Real Capital Stock Estimation for Industries Using Perpetual Inventory Method: A Methodological Exploration

Abstract

A study of industrial structure and growth, in terms of capital intensity and capital productivity of industries, inevitably encapsulates the requirement and associated challenges of estimation of capital stock time series in real terms. An incorrect (under- or over-) estimation of real capital stock leads to dubious conclusion and, thus, ill-informed policy implications derived from the analysis. The industrial survey database–ASI–reports the time series of capital stocks for industries in nominal (at current prices) terms instead of in real (at constant prices) terms which is more meaningful for the analysis. The choice of correct deflator, consideration of suitable depreciation, discard and revaluation of capital stocks, make real capital stock estimation a matter of disquisition. A plethora of studies addresses these challenges of capital estimation deploying perpetual inventory method. However, the approaches used in the previous studies pose limitations in terms of price deflator selection, consideration of benchmark period for initial capital and choice of depreciation rates and methods. The present study addresses these limitations for the registered Indian manufacturing industries. The result of the present study exhibits a robust approach of real capital stock estimate and an advancement from the existing approaches.

Does green financial infrastructure promote the improvement and convergence of regional carbon emission efficiency? Based on provincial data of China

“…The physical capital stock (K), human capital stock (H) and energy input (N) are selected as input indicators, and the output level (Y) and carbon emissions (CE) are selected as desired and undesired output indicators, respectively. The physical capital stock (K) is estimated by the perpetual inventory method based on Soni et al (2019); the human capital stock (H) is expressed as the product of the number of employees in society and the average years of education (Zhang and Yue, 2019); the energy input (N) is the total regional energy consumption (House et al, 2009;Al-mulali and Sab, 2013;Akalpler and Hove, 2019), in million tonnes of standard coal; the output level is taken as a proxy for the regional real GDP per capita, taking into account the regional development differences; the carbon emission per capita is used as a proxy for CO 2 emissions in this paper, which is obtained by dividing each province's CO 2 emissions divided by the province's total population (Sarkodie and Strezov, 2019;Yang et al, 2022b;Wang and Huang, 2022). In particular, it should be noted that carbon emissions at the provincial level are usually difficult to account for, so there is no uniform measurement method.…”