Evidence of International Trade
国际贸易实证代写 QUESTION 0 Please, report truthfully at the beginning of your document (with the answers) the following information:
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QUESTION I: Break the ice [10 Points] 国际贸易实证代写
Timmer et al. (2014, p. 104) present evidence in Table 1 that the foreign value added embodied in German fifinal output in the “automotive and transport” industry has increased from about 21 % in 1995 to 34 % in 2018.
1.Evaluate the following quote:
“The evidence in Table 1 means that in 2008, 34 % of German fifinal output in the automotive industry has not been manufactured by German fifirms”.
True or False? Motivate your answer in light of the evidence presented in Baldwin and Okubo (2014). [few lines, 7 points]
2.Is there evidence of an integrated production chain between Germany and Eastern European countries in the lecture slides titled “Value Added Trade” other than the evidence provided in Timmer et al. (2014)? [few lines, 3 points]
QUESTION II: Labor Markets and Trade Exposure [50 points] 国际贸易实证代写
In a recent article, Acemoglu et al. (2016) build on Autor et al. (2014) and discuss the great US employment sag of the 2000s in relation to import competition.
1.Focus your attention on Table 2 in Acemoglu et al. (2016).
a) Explain the specififications used in columns 2 and 3: write down and explain the linear specifification, the dependent variable, the main regressor, and the instrument (if applicable). Finally, if the specifification contains fifixed effffects, explain the rationale for including them. [1–2 paragraphs, 5 points]
b) State which column in Table 2 is in your opinion most similar to the specifification reported in Table IV, column 1 (Panel B) in Autor et al. (2014). Motivate your answer. [1 paragraph, 7 points]
c) Mention what are in your opinion the main difffferences between the variable of interest and the instrument employed in this paper with the ones used in Autor et al. (2014). [few lines, 5 points]
d) Interpret the coeffiffifficient of “−.30” reported in Column 1. [few lines, 3 points]
2.Focus your attention on Table 6 in Acemoglu et al. (2016).
a) How is the specifification reported in Column 2 (Panel A) difffferent from the corresponding specifification in Column 3 of Table 2 in the same paper? [few lines, 10 points]
b) Explain brieflfly why the approach undertaken in Panel B is necessary. [few lines, 5 points]
3.The approach followed in Acemoglu et al. (2016) departs from the approach undertaken in Autor et al. (2014): Explain in which way and what we learn from it. [2–3 paragraphs, 15 points]
QUESTION III: FDI and Gravity [40 points] 国际贸易实证代写
Two well known authors from the course have an article on FDI in the form of Mergers and Acquisitions – Head and Ries (2008). Guess what . . . their model delivers predictions in terms of bilateral stocks of inward/outward FDI. Their core equation to make predictions about dyadic FDI is arguably equation (5). By making some clever distributional assumptions, they arrive at equation (8), which you should take for granted.
Answer the following:
1.Explain the difffference between green-fifield FDI and M&As FDI. [4 points]
2.Show how to derive equation (10) from equation (8). [6 points]
3.Explain in which sense equation (10) is a gravity equation. [few lines, 5 points]
4.Head and Ries (2008) actually bring equation (10) to the data (cf. equations (15)–(17), p. 10-11, and Table 3).
a) The estimates are presented in Table 3. Most of the variables appearing in Table 3 (col. 4) are also regressors in the augmented gravity equation of trade. Comment if their impact on bilateral FDI is the same as for bilateral trade. [few lines, 5 points]
b) Consider just the specifific country-pair Japan-US (US as host country): Comment if the dyadic variables listed in Table 3 (col. 4) are good predictors of Japan’s outward FDI in the US. [1 paragraph, 8 points]
c) Keep considering the specifific dyad Japan-US. Which factor included in the gravity equation (10) could justify a large stock of Japanese FDI in the US as documented in Baldwin and Okubo (2014)? [Hint: Table 4 is unnecessary for answering this question, but it might provide evidence (or even inspiration) for your argumentation . . . ] [2–3 paragraphs, 12 points]
Lab I: Gravity Time! [80 points]
- Download the dataset datExam.RData from Stud.IP (folder “Hand-out”).
- Note that you can load this dataset with the function load(), e.g. load(“datExam.RData”).
- The dataset consists of the following variables:
- Whenever you are asked to run a regression, please use the function summary() to report a summary of your regression.
- Note: For the tasks below you will need to work with the log transformation and therefore have to drop observations with zero trade flflows.
1.What is the total number of observations in the dataset? How many observations do you need to drop in order to apply the log transformations? [8 points]
2.Estimate a Gravity regression where you control only for GDP and bilateral distance. Interpret your estimated coeffiffifficient of distance. [12 points]
3.Estimate a Gravity regression where you control for GDP, bilateral distances and year fifixed effffects. [16 points]
4.Estimate a Gravity regression where you control for GDP, bilateral distances and importer as well as exporter fifixed effffects. [24 points]
5.Estimate a Gravity regression where you control for GDP, bilateral distances, common currency, common language, colonial relationship, contiguity, year fifixed effffects and importer as well as exporter fifixed effffects. [20 points]
Lab II: Simulation [20 points] 国际贸易实证代写
This simulation depicts a hypothetical small ski resort. Even if all ski lifts are closed, on an average day at 0 degrees 200 people come to the resort (some just don’t realize that all lifts are closed!). Each operating lift attracts 20 additional visitors. Moreover, for each degree ambient temperature decreases, 30 additional visitors arrive. However, if temperature is 2 degrees or above, the average number of visitors drops by 80 (because they expect the snow to be melting).
1.Before making any random draws, set your student ID as seed! [−5 points if you do not comply]
2.Write down the linear relationship between the expected number of visitors and the variables that determine it, i.e. the data generating process. [4 points]
3.Simulate the number of visitors for 10000 days.
- For each day, randomly draw the number of open lifts (integer between 0 and 6; hint: ?sample).
- Also randomly draw a temperature for each day, assuming that temperatures are uniformly distributed between −10 and +3 degrees.
- Take into account that the actual number of visitors flfluctuates around the expected value. Capture this flfluctuation with a normally distributed error term with standard deviation 2.
Please generate the variables in exactly this order (lifts, temperature, error term), immediately after setting the seed and not interrupted by other commands (to ensure reproducibility).
What is your average number of visitors? [10 points]
4.Regress the number of daily visitors on an indicator variable for temperature being at least 2 degrees. Report and interpret the estimated coeffiffifficient. [6 points]
Acemoglu, D., D. Autor, D. Dorn, G. H. Hanson, and B. Price (2016). “Import Competition and the Great US Employment Sag of the 2000s”. In: Journal of Labor Economics 34.S1, S141–S198. doi: 10.1086/682384. eprint: https://doi.org/10.1086/682384. url: https://doi.org/10.1086/682384.
Autor, D. H., D. Dorn, G. H. Hanson, and J. Song (2014). “Trade Adjustment: Worker– Level Evidence”. In: The Quarterly Journal of Economics 129 (4), pp. 1799–1860. doi: 10.1093/qje/qju026.
Baldwin, R. and T. Okubo (2014). “Networked FDI: Sales and Sourcing Patterns of Japanese Foreign Affiffiffiliates”. In: The World Economy 37 (8), pp. 1051–1080. doi: 10.1111/twec.12116.
Head, K. and J. Ries (2008). “FDI as an outcome of the market for corporate control: Theory and evidence”. In: Journal of International Economics 74.1, pp. 2–20. doi: https : / / doi . org / 10 . 1016 / j . jinteco . 2007 . 04 . 004. url: http : / / www . sciencedirect.com/science/article/pii/S0022199607000815.
Timmer, M. P., A. A. Erumban, B. Los, R. Stehrer, and G. J. de Vries (2014). “Slicing Up Global Value Chains”. In: Journal of Economic Perspectives 28 (2), pp. 99–118. doi: 10.1257/jep.28.2.99.