Marketing investments and firm performance in manufacturing sector: a panel threshold model for China

Abstract

Many firms find it difficult to accurately identify the level of investments in marketing activities that can maximize their profitability. The current work is aimed at helping firms in identifying the optimal level of marketing expenditure. The study has been conducted for 1363 publicly listed firms in China for the period 2008–2017. The current study utilizes threshold panel regression analysis. The study contends that the optimal level of investments in marketing is contingent upon firm’s size. The results confirm the existence of a single threshold value that helps in determining the optimal level of marketing investments. It is found that, for firms that are smaller that the cut-off value of size, high level of investments in marketing is associated with improved firm performance. However, for the firms that are larger than the cut-off value of size, high level of investment in marketing is associated with reduced firm performance.

Keywords:

• Firm size
• firm performance
• manufacturing sector in China
• marketing investments
• threshold panel regression
• threshold size

Acknowledgements

The authors would like to thank Professor Bruce E. Hansen for providing the therehod panle regression codes. The authors would also like to thank the editor of the Journal of Aisa Pacific Economy and an anonymous reviewer for providing extremely useful insights.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Dinesh Jaisinghani is currently working as a Assistant Professor in the area of Finance at Fortune Insitute of International Business, New Delhi. He has completed his FPM from International Management Institute (IMI), New Delhi, India. His major areas of interest are Corporate Finance, Financial Econometrics, Market Microstructure and Financial Economics.

Kakali Kanjilal is currently working as a Professor with International Management Institute (IMI), New Delhi, India. She has more than 15 years of industry, teaching and research experience. She has published research articles in many renowned international journals including Economic Modelling, Macroeconomics and Finance in Emerging Market Economies, Energy Policy, Energy Economics, and Pacific Asian Journal of Energy among others.

Notes

1 In terms of studies pertaining to emerging markets, Jaisinghani and Kanjilal (2017) investigate the non-linear relationships among firm size, capital structure, and firm performance for the Indian manufacturing sector. Their results show that capital structures differentially impacts firm performance for different sized firms.

2 This filter has been applied to prevent the dataset from taking the form of an unbalanced panel. Threshold panel regression methodology can only be deployed for the balanced panel.

3 The descriptive analysis of the data reveals that the mean ROA for the sample firms is around 5.88%. Further, the mean spending in marketing investemnet is around 7.12% of sales. All the variables considered show great variability in terms of mean, maximum, and minimum values. Hence the sample is a good representation of the Chinese manufacturing sector. Moreover, the analysis of correlations indicates that there is no severe multicollinearity issue in the data. These results are not shown here but are available from the authors upon request.

4 The overall significance of different cut-off values is determined by analyzing the F-statistics. The F-statistics and the associated p values are obtained through deploying the bootstrap procedure. The bootstrapping procedure has been repeated 300 times.

5 The estimation procedure and the tests of hypotheses concerning the threshold parameters are explained in detail in Hansen (1999).

6 Software package GAUSS, version 10, has been utilized to generate the results.

7 The analysis of the heteroscedasticity corrected error terms also provides very similar results