4th IDSC of IZA Workshop: Matching Workers and Jobs Online - New Developments and Opportunities for Social Science and Practice

Laura Gee (Tufts University and IZA)
Lisa Kahn (University of Rochester and IZA)
Danielle Li (MIT Sloan School of Management)

• The effectiveness of the new internet-based job search methods, both relative to more traditional forms of job search and to each other.
• Descriptive studies of how workers and firms look for each other online: How do firms craft job ads? How do workers search for jobs over time? To what extent are recruiting and job search ‘batch’ or sequential processes? How effectively do job ads direct applications? What is the role of informal networks and referrals, both on- and off-line, in the labor search and matching process? What does all this descriptive information mean for theoretical models of labor market search and matching?
• Experimental and other studies of online search with the potential to improve the efficiency of online matching. Examples include improving job and worker categorizations, better algorithmic recommendations, certification of worker qualifications, online reviews of employers and workers, and increasing the information content of postings (for example adding information on the number of competing applicants).
• Using data derived from online labor market matching processes to study key research questions in labor economics, including minimum wages, labor market dynamics, discrimination, the effects of unemployment insurance, and trends in the types of skills demanded.
• The potential for data from online labor market matching process to supplement existing publicly-available data on labor market trends and conditions. Examples include measuring and forecasting local, national and occupation-level unemployment and vacancy rates, forecasting labor market shortages and ‘bottlenecks’, and informing educational and training institutions about emerging skill needs.
• Other topics related to the online matching of workers and firms.