partici_idx: Compute Participation Index for Forward and Backward Linkage

In common2016/MeasureGVC: Compute Participation Index for Forward and Backward Linkage, and Inner Circle

Compute Participation Index for Forward and Backward Linkage

Description

Compute Participation Index for Forward and Backward Linkage

Usage

partici_idx(wwz, linkage = "forward")

Arguments

wwz	a decompr class object from the decompr package.
linkage	calculating method, forward or backward. Wang et al. (2017) puts forward algorithms of GVC participation index for forward and backward linkage. I show a another method named inner.

Details

A higher degree of forward participation than backward participation implies that the country/sector is more actively engaged in upstream production activities in GVCs.

Value

a data.frame including countries, industires, GVC participation index

1. cnts: contries

2. industry

3. up: GVC participation index for forward linkage

4. dw: GVC participation index for backward linkage

5. up_inner: inner circle measure for forward linkage

6. dw_inner: inner circle measure for backward linkage

References

Pu Chen and Yuanhai Fu, Measurement and Application of Economic Inner Cycle From the Perspective of Global Value Chain (In Chinese). 2022, Statistical Research.

Wang, Z., Shang-Jin Wei, Xinding Yu, Kunfu Zhu, Measures of Participation in Glabal Value Chains and Global Business Cycles. 2017, NBER. Number:23222.

Examples

# load example data
data(leather, package = 'decompr')
# create intermediate object (class decompr)
decompr_object <- decompr::load_tables_vectors(leather)
partici_idx(decompr_object, 'forward')

common2016/MeasureGVC documentation built on May 22, 2023, 5:59 a.m.