Abstract
ABSTRACTDo input–output linkages of intermediate products affect the spread of sectoral shocks at the aggregate level in Lithuania, a small and open economy? What role does openness play in the empirical exercise? We answer these questions by: (i) constructing the Lithuanian input–output transactions tables with domestic-only and domestic and imported sector-by-sector direct requirements, and (ii) applying Acemoglu, Carvalho, Ozdaglar, and Tahbaz-Salehis [(2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977–2016] network-based methodology and Gabaix and Ibragimov's [(2011). Rank-1/2: A simple way to improve the ols estimation of tail exponents. Journal of Business & Economic Statistics, 29(1), 24–39] modified log rank-log size regression. Our results indicate that the structure of input–output linkages cause aggregate economic volatility to decay at a rate lower than the established theoretical prediction. Indirect linkages play an equally important role for both domestic-only and aggregated domestic and import transactions.
Highlights
The diversification argument of Lucas (1977), similar in spirit to the portfolio diversification argument put forward by Markowitz (1952), indicates that, following the materialization at the sectorial level of a number of economic disturbances, aggregate output reverts to its mean at a known rate, computed to be n, where n is the number of sectors in the economy
The current study investigates the importance of inter-sectoral linkages of intermediate products as conduits of sectoral shocks at the aggregate level in Lithuania
We refine the analysis by considering the relevance of imported intermediate products and how these may alter the conclusions of the exercise as compared to the domestic-only case
Summary
The diversification argument of Lucas (1977), similar in spirit to the portfolio diversification argument put forward by Markowitz (1952), indicates that, following the materialization at the sectorial level of a number of economic disturbances (expected to occur independently √of each other), aggregate output reverts to its mean at a known rate, computed to be n, where n is the number of sectors in the economy. Type of data is not available for Lithuania, we need to construct the domestic as well as the aggregated sector-by-sector direct requirements table using the Lithuanian input–output transactions table. Account second-order connections, the aggregate volatility decays at a rate smaller than n0.22 This is in line with the argument that indirect linkages play an important role in the propagation of shocks. Due to these connections and the unbalanced structure of the input–output intermediate production networks, sectoral shocks to the one of the dominant sectors would propagate through its downstream sectors and lead to fluctuations at the aggregate level.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
