这是一篇来自澳洲的关于解决下面关于贷款方面和石油价格方面相关2个问题的应用计量经济学代写
Question A: (3000 words)
The legendary country of Albion consists of a northern and a southern state. To mitigate the effects of the current crisis, the northern state introduced a job retention scheme in 2020, which provided a loan worth 20% of the total payroll of the firm but had to be repaid within five years. All firms that applied for the loan received the loan but many firms did not apply. The southern state, concerned about the expense of such a scheme, did not introduce a job retention scheme.
The government would like you, firstly, to estimate a model to show which factors predict receipt of the loan. (25%).
Secondly, the government would like you to estimate the causal effect of the loan on firm employment.(75%).
To allow you to conduct such an evaluation, you are given data from a random sample of 1,000 firms for the period 2018-20 (see Table 1 for a description of the variables in the dataset). 500 of these firms are located in the northern region and 500 are located in the southern region. Each of you will analyse a different sample (so your results will be different to those of your colleagues).
Table 1. Variable Descriptions
| Variable | Description |
| id | Firm identification number |
| year | Year |
| employment | Number of employees at end of the year |
| loan | Dummy variable coded 1 if firms receives the loan |
| age | Age of firm at start of the year |
| leverage | Total liabilities divided by total assets at start of the year |
| industry | Categorical variable coded 1 if firm is in agriculture, 2 if firm is in manufacturing, 3 if firm is in services |
| state | Dummy variable coded 1 if firm is located in the northern region |
Question B: (3000 words) (50 Marks)
Russia’s conflict with Ukraine has increased energy prices and high market volatility of energy prices affecting the economies around the world. Also, the sanctions imposed by the USA and other European countries seem to have fragmented the oil market.
In this question you are going to investigate the interactions between various oil markets. If you are a consumer of oil, you would like to diversify your supply. In this exercise we would like to have a mix of various markets (WTI, BRENT, URALS, etc) as our portfolio.
Choose four markets and download the daily prices of oils from various markets till the end of January 2023) and answer the following questions:
- Check for non-stationarity of the oil prices and then investigate the descriptive statistics (including higher moments) of the returns. How would you compute the confidence intervals for the moments? What is your inference?(25%)
- Compute the pairwise difference of the prices (also known as spread), estimate the time-series models for the spread and check for stationarity. Also analyse whether the oil prices are pairwise co-integrated. Compare and comment on the results.(25%)
- Estimate models for the return’s volatility of your chosen oil market for the entire sample period and for the periods before and after the start of the Russian-Ukrainian conflict (your choice of start date).Thus, you need to estimate three models. Compare and comment on your results. Also compare the estimated higher moments for the volatility models with the results from part 1).(25%)
- How many co-integration relationships do you find among the oil markets? Check for the entire sample and then split the sample at an appropriate point (start of Russian-Ukrainian conflict?) and redo the exercise. Comment on your results.(25%)
Useful references
Narayan, Paresh Kumar, and Seema Narayan. “Modelling oil price volatility.”
You can download oil prices from any publicly available sources or WRDS> Thomson-Refinitiv, Bloomberg (terminals are available at the business school)
Overall word limit: 6000 words
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Assignments should be typed, using 1.5 spacing and an easy-to-read 12-point font. Assignments and dissertations/business projects must not exceed the word count indicated in the module handbook/assessment brief.
The word count should:
- Includeall the text, including title, preface, introduction, in-text citations, quotations, footnotes and any other items not specifically excluded below.
- Excludediagrams, tables (including tables/lists of contents and figures), equations, executive summary/abstract, acknowledgements, declaration, bibliography/list of references and appendices. However, it is not appropriate to use diagrams or tables merely as a way of circumventing the word limit. If a student uses a table or figure as a means of presenting his/her own words, then this is included in the word count.
Examiners will stop reading once the word limit has been reached, and work beyond this point will not be assessed. Checks of word counts will be carried out on submitted work, including any assignments or dissertations/business projects that appear to be clearly over-length. Checks may take place manually and/or with the aid of the word count provided via an electronic submission. Where a student has intentionally misrepresented their word count, the School may treat this as an offence under Section IV of the General Regulations of the University. Extreme cases may be viewed as dishonest practice under Section IV, 5 (a) (x) of the General Regulations.
Very occasionally it may be appropriate to present, in an appendix, material which does not properly belong in the main body of the assessment but which some students wish to provide for the sake of completeness. Any appendices will not have a role in the assessment – examiners are under no obligation to read appendices and they do not form part of the word count. Material that students wish to be assessed should always be included in the main body of the text.