Syllabus/achievement requirements

Students attending Master's courses will be able to participate on a library course. At the course you will learn how to do searches in both national and international databases, and you will have the opportunity to search the articles that is on your curriculum.The course is voluntary, but we strongly recommend that students attend. More information to come.

Books

Morgan, SL & Winship, C (2015) Counterfactuals and Causal Inference: Methods and Principles for Social Research, Cambridge University Press 2nd edition

Angrist, JD & Pischke, JS (2015) Matering Metrics: The Path from Cause to Effect, Princeton University Press

Downloadable articles, books and other texts

You can search the articles and e-books in the e-journal database available at the University of Oslo Library. This requires having access to and being logged onto the UiO system. Contact the Reference Services at the Humanities and Social Sciences Library if you have problems finding the literature.

 

Acharya, A., Blackwell, M., and Sen, M. (2014a). The political legacy of american slavery

Acharya, A., Blackwell, M., and Sen, M. (2015b). Explaining causal findings without bias: Detecting and assessing direct effects

Altonji, J. G., Elder, T. E., and Taber, C. R. (2005). Selection on observed and unobserved variables: Assessing the effectiveness of catholic schools. Journal of Political Economy, 113(1):151–183

Angrist, J. and Pischke, J. S. (2010). The credibility revolution in empirical economics:How better research design is taking the con out of econometrics. Journal of Economic Perspectives, 24(2):3

Aronow, P. M. and Samii, C. (forthcoming). Does regression produce representative estimates of causal effects? American Journal of Political Science

Bates, R. H. and Block, S. A. (2013). Revisiting african agriculture: Institutional change and productivity growth. The Journal of Politics, 75:372–384

Bechtel, M. M., Hangartner, D., and Schmid, L. (2015). Does compulsory voting increase support for leftist policy? American Journal of Political Science

Bechtel, M. M. and Sattler, T. (2015). What is litigation in the world trade organization worth? International Organization, 69(2):375 – 403

Blackwell, M. (2013a). A framework for dynamic causal inference in political science. American Journal of Political Science, 57(2):504 – 519

Blackwell, M. (2013b). A selection bias approach to sensitity analysis for causal effects. Political Analysis, 22(1):169 – 182

Bollen, K. A. and Pearl, J. (2013). Handbook of Causal Analysis for Social Research, chapter Eight Myths About Causality and Structural Equation Models, pages 301 –330. Springer

Caughey, D. and Sekhon, J. S. (2011). Elections and the regression discontinuity design: Lessons from close u.s. house races, 1942 - 2008. Political Analysis, 19:385

Clarke, K. A. (2009). Return of the phantom menace: Omitted variable bias in political research. Conflict Management and Peace Science, 26(1):46–66

Eggers, A. C., Fowler, A., Hainmuller, J., Hall, A. B., and Snyder, J. M. (2015). On the validity of the regression discontinuity design for estimating electoral effects: New evidence from over 40,000 close races. American Journal of Political Science, 59(1):259 – 274

Finseraas, H. (2015). The effect of a booming local economy in early childhood on the propensity to vote: Evidence from a natural experiment. British Journal of Political Science, FirstView:1–21

Glynn, A. N. and Quinn, K. M. (2011). Why process matters for causal inference. Political Analysis, 19:273 – 286

Hainmuller, J. (2012). Entropy balancing for causal effects: A multivariate reweighting method to produce balance samples in observational studies. Political Analysis, 20(1):25 – 46

Hainmuller, J., Hall, A. B., and Snyder, J. M. (2015). Assessing the external validity of election rd estimates: An investigation of the incumbency advantage. Journal of Politics, 77(3):707 – 720

Ho, D. E., Imai, K., King, G., and Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15(1):199 – 236

Iacus, S. M., King, G., and Porro, G. (2012). Causal inference without Balance checking: Coarsed exact matching. Political Analysis, 20(1):1 – 24

Imai, K., Keele, L., Tingley, D., and Yamamoto, T. (2011). Unpacking the black box of causality: Learning about causal mechanisms from experimental and observational studies. American Political Science Review, 105(4):765 – 789

Keele, L. and Stevenson, R. T. (2014). The perils of the all cause model. Working Paper

Keele, L. (2015a). The discipline of identification. PS: Political Science amp; Politics, 48:102–106

Keele, L. (2015b). The statistics of causal inference: A view from political methodology.Political Analysis, 23(3):313 – 335

Keele, L. and Minozzi, W. (2013). How much is minnesota like wisconsin? assumptions and counterfactuals in causal inference with observational data. Political Analysis, 21(1):193 – 216

Keele, L. and Titiunik, R. (2015). Geographic boundaries as regression discontinuities. Political Analysis, 23(1):127 – 155

Longo, M., Canetti, D., and Hite-Rubin, N. (2014). A checkpoint effect? evidence from a natural experiment on travel restrictions in the west bank. American Journal of Political Science, 58(4):1006–1023

Pearl, J. (2012). Handbook of Structural Equation Modeling, chapter The Causal Foundations of Structural Equation Modeling, pages 68 – 91. Guildford Press: New York

Sekhol, J. S. (2009). Opiates for the matches: Matching methods for causal inference. Annual Review of Political Science, 12:487 – 508

Sekhol, J. S. and Titiunik, R. (2012). When natural experiments are neither Natural nor experiments. American Political Science Review, 106(1):35 - 57

Skovron, C. and Titiunik, R. (2015). A Practical Guide to Regression Discontinuity Designs in Political Science. Working Paper.

Sovey, A. J. and Green, D. P. (2011). Instrumental variables estimation in political science: A readers' guide. American Journal of Political Science, 55(1):188 -200

Ward, M. D., Greenhill, B. D., and Bakke, K. M. (2010). The perils of policy by p-value: Predicting civil conflicts. Journal of Peace Research, 47(4):363 – 375

 

 

Published Nov. 23, 2015 4:53 PM - Last modified Jan. 18, 2016 1:35 PM