This study investigates the impact of government policy responses of COVID-19 pandemic on stock market liquidity for listed Australian companies and for 11 different industries separately. A quantitative deductive approach is used for a sample of 1,452 companies with a total of 292,164 firm-day observations over a period from January 25, 2020 to December 31, 2020 during the outbreak of COVID-19. Univariate and multivariate (two-way cluster-robust panel regression) analysis were conducted. Data were collected from the Oxford COVID-19 Government Response Tracker, Worldmeter, Refinitiv Workspace and Datastream. Our findings indicate that the influences of the six out of seven stringency policy responses reduced Australian equity market liquidity. However, public information campaigns enhanced market liquidity and hence trading activity. Among the 11 industries, our analysis shows that the non-pharmaceutical interventions by the Australian government have significant and positive effects on four industries: Consumer non-cyclicals, healthcare, financial and technology. However, the worse effects were depicted in the industrial (transportation) and energy industries. This study is important for investors, policymakers and regulators to understand the diverse effects of government policy responses of COVID-19 on stock market liquidity to enhance financial stability. Moreover, understanding this effect is particularly important to decision-makers such as portfolio and fund managers to manage their portfolios and trading activities during extreme turbulence times, such as COVID-19. Unlike previous studies that focus on country analysis, this study examines on firm basis the impact of government interventions on stock market liquidity in a well developed Australian stock market.

The outbreak of COVID-19 has weakened the economy of Australia and its capital market since early 2020. The overall stock market has declined. However, some sectors become highly vulnerable while others continue to perform well even in the crisis period. Given this new reality, we seek to investigate the initial volatility and the sectoral return. In this study, we analyse data for eight sectors such as, transportation, pharmaceuticals, healthcare, energy, food, real estate, telecommunications and technology of the Australian stock market. In doing so, we obtain data from Australian Securities Exchange (ASX) and analysed them based on 'Event Study' method. Here, we use the 10-days window for the event of official announcement of the COVID-19 outbreak in Australia on 27 February 2020. The findings of the study show that on the day of announcement, the indices for food, pharmaceuticals and healthcare exhibit impressive positive returns. Following the announcement, the telecommunications, pharmaceuticals and healthcare sectors exhibit good performance, while poor performance is demonstrated by the transportation industry. The findings are vital for investors, market participants, companies, private and public policymakers and governments to develop recovery action plans for vulnerable sectors and enable investors to regain their confidence to make better investment decisions.

"In this article we show that, considering only economic effects, even if population growth, by natural increase or immigration, increases congestion, pollution, and other forms of external costs, that provided pre-existing citizens own the resources giving rise to the externalities, and provided they efficiently price usage of such, that existing citizens must, in net average terms, be better off with population growth than without it. In simple terms the increased revenues they gain from efficient pricing at increased demand levels will be strictly greater than the monetary value of the increased external costs together with the higher tax costs they incur as consumers of the resources."

"The purpose of this paper is to present a survey and synthesis of those economic models that have been used to derive estimates of marginal child costs from cross-sectional data on household expenditure patterns [in Australia].... In the next section the argument that the 'costs of children' should not be a concern of social policy is considered (and rejected). Section III then summarises the models.... In Section IV an Engel curve system estimated from the 1988-89 Household Expenditure Survey is used to compare [the models].... In the concluding section some directions for further research and data collection strategies are discussed."

The author analyses individual fertility patterns in Australia from the perspective of recent economic models of the family. The emphasis is on the relationship between fertility and economic variables such as human capital, market wages, and wealth. "Several dimensions of fertility are considered, including 'quality' of children, completed family size, and the decision whether to have children or not." Data are from the 1973 Social Mobility in Australia Survey.

An analysis of migration from the United Kingdom to Australia during the period 1900 to 1930 is presented. The author attempts "first to explicitly develop and estimate a model of the behavioural relations of the two blades of the Marshallian scissors, rather than mixing supply and demand (under the polyglot terms of 'push-pull') in a single equation without regard to the problem of identification. And second, [he attempts] to incorporate in these structural equations key elements of government intervention in the migration process." The relationship between economic factors and Australian government support for immigration is considered. The author also identifies three factors influencing annual variations in the flow of migration from the United Kingdom: expected income gains, transport costs, and the costs of job search.