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Empirical Project 1: Institutional Distance

The paper by Berry, Guillen, and Zhou (2010) proposes an institutional approach to measuring distance between countries.

In this first empirical project, you will construct at least one of the measures of institutional distance in the Berry et al. paper. I used the Financial distance measure in the draft of the solution do-file but you are welcome to choose any other measure for which data is easily available. The end product will be a narrative (or story) in which you describe what you have learned about institutional distance between the United States and other countries in 2020. Listed below are the specific analyses and questions that your narrative must address.  It should be double spaced with references, graphs, and maps.

Instructions

Please submit your Empirical Project on BB. Please follow the guidelines for empirical projects (please follow these guidelines for ALL projects going forward). Only 1 submission per group is required.

Your submission should include three files:

1. A 3-4 page narrative as a word document “Project1_LastNames.docx”.

2. The data file you used

3. Your do-file labeled “Project1_LastNames.do”. We have provided a sample file to get you started for the first project. Please follow this convention for problems going forward.

Specific questions to address in your narrative

1. First pick the institutional distance measure you would like to examine in the Berry et al. paper. Download the different data components required to construct the distance measure from the World Development Indicators Database . You will download data for all countries for just one year – 2020

In your narrative, define the institutional distance measure you pick, the data sources and meanings/definition for each of the sub-components, and how you interpret what the distance measure means (what does a larger or smaller distance measure mean for a MNC)             (20 points)

2. Summarize the individual sub-components of the distance measure. Report and interpret the minimum, maximum, mean, median, standard deviation for each of the sub-components and the correlation between each of these sub-components            (20 points)

3. Calculate the distance measure using the Mahalanobis distance. Explain why you use the Mahalanobis distance over the Euclidean distance                                              (20 points)

4. Summarize the Mahalanobis distance measure between the United States and other countries in the world. Which 3 countries does the United States have the smallest distance or largest distance with? If you were the CEO of a Multinational company looking to expand operations to countries, which country would you pick to expand operations to, given your analysis and why?            (40 points)

Extra credit

5. Compute the Euclidean distance as well and see how it compares to the Mahalanobis distance. Which country does the United States have the smallest and largest Euclidean distance with?

Guidelines for empirical projects

1. Please assign a separate directory (or folder) on your computer for each empirical project. Store all the data, programs, analyses and assignment submissions for the entire project in this folder.

2. Always make a copy of the source data file so that if you make changes to the data in your program, you have a master copy which is unchanged. I cannot stress this enough!

3. Please make sure you make detailed comments on each of the programming steps in your do-file. Adding comments is not just good programming practice but also

a. Allows for easier comprehension if you come back to the program after an extended period of time

b. Allows for easier debugging.

c. Allows me to understand what you are trying to accomplish

Points will be deducted if I cannot comprehend what you are trying to do!

4. Do not dive into constructing new measures and variables without understanding your data thoroughly. This included determining if you have duplicate observations (and what to do with them), missing data (and what to do with them), zeroes where you expect a numeric value, and if the range of values make sense or if you need to drop outlier observations.

5. Make sure both your narrative and program clearly show which question in the project you are addressing.

Hints:

For the financial distance measure, the data is available at https://databank.worldbank.org/reports.aspx?source=world-development-indicators

1. Make sure you are only selecting countries and NOT regions.

2. Select only the year requested.

3. Download the data in the proper format. Typically, we have the variables (Series) arranged in columns and the countries in rows.

4. Download the data as an excel file and call it WDI_Data.xlsx.

5. Rename the variables in the excel file (you could also do it in Stata but it may be easier in Excel). Give it names that are intuitive and make sure there are no spaces or dashes(-) in the variable names. Underscore can be used instead.

6. Replace missing data (..) with . because Stata recognizes the single period as missing data. If you don’t replace it, the two dots are considered as a string variable.