference. In other words, a change in one variable verifiably causes an effect or change in another variable. Correlation is different since it only occurs when a relationship or association can be established between two or more variables. Correlation does not equal causation! Just because two variables, measures, constructs, actions, etc. are related, does not mean that one caused the other. Indeed, in some cases, the correlation may be spurious, or a false relationship. This scenario can often occur in analyses, especially if particular variables are omitted or constructed improperly.

A good example involves capitalism and democracy. Political scientists assert that capitalism and democracy are correlated. When we see capitalism, we see democracy, and vice versa. Notice, that nothing is said about which variable causes the other. It may well be that capitalism causes democracy. Or, it could be that democracy causes capitalism. So X could cause Y or Y could cause X. In addition, X and Y could cause each other, that is capitalism and democracy cause each other. Similarly, there could be an additional variable Z that could cause both X and Y. For example, it may not be that capitalism causes democracy or that democracy causes capitalism, but instead something completely unrelated, such as the absence of war. The stability that comes from an absence of war could be what allows both capitalism and democracy to flourish. Finally, there could be a(n) intervening variable(s), between X and Z. It is not capitalism per se that leads to democracy, or vice-versa, but the accumulation of wealth, often referred to as the middle class hypothesis. In this case, it would be X→A→Y. Using our example, capitalism produces wealth, which then leads to democracy.

Real world examples exist. Most wealthy countries are democratic, such as the United States. However, this is not the case for all. The oil-producing countries in the Persian Gulf are considered wealthy, but not democratic. Indeed, the wealth produced in natural resource-rich countries may reinforce the lack of democracy as it mostly benefits the ruling classes. Also, there are countries, such as India, which are strong democracies, but are considered developing, or poorer nations. Finally, some authoritarian countries adopted capitalism and eventually became democratic, which would seem to confirm the middle-class hypothesis, including South Korea and Chile. However, plenty of other countries, such as Singapore, are considered quite capitalistic with a developed strong middle class, but have yet to fully adopt democracy.

These potential contradictions are why political scientists are careful with making causal statements. Causality is difficult to establish, especially when the unit of analysis involves countries. Causality is a bit easier to establish when experimentation involves individuals, the inclusion of a treatment variable, or the manipulation of just one variable across a number of cases. The reiteration of an experiment multiple times can confirm this idea. A good example includes interviewer effects among respondents in surveys. Experiments consistently show that the race, gender, and/or age of the interviewer can affect how an interviewee responds to a question, especially if the interviewer is a person of color and the interviewee is white and the question that is asked is about race or race relations. In this case, we can make a strong argument that interviewer effects are causal. That X causes some kind of effect in Y.

Are there any causal statements made by comparativists? The answer is a qualified yes. Often, the desire for causality is why comparative political scientists study a small number of cases or countries. One case/country, or a small number of cases/countries, analyses lend well to searching for a causal mechanism. Are there any causal statements in comparative politics that involve lots of cases/countries? The answer is again a qualified yes. Democratic peace theory is explained later in this textbook:

“Democracies per se do not go to war with each other because they have too much in common - they have too many shared organizational, political and socio-economic values to be willing to fight each other - therefore, the more democratic nations there are the more peaceful the world will become and remain.”

Even in democratic peace theory, there are ‘exceptions’. Some cite the U.S. Civil War as a war between two democracies. However, an argument can be made that the Confederacy was a flawed or unconsolidated democracy and ultimately not a war between two real democracies. Others point to U.S. interventions in various countries during the Cold War. These countries, Iran, Guatemala, Indonesia, British Guyana, Brazil, Chile, and Nicaragua, were all democracies. Yet, even these interventions are not convincing to some scholars as they were covert missions in countries that were not quite democratic (Rosato, 2003).

Statistical Methods

Statistical methods are the use of mathematical techniques to analyze collected data, usually in numerical forms, such as interval or ratio-scale. In political science, statistical analyses of datasets are the preferred method, especially when focusing on how individuals make political decisions, such as voting in a given election, or how they may express themselves ideologically.

Surveys are one way to collect evidence regarding human behavior. Potential respondents are sampled through the use of a questionnaire constructed to elicit information regarding a particular subject. For example, a survey may ask U.S. residents about taking one of the approved COVID-19 vaccines, if they intend to get a booster in the future, and their thoughts on pandemic-related restrictions. Respondent choices are then coded, usually using a scale of measurement. Next, the data is analyzed, often with the use of a statistical software program. Researchers may also rely on the existing data from various sources (e.g., government agencies, think tanks, and other researchers) to conduct their statistical analyses. Scholars search for correlations among the constructed variables for evidence in support of their hypotheses on the topic (Omae & Bozonelos, 2020).

Statistical methods are great for discerning correlations, or relationships between variables. Given that causation is difficult to prove in political science, many researchers default to the use of statistical analyses to understand how well certain things relate. This idea is particularly true when it comes to applied research. Applied research is defined as “research that attempts to explain social phenomena with immediate public policy implications'' (Knoke, et. al. 2002, pg. 7).

Statistical methods are also the preferred approach when it comes to the analysis of survey data. If the sample is representative of the population, then the findings of the sample will allow for the formation of inferences about some aspect of the population (Babbie, 1998).

To quickly review of information is analyzed:

• Quantitative method centers on testing a theory or hypothesis through mathematical and statistical means, using data from a large sample size. Scientists may collect data, known behavior actions, or close-ended research.
• Qualitative method centers on exploring ideas and phenomena, potentially with the goal of consolidating information or developing evidence to form a theory or hypothesis to test. Here, scientists collect data on unknown actions, or open-ended research where we do not already know what to look for, and then make verbal statements about them.

Experimental and statistics fall squarely into the quantitative camp, whereas comparative politics is mostly considered as qualitative. The fields of behavioral economics and social psychology are well-suited for experiments. Both studies focus on the behavior of individual people. As political science has shifted more towards the study of individual political behavior, experimentation and statistical analysis of collected data, through experiments, surveys and other methods are utilized.

For more on the history of this divide and how it has affected political science, see Franco and Bozonelos’s (2020) chapter on the History and Development of the Empirical Study of Politics in Introduction to Political Science Research Methods.

The Comparative Method

What is the Comparative Method? Ancient Greek philosophers, such as Plato, the author of The Republic, Aristotle, the author of Politics, and Thucydides, the author of the History of the Peloponnesian War wrote about politics in their times in a comparative manner. Indeed, as Laswell (1968) said, all science is 'unavoidably comparative'. Most scientific experiments or statistical analyses will have a control or reference group. This way, the results of a current experiment and/or analysis can be compared to some baseline group. Knowledge develops by grafting new insights through comparison.

Likewise, comparison is more than just description. We are not only analyzing the differences and/or similarities, we are conceptualizing. For political scientists, concepts are “generally seen as nonmathematical and deal with substantive issues” (Goertz, 2006). For example, if we want to compare democracies, we must first define what exactly constitutes a democracy.

Even in quantitative analyses, concepts are always understood in verbal terms. Given that there are quite a few ways to formulate quantitative measurements, conceptualization is key. Developing the right scales, indicators, or reliability measures is predicated on having one’s concepts right. A good example is the simple, yet complicated concept of democracy. Again, what exactly constitutes a democracy? We are sure that it must include elections, but not all elections are the same. An election in the U.S. is not the same as an election in North Korea. Clearly, if we want to determine how democratic a country is, and develop good indicators from which to measure, then concepts matter.

Comparative methods involve “the analysis of a small number of cases, entailing at least two observations”. In other words, the comparative method involves more than a case study, or single-N research (discussed in detail below), but less than a statistical analysis, or large-N study. It is for this reason that comparative politics is so closely intertwined with the comparative method. As we tend to compare countries in comparative politics, the numbers end up somewhere in between, anywhere from a few to sometimes over fifty. Cross-case analysis through the comparison of key characteristics is the preferred method.

Case Studies

Why would we want to use a case study? One of the major techniques, they provide for in-depth traditional research. Many times there is a gap in knowledge, or a research question that necessitates a certain level of detail. According to Naumes and Naumes (2015), case studies involve storytelling, and power exists in the story’s message. Fact-based stories describe situations, characters, and the mechanisms for why things happen. For example, the exact cause of how the SARS-CoV-2 virus, more commonly referred to as COVID-19, grow into a pandemic will involve telling a story.

A case can be simply defined as a “factual description of events that happened at some point in the past” (Naumes and Naumes, 2015). A case could be a person, a family household, a group or community, or an institution, such as a hospital. The key question in any research study is to clarify the cases that belong and the cases that do not belong (Flick, 2009). If we are researching COVID-19, at what level should we research? This action is referred to as case selection.

For many comparativists in political science, the unit (case) is often observed as a country or a nation-state. A case study can provide an intensive look into that single case, often with the intent to better understand a particular variable of interest. For example, we could research a country’s successful COVID-19 response. This case study could consist of a single observation within the country, and include the country’s level of health readiness, the government’s response, and the buy-in from their citizens.

This description represents the traditional understanding of case study research - the in-depth analysis of one case. Once we research and discover the internal processes that led to the successful response, we naturally want to compare it to other countries (cases). This shifting the analysis from just one country (case) to other countries (cases) is called a comparative case study.

Finally, as mentioned in Chapter One, there can also exist subnational case study research. This type of research can happen entirely within a country (case), such as comparing COVID-19 response rates among states in Mexico. Or it can happen between countries, where subnational governments are compared, such as within Europe. There are quite a few subnational governments with significant amounts of autonomous power, such as Catalonia in Spain. Flanders and Walloons in Belgium are considered partially autonomous regions. Meanwhile, Scotland within the UK is a region that has experienced devolved power.

Use of Case Studies in Comparative Politics

Case studies can be used in other areas, such as business. Ellet (2018) notes that case studies are “an analogue of reality”. They help readers understand particular business decision scenarios, or evaluation scenarios where some process, product, service, or policy is being evaluated on their performance. Business case studies also feature problem diagnosis scenarios, where the authors research when a business is not successful, and try to understand the actions, processes, or activities that led to failure. Case studies are also relevant in medical studies. Clinical case studies investigate how a diagnosis was made. Solomon (2006) notes that many of the case studies published by physicians are anecdotal reports, where they notate procedures for diagnosis. These case studies are vitally important for the field of medicine as they allow researchers to form hypotheses on particular medical disorders and diseases.

Case studies are vital to theory development in political science, which serve as the cornerstones of different discourses in the discipline. Blatter and Haverland (2012) note that a number of case studies have reached ‘classic’ status in political science, including Robert Dahl’s Who Governs? [1961], Graham T. Allison’s Essence of Decision [1971], Theda Skocpol’s States and Social Revolutions [1979], and Arend Ljiphart’s The Politics of Accommodation [1968].

• Dahl’s work popularized the concept of pluralism, where different actors hold power.
• Allison studied the decision-making processes during the 1962 Cuban Missile Crisis, whose work was influential for public policy analysis.
• Skocpol’s book laid out the conditions under which a revolution may take place. Skocpol’s work coincided with the rise of neo-institutionalism in the 1970s, where political scientists began to refocus their attention on the role of institutions in explaining political phenomena.
• Ljiphart provided the concepts of “politics of accommodation” and “consensus democracy”. The terms are central to our understanding of comparative democracy.

Historically, comparative politics have focused on the nation-state. By this, researchers compare countries often involving regime types (both democratic and nondemocratic), political economies, political identities, social movements, and political violence. This “looking within” is what separates comparative politics from other fields of political science. Thus, the nation-state is the most relevant and important political actor.

Clearly, the nation-state is not the only actor in politics. Nor is it the only level of analysis. Other actors exist in politics, from subnational actors, ranging from regional governments to labor unions, and all the way to insurgents and guerillas. There are also transnational actors, such as nongovernmental organizations, and multinational corporations, as well as more sinister groups such as criminal and terrorist networks. In addition, we can analyze at an international (systemic) level, subnational level, and individual level. However, nation-states remain the primary unit and level of analysis in comparative politics.