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Articles

The effects of wage spillover from foreign firms on total factor productivity: do job characteristics matter?

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Pages 766-785 | Published online: 20 Jul 2021
 

Abstract

This study investigates whether an increase in wages of foreign firms generates the total factor of productivity (TFP) growth of Indonesian manufacturing firms by considering different job characteristics and geographical boundaries. Using system GMM, the result shows that on average the wage spillover in production jobs within an industry positively affects the TFP, while the wage spillover in non-production jobs contributes negatively. Moreover, the wage spillover in production jobs and non-production jobs within a province do not affect the TFP of Indonesian manufacturing firms. These results indicate that employees in production jobs have larger contributions to increasing TFP than those in non-production jobs when foreign firms increase their wages. Such contributions occur within an industry, not within a province. For the Government, the different contributions to the TFP of firms from wage spillovers in production and non-production jobs indicate the importance of skill mobility to the national economy.

Acknowledgments

I would like to thank Associate Professor Anil V Mishra and Associate Professor Dilupa Nakandala for suggestions that provided insight and expertise.

Disclosure statement

The author declares that He has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Notes

1 Import substitution is a government policy that focuses on producing own goods and services, without importing from other countries.

2 This Act was altered to Act No. 25 in 2007 concerning investment. The Government makes this regulation to create conducive climate for investors so it can strengthen national economy.

3 In Indonesia there is no ‘unemployment benefit’. This term can be used to refer to the provincial minimum wage in each city or province in Indonesia.

4 In this study the scope of the smallest geographical boundaries is Indonesian provincial geographical boundaries.

5 Source: www.its.ac.id

6 The data that support the findings of this study are available from Badan Pusat Statistik (Indonesian Central Bureau of Statistics). Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the authors with the permission of Badan Pusat Statistik.

7 The process of data collection started in 2015. Indonesian manufacturing firm level data is available only up to 2014.

8 The outlier detected results using Chebyshev Theorem are available from the author.

9 The input factors are chosen based on the least standard errors of TFP construction.

10 In Indonesia there is no ‘unemployment benefit’. This term can be used to refer to the provincial minimum wage in each city or province in Indonesia.

11 Export-import dummy variables are included in the model to control for the international trade activities of each firm (Melitz and Ottaviano Citation2008)

12 According to a Monte Carlo study observed by Windmeijer (Citation2005), two-step GMM results in more accurate inferences than a one-step GMM, even in finite sample variance, due to the initial consistent parameter estimates in the weight matrix used in the measurement of the two-step GMM estimator.

13 The predetermined variable is the variable whose current value is determined by its value in the previous time period.

14 Forward orthogonal deviation is used to eliminate unobserved time invariant fixed effect factors.

15 Grogger and Hanson (Citation2011) use the term ‘income maximization behavior’ to explain the main factor of migration.

16 Under the Big Bang Policy, the Government strives to reverse the ratio of student numbers in senior and vocational high schools.

17 Vocational high school is an alternative secondary pathway which has equal level of degree to senior high school.

18 Rupiah is the currency of Indonesia.

19 The likelihood ratio test cannot be used for the non-inefficiency production function since the result of the number of observations when using the translog production function is different from the result of the number of observations when using the no-inefficiency production function.

Additional information

Notes on contributors

Dadang Ramdhan

Dadang Ramdhan is a researcher at Indonesian Institute of Sciences, and as a lecturer at School of Communication and Business, Telkom University. His research interests are in the area of international business, regional economics, public policy, econometrics, human resource management, and science and technology (S&T) policy. His last publication is in a form of proceeding with title, “Total Factor Productivity Growth (TFPG) of Indonesian Manufacturing Industry in Indonesian Provinces: Time-Varying Technical Efficiency—Stochastic Frontier Analysis which already presented at international conference hosted by Indonesian Ministry of Trade in 2017 with ISSN: 2598-8166.

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