Global and local technical changes: a new decomposition of the Malmquist productivity index using virtual units
In estimating productivity change over time, technical change is frequently miscalculated as the geometric average of technological changes between two periods based on firm-specific information in the dataset. However, the frontier shift over time is a global phenomenon linked to relative technolog...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/102424 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/102424 |
| Access Level: | acceso abierto |
| Palabra clave: | C43 D24 O47 Productivity change Malmquist index Global technical change Local technical change Unit hypercube Virtual units Economía Investigación operativa (Matemáticas) 5307.15 Teoría Microeconómica 1207 Investigación Operativa |
| Sumario: | In estimating productivity change over time, technical change is frequently miscalculated as the geometric average of technological changes between two periods based on firm-specific information in the dataset. However, the frontier shift over time is a global phenomenon linked to relative technological progress or regress across the entire frontiers. In this paper, we fill this gap by determining the technical change using synthetic observations generated at random within a unit hypercube and calculating the distances between them and the two frontiers being evaluated. Accordingly, we propose a decomposition of the Malmquist index's traditional technical change into two components: average global technical change, which is shared by all production units, and local technical change, which captures how each firm experiences global technical change. In this way, our approach establishes a new research avenue in production economics based on using randomly generated virtual points to assess overall phenomena. |
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