The Synthetic Control Method (SCM) is a statistical approach for estimating the causal effect of a treatment in comparative case studies. It is particularly suited for a case where there is one treated unit (e.g., village, state, country) and multiple untreated units observed across time. Therefore, it is applicable to aggregated time-series data. The methodContinue reading “Quasi-Experimental Design: Synthetic Control Method”
Author Archives: Taiwo A. Ahmed
Quasi-Experimental Design: Natural Experiment and Instrumental Variable
Natural Experiment Before discussing natural experiment, it makes sense to explain randomized assignment. By this, I mean that we randomly assign eligible units (or observations) to either a treatment or a control group. Due to the random assignment, there is a 50-50 chance for each eligible observation to be selected, which leads to an internallyContinue reading “Quasi-Experimental Design: Natural Experiment and Instrumental Variable”
Quasi-Experimental Design: Regression Discontinuity Design
Regression discontinuity design (RDD) is a quasi-experimental method for causal inference. RDD has become a prominent method for causal inference since the 2000s. One can account for both observed and unobserved heterogeneity. We can leverage our knowledge of treatment assignment to estimate the effect of a treatment, such as policy, an intervention, on an outcome.Continue reading “Quasi-Experimental Design: Regression Discontinuity Design”
Survey research
Survey is the most widely used technique in social science to gather data. There are different types of surveys —phone interviews, internet opinion polls, and variety in the types of questionnaires. They are all based on the ideals of the professionalized social research survey. Although there are those who claim that they will conduct aContinue reading “Survey research”
Tableau for Data Visualisation: Part 2
I have completed part I (chapter 1-17) and part II (chapter 18 – 46) of Practical Tableau by Ryan Sleeper. I think Alexander’s book and Ryan’s book complement each other. Alexander succeeded in focusing on the fundamentals of Tableau and kept the page count modest. It definitely gave me a good start with Tableau. Continue reading “Tableau for Data Visualisation: Part 2”
Econometrics: Univariate Timeseries Modelling and Forecasting
Univariate Timeseries Modelling (UTM) is simply the modelling and prediction of future economic variables using information from own past values and present/previous residual values. In other words, the values of y-variable in past periods (along with the current residual) influences the value of y-variable. We neither have explanatory x-variables nor other explained y-variables; we hardlyContinue reading “Econometrics: Univariate Timeseries Modelling and Forecasting”
Research: The Search for Knowledge
I have come across many books and articles on research methods that cover the logic of inquiry. But I have only read few that devote time to explain the logic of discovery, which Christopher Daya and Kendra L. Koivub (2018) describe “as a set of formal principles for devising a research question.” How does oneContinue reading “Research: The Search for Knowledge”
Tableau for Data Visualisation
Although I love to use R for customization and visualisation, certain graphs are much more easy and intuitive in Tableau because most of its interactions are achieved simply by dragging and dropping items onto the canvas. I recently ordered two books, which I am using to learn Tableau. Visual Analytics with Tableau by Alexander LothContinue reading “Tableau for Data Visualisation”
Game theory
In my reading of a few books on social science methods, quantitative methods in the social sciences can be divided into two fields: statistical analysis and mathematical models. In this post, I want to take about an essential field in mathematical models: Game theory. Game theory is when one applies mathematical models to have anContinue reading “Game theory”
Quasi-Experimental Design: Genetic Matching
The term matching is a procedure where we try to find for a sample observation other observations in the sample that have similar observable features. We often refer to the selected observations as matches, and after a repetition of this procedure for all or part of these observations, the subsample of observations that come out of this isContinue reading “Quasi-Experimental Design: Genetic Matching”
Taiwo A. Ahmed 