The impact of firm-level innovation on labor productivity and employment in selected African countries - Zerayehu Sime; Getaw Tadesse (Journal of Innovation and Entrepreneurship)
Abstract The paper examines the impact of different types of innovations—such as process, product, and R&D—on labor productivity and employment across several African nations. Utilizing data from the World Bank Enterprise Survey, the study constructs pseudo-panel data based on legal status, firm size, and industry type and employs the propensity score matching and the dose–response model to explore the relationship between innovation and labor market outcomes. The descriptive analysis indicates that 2,673 firms are engaged in at least one of the innovation activities, and 250 firms do not have any innovation activities. The propensity score matching finds that the overall combined effect of all types of innovation is statistically significant and has a positive effect on the employment of non-production workers and skilled workers, but it harms their productivity. Not only this, but it has also a negative impact on the productivity of permanent, and unskilled workers. The only positive impact goes to the productivity of production workers. Except for skilled labor, no segments of the labor force have been impacted by product innovation, but it has statistically significant influences on the productivity of all types of workers, still, production workers received a positive influence. It also finds that process innovation positively influences the productivity of production workers and the employment of skilled, non-production, and production workers. On the other hand, permanent, non-production, and skilled employees respond negatively to process innovation. Regarding R&D innovation, except for production workers, all are negatively impacted and statistically significant. On employment creation, R&D has also a positive and statistically significant impact on employment except for permanent employees. On top of this, the findings of the dose–response function are also in line with the propensity score matching method except for the combined effect of innovation on production workers. In other words, the intensity has a declining dose effect while innovation has a growing effect by the propensity score method for production workers. Additionally, the dose–response function shows a strong positive correlation between the intensity of innovation and skilled workers with various trends as well as permanent employees. The effect is initially diminishing for unskilled workers and non-production workers, but it gradually increases over time. In general, the finding challenges the assumption that innovation uniformly improves productivity, instead revealing a more complex dynamic where job creation comes at the cost of lower productivity in certain labor segments.