The determinants of productivity in Chinese large and medium-sized industrial firms, 1998–2007

Abstract

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract Using a large firm-level dataset, this paper examines total factor productivity (TFP) and its determinants in China. Our preferred GMM estimation results indicate increasing returns to scale in most industries and a usually large positive trend representing technical change.Various firm characteristics such as age, ownership, political affiliation, export behavior, liquidity, and geographic location are included in the production function. Our results show that in the context of China's institutional background, including such factors is important when estimating TFP. The average TFP growth in Chinese industries is 9.6 % per annum during the period 1998-2007, and is mainly driven by firm entry. The subsector decomposition exercises show that the inter-firm resource reallocations are more prominent across industries than across provinces.

Firm employment growth in China: The role of marketization and regional economic factors

“…Similar considerations hold for the agglomeration covariates and for the local government expenditures in education and science, in line with the recent findings offered by Zhu et al (2019). These results confirm that during the reform period 1998-2007 the regional mechanisms fostering productivity gains in the incumbent firms (Ding, Guariglia, & Harris, 2016) promoted also the growth of firm employment and sales. As to the firm-level variables, the estimates confirm previous findings.…”

“…While our focus here is on the implications in terms of firms' growth and performance, others studies have dealt with the negative effects of pollution in terms of health and life expectancy (Chen et al, 2013). 13 This data set has already been explored by a number of authors, such as Bin et al (2018); Brandt et al (2012); Ding et al (2016); Guariglia et al (2011); Manova and Yu (2016); Rizov and Zhang (2014); Yu (2015).…”

“…24 While other estimation methods are available, Olley and Pakes (1996) is the most popular approach among the empirical works focusing on firm-level data in China. This is possibly due to the dismal results (i.e., negative estimated coefficients) obtained after applying the approach developed by Levinsohn and Petrin (2003) and its recent reformulation by Wooldridge (2009), as found by Ding et al (2016). 25 It could be argued that, to the extent that more productive firms tend to minimise inputs per unit of output, firms shedding (hiring) workers fast may improve (lower) the productivity, with a reverse direction of causality.…”

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“…7 We think it is important not to, a priori, drop what may seem to be outliers without direct evidence . 8 TFP was taken from Harris and Li (2016),which uses the same methodology as that used in Ding et. al.…”

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“…Examples include Zhu (2012), who reported similar estimates for the Chinese economy, and Gao (2015), who investigated the agricultural sector. Brandt et al (2012) and Ding et al (2016) focused on the manufacturing sector. Figure 3 in Morrison (2013).…”