A cross-country analysis of total factor productivity using micro-level data

Seker, Murat; Saliola, Federica

doi:10.1016/j.cbrev.2018.01.001

Cited by 56 publications

(32 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It may also be argued that large firms could have more efficient production by better accessing technology, learning, and dealing with uncertainty and selection processes. This finding is in line with Seker and Saliola (2018), Aiello et al (2016). Expenses on technology also have a significant positive impact on TFP.…”

Section: Regional Factorsupporting

confidence: 92%

“…The determinants in these studies are usually exports, imports (Sjoholm 1999;Blalock & Veloso, 2007); foreign presence or foreign technology license (Waldkirch & Ofosu, 2010;Lopez, 2008); technology (Paptist & Teal, 2014), and firm size (Fernandes, 2008). Seker and Saliola (2018) recently found that the determinants of heterogeneity in TFP across countries includes firms' exporting, innovation, access to finance, foreign ownership, and countries' regulations.…”

Section: Literature Review and Empirical Studiesmentioning

confidence: 99%

“…Another advantage of this model is to allow a wide variety of correlation patterns (or variance-covariance structures) by letting each group of observations have its own intercept (possibly slope) randomly deviating from the mean intercept or slope of each group (Seltman, 2015). However, most studies on firm TFP have focused on the determinants as the firms' characteristics (Sjoholm, 1999;Blalock &Veloso, 2007;Waldkirch & Ofosu, 2010;Lopez, 2008;Baptist & Teal, 2014;Fernandes, 2008;Seker & Saliola, 2018). In Vietnam, studies on TFP are still very limited (CIEM, 2010), although TFP is perceived as a key role of development quality (Tran Tho Dat & Do Tuyet Nhung, 2013).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Determinants of firms’ total factor productivity in manufacturing industry in Vietnam: An approach of a cross-classified model

Oanh¹

2019

JABES

View full text Add to dashboard Cite

show abstract

Section: Regional Factorsupporting

confidence: 92%

Section: Literature Review and Empirical Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Determinants of firms’ total factor productivity in manufacturing industry in Vietnam: An approach of a cross-classified model

Oanh¹

2019

JABES

View full text Add to dashboard Cite

show abstract

“…They used six different models to estimate the TFP and all countries were ranked with respect to these specifications. The TFP of Vietnam in 2009 was in third place, in the same group with Botswana 2006, Cote d'Ivoire 2009, Uzbekistan 2008, Mexico 2010, and Syria 2009, while first place included Brazil 2009, Jordan 2006, Kyrgyzstan 2009, Cameroon 2009, Ethiopia 2006, and Indonesia 2009 In Southeast Asia, the TFP of Vietnam stood behind Indonesia 2009, but it was greater than Malaysia 2007 (4th place) and Thailand (7th place) (Seker and Saliola 2018). Comparing with other continents, Asian countries including Vietnam have shown a positive growth of TFP, but in contrast, the growth of TFP in the agricultural sector of 30 African countries was −0.15% annually (Avila and Evenson 2010).…”

Section: Discussionmentioning

confidence: 99%

“…China and Cambodia were highest (1.060 and 1.057, respectively), whereas Haiti and Chad were lowest (0.957 and 0.947, respectively) (Coelli and Rao 2005). Seker and Saliola (2018) recently examined the TFP of 69 developing countries of their manufacturing firms, with the determinants including exporting, innovation, access to finance, foreign ownership, and regulations. They used six different models to estimate the TFP and all countries were ranked with respect to these specifications.…”

Section: Discussionmentioning

confidence: 99%

Total Factor Productivity of Agricultural Firms in Vietnam and Its Relevant Determinants

et al. 2019

View full text Add to dashboard Cite

In Vietnam, agriculture is a key sector that promotes economic growth and poverty reduction. Therefore, improving productivity in agriculture is indispensable to the sustainability of the country. This research examined productivity and its determinants from 420 enterprises operating in agriculture. Productivity was measured as the total factor productivity (TFP) obtained from fixed and random effects models. The determinants of TFP including size and age, share of state and foreign ownership, export, accessibility to Internet and bank loan of firms, controlled for year fixed effects, were analyzed. It was shown that 74.6% companies in the agricultural sector were small in size (<10<200 employees). Although the number of large firms (>300 employees) explained 10.6%, they had a remarkable and positive TFP (38.8%, p < 0.01), while both small and very small (<10, and <200 employees, respectively) had strikingly negative TFP values (−71.3% and −32.1%, respectively, p < 0.01), as compared to the medium sizes (<200<300 employees). It was also revealed that although foreign ownership was only 3.8% on average, it had a notably positive effect on TFP (55.0%, p < 0.01). In contrast, state ownership accounted for 30.7%, but it had a negative influence on TFP (−7.5%). The export contributed a negligible and statistically significant effect to TFP (2.6%), which might be attributed to a limited number of firms (4.5%) having mobility in agricultural export. 73% received a bank loan, and only 18.2% had access to the Internet, but both of them yielded remarkable TFP values (18.5%, p < 0.01 and 3.4%, p < 0.05 respectively). The Hausman test indicated that the fixed effects (FE) model was more effective than the random effects (RE) model to estimate the TFP. The findings of this study suggested that reform efforts should focus on improving the productivity of small agricultural enterprises. In addition, foreign investment, effective use of bank loan and Internet accessibility should be further enhanced. The results of this study may provide insights for policymakers who aim to improve the productivity in agricultural enterprises and thereby contribute to the sustainable growth of the country.

show abstract

Factor productivity and marketed surplus of non‐timber forest products in Similipal forest of Odisha

Jena

2020

Journal of Public Affairs

View full text Add to dashboard Cite

The article examined the factor productivity and the marketed surplus of non‐timber forest products (NTFPs) in the Smilipal forest of Mayurbhanj district of Odisha, India by using the econometric models. It is found that more than 90% of households earned their livelihood from NTFPs in the study area, where the women's participation is more than the male in the production/collection of NTFPs. Most of the households are illiterate, working‐age people, and have more than 30 years of experience in the production of NTFPs. The production of NTFPs is highly seasonal and households produce or collect NTFPs during the winter season. Households having more family members produce or collect higher quantities of NTFPs than others. The marked surplus of NTFPs depends on the production or collection of NTFPs as well as the retention amount and wastes. The higher factor productivity indicates the NTFPs are the best source of livelihood in this area.

show abstract

A cross-country analysis of total factor productivity using micro-level data

Cited by 56 publications

References 22 publications

Determinants of firms’ total factor productivity in manufacturing industry in Vietnam: An approach of a cross-classified model

Determinants of firms’ total factor productivity in manufacturing industry in Vietnam: An approach of a cross-classified model

Total Factor Productivity of Agricultural Firms in Vietnam and Its Relevant Determinants

Factor productivity and marketed surplus of non‐timber forest products in Similipal forest of Odisha

Contact Info

Product

Resources

About