Abstract
Purpose This paper aims to study the inter-sectoral linkages in the Egyptian economy, to increase the efficiency of allocating L.E 100bn fiscal stimulus package (FSP) to tackle the economic fallout from COVID-19 based on the strength of the backward and forward linkages of various sectors, and the values of both employment and value-added multipliers. The paper also measures the impact of the new FSP on the capability of various sectors in creating job opportunities and increasing economic growth. Design/methodology/approach The paper studies the intersectoral linkages by calculating backward and forward linkages index based on the latest input and output tables available for the Egyptian economy published in 2018. It also depends on a bivariate optimization model to distribute new investments allocated through the FSP based on the values of both employment and value-added multiplier for those sectors. The paper calculated both employment and value-added coefficients to measure the impact of the FSP on creating job opportunities and increasing growth rates. Findings Based on the results of the empirical analysis, both key sectors (with strong backward and forward linkages) and sectors with strong backward linkages have the highest impact on creating job opportunities and increasing growth rates in the Egyptian economy, which means that allocating FSPs in a way which targets those sectors, especially during economic crisis, could help in increasing the positive impacts of those packages. Originality/value The paper is based on the unbalanced growth theory of Hirschman and uses the empirical analysis to study the intersectoral linkages and allocate new investments through FSP through different sectors. The main policy implication of the empirical results of this paper suggests targeting the key sectors and the sectors with strong backward linkages during tough economic times related to COVID-19, to increase the positive impact of the package on the whole economy.
Highlights
The world economy has witnessed a period of declining rates of economic growth and employment in response to COVID-19 pandemic crisis, with a majority of the population staying home, and many routine services closed as “non-essential”, income and spending was drastically affected
The main policy implication of the empirical results of this paper suggests targeting the key sectors and the sectors with strong backward linkages during tough economic times related to COVID-19, to increase the positive impact of the package on the whole economy
The Key sectors came in the second stage in terms of the investments allocated through the fiscal stimulus from the optimization model, as they are characterized by their strong value-added and employment multiplier which ensures their positive impact on the economy as a whole in terms of increasing growth rates and increasing job opportunities, in this regard LE 27.98 bn of the fiscal stimulus are being allocated among key sectors representing nearly 27.98%
Summary
The world economy has witnessed a period of declining rates of economic growth and employment in response to COVID-19 pandemic crisis, with a majority of the population staying home, and many routine services closed as “non-essential”, income and spending was drastically affected. 3. Methodological framework and data set The paper methodology depends on using the latest the input-output matrix available for the Egyptian economy published in august 2018, which includes 90 subsectors, to: estimate intersectoral linkages in the Egyptian economy, compute employment and value-added multipliers of various sectors and allocate FSP based on multipliers effects in a way that maximizes employment and growth rates, the empirical tools used in this regard could be highlighted as follows: 3.1 Determining sectoral linkages The underlying idea of calculating sectoral linkages is based mainly on finding the sectors with the highest degree of interrelation using Rasmussen approach, each sector simultaneously plays the role of a seller of its output to other industries and final demanders, and of a purchaser of outputs of other industries and of primary inputs. Where: L is row vector containing the (nþ1) Type II labor multipliers of the ratio of the labor coefficient to the gross output for each sector R is the inverse of Leontief matrix L* is a diagonal matrix (nþ1) Â(nþ1) whose diagonal components are the elements of the (nþ1)Â(nþ1) row vector of labor coefficients
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