Public policy analysis case studies


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The Public Policy Case Collection is a free educational resource designed for the use and training of public policy and development students and practitioners around the world. Full access to this password-protected collection is available via collection membership. Cases are available for inclusion in a wide variety of online platforms , and educators have access to lesson plans and epilogues. In , all cases will be available for download and inclusion in leading online educational platforms including:.

This case explores the implementation of open data systems in New York City and Rio de Janeiro and the 'Civic Tech' movements that they have helped create. Click here for access to full video and written case material password required. Can techniques such as "no-till farming" work in a developing country such as Ghana? Can they help sequester carbon from the atmosphere and help solve global warming? Filmed on location in the South Bronx, Rio, and Mumbai, this case explores global efforts to make urban schools work. For access to a database of nearly additional Columbia University Case Consortium produced case studies and their accompanying material, please click here.

Case Method Resources. All schools collaborate widely with dual degree programs and collective research. Send us your contact information to request a free membership and receive full access to all video cases and written support materials. My video. Indeed, it is difficult to devise a program of falsification the first time a new theory is proposed. Path-breaking research, almost by definition, is protean. Subsequent research on that topic tends to be more definitive insofar as its primary task is limited: to verify or falsify a pre-existing hypothesis.


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Thus, the world of social science may be usefully divided according to the predominant goal undertaken in a given study, either hypothesis generating or hypothesis testing. There are two moments of empirical research, a lightbulb moment and a skeptical moment, each of which is essential to the progress of a discipline. Case studies enjoy a natural advantage in research of an exploratory nature.

Several millennia ago, Hippocrates reported what were, arguably, the first case studies ever p.

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They were fourteen in number. Piaget formulated his theory of human cognitive development while watching his own two children as they passed from childhood to adulthood. Evidently, the sheer number of examples of a given phenomenon does not, by itself, produce insight. It may only confuse. How many times did Newton observe apples fall before he recognized the nature of gravity?

This is an apocryphal example, but it illustrates a central point: case studies may be more useful than cross-case studies when a subject is being encountered for the first time or is being considered in a fundamentally new way. Let us briefly explore why this might be so. Traditionally, scientific methodology has been defined by a segregation of conjecture and refutation.

One should not be allowed to contaminate the other. Inspiration is more likely to occur in the laboratory than in the shower. The circular quality of conjecture and refutation is particularly apparent in case study research. Each of these topics entails a different population and a different set of causal factors.

A good deal of authorial intervention is necessary in the course of defining a case study topic, for there is a great deal of evidentiary leeway. It is the very fuzziness of case studies that grants them an advantage in research at the exploratory stage, for the single-case study allows one to test a multitude of hypotheses in a rough-and-ready way. The relationships discovered among different elements of a single case have a prima facie causal connection: they are all at the scene of the crime.

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This is revelatory when one is at an early stage of analysis, for at that point there is no identifiable suspect and the crime itself may be difficult to discern. The fact that A , B , and C are present at the expected times and places relative to some outcome of interest is sufficient to establish them as independent variables. Proximal evidence is all that is required.

A large-N cross-study, by contrast, generally allows for the testing of only a few hypotheses but does so with a somewhat greater degree of confidence, as is appropriate to work whose primary purpose is to test an extant theory. There is less room for authorial intervention because evidence gathered from a cross-case research design can be interpreted in a limited number of ways. It is therefore more reliable. Another way of stating the point is to say that while case studies lean toward Type 1 errors falsely rejecting the null hypothesis , cross-case studies lean toward Type 2 errors failing to reject the false null hypothesis.

This explains why case studies are more likely to be paradigm generating, while cross-case studies toil in the prosaic but highly structured field of normal science. I do not mean to suggest that case studies never serve to confirm or disconfirm hypotheses. Evidence drawn from a single case may falsify a necessary or sufficient hypothesis, as discussed below.

However, general theories rarely offer the kind of detailed and determinate predictions on within-case variation that would allow one to reject a hypothesis through pattern matching without additional cross-case evidence. Thus, one is unlikely to reject a hypothesis, or to consider it definitively proved, on the basis of the study of a single case. Harry Eckstein himself acknowledges that his argument for case studies as a form of theory confirmation is largely hypothetical.

At the time of writing, several decades ago, he could not point to any social science study where a crucial case study had performed the heroic role assigned to it. Indeed, it is true even of experimental case studies in the natural sciences. When one finds, for example, that competent observers advocate strongly divergent points of view, it seems likely on a priori grounds that both have observed something valid about the natural situation, and that both represent a part of the truth. The stronger the controversy, the more likely this is.

Thus we might expect in such cases an experimental outcome with mixed results, or with the balance of truth varying subtly from experiment to experiment. The more mature focus…avoids crucial experiments and instead studies dimensional relationships and interactions along many degrees of the experimental variables.

The tradeoff between hypothesis generating and hypothesis testing helps us to reconcile the enthusiasm of case study researchers and the skepticism of case study critics. They are both right, for the looseness of case study research is a boon to new conceptualizations just as it is a bane to falsification. Questions of validity are often distinguished according to those that are internal to the sample under study and those that are external i.

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Cross-case research is always more representative of the population of interest than case study research, so long as some sensible procedure of case selection is followed presumably some version of random sampling. Case study research suffers problems of representativeness because it includes, by definition, only a small number of cases of some more general phenomenon. Are the men chosen by Robert Lane typical of white, immigrant, working-class, American males? This means that case study research is generally weaker with respect to external validity than its cross-case cousin.

The corresponding virtue of case study research is its internal validity. Often, though not invariably, it is easier to establish the veracity of a causal relationship pertaining to a single case or a small number of cases than for a larger set of cases. Case study researchers share the bias of experimentalists in this regard: they tend to be more disturbed by threats to within-sample validity than by threats to out-of-sample validity. Thus, it seems appropriate to regard the tradeoff between external p. A third tradeoff concerns the sort of insight into causation that a researcher intends to achieve.

Two goals may be usefully distinguished.

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The first concerns an estimate of the causal effect ; the second concerns the investigation of a causal mechanism i. By causal effect I refer to two things: a the magnitude of a causal relationship the expected effect on Y of a given change in X across a population of cases and b the relative precision or uncertainty associated with that point estimate. Evidently, it is difficult to arrive at a reliable estimate of causal effects across a population of cases by looking at only a single case or a small number of cases.

The one exception would be an experiment in which a given case can be tested repeatedly, returning to a virgin condition after each test. But here one faces inevitable questions about the representativeness of that much-studied case. It is now well established that causal arguments depend not only on measuring causal effects, but also on the identification of a causal mechanism.

Moreover, without a clear understanding of the causal pathway s at work in a causal relationship it is impossible to accurately specify the model, to identify possible instruments for the regressor of interest if there are problems of endogeneity , or to interpret the results. In the task of investigating causal mechanisms, cross-case studies are often not so illuminating. It has become a common criticism of large-N cross-national research—e. We learn, for example, that infant mortality is strongly correlated with state failure; 23 but it is quite another matter to interpret this finding, which is consistent with a number of different causal mechanisms.

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Sudden increases in infant mortality might be the product of famine, of social unrest, of new disease vectors, of government repression, and of countless other factors, some of which might be expected to impact the stability of states, and others of which are more likely to be a result of state instability. Case studies, if well constructed, may allow one to peer into the box of causality to locate the intermediate factors lying between some structural cause and its purported effect.

Thus, Dennis Chong uses in-depth interviews with a very small sample of respondents in order to better understand the process by which people reach decisions about civil liberties issues. Chong comments:. One of the advantages of the in-depth interview over the mass survey is that it records more fully how subjects arrive at their opinions. While we cannot actually observe the underlying mental process that gives rise to their responses, we can witness many of its outward manifestations.

The way subjects ramble, hesitate, stumble, and meander as they formulate their answers tips us off to how they are thinking and reasoning through political issues.

Dietrich Rueschemeyer and John Stephens offer an example of how an examination of causal mechanisms may call into question a general theory based on cross-case evidence. The thesis of interest concerns the role of British colonialism in fostering democracy among postcolonial regimes. But, critically, we argued on the basis of the contrast with Central America, British colonialism did prevent the local plantation elites from controlling the local state and responding to the labor rebellion of the s with massive repression.

Against the adamant opposition of that elite, the British colonial rulers responded with concessions which allowed for the growth of the party— union complexes rooted in the black middle and working classes, which formed the backbone of the later movement for democracy and independence. Thus, the narrative histories of these cases indicate that the robust statistical relation between British colonialism and democracy is produced only in part by diffusion.

The interaction of class forces, state power, and colonial policy must be brought in to fully account for the statistical result. To be sure, causal mechanisms do not always require explicit attention. They may be quite obvious. And in other circumstances, they may be amenable to cross-case investigation. For example, a sizeable literature addresses the causal relationship between trade openness and the welfare state. The usual empirical finding is that more open economies are associated with higher social welfare spending. The question then becomes why such a robust correlation exists.

What are the plausible interconnections between trade openness and social welfare spending?

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