A Cycling Method for Constructing Input–output Table Time Series From Incomplete Data

Abstract

There are a number of approaches for constructing time series of input-output tables. Some authors generate an initial estimate for a base year, and then serially estimate tables for subsequent years using the balanced prior-year table as an initial estimate. Others first generate a series of initial estimates for the entire period, and then balance tables in parallel. Current serial methods are affected by sudden leaps in the magnitude of table elements, which occur straight after a period of data unavailability. Current parallel methods require two complete tables for base and final years in the same classification, and therefore do not work under misaligned or incomplete data. We present a new method for constructing input-output table time series that overcomes these problems by averaging over alternate forward and backward sweeps across the time series period. We also solve the problem of hysteresis causing forecast and backcast table estimates to differ.

Recent Progress in Assessment of Resource Efficiency and Environmental Impacts Embodied in Trade: An Introduction to this Special Issue

“…As we concluded earlier in Tukker and Dietzenbacher (), this has important advantages in assessing impacts of final consumption that take place in relatively poor countries with a low gross domestic product (GDP) not covered in other databases (Lenzen et al. ) and is also important to attribute impacts to individual countries (as opposed to a large aggregated Rest of World [RoW]).…”

“…r A main application of GMRIOs has been assessment of global value-chain networks and the environmental pressures they create in the past and present (Peters et al 2011a;Lenzen et al 2012;Steen-Olsen et al 2012;Tukker et al 2016). But equally important are answering questions around what kind of policies can be applied to improve the situation, especially given the strong link between income and environmental impact (Ivanova et al 2017;Simas et al 2017) that gives rise to the rebound effect (Hertwich 2005).…”

Incorporating data quality improvement into supply–use table balancing

“…SUTs balancing is done in such a way as to minimise the differences between the same cells of the SUTs from one year to the next (Wood, 2011;Temurshoev and Timmer, 2011) both forward and backwards in time (Lenzen et al, 2012). Published SUTs are regularly revised.…”

Updating Input–Output Tables with Benchmark Table Series

“…Jackson and Murray (2004) Kuroda's method Kuroda (1988) and Wilcoxen (1989) Cross entropy method (CE) Golan et al (1994) TRAS St Louis (1999, 2004) Information in addition to row and column totals KRAS Lenzen et al (2006Lenzen et al ( , 2007Lenzen et al ( , 2009), Wood (2011) A non-sign-preserving RAS variant Lenzen et al (2014) Cycling method for constructing I-O table time series Lenzen et al (2012) Incomplete data this paper are as follows. First, time series analysis is used to forecast I-O tables for the target years.…”

“…Moreover, they proposed several alternative minimands, including absolute differences, weighted absolute differences, weighted squared differences (Lahr, 2001), global change constant, and sign-preserving squared differences, which all minimize the distance between the target and prior tables under particular constraints. Most recently, Lenzen et al (2012) presented a new method for constructing I-O table series from incomplete data by averaging over alternate forward and backward sweeps across the time series period. They also solved the problem of hysteresis, which causes the forecast and backcast table estimates to differ.…”