英文作业代写案例（题目）- 人文旅游类作业题

In order to verify the influence of the variables listed above on the number of tourists and determine their specific direction of action, this paper constructs four variables by using the data of China's sulfur dioxide emissions from 2009 to 2020, RMB exchange rate, the number of passengers carried by aircraft and whether there is an entry quarantine policy. The policy variables are 0-1 variables. Taking 2019 as the boundary, there was no COVID-19 outbreak before 2019, and China did not implement relevant epidemic prevention and control policies. However, after 2019, the COVID-19 outbreak and the situation became severe, China implemented strict epidemic containment for epidemic prevention and control. For foreign tourists who want to travel in China, they need to be quarantined for a long period of time in advance. In addition to paying high time cost, they also need to bear a large amount of quarantined expenses, which will hinder the people who want to travel and make them delay or even give up their travel plans. It is worth mentioning that according to the outbreak timeline released by the official news, the end of 2019 is also included. Considering the accuracy of measurement, this paper assigns the epidemic policy variables of 2019 and 2020 as 1, while the other years are all assigned as 0. In order to obtain more accurate regression results, this paper centralizes policy variables and then conducts regression. The variables mentioned above are gradually added for panel data regression, and all variables are processed logarithmically during the regression. In addition, considering that the variables considered here have a certain delay effect on the number of tourists, the current situation cannot be immediately reflected in the number of tourists at that time, but only after the change of relevant factors appears for a period of time, tourists can feel the change and make a response. Therefore, in the specific regression, in addition to considering the time trend of the number of tourists, the logarithm of the number of tourists in the last period is taken as an explanatory variable for regression, other variables are also treated with first-order lag, and the final regression results are shown in the table below, with robust standard error in brackets.

The first column in the table shows the regression result of the number of tourists in the current period to the number of tourists lagging behind. The regression coefficient is significantly positive, which is also in line with our previous expectations. The regression coefficient is 0.996, indicating that on the whole, the number of tourists in the later period is slightly lower than the number of tourists in the previous period, showing a downward trend. In the regression presented in the second column, this paper controls the fixed effects from different countries in order to eliminate the influence of some country-related factors on regression. After controlling the fixed effect, the result coefficient of regression has an obvious decline, from 0.996 to 0.577, but the coefficient is still significantly positive at the 1% level. Based on the regression formula in column (1), the factors of RMB exchange rate are taken into consideration and the regression results in column (2) are obtained. Again, the RMB exchange rate is treated with a one-step lag. The obtained results show that the RMB exchange rate has a significant positive impact on the number of tourists, that is, the higher the RMB exchange rate, the more the number of tourists. Based on the above analysis, we know that the RMB exchange rate reflects the relative value of RMB, the higher the exchange rate means that one dollar can be exchanged for more RMB, the less valuable RMB is, and the more money is saved for tourists. Therefore, A rise in the yuan's exchange rate will spur an increase in tourism. (3) The centralized policy variable is added to the regression equation corresponding to column 4. The policy variable itself is not significant, but the addition of this variable reduces the regression coefficients of the previous two variables, but its significance is not affected. The author guesses that the reason why policy variables are not significant here is that the time range of data selected in the empirical study in this paper is from 2009 to 2020, with a time span of 12 years, while the scope of policy factors only covers 2019 and 2020. Compared with the overall data, the time is too short to explain the overall data changes well. So the results are not significant. Columns (4) and (5) are the results obtained after adding aircraft capacity factor and environmental pollution factor respectively. According to the final overall regression results shown in column (5), only the policy factor is not significant, while other variables all show significant influence.The previous period's RMB exchange rate positively affects the number of inbound tourists in the current period at the 5% level of significance, probably because tourists perceive the change in foreign exchange and when the RMB depreciates, it is more cost-effective for them to travel at foreign exchange rates, so the more inbound tourists there are. The number of inbound tourists in the previous period affects the number of inbound tourists in the current period at the 1% level of significance, probably because of the interaction between tourists. Infrastructure development in the previous period also positively affects the number of inbound tourists in the current period. The better the infrastructure development, the easier the access and the more flights are opened, the more favourable the arrival of inbound tourists. Air pollution in the previous period also positively affects the number of inbound tourists in the current period at the 5% level of significance, and tourist cities may have slightly lower levels of air pollution than other countries, so inbound tourists will come to visit them.

The first column in the table shows the regression result of the number of tourists in the current period to the number of tourists lagging behind. The regression coefficient is significantly positive, which is also in line with our previous expectations. The regression coefficient is 0.996, indicating that on the whole, the number of tourists in the later period is slightly lower than the number of tourists in the previous period, showing a downward trend. In the regression presented in the second column, this paper controls the fixed effects from different countries in order to eliminate the influence of some country-related factors on regression. After controlling the fixed effect, the result coefficient of regression has an obvious decline, from 0.996 to 0.577, but the coefficient is still significantly positive at the 1% level. Based on the regression formula in column (1), the factors of RMB exchange rate are taken into consideration and the regression results in column (2) are obtained. Again, the RMB exchange rate is treated with a one-step lag. The obtained results show that the RMB exchange rate has a significant positive impact on the number of tourists, that is, the higher the RMB exchange rate, the more the number of tourists. Based on the above analysis, we know that the RMB exchange rate reflects the relative value of RMB, the higher the exchange rate means that one dollar can be exchanged for more RMB, the less valuable RMB is, and the more money is saved for tourists. Therefore, A rise in the yuan's exchange rate will spur an increase in tourism. (3) The centralized policy variable is added to the regression equation corresponding to column 4. The policy variable itself is not significant, but the addition of this variable reduces the regression coefficients of the previous two variables, but its significance is not affected. The author guesses that the reason why policy variables are not significant here is that the time range of data selected in the empirical study in this paper is from 2009 to 2020, with a time span of 12 years, while the scope of policy factors only covers 2019 and 2020. Compared with the overall data, the time is too short to explain the overall data changes well. So the results are not significant. Columns (4) and (5) are the results obtained after adding aircraft capacity factor and environmental pollution factor respectively. According to the final overall regression results shown in column (5), only the policy factor is not significant, while other variables all show significant influence.The previous period's RMB exchange rate positively affects the number of inbound tourists in the current period at the 5% level of significance, probably because tourists perceive the change in foreign exchange and when the RMB depreciates, it is more cost-effective for them to travel at foreign exchange rates, so the more inbound tourists there are. The number of inbound tourists in the previous period affects the number of inbound tourists in the current period at the 1% level of significance, probably because of the interaction between tourists. Infrastructure development in the previous period also positively affects the number of inbound tourists in the current period. The better the infrastructure development, the easier the access and the more flights are opened, the more favourable the arrival of inbound tourists. Air pollution in the previous period also positively affects the number of inbound tourists in the current period at the 5% level of significance, and tourist cities may have slightly lower levels of air pollution than other countries, so inbound tourists will come to visit them.

结语很棒，和我想的一样，只是用更体系的话表达出来了。更加坚定的我的心

我感觉文学鉴赏力好像是天生的，文学和艺术一样，训练是需要的，但更重要的是一种与生俱来的审美和理解力。

这个能用马工程的教材嘛

特别想提问，针对这些考研的考点，老师是否觉得这些考试内容真的可以培养独立思考的能力？

当有些内容成为一个非常小众，大家都非常了解的东西都时候，他会无形当中建构一个人的价值观。

请问《文学理论教程》的版本是哪一版的

重要的研究方向：文艺学、美学、大众文化研究,文艺学：内容基本等于文学理论

什么时候才能看到老师讲的抒情性作品的结构问题和审美问题呢？

哲学生听起来相当亲切，很多都是学过的，美学还是专业课。老师讲的几个哲学家的关于”美“和索绪尔的思想都是学过的。

老师讲的太好了，可惜我没看过这本小说。如果我是作者，我会延展为鸽子的停留、盘旋是因为养鸽人在家里。而鸽子对养鸽人是有感情的，就好比你在哪家就在哪的感觉，如果养鸽人引导性地走向终点，那么鸽子也很有可能随着他飞往终点。不论养鸽人的目的是什么，但对于鸽子来说养鸽人提供的不仅是食宿，还有家，或者说生命的寄托和终点，养鸽人对于它是灯塔一样的存在。

老虎和美女故事，可以是小伙子走向公主指的相反方向，因为如果公主指的是老虎那她是自私的爱不值得坚守，完全可以跟别人在一起，如果公主指的是美女，那她是大爱，值得付出生命。

颠覆了我对文科生的刻板印象。学者该具备的理性一点没少

快来学习一下吧，老师讲课很棒哦

为什么我看到的书是这样说的：一部由作者创作出来的语言艺术品，当其未经读者阅读时，就还只是文本；而当其被读者阅读后，才变成了作品。 简言之：文学文本加作者阅读大体就等于文学作品了

朝饮木兰之坠露兮，夕餐秋菊之落英

我们老师上课只讲理论，几乎不结合文学作品分析，刚开学，直接布置了文学评论的大作业，我都没学过我怎么写，老师还美名曰学了理论就是让我们实践的

想自己尝试写作，董老师有什么写作课程推荐嘛

老师好…从朋友处介绍而来……虽然迟了，但是还好不晚…谢谢分享…祝顺遂

学习比较文学形象学会发现更多这样的问题，很多文学作品和影视作品为了迎合西方，会塑造这样的角色和故事情节，我觉得很悲哀。

取得成功有很多因素，每个人也都是不同的个体，“社会提供的客观条件是人们创造和实现人生价值的前提”所以个人认为酱酱的家庭是决定因素，给了她良好的起点，而她自身的努力是主要因素，决定了她飞多高多远，至高的成就总是离不开天时地利人和

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