Variance decomposition of firm productivity: evidence from the Peruvian economic context

• Ano de defesa: 2017
• Autor(a) principal: Mejia, Lino
• Orientador(a): Brito, Luiz Artur Ledur
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Palavras-chave em Português: Economias emergentes; Produtividade; Desempenho; Análise multinível
• Palavras-chave em Inglês: Emerging economies; Productivity; Performance; Multilevel analysis
• Palavras-chave em Espanhol: Economías emergentes; Productividad; Desempeño; Análisis multinivel
• Link de acesso: http://hdl.handle.net/10438/18373

Academics have performed several studies on variance decomposition of several types of performance in context of developed economies. Nevertheless, empirical research of variance decomposition in emerging economies is more limited than that of developed economies. This study analyzes the variance decomposition of Peruvian enterprises in the period between 2010 and 2014, employing multidimensional performance measures, and thus two objectives are present. Firstly; determine the financial performance variance composition and compare this with developed economies. Secondly; determine the variance composition of productivity and compare it with the variance structure of financial performance. This empirical research is based on an original longitudinal dataset which contains financial, production and labour market information at firm level and it uses the Hierarchical Lineal Model (HLM) which provides conceptual and robust statistics for analyzing the nested structure of the data. Regarding the first objective, the empirical results demonstrate that the industry effect account for 34% and the firm effect account for 66% of the variance explained. This differs with previous studies such as Makino et al. (2004) who presented an industry effect of 18% of the variance explained in a developed economy. Regarding the second objective, three measures of performance are used to capture the multidimensional nature of performance. The dimensions are financial (measured as ROA and ROS) and operational (measured as productivity). The findings show that operational productivity model explain 65% of their variability; whereas the ROA and ROS explain 55% and 61% respectively. This study also confirms that the variance structure impacts the performance of each aggregate sector separately. For manufacturing, the result show that the percentage of industry effect is stronger than that of other aggregate sectors. For service, the industry effect (when it uses profitability measures) show similar values with some studies in the Latin American context. Finally; for wholesale & retail trade, the results confirm that the industry effect is lower than the other aggregate sector, and shows values around 4%, and therefore, firm effect ranges between 40% and 70% of the total variance.