Fluent Essays

400 words included introduction and argumentsWhat do we know about Australia’s self-employed? Introduction In Australia, the self-employed make up a small but significant part of the workforce. In 2013, the self-employment rate was 10.4 per cent (World Bank 2016). This represents approximately 1.2 million Australians (Australian Bureau of Statistics 2016a). There are two reasons to study the self-employed. Firstly, many countries view self-employment as a positive force in the economy, with many European governments using self-employment as an active labour market policy (European Foundation for the Improvement of Living and Working Conditions 2011). Secondly, the face of self-employment is likely to be changing in Australia. Traditionally the self-employed were tradespeople, retail owners and professionals. However, with companies re-hiring ex-workers as contractors, Australians adopting the sharing economy as a source of income, and an aging workforce, the demographics of self- employment are now likely to have changed. This review examines what self-employment looks like in Australia, how it is changing and whether it is beneficial for the economy. It concludes there is little available literature on self-employment in the Australian context and that as such, both academia and governments would benefit from further research in this area. What does self-employment look like in Australia? The Australian Bureau of Statistics (ABS) classifies self-employed workers as either: ‘employer’-an owner of an unincorporated firm hiring employees; ‘own account worker’- an owner of an unincorporated firm who hires no employees; and ‘contributing family worker’. Of note, owners of incorporated firms are counted as ‘employees’ rather than self-employed (Australian Bureau of Statistics 2013). According to the ABS these groups now make up the following proportion of employed Australians:  ‘employer’: 2 per cent  ‘own account worker’: 3 per cent  ‘contributing family member’: 0.2 per cent  ‘owner of an unincorporated enterprise’: 7 per cent (Australian Bureau of Statistics 2016b). Atalay et al. (2014) used data from another source-the Household, Income and Labour Dynamics in Australia (HILDA)-and estimated that the self-employed are likely to be older and male. The self-employment rate in older workers (aged more than 55 years) was around double that of younger workers as was the self-employment rate of males compared to females (Atalay, Kim, and Whelan 2014, 477). Beyond this we know little else about the self- employed in Australia because most literature focuses on the United States, Canada and the European Union. For example we have no indication of Australia’s self-employed work motivation, average earnings, main industries and education levels. In contrast, data from the US suggests that the relationship between education and self-employment is U shaped; the least educated and most educated have a higher propensity toECON5004: Communication in Economics Semester 1, 2021 Instructor: Denny Lie 1 Assignment: Academic Writing Project Assignment Outline Students are required to draft an academic essay over the course of the first 8-9 weeks of the semester. The paper will be drafted in phases, with opportunities for detailed feedback, revision and improvement at each phase. Since it is not possible to write a full academic paper in 1500 words (and the research required for a full academic paper would exceed the workload requirements for this course), the essays will follow one of the following formats: 1. Literature review. Students can write a review of the literature in a specific topic area. This will need to be more than just a series of paragraphs summarizing various papers – it will need to have a central thesis (argument) and cite academic literature to support that argument (most likely, arguing what the main takeaway of the literature is). So, ideally, for this kind of essay the student would identify an area of literature where there is some debate, with multiple papers taking different sides of an issue. The student’s essay would then argue in support of one side of the debate, citing and acknowledging literature on both sides of the debate, and in most cases, ultimately coming down in support of one side. 2. Research proposal. Students can write a proposal for a specific research project. You can think about this in a number of ways – as the narrative section of a research grant, as a proposal that one would write to receive permission to conduct research in a public sector or professional context, or as the proposal for a masters or PhD thesis. 3. Persuasive essay. Students can use academic literature to backup an argument about an issue of economic interest. This could be a public policy issue, a business issue, or a more academic issue. In any case, the essay should be grounded in supporting a particular argument using economic reasoning and supported by credible academic economic literature. Students are encouraged to select an essay format that best fits their personal and professional interests. The potential subject matter is broad. The core requirement is that the essay use economic reasoning and argumentation to make its main points, and be based on credible academic economics literature. In general the essays will have the following format: introduction, evidence/exposition, conclusion. The introduction will motivate the central argument (the “hook”), outline the main aspects of the essay, and argue for the importance of the essay. The evidence/exposition is the meat of the essay – it will bring the student’s research to bear, in outlining the evidence for the main argument or point of the essay, while the conclusion will succinctly tie up the essay. The final submission will be capped at 1500 words, exclusive of literature references. Format: double spaced, 12-point font, 2.5 cm margi1 Is the Use of Big Data with Smart Cities in the U.S economically Effective? Yinfan Li 500707676 ECON5004: Communication in Economics Semester 1, 2021 Instructor: Denny Lie Is the Use of Big Data with Smart Cities in the U.S economically Effective? Introduction There has been a heated debate on the significance of big data analytics and how it promotes economic growth. Some sources have argued that big data analytics in the management of cities has enhanced economic growth by improving service delivery and a clean environment. Other sources have claimed that the application of data analytics with smart cities has led to an economic downturn because many operations have been automated, leading to massive loss of jobs (Allam & Dhunny, 2019). This essay will analyze how the U.S has influenced from applying big data analytics in developing its major cities and what’s advantages and disadvantages of widespread applying big data analytics for economic growth. What’s the benefit of applying big data analytic Hashem et al (2016) has linked the application of big data analytics in smart cities with the advancement in technology. According to these sources, the rise in technology, globalization, and rapid population increase has influenced big data with smart cities. In the U.S, bid data analytics has helped improve urban mobility by eliminating traffic, reducing carbon footprint, and managing infrastructure in a sustainable, cost-effective, and secure manner. The traffic in major cities in the U.S has reduced significantly over the past decade since the adoption of data analytics with smart cities. According to Kitchin (2014), the reduction of traffic has helped enhance movement and has helped save time and resources. Some sources argue that before adopting big data analytics in the transport sector, the U.S was losing over $2 billion every year on traffic gum. The waiting time was approximated to be about 3 hours. Over 60,000 liters of gas were wasted in the traffic during this period. Many employees were arriving 2 hours late at workplaces. The approximation of the money lost through arriving late at work was over $6 billion annually. However, with the adoption of big data analytic, all this money has been saved. These measures have influenced the past decades economic increase that the government undertook to reduce and eliminate traffic gum and congestion in big and small cities using big data analytics. Other sources have indicated how the use of big data analytics has reduced pollution in the cities. According to Lim, Kim & Maglio (2018), big data analytics have enhanced environmental conservation. The report shows that reducing traffic gum in cities has led to less pollution in the cities. Big data analytics to purify the air in companies has also helped reduce pollution in big cities significantly. What’s the disadvantages of applying big data analytic Despite big data analytic economic achievements in cities development, s