Labour informality in forestry: A longitudinal (2009–2020) cross-country analysis of determinants in 70 developing countries

Lippe, Rattiya Suddeephong; Ojeda Luna, Tatiana; Katajamäki, Waltteri; Schweinle, Jörg

doi:10.1016/j.forpol.2023.103056

Cited by 2 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We selected indicators that are relevant to the transformation of the Northeast Stateowned Forest Areas based on scientific rigor, practicality, comprehensiveness, representativeness, operability, and data availability. The indicators selected originate from well-established frameworks, including the modern forestry development index system [51][52][53][54][55][56], economic transformation index system [57][58][59], resource-based city transformation ability index system [60][61][62], and transformation index system of state-owned forest areas [3,[6][7][8]10,36,37,63], as suggested by several scholars. The indicators are organized based on three characteristics that reflect the capacity of state-owned forestlands to undergo change.…”

Section: Descriptive Statisticsmentioning

confidence: 99%

Calculation and Cause Analysis of Hidden Unemployment—A Case Study of the Northeast State-Owned Forest Areas in China

Wang,

Cao,

Wen

2024

Sustainability

View full text Add to dashboard Cite

The Northeast State-owned Forest Areas comprise the largest region of resources in China. The transformation of the Northeast State-owned Forest Areas is due to various stimuli, such as policies, systems, and markets. In the context of ecological construction and the reform of the state-owned forest system in Northeast China, these have undergone a transformation in terms of economy, society, and ecology. However, a mismatch persists between employment and industrial structures, leading to hidden unemployment. This study employs the framework of hidden unemployment theory, utilizing the Cobb–Douglas production function to quantify the hidden unemployment rate, revealing the relationship between transformation and hidden unemployment. Through this analysis, the underlying causes of hidden unemployment in Northeast China’s state-owned forest regions are scrutinized. There is a bidirectional causal relationship between ecological transformation and hidden unemployment, while there is a unidirectional causal relationship between economic transformation and hidden unemployment. Variance decomposition analysis highlights the substantial contribution of social transformation, followed by economic transformation, with ecological transformation playing a comparatively smaller role. Based on the above research, this article proposes expediting the reforms within the forest industry groups, facilitating the separation of governmental and corporate interests. Additionally, it advocates for strategic forestry development planning to effectively absorb surplus labor, and proposes three policy directives aimed at supporting forest area employees, including provisions for job transfers and reemployment opportunities.

show abstract