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Open Access
Article
Publication date: 8 June 2021

Sam Kris Hilton

Considering the continuous rise in the public debt stock of developing countries (particularly Ghana) with the unstable economic growth rate for the past decades and the recent…

12972

Abstract

Purpose

Considering the continuous rise in the public debt stock of developing countries (particularly Ghana) with the unstable economic growth rate for the past decades and the recent borrowing because of the impact of COVID 19, this paper aims to examine the causal relationships between public debt and economic growth over time.

Design/methodology/approach

The paper uses a dynamic multivariate autoregressive-distributed lag (ARDL)-based Granger-causality model to test the causal relationships between public debt and economic growth [gross domestic product (GDP)]. Annual time-series data that spanned 1978–2018 were sourced from the World Bank Development Indicator database and the IMF fiscal Affairs Department Database and WEO.

Findings

The results reveal that public debt has no causal relationship with GDP in the short-run but there is unidirectional Granger causality running from public debt to GDP in the long run. Again, investment spending has a negative bi-directional causal relationship with GDP in the short-run but they have a positive bi-directional causal relationship in the long run. Conversely, no short-run causal relationship exists between government consumption expenditure and GDP but long-run Granger causality runs from government consumption expenditure to GDP. Finally, public debt has a positive impact on the inflation rate in the short run.

Practical implications

The findings imply that government(s) must ensure high fiscal discipline to serve as a precursor for the effective and efficient use of recent borrowing, that is, the loans should be used for highly prioritized projects (preferably investment spending) that are well evaluated and self-sustained to add positively to the GDP.

Originality/value

This paper provides contemporary findings to augment extant literature on public debt and economic growth by using variables and empirical models, which prior studies could not sufficiently cover in a developing country perspective and affirms that public debt contributes to GDP only in the long run.

Details

Asian Journal of Economics and Banking, vol. 5 no. 2
Type: Research Article
ISSN: 2615-9821

Keywords

Open Access
Article
Publication date: 12 February 2021

Manesh Muraleedharan and Alaka Omprakash Chandak

The substantial increase in non-communicable diseases (NCDs) is considered a major threat to developing countries. According to various international organizations and…

12618

Abstract

Purpose

The substantial increase in non-communicable diseases (NCDs) is considered a major threat to developing countries. According to various international organizations and researchers, Kerala is reputed to have the best health system in India. However, many economists and health-care experts have discussed the risks embedded in the asymmetrical developmental pattern of the state, considering its high health-care and human development index and low economic growth. This study, a scoping review, aims to explore four major health economic issues related to the Kerala health system.

Design/methodology/approach

A systematic review of the literature was performed using PRISMA to facilitate selection, sampling and analysis. Qualitative data were collected for thematic content analysis.

Findings

Chronic diseases in a significant proportion of the population, low compliance with emergency medical systems, high health-care costs and poor health insurance coverage were observed in the Kerala community.

Research limitations/implications

The present study was undertaken to determine the scope for future research on Kerala's health system. Based on the study findings, a structured health economic survey is being conducted and is scheduled to be completed by 2021. In addition, the scope for future research on Kerala's health system includes: (1) research on pathways to address root causes of NCDs in the state, (2) determine socio-economic and health system factors that shape health-seeking behavior of the Kerala community, (3) evaluation of regional differences in health system performance within the state, (4) causes of high out-of-pocket expenditure within the state.

Originality/value

Given the internationally recognized standard of Kerala's vital statistics and health system, this review paper highlights some of the challenges encountered to elicit future research that contributes to the continuous development of health systems in Kerala.

Details

Journal of Health Research, vol. 36 no. 2
Type: Research Article
ISSN: 0857-4421

Keywords

Open Access
Article
Publication date: 31 July 2020

Omar Alqaryouti, Nur Siyam, Azza Abdel Monem and Khaled Shaalan

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help…

6654

Abstract

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.

Details

Applied Computing and Informatics, vol. 20 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

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