Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/194737 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 5 [Issue:] 1 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2017 [Pages:] 1-18
Verlag: 
Taylor & Francis, Abingdon
Zusammenfassung: 
The purpose of this study is to investigate the role of macroeconomic conditions and predict the base performance of a firm as represented by Return on Asset (ROA) and macroeconomic variables. The predictor variables used in the construction of the models were selected using PCA. For the full sample and the industry-specific sample of data, the regression model evaluated the significance of macroeconomic factors based on t-statistics and the R2 test. The results of the study are promising. The full sample and five out of six industry variable models incorporating lead-lag relationships have an R2 between 0.79 and 0.95. For the full sample, the results of this study indicate that macroeconomic conditions should be incorporated when predicting firms' performance. For the industry-specific models, the empirical results present a mixed picture of the effect of macroeconomic factors and the lagged ROA on firm performance and the same conclusion for full sample cannot be reached easily when looking at the industry specific results. The results of this paper provide a compelling argument that firm performance is a function of the prior year ROA, and macro-economic variables and that macroeconomic variables and prior year ROA can have impact on future firm performance measure by ROA.
Schlagwörter: 
return on asset
firm performance
multiple regression
principal component analysis
macroeconomic variables
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