The Productivity Paradox
Open Access
- Area of Honors:
- Finance
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Brian Spangler Davis, Thesis Supervisor
- Brian Spangler Davis, Honors Advisor
- Keywords:
- finance
- macro econ
- economics
- productivity
- GDP
- k
- Abstract:
- In the age of the internet, everyone is able to do more than ever before. But if this is truly the case, then why do we not see this in productivity statistics? We can break the issue into four different reasons: mis- measurement, redistribution, time lag, and mis-management (Brynjolfsson). If considering this in the context of wages, research enhancements can be developed to address this paradox. The first change is implementing a new measure called Product Buying Equivalence Turnover (PBET)—a measure that looks at the time it takes for the adjusted price of a next generation product to reach that of the older generation. This could be the time it takes for the iPhone 8 to be the same as the iPhone 7. PBET can serve as a pseudo productivity measure by looking at buying power. To address measuring intangibles, it is crucial to adopt accounting methods based on managerial intent allowing R&D to be quantified more accurately and consistently (Hunter). At the moment, many intangible assets are labeled as expenses, making it difficult for analysts or economists to make forecasts. Lastly, in order to address time lag effects on measurement, the research suggests that shifting human capital towards areas of need is required, i.e. changing the way we incentivize college and provide stipends or subsidies for certain majors while cutting back on others. The distribution of H-1B visa workers is disproportionately towards data science jobs. Changing in house human capital can help make the high demand workers ubiquitous. Combining these approaches should help mitigate the paradox that we have today by both improving economic productivity and improving our measurements of productivity.