Applied Empirical Accounting Research
The master course Applied Empirical Accounting Research is a highly intensive and extracurricular individual preparation of students who are accepted for writing their master thesis at the Professorship of Empirical Accounting. Although the course is voluntary, we strongly recommend to pass this training right after the acceptance for a master thesis. Due to the specialized nature of this course, master thesis candidates of other professorships cannot apply this course.
Although the University of Cologne offers a wide range of courses that promote young scholars' research activities (e.g., the course Empirical Accounting Research Design formally offered by Prof. Dr. Julia Nasev and several course in the Area Finance and the Area Statistics and Econometrics), we believe that a more specific training which is tailored to successfully deal with the challenges of a master thesis at the Professorship of Empirical Accounting is conductive for the student and the mentor during the production of the Master Thesis. Thus, the purpose of this course is to coach students to independently initiate, plan, and conduct empirical research projects in the fields of empirical financial and non-financial accounting.
Consequently, the course does not follow a strict/unified schedule. Instead, the course is matched to the individual situation of each participating student. However, the following steps define a "carcass" that, if applicable to the topic, should be reached by all candidates of a cohort:
Step 1: Identification of research opportunities
The first - and maybe most difficult - step of a research project is to identify and draft a research idea that has the potential to truly make an incremental contribution over and above prior research and practitioners' insights. The result of this first step should be a short statement of one/two phrases ("elevator pitch") that summarizes the purpose and potential implication of a possible research project. This initial step might take about one month. In this interval the participant is required to give a short feedback about the current progress at least once a week in a short meeting or phone call with the adviser.
Step 2: Positioning of the topic in the prior literature
The student and the adviser discuss whether and how the research question can be classified and positioned in the light of the prior theoretical and empirical literature. Therefore, the participants become familiar with the "research question scorecard"-technique which helps to identify the way how an analysis can contribute to closing so-far existing "research gaps".
Step 3: Discussion of the identification strategy
The next step is to develop a clear identification strategy to empirically study a hypothesized phenomenon. Thereby, the key challenge is to find settings where an exogenous event occurs that is closely related to the research question (e.g., a regulatory change or an environmental disasters) or, otherwise, to convincingly address endogeneity concerns (e.g., endogeneity arising from self-selection if the event occurs in a voluntary setting).
Step 4: Sampling techniques
To produce preliminary evidence for a research question, it is typically necessary to conduct pre-tests based on reduced samples. The derive meaningful indications whether a hypothesized phenomenon actually exists, researchers often use randomly chosen samples. Thus, in Step 4, the student discusses several potentially suitable techniques to define such samples with the advisor (e.g., methods of (perfect/imperfect) random sampling and weighted sampling). In this step, the student learns how to estimate and consider the length and the costs of the data collection procedure already in the definition of the reduced sample.
Step 5: Dataset and preliminary empirical analyses
Next, the student has to hand-collect and/or independently obtain (e.g., download from available databases) a probate dataset to provide preliminary evidence for the research question. The advisor makes sure that this data collection process does not take more than three days. Using the dataset, the student has to conduct a small set of descriptive analyses and, if applicable to the research question, some statistical tests. However, it is generally not required to conduct more complex statistical analyses (e.g., multivariate regression analyses).
Step 6: Drafting the research idea
Finally, the student has to draft the research idea, position the research question against prior literature, applicable research methodology and preliminary findings, and research prospects in a proposal of less than thousand word (about two pages). Moreover, the student should self-critically summarize the steps and progress of the proposed research idea in colloquium of about 15 minutes.
Step 7: Official start of the master thesis
After successfully passing the final colloquium it is up to the student to begin with the production of the master thesis.