In June 2021, the diffusion index of expected changes in incoming prices reached 97% – the highest value since 2003 and a typical level for 1993–1995. Apart from that, June can be called a very favorable month, taking into account high values of the level of capacities and labor utilization...

This paper builds on the work of Acemoglu et al. (2012) and considers a production network with unobserved common technological factor and establishes general conditions under which the network structure contributes to aggregate fluctuations. It introduces the notions of strongly and weakly...

Asymmetric climate policies are expected to distort the level-playing field regarding international trade, singularly to the detriment of small open economies. The paper develops a flexible method that provides essential input regarding the design of offsetting measures. It builds on...

We adopt a spatial econometric approach to estimate intra- and inter-industry productivity spillovers in total factor productivity transmitted through input-output relations in a sample of 13 OECD countries and 15 manufacturing industries. Both R&D spillovers as well as remainder,...

Output and input market distortions manifest as wedges in the firm's first order conditions. The production approach to markup estimation recovers the markup wedge using the output elasticity for a variable and undistorted input. We show that using the revenue elasticity for any variable input,...

Input-Output models and their extensions offer multiple prospects to explore the energy, water, food inter-linkages - Energy, Water, Food nexus (EWF-n). This paper takes India as a case study to examine a nexus-informed approach to policy making for redressing the EWF security (EWF-s)...

The employment impacts of the transition to a post-carbon economy are gaining increasing attention. The post-carbon transition implies fundamental changes in the economy followed by significant changes in the structure of labour demand. Industries with the highest carbon footprint are of utmost...