Defence Spending and Economic Growth: Re-examining the Issue of Causality for Pakistan and India

What is the impact of carrying a heavy defence burden on the country’s economic development and growth? Views expressed in the literature1 argue that national defence is a consumption good which reduces economic growth by reducing saving and capital investment. A number of empirical studies have investigated the possible trade-offs between defence spending and other government expenditures like health and education. Empirical evidence concerning the relationship between defence spending and economic growth for developed countries is not inconsistent with the view that defence reduced the resources available for investment and hurts economic growth. See, for example, Benoit (1973). The evidence for developing countries, however, has not been entirely consistent or conclusive.2 Benoit (1978), using data on 44 less developed countries (LDCs) for the period 1950–65, found a strong positive association between defence spending and growth of civilian output per capita. Fredericksen and Looney (1982), using data for the period 1960–78 on a large cross-section, concluded that increased defence spending assists economic growth in resource-rich countries and not in resource-constraint ones. Using a sample of 54 LDCs pertaining to the period 1965–73, Lim (1983) found that defence spending hurts economic growth. Biswas and Ram (1986) in a sample of 58 LDCs for time-periods 1960–70 and 1970–77, using conventional and augmented growth models, concluded that military expenditures neither help nor hurt economic growth to any significant extent.

Can Autism be Catered with Artificial Intelligence-Assisted Intervention Technology? A Literature Review

This article presents an extensive literature review of technology based intervention methodologies for individuals facing Autism Spectrum Disorder (ASD). Reviewed methodologies include: contemporary Computer Aided Systems (CAS), Computer Vision Assisted Technologies (CVAT) and Virtual Reality (VR) or Artificial Intelligence (AI)-Assisted interventions. The research over the past decade has provided enough demonstrations that individuals with ASD have a strong interest in technology based interventions, which are useful in both, clinical settings as well as at home and classrooms. Despite showing great promise, research in developing an advanced technology based intervention that is clinically quantitative for ASD is minimal. Moreover, the clinicians are generally not convinced about the potential of the technology based interventions due to non-empirical nature of published results. A major reason behind this lack of acceptability is that a vast majority of studies on distinct intervention methodologies do not follow any specific standard or research design. We conclude from our findings that there remains a gap between the research community of computer science, psychology and neuroscience to develop an AI assisted intervention technology for individuals suffering from ASD. Following the development of a standardized AI based intervention technology, a database needs to be developed, to devise effective AI algorithms