Title: Technology adoption and the impact on average productivity
Abstract: Abstract In this paper, a framework is developed to analyze how the specifications of new technologies and the heterogeneity of micro-units of production affect the input use, the adoption pattern, and the productivity of inputs. It shows that asset-productivity-enhancing (APE) technologies tend to be adopted by micro-units with high-quality assets, while variable-input, efficiency-enhancing (VIEE) technologies tend to be adopted by micro-units with low-quality assets. In both cases, the variable input productivity increases, but the average productivity of the fixed asset may decline in the case of the VIEE technology. The distribution of asset quality and the new technology specifications will therefore determine the impacts of production technology innovations on aggregate behavior and consequently the change in average productivity of the fixed asset. Keywords: effective input useheterogeneity in asset qualityaggregate behavioradoption patternproductivity JEL Classification : D24L64033 Notes For details in early development of the threshold model, see David Citation(1975), Stoneman Citation(1983), and Feder, Just, and Zilberman Citation(1985). The initial threshold model downplayed social interaction, but it can be expanded to include network externalities. In David (1969) and some others, a firm will adopt a new technology if its size is greater than or equal to some critical level. Unambiguous statements about the directional effect of adoption on quasi-rent Δ Π>0, however, cannot be made as it depends on the size of the investment costs, Δ c. This two-stage problem is done numerically by first solving for optimal input under each technology specification, and then comparing the maximized quasi-rents under all possible technology specifications. The first step can be conducted easily using numerical optimization tools such as the Optimization Toolbox in MatLab. The second step can also be carried out easily. The adoption decisions over the type space can be represented by a step function which takes values from 0 (traditional technology) and 1, 2, 3 (new technologies). An X–Y view of this function will generate the right graphs of Figures 5 and 6 because normally the software will use different colors to distinguish different heights of the function values.
Publication Year: 2010
Publication Date: 2010-12-25
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 12
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot