给大家推荐一篇关于The Economic Impact of the Olympics的paper范文,供大家参考学习,这篇论文讨论了奥运会对经济的影响。根据专家们的调查结果分析,2008年北京奥运会对中国经济产生了比较大的影响,包括奥运会对城市的经济产生一些积极的影响,也在一定程度上改善了城市的基础设施和交通基础设施。另外,它还提高了就业率和工资水平。
From the article of "Impact of the 1996 Summer Olympic Games on Employment and Wages in Georgia", it is found that there is a positive relation between the employment rate and the Olympic city, Atlanta, Georgia. Julie used differences-in differences (DD) statistical method to conduct the research.
Of Julie's research, she has classified the counties in two groups, one is venue counties and the other one is near-venue counties. The above counties are classified VNP counties. And Julie has identified three VNP county groups: it includes the North, Savannah and Columbus.
Julie has used the DD approach to conduct the research, and she has used the OLS regression to analyze the data. The logic of the article is to compare the employment rate and the wage level among different groups. After analyzing the data, Julie has found that the employment is increasing 17% in VNV counties than non-VNV counties. And the wage is increasing the amount of 7% compared the post-Olympics and before Olympics. There is more demand in labor for the Olympics, the labor demand is increasing more than the supply, which causes the wages to increase.
And Julie has used the random-growth models to work as the robustness check. In the year of 1989, Heckman and Hotz has found a method to quantify the impact of events such as the Olympics. And as a result of the robustness check, it shows the similar results as that the Olympics helps counties to increase employment rate. The employment rate is increasing by 17 percent, which is about 293,000 more jobs of the VNP counties. And the other DD analysis states that the employment rate is also increasing in other area of Georgia.
The relationship between wage increasing and Olympics is not clear, the random-growth model didn't show the statistical significance of the wage increasing and Olympics. So the author assumes that the increasing employment rate shifts the supply curve, which causes the wages increasing. Unfortunately, there is lack of data to support the estimation.
Beijing held the 2008 Olympics Games, and there were a lot of reports and analysis regarding the event, and there are several methods to analyze the event such as financial analysis methods, event analysis, cost-benefit analysis and macroeconomic model analysis. For the Olympics or other big events, the input-output model and the computable general equilibrium are often used.
I would like to research the economic impact of the Beijing Olympics of the year of 2008 and to use the methods of econometrics, I have to make it clear that Beijing is a very special city. It is greatly impacted by China economics policy and also greatly impacted by other cities. So the model is not used to analyze Beijing economics as a whole, it is only for to research the economic impact of the Beijing Olympics. And the investment to the Beijing Olympics will only include the years between 2002 and 2007. It will be a little different from the real investment but will have little impact of the research.
And the investment includes two sections: one section is the direct investment, the other one section is indirect investment. Direct investment means the direct investment of the 2008 Beijing Olympics, indirect investment means investment to Beijing, but which is not related to the Olympics.
What's more, for the investment of Chinese government, it is a macro and logical decision based on GDP. GDP can be stated as of below:
GDP= consumption + investment + government spending+ (exports-imports)
The models will include the followings:
PCR_(t=) β_0+β_1 PCR_(t-1)+β_2 GDP_t
EIR_t=β_0+β_1 EIR_(t-1)+β_2 GDP_t
PIR_t=β_0+β_1 PIR_(t-1)+β_2 GDP_(t-1)
GIR_t=β_0+β_1 GDP_t+β_2 GDP_(t-1)
PCR_t Means the citizens' consumptions at the period time of t, GDP means the national gross domestic product at the time period of t, EIR means the export amount at the time period of t, PIR means the individual investment amount at the time period of t, GIR means the government investment at the time period of t, GCR means the government consumption at the time period of t, SR means the increasing of goods and services at the time period of t.
And the endogenous variables include GDP, PCR, EIR, GIR and PIR; GSR and SCR are exogenous variables. Based on the above model, to use the least square method, we can get the following equations:
PCR_(t=) 0.0161+0.3832PCR_(t-1)+0.1295GDP_t
EIR_t=11.2019+0.7355EIR_(t-1)-0.0658GDP_t
PIR_t=-2.1472+1.2339PIR_(t-2)+0.0132GDP_(t-1)
GIR_t=-23.6439+1.7265GDP_t-1.2944GDP_(t-1)
Whilst there is a little bit problem of the data, I used the least square method to conduct the data analysis again, the result is as followings:
PCR_(t=) 0.3926+0.8837PCR_(t-1)+0.0448GDP_t
EIR_t=4.0564+0.8732EIR_(t-1)-0.0368GDP_t
PIR_t=-1.4825+1.4886PIR_(t-2)+0.0084GDP_(t-1)
GIR_t=-40.8575+0.1397GDP_t+0.5113GDP_(t-1)
GDP=13.682+0.58GIR_t+0.75GDP_(t-1)
From the above economics analysis, there will be economics impact to the city which holds the Olympics games, and the 2008 Olympics helps Beijing to build more infrastructure especially more sports infrastructure, and to improve the Beijing transportation, to create more employment opportunities, it has a positive impact of the employment structure and industry sector adjustment.
And the direct investment is increasing Beijing nominal GDP between the years of 2002-2007, which is 399.7 million, 16.094 billion, 38.037 billion, 63.758billion, 80.483billion and in the total amount of 278.717 billion. Whilst the model is limited, and the model doesn't state the specific impacts to Beijing economics. And there is also some errors, if we can get more accurate data, the analysis will be more accurate and more specific.
The Values of the Olympics
There a lot of methods to analyze the Beijing Olympics' impact on economics, which includes The Olympics might do some positive impacts on the economics of the city, and it also improves the city infrastructure and transportation infrastructure. It will also increase the employment rate and it will increase the wages level. The challenges is to build the economic model, the correction of the model and the data collection problems. The data is not accurate enough and the statistical correlation still needs more data and more data analysis to support, related further research can be conducted in the future.
References
Hotchkiss, J. L., Moore, R. E., & Zobay, S. M. (2003). Impact of the 1996 Summer Olympic Games on Employment and Wages in Georgia. Southern Economic Journal, 69(3), 691. doi:10.2307/1061702
Jones, C. (2001). Mega-events and host-region impacts: determining the true worth of the 1999 Rugby World Cup. International Journal of Tourism Research, 3(3), 241-251. doi:10.1002/jtr.326
Sydney 2000 Olympic Games Journal. (2011). The Automated Lighting Programmers Handbook, 149-168. doi:10.1016/b978-0-240-81553-4.00034-0
The Impact and Evaluation of Major Sporting Events. (2007). doi:10.4324/9781315878195
Weed, M. (2014). Sports Mega-Events and Mass Participation in Sport. Leveraging Legacies from Sports Mega-Events, 39-49. doi:10.1057/9781137371188_4
www.bjstats.gov.cn
www.stats.gov.cn
References
VNP: near and near-venue (VNP) counties
VNP county groups: North (including Atlanta and Athens), Savannah on the coast, and Columbus
51due留学教育原创版权郑重声明:原创美国论文代写范文源自编辑创作,未经官方许可,网站谢绝转载。对于侵权行为,未经同意的情况下,51Due有权追究法律责任。主要业务assignment代写、essay代写、paper代写、美国论文代写服务。
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From the article of "Impact of the 1996 Summer Olympic Games on Employment and Wages in Georgia", it is found that there is a positive relation between the employment rate and the Olympic city, Atlanta, Georgia. Julie used differences-in differences (DD) statistical method to conduct the research.
Of Julie's research, she has classified the counties in two groups, one is venue counties and the other one is near-venue counties. The above counties are classified VNP counties. And Julie has identified three VNP county groups: it includes the North, Savannah and Columbus.
Julie has used the DD approach to conduct the research, and she has used the OLS regression to analyze the data. The logic of the article is to compare the employment rate and the wage level among different groups. After analyzing the data, Julie has found that the employment is increasing 17% in VNV counties than non-VNV counties. And the wage is increasing the amount of 7% compared the post-Olympics and before Olympics. There is more demand in labor for the Olympics, the labor demand is increasing more than the supply, which causes the wages to increase.
And Julie has used the random-growth models to work as the robustness check. In the year of 1989, Heckman and Hotz has found a method to quantify the impact of events such as the Olympics. And as a result of the robustness check, it shows the similar results as that the Olympics helps counties to increase employment rate. The employment rate is increasing by 17 percent, which is about 293,000 more jobs of the VNP counties. And the other DD analysis states that the employment rate is also increasing in other area of Georgia.
The relationship between wage increasing and Olympics is not clear, the random-growth model didn't show the statistical significance of the wage increasing and Olympics. So the author assumes that the increasing employment rate shifts the supply curve, which causes the wages increasing. Unfortunately, there is lack of data to support the estimation.
Beijing held the 2008 Olympics Games, and there were a lot of reports and analysis regarding the event, and there are several methods to analyze the event such as financial analysis methods, event analysis, cost-benefit analysis and macroeconomic model analysis. For the Olympics or other big events, the input-output model and the computable general equilibrium are often used.
I would like to research the economic impact of the Beijing Olympics of the year of 2008 and to use the methods of econometrics, I have to make it clear that Beijing is a very special city. It is greatly impacted by China economics policy and also greatly impacted by other cities. So the model is not used to analyze Beijing economics as a whole, it is only for to research the economic impact of the Beijing Olympics. And the investment to the Beijing Olympics will only include the years between 2002 and 2007. It will be a little different from the real investment but will have little impact of the research.
And the investment includes two sections: one section is the direct investment, the other one section is indirect investment. Direct investment means the direct investment of the 2008 Beijing Olympics, indirect investment means investment to Beijing, but which is not related to the Olympics.
What's more, for the investment of Chinese government, it is a macro and logical decision based on GDP. GDP can be stated as of below:
GDP= consumption + investment + government spending+ (exports-imports)
The models will include the followings:
PCR_(t=) β_0+β_1 PCR_(t-1)+β_2 GDP_t
EIR_t=β_0+β_1 EIR_(t-1)+β_2 GDP_t
PIR_t=β_0+β_1 PIR_(t-1)+β_2 GDP_(t-1)
GIR_t=β_0+β_1 GDP_t+β_2 GDP_(t-1)
PCR_t Means the citizens' consumptions at the period time of t, GDP means the national gross domestic product at the time period of t, EIR means the export amount at the time period of t, PIR means the individual investment amount at the time period of t, GIR means the government investment at the time period of t, GCR means the government consumption at the time period of t, SR means the increasing of goods and services at the time period of t.
And the endogenous variables include GDP, PCR, EIR, GIR and PIR; GSR and SCR are exogenous variables. Based on the above model, to use the least square method, we can get the following equations:
PCR_(t=) 0.0161+0.3832PCR_(t-1)+0.1295GDP_t
EIR_t=11.2019+0.7355EIR_(t-1)-0.0658GDP_t
PIR_t=-2.1472+1.2339PIR_(t-2)+0.0132GDP_(t-1)
GIR_t=-23.6439+1.7265GDP_t-1.2944GDP_(t-1)
Whilst there is a little bit problem of the data, I used the least square method to conduct the data analysis again, the result is as followings:
PCR_(t=) 0.3926+0.8837PCR_(t-1)+0.0448GDP_t
EIR_t=4.0564+0.8732EIR_(t-1)-0.0368GDP_t
PIR_t=-1.4825+1.4886PIR_(t-2)+0.0084GDP_(t-1)
GIR_t=-40.8575+0.1397GDP_t+0.5113GDP_(t-1)
GDP=13.682+0.58GIR_t+0.75GDP_(t-1)
From the above economics analysis, there will be economics impact to the city which holds the Olympics games, and the 2008 Olympics helps Beijing to build more infrastructure especially more sports infrastructure, and to improve the Beijing transportation, to create more employment opportunities, it has a positive impact of the employment structure and industry sector adjustment.
And the direct investment is increasing Beijing nominal GDP between the years of 2002-2007, which is 399.7 million, 16.094 billion, 38.037 billion, 63.758billion, 80.483billion and in the total amount of 278.717 billion. Whilst the model is limited, and the model doesn't state the specific impacts to Beijing economics. And there is also some errors, if we can get more accurate data, the analysis will be more accurate and more specific.
The Values of the Olympics
There a lot of methods to analyze the Beijing Olympics' impact on economics, which includes The Olympics might do some positive impacts on the economics of the city, and it also improves the city infrastructure and transportation infrastructure. It will also increase the employment rate and it will increase the wages level. The challenges is to build the economic model, the correction of the model and the data collection problems. The data is not accurate enough and the statistical correlation still needs more data and more data analysis to support, related further research can be conducted in the future.
References
Hotchkiss, J. L., Moore, R. E., & Zobay, S. M. (2003). Impact of the 1996 Summer Olympic Games on Employment and Wages in Georgia. Southern Economic Journal, 69(3), 691. doi:10.2307/1061702
Jones, C. (2001). Mega-events and host-region impacts: determining the true worth of the 1999 Rugby World Cup. International Journal of Tourism Research, 3(3), 241-251. doi:10.1002/jtr.326
Sydney 2000 Olympic Games Journal. (2011). The Automated Lighting Programmers Handbook, 149-168. doi:10.1016/b978-0-240-81553-4.00034-0
The Impact and Evaluation of Major Sporting Events. (2007). doi:10.4324/9781315878195
Weed, M. (2014). Sports Mega-Events and Mass Participation in Sport. Leveraging Legacies from Sports Mega-Events, 39-49. doi:10.1057/9781137371188_4
www.bjstats.gov.cn
www.stats.gov.cn
References
VNP: near and near-venue (VNP) counties
VNP county groups: North (including Atlanta and Athens), Savannah on the coast, and Columbus
51due留学教育原创版权郑重声明:原创美国论文代写范文源自编辑创作,未经官方许可,网站谢绝转载。对于侵权行为,未经同意的情况下,51Due有权追究法律责任。主要业务assignment代写、essay代写、paper代写、美国论文代写服务。
51due为留学生提供最好的美国论文代写服务,亲们可以进入主页了解和获取更多assignment代写范文 提供美国作业代写服务,详情可以咨询我们的客服QQ:800020041。