| Revista: | Journal of applied economics |
| Base de datos: | CLASE |
| Número de sistema: | 000430347 |
| ISSN: | 1667-6726 |
| Autores: | Pei-Chun Lai1 Bessler, David A2 |
| Instituciones: | 1Capital University of Economics and Business, International Shool of Economic Management, Beijing. China 2Texas A&M University, Department of Agricultural Economics, College Station, Texas. Estados Unidos de América |
| Año: | 2015 |
| Periodo: | May |
| Volumen: | 18 |
| Número: | 1 |
| Paginación: | 173-197 |
| País: | Argentina |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico, descriptivo |
| Resumen en inglés | This paper considers the use of two machine learning algorithms to identify the causal relationships among retail prices, manufacturer prices, and number of packages sold. The two algorithms are PC and Linear Non-Gaussian Acyclic Models (LiNGAM). The dataset studied comprises scanner data collected from the retail sales of carbonated soft drinks in the Chicago area. The PC algorithm is not able to assign direction among retail price, manufacturer price and quantity sold, whereas the LiNGAM algorithm is able to decide in every case, i.e., retail price leads manufacturer price and quantity sold |
| Disciplinas: | Economía, Matemáticas |
| Palabras clave: | Precios, Economía industrial, Matemáticas aplicadas, Industria refresquera, Algoritmos, Modelos matemáticos, Chicago, Estados Unidos de América, Bebidas |
| Texto completo: | Texto completo (Ver PDF) |
