Study of Cross-country Additional Value of Skills Based on Data from E-recruiting Websites

The demand for certain skills often changes, that is why it is important to determine the most requested skills presently. Moreover, identifying the demand for different knowledge can help to decrease the education-job mismatch. Therefore, the purpose of this work is to determine the demand for skills in the IT field. We use R and Python to automatically collect data from job search portals in the United States (Indeed) and Russia (HeadHunter). We extract the most frequent required skills in the job postings and then analyze the structure of the demand for skills using hierarchical clustering. A linear regression method is used with the logarithm of wages as a dependent variable and skills as explanatory variables to determine the added value of a particular skill. The results of this paper can be used by job seekers to update their skill set to more valuable and for universities to change their curriculum to offer more demanded courses.