This study investigates the nexus between financial market and real estate (RE) sector against the backdrop of ECB's unconventional monetary policy. A financial dynamic computable general equilibrium (DCGE) model is calibrated on the financial social accounting matrix (FSAM) of Italian economy. The findings confirm that the inclusion of financial intermediation into real economy affects the real estate sector's output, value added, and pricing.
PurposeWith the global outbreak of COVID-19 that has made the economic activities standstill, countries have taken immediate measures to safeguard not only the human lives but also the economies. This study investigates empirically the lockdown impact of current pandemic on the Saudi economy.Design/methodology/approachThe study employs inoperability input–output model (IIOM) on the input–output table (IOT) of Saudi Arabia for the analysis.FindingsFindings show that with the closure of few sectors for the period of two months, the GDP declined to 6.49%. Findings also show a negative impact on consumption, investments and exports.Research limitations/implicationsOne limitation of current study is that it uses IOTs which lack primary and secondary income distribution that is vital for presenting complete interindustry connections in the analysis. The interindustry structures relate to the consumption structures which ultimately lead to the income distribution and affect the consumption behaviors of economic agents. Hence, the complete income circular flow is not incorporated in IIOM using IOT. The findings of current study would be well grounded if it endogenized the primary and secondary income distribution.Practical implicationsThe practical implication of this study is the use of IIOM for anticipating the potential loss against the backdrop of catastrophes and pandemics. The IIOM has the capability to predict the economic effects of disruptive events and hence the policy-makers can better predict and devise prudent policies to avoid the likely threats to the economy.Originality/valueThe current situation is unprecedented, and it is challenging for governments to forecast the economic repercussions. Several economic sectors have been inoperative due to lockdown implemented by the governments. This study empirically estimated the inoperability produced by the current pandemic. The findings are consistent with other estimated statistics, thereby proving the efficacy of IIOM to anticipate the economic repercussions of natural hazards.
PurposeThis study quantifies empirically the induced impact of income distribution and consumption expenditure on the structures of agriculture production of Nigerian economy.Design/methodology/approachThe study calibrates an extended input-output model on a social accounting matrix (SAM) for Nigeria for the year 2010. Moreover, the study conducts a dispersion analysis to identify the key agriculture sectors/subsectors both in exogenous and endogenous setup.FindingsThis study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup. The comparison of both findings confirms that the composition of income distribution and consumption expenditure significantly influences the composition and the aggregated and disaggregated order of structure of agriculture production.Originality/valueKnowledge of interindustry connections is vital in policy implications since the policy makers prefer strongly interconnected sectors to the sectors with poor industry linkages. These connections are estimated as forward and backward linkages, which provide indices to set the criteria for key sectors identification. This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.