fdi case study dataset download

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Fdi case study using tableau.

In this Case Study, we will explore the FDI dataset and analyse it from the perspective of the business. We shall look at various sectors to determine which sector will prove most beneficial to collaborate with, for the company.

FDI : A foreign direct investment (FDI) is an investment made by a corporation of a certain country into a corporation of another country. However, FDI is different form indirect investments. If a foreign investor passively invests in an Indian company by owning stocks or bonds, this will not be considered as FDI. But, if a foreign investor invests in an Indian company, and controls technology, management and other aspects, this will be considered as foreign direct investment. For example, a foreign institution invests in a company that is listed on a major stock exchange. However, such institutions do not control various aspects of management in the firms in which they invest in. For an investment to be considered FDI, the firm you invest in should be located in a foreign jurisdiction and control ownership to a degree. Often, it is the large firms that engage in FDI.

Here I have gone through the data and analysed visually and got insights on the following

a)Which sector receives the maximum direct funding for a given year?

b)Which sector receives the minimum direct funding for a given year?

c)Is there any trend of overall foreign direct investment(filter to select any indivual sector)

d) Which sectors reported high growth in FDI in last 5 years?

e) Which sectors reported lowest growth in FDI in last 5 years?

f)Which sectors reported the most variation overall?

g)What is the proportion of each sector in FDI?

h)Are there some specific clusters that are present here?

i)What is the forecast for next year?

You can view FDI-Case Study Dashboard on my Tableau Public Profile link- https://public.tableau.com/profile/borugadda.manoj#!/

Leonie M Windari

Dec 29, 2020

Tableau Case Study : Foreign Direct Investment

In this post I will share the result of Data Visualization using Tableau in a Foreign Direct Investment Case Study. Please note that this post is based on edureka Youtube Video below.

I am trying to improve my skills and deepen my understanding in using Tableau so I will do a few Case Study projects before deciding to do my own. So the purpose of this post is to test my understanding and also share some information with you guys.

So, based on investopedia , Foreign Direct Investment is an investment made by a firm or individual in one country into business interests located in another country. Generally, FDI takes place when an investor establishes foreign business operations or acquires foreign business assets in a foreign company.

Of course, before we start it is better if we determine the purpose of this case study first. That way you will have a clear path on what you should do and what you’re trying to achieve (and you won’t get lost along the way).

You can download the dataset here .

Because I want to test my understanding in data visualization and tableau, I try to visualize the dataset by myself first and then I watch the youtube tutorial. Please note that the data has been cleaned before (removing the Grand Total from the FPI Value and transform the data into Pivot, extracting only the year from Year column).

This dataset only have 3 variable : Sector, FPI Value, and Year but in here you will see that with only these 3 variable, we can draw a lot of conclusion and insight.

In this case study we will explore the dataset to answer some questions :

For me personally, I think a horizontal bar will give a good visualization on this. So I set the SUM of the FPI Value as the Columns and Sector as the Rows . I will take the top and bottom 5 of the data by using Filter to the Sector variable.

Here you can see that the Service Sector have the biggest FPI Value, followed by Computer Software, Construction, and so on. While Photographic, Coal Production, and so on have the least value than the others.

We can draw a conclusion from this graph but it’s still not clear. If you are an investor and you are trying to decide which sector you should choose, this graph can help but you still need another insight, like : the trends, the growth.

You can also filter it by Year to see the Top and Bottom 5 FPI Value each year. In here I also set the sum of the FPI Value as the label so you can see it more clearly. I differentiate the color between the two to show the contrast between them. (Usually the bottom is defined by red color, no?)

2. Is there a trend for direct investment for individual sector?

If you heard the word ‘trend’ it doesn’t take a long time for you to think that it has to do with time , and what a better way to visualize it? For me, I think using trend lines will best visualize a trend. So for this I set the Year as the Columns and SUM (FPI Value) as the Rows.

Here we can see the trend of the FPI each year. You can see that in 2010 and 2012 there are some declining lines. Something must’ve cause that to happen, but after that the line is increasing for 4 years in a row, which means that there a high chance/possibilities that the line will also increase in the next year. We don’t know yet but we will see in the forecasting section below.

To make it clearer, I add labels and colors to make the graph more define. You don’t have to do that but I find it much more easier to see or draw conclusion and insight.

3. Which sectors reported the highest growth and decline in the past 5 years?

At first I was kinda confused because I don’t know how to visualize the growth/decline. At first I thought I can do it with FPI Value and line graph but I want to know which sector have the highest and lowest growth, certainly I can’t drew this conclusion from a line graph.

It turns out that using percentage of rate helps. Why didn’t I think of that? It’s okay though, I got another knowledge! So what I did is I set the Year as the Column and the Sector as the Rows . I add the FPI Value in the Text and if you click on it, it will show the The Compound Growth Rate in the Quick Table Calculation.

I don’t know what is the best way to visualize it (in the edureka video, they use table). I tried to use side-by-side bars but I’m not sure if you can draw a conclusion out of it? I don’t know, which one you think is the best? I will attach side by side comparison.

Here we can also draw a conclusion. It seems like the Service and Computer Software Sector have the biggest growth. From the section before, we also know that the Service Sector and Computer Software Sector have the biggest FPI Value. It seems like it’s a good sector to choose.

Here I use the filter to filter out the Top 5 and Bottom 5 of the Growth Rate. I also add the Growth Rate as the label in the side-by-side bars. What do you think? Which one gives the better insight?

4. What is the proportion of investment between sectors from the FDI perspective?

If we want to find out which sector have the most proportion out of all sector? We can see it from the SUM of the FPI Value but it’s hard to compare to one another. So what I did was I use the horizontal bar to visualize this. I use divide it by the sector and use color to define the sum of the FPI Value. I find it easier to draw an insight through this.

Here we can draw a conclusion that Services, Computer Software, and Construction Development Sector have the most proportion out of the rest of the sector. We all know from before that Services and Computer Software Sector also have the highest FPI Value and Growth Rate. For Construction Development, it have a high FPI Value but the Growth Value is less than Automobile and Telecommunications but still it’s on the Top 5.

If we’re still thinking which sector we should choose, we can also try to see the Trend for each sector. We can use Sector as the filter in the Trend section. I also add the percentage of the FPI Value as the labels to show some comparison besides the color depth.

5. Are there any specific clusters present in the data?

We have a lot of sector and some of the sector fall into the same clusters. We can analyze and get some insight through each sector. Here we use the Clusters Analytics function in Tableau to cluster some sector that have similar characteristics.

From Datacamp , we know that :

Tableau uses the Calinski-Harabasz criterion to assess cluster quality. Here is the mathematical interpretation of the Calinski-Harabasz criterion:

“where SSB is the overall between-cluster variance, SSW is the overall within-cluster variance , k is the number of clusters, and N is the number of observations” ( Source ).

This ratio gives a value which determines the cohesiveness of the clusters. So the higher this value, clusters are more closely associated having low within-cluster distance and high between-cluster distance.

We can decide how many clusters we wanted but based on the data, it seems like it fell into 11 different sectors. From this result, we can drew some conclusion if we analyze each cluster seperately and hopefuly draw some insight of it.

6. Can we forecast the trend for the following year?

The last one is we can use the Forecast in Tableau to predict the future outcomes. Of course it’s not 100% accurate and even if it have a high possibility, there may be some external factor that affecting it. But at least from this we can see the tendency of the outcomes.

Here we can see that the forecasting give the future outcomes of the lines increasing. We can use filter to see the forecasting of each sector to give a much detailed forecasting.

That’s all guys! I learn a lot from this exercise, it is really important to think first about how you expect the visualization of the quesions will be, before jumping into Tableau itself.

I will be posting my next exercise (hopefuly). I hope this can help you guys!

I also posted my workbook in here so you can check it out!

More from Leonie M Windari

a curious human being. current enemies : manual data entry. current motivation : weekends and deadlines.

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Working paper 335 - intra-african foreign direct investment (fdi) and employment: a case study.

Most foreign direct investment (FDI) into Africa is currently concentrated on natural resources, but investment in non-resource-based FDI, and in particular, FDI in manufacturing, generates more jobs and has the potential to alleviate the continent’s unemployment problem. The key factors that drive intra-African FDI can be analyzed by focusing on investments from South African multinationals to other African countries. This paper does so using a panel-corrected standard errors estimator with a firm-level FDI dataset for 2003–2016. The results suggest that market attractiveness has a positive impact on intra-regional FDI, while business regulations have an adverse effect. Doubling GDP per capita or doubling the share of labor force is expected to increase South African FDI by about 31% or 46%, respectively. Inversely, for host countries, an increase in the capital requirement, the lack of legal rights, or the tax burden is expected to reduce FDI by about 31%, 62%, or 17%, respectively. However, a reduction in legal rights from the median country level to that of the least restrictive country and a decrease in the tax burden from the median country level to that of the least restrictive country should raise South African FDI by 59% and 31%, respectively. Overall, these results underline the adverse impact of business regulations on intra-regional investment flows and suggest that policies that foster economic growth, promote higher per capita incomes, expand the labor force, and improve the business environment in African countries will facilitate intra-regional FDI.

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