Seminar 8: How to Do Causal Process Tracing – Historical

What is “systematic process tracing analysis’? Why has this method become so poplar in political science studies that use a small number of cases?

Most qualitative researchers in the process tracing tradition adopt a comparative-historical approach and tend toward a positivist perspective of the social sciences.

First, they consider causal inference as a problem of identifying a configurative set of variables (whose values “vary” across time and space i.e. X1…Xn), that expert a causal impact on a set of outcomes (Y1…Yn).

Second, they generally hypothesise or specify a ‘theory’ on how and why these variables interact in the way that they do, and affect the outcome in question.

This is what we call the “causal mechanism”.

Peter A Hall identifies three distinctive approaches within this systematic process tracing tradition in the social sciences: historically specific, multivariate and theory oriented.

As discussed previously, historically specific modes of explanation try to identify the full set of causal factors important to an outcome (y), and they try to understand why the outcome occurred in a specific time and place.

Historians tend to give priority to a very particular context, and the spatial or temporal specificities affecting their cases. The study of politics and history have always been closely connected. But even historians are rarely just “listing one damned thing after another”.

From a political science perspective, to say that the arbitrary efforts of King Charles to raise taxes caused the English revolution in 1640, usually implies that, under a given set of conditions, raising arbitrary taxes will tend to cause political discontent.

Multivariate explanations identify a small set of variables that cause an outcome, which are independent of other factors feeding into the causal chain. The objective is to measure the precise magnitude of the effect of each variable, and the confidence with which we can assert its effect, such that it generates precise parameter estimates.

Theory oriented explanations construe the task of causal explanation as one of elucidating and testing a theory. The task is to specify and hypothesise the causal mechanism, and the regularities in the causal process through which the relevant outcome is generated.

As we have discussed at length, under a given set of conditions, regression analyses and statistical methods are more effective for causal inference. For example, basic socio-structural factors such as per capita income, literacy and economic development have been found to be sufficient to stabilise democratic regimes. Here it is better to use marginal effect analyses.

But when comparative case studies began to show that stable democracy was really a product of complex strategic interactions among reformists, extremists, and defenders of the old regime, statistical methods became less useful in assessing the causal chain.

Instead, theorists turned to historically specific methods to test theories, now understood as causal mechanisms. Discuss.

This “mechanism” approach to social science gave birth to “process tracing”, in which many facets of the causal chain are intensively investigated, to test and formulate theories.

  1. Step 1: the investigator begins by formulating a set of theories that identify the principal causal variables that are said to conduce a specific type of outcome to be explained. The object is to test one theory against another. It is a three-cornered fight among a theory, a rival theory, and a set of empirical investigations.
  2. Step 2: for each of the theories to be considered the investigator then derives a set of predictions about the patterns that will appear if the theory is valid or false. This is a process of deriving predictions that are consistent with one theory but not another. In the course of the research these predictions will be often specified as hypotheses to be examined.
  3. Step 3: observations relevant to these predictions are then made. An observation consists of a piece of data drawn from, or observed, in the case, using whatever technology is appropriate: documentary research, field work, interviews or computation. The observations are designed to assess whether the process is present in the cases being investigated. Observations are ‘clues’ about events expected to occur if the theory is valid; the sequence of those events; the specific type of actions taken by various actors; and  statements by those actors about why they took those actions.
  4. Step 4: observations are drawn from the cases to compare predictions from theories, to reach a judgement about the relative merits of each theory. It is about comparing the plausibility of the theory with the validity of the observations. Effective theory building is as important as gathering empirical data.

In class exercise – consider the case of John Owen’s (1994) ‘Democratic Peace Theory‘, which specifies an ideational causal mechanism for why liberal states do not go to war with other liberal states, whilst also arguing that those same ideas often spur liberal states to wage war with non-liberal states.

Process tracing analysis is most useful when a researcher is theory oriented and interested in comparative-historical oriented modes of explanation. This is especially true of processes that are path dependent or rooted in rational choice or strategic interactions (i.e game theory).

Think about Andrew Moravcsick’s explanation for European integration.

But what is “path dependence” in the study of politics? How useful is the concept of “increasing returns” in explaining path dependence?  Discuss with reference to Paul Pierson’s article on ‘Increasing Returns, Path Dependence, and the Study of Politics (2000).

Process tracing.jpg




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