Graduate School for Social Research Autumn 2016 tomescu.1@osu.edu Research Methodology and Methods of Social Inquiry socialinquiry.wordpress.com Irina Tomescu-Dubrow and Kazimierz M. Slomczynski This is a course in how to do theoretically informed research. How do we know the things that we think we know?  In particular, how can we build and test social theory in a manner that takes advantage of the best available evidence? By the end of this course you should have a better idea of: 1) the range of methods available to social scientists, and 2) how to select and craft a research design so that the theory to be tested and the data collected have a solid match. To these ends we will cover such topics as research design, reliability and validity, causality, sampling, modeling, and types of data collection, and secondary data analysis.    WEBPAGE socialinquiry.wordpress.com   COURSE REQUIREMENTS are as follows: Three 4 main projects, spread throughout the course: - two take-home assignments (each approx. four pages long, 12-point font, double-spaced; 15% each) - one critical assessment paper (approx. 10 pages long, 12-point font, double-spaced ; 40% of grade)  - one group exercise (in the field) – 15% Classroom participation, involving class assignments and regular classroom participation throughout the semester (for a total of 15%). Active engaging in theoretical debates with colleagues is core to social science researchers.  I expect discussion to be professional and polite, but engaged.  Do not shy away from points.  Do push arguments. Do not accept two logically inconsistent points as "equally valid perspectives."  Do seek to integrate alternative perspectives and understand the basic assumptions that drive different conclusions. 

Causality and Causal Inference Descriptive Studies Language of Science – Terminology Theory Causality and Causal Inference Descriptive Studies

3. Empirical Generalizations 4. Laws 5. Theories Terminology Concepts & Constructs 2. Hypotheses 3. Empirical Generalizations 4. Laws 5. Theories Concepts may be abstract; refer to aspects or qualities that groups of things hold in common. Hypoth: hypothesis corresponding to the empirical generalization about religion and suicide rates above would be that: "cohesive groups have fewer suicides per capita than non-cohesive groups."

Science as Process Theories Empirical Hypotheses generalizations Observations (testing hypotheses)

Hypotheses - a causal framework A hypothesis is a prediction about how variables relate to each other (i.e. what is the relationship btw. the variables). Relationships between variables: changes in the values of one variable are accompanied by systematic changes in the other variable(s). A hypothesis is usually based on theoretical expectations about how things work. At minimum, any hypothesis involves two variables: - the dependent variable (DV) measures the presumed effect/outcome; Y - the independent variable (IV) measures the presumed cause; X In addition: controls, intervening Variables; Z Based on theory, we specify the direction of influence among variables. i.e we formulate hypotheses.

Causality: David Hume (1711-1776) Causality cannot be directly observed; it is an interpretation. Conditions: (1) A and B are contiguous in space and time (spatial and temporal contiguity) (2) A precedes B (time ordering) (3) A & B always occur together (constant conjunction)

Causality: John Stuart Mill (1806-1873) System of Logic (1843) conditions of causality No factor can be regarded as a cause if: (1) it is present while the effect is absent (i.e. method of agreement), (2) it is absent while the effect is present (i.e. method of difference), (3) it varies while the effect does not vary (i.e. method of concomitant variation)

Causes Causes = two types: necessary and sufficient. A third type = a contributory cause - requires neither necessity nor sufficiency in and of itself, but which contributes to the effect

NSC Necessary causes - If x is a necessary cause of y, then the presence of y necessarily implies the presence of x. The presence of x, however, does not imply that y will occur Sufficient causes - If x is a sufficient cause of y, then the presence of x necessarily implies the presence of y. However, another cause z may alternatively cause y. Presence of y does not imply the presence of z Contributory causes - For some specific effect, in a singular case, factor that is a contributory cause is one amongst several co-occurrent causes. It is implicit that all of them are contributory.

INUS J. L. Mackie Insufficient but Non-redundant parts of a condition which is itself Unnecessary but Sufficient for the occurrence of the effect

Causality in the social sciences (Daniel Little, Varieties of Social Explanation, 1991) 1. Causal Mechanism specifies how a cause exerts its effects. C is a cause of E if there is a series of events Ci leading from C to E, & the transition from each Ci to Ci+1 is governed by law L. 2. Inductive regularity: C is a cause of E if there is a regular association btw. events Ci and E, and Ci happens reasonably before E. 3. Necessary and sufficient conditions C is a cause of E if events Ci are necessary condition for the occurrence of E, and events Ci are jointly sufficient to give rise to E.

Deterministic and probabilistic approach to causality Deterministic approach: finding a variety of conditions C, for F causing. If all conditions C, then always F E Probabilistic approach: likelihood of the relationship F E

Statistical inference Substantive and null hypotheses A substantive hypothesis is the actual expectation about the relationship between two or more variables. (E.g.: Education has positive impact on pro-democratic attitudes) To decide if a substantive hypothesis is supported by the data, it is necessary to test a related hypothesis, called the null hypothesis (E.g.: Education has no effect on pro-democratic attitudes) Spurious Associations A statistically significant association between two variables, driven by a third variable, which affects both. Generally, social science research tests hypotheses. What is statitically significant?

Black box Black box = mechanism through which F E E.g.: Father’s education & occupation status affect son’s outcome (income) - why? (Resource and socialization) ___________________________________________ In causality, time matters - immediate vs. lagged effects Measurement of time: calendar time (periods) and age. Cohort effects

Descriptive Studies and Causal Inferences Descriptive Studies: - specify up-front what researchers intend to do in their research - justify the need for good understanding of the complexity of context/culture of the studied phenomena - provide observable consequences/manifestations of the studied phenomena - focus on description of events in precise & systematic manner - use variety of quantitative and quantitative measures

Improvements - Inferences Inference is the process of using the facts we know to learn about facts we do not know To enhance descriptive studies: 1) select observations such that the facts that you have will allow you to infer information about unobserved facts 2) among the facts (observations) that you have, distinguish the systematic components from the non-systematic/‘random’ ones . 3) make linkages to the theory (Descriptive studies as testing cases)

Rules Data balance - more observations on the implications of a specific theory will help us evaluate that theory - avoid data selectivity problem: do not discard data - learn from preliminary data about the need for additional data - systematize data and make sure to distinct data and interpretation

Specific problems of descriptive studies regarding causality - Path dependency - Counterfactuals

Path dependency Path dependence = the dependence of outcomes on the path of previous outcomes, rather than simply on current conditions. In a path dependent process, “history matters” — it has an enduring influence. Choices made on the basis of transitory conditions can persist long after those conditions change. Origin of the concept:  Paul David’s (1985, 1986) interpretation of the emergence and persistence of the QWERTY standard (vs. Dvorak Simplified Keyboard or other solutions)

Path dependency, policies and efficency Liebowitz, S. J. and Margolis, S. E. 1995. Path dependence, lock-in and history," Journal of Law, Economics, and Organization 11: 205-226. Roe, M. J. 1996. Chaos and evolution in law and economics. Harvard Law Review 109: 641-68 "weak path dependence" = a choice has no efficiency consequences.  "semi-strong form" path dependence = a choice that has become inefficient but is not worth changing third degree path dependence = a choice that has become inefficient and there are weak efficiency reasons to not to change

Mechanisms Positive feedback mechanisms. Reinforcing pattern, in which industries 'tip' towards one or another product design. Inertia. Institutional mechanisms. Uncoordinated stanadardization.

Counterfacuals and causal inference Morgan, Stephen L, and Christopher Winship. 2007/2014. Counterfactuals and Causal Inference: Methods and Principles for Social Research. Cambridge. Alternative estimation techniques using both the potential outcome model and causal graphs Conditioning techniques, such as matching and regression to acount for a potential outcomes. perspective. instrumental variable estimators. The importance of causal effect heterogeneity.

Discussion Hypothesis: Introduction of gimnasium into educational system in Poland resulted in the increase in educational achievement of students 15 years old. Observation:By any measure, Poland has made remarkable education progress since 1999 (when gimnasium was introduced). PISA (re 15 year old students) documents this. Between 2003 and 2012 Poland gained 2.6 points a year while the rest of the world, on average, remained unchanged. Counterfactual: Assume that gimnasium was not introduced in Poland. Is the remarkable education progress in Poland attributable to gimnasium?