I'm back from my trip to Saigon and it was exciting as this was my first trip to Vietnam. Besides being a huge fan of the cuisine (love the pho, banh cuon, banh hoi, banh xeo, banh mi, com tam), it was also very interesting to see the country in action. Made me a bit curious on if I should consider investing in the country.

PROs

Demographics Vietnam has good demographic trends for growth in the next 10~20 years. Using data from the World Bank, 2 charts signify this: 1. Low dependence from the elderly (Percentage of population > 65 is fairly low) and 2. Relatively high birth rate. Literacy rate in Vietnam is also very high (est 90~94% vs in the 70s for India).

In [1]:

%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

In [2]:

import wbdata

In [21]:

countries = ['VNM', 'USA', 'CHN', 'JPN', 'KOR', 'BRA', 'IND']

In [42]:

indicators = {'SP.POP.DPND.OL':'Age Dependency Ratio', 'SP.DYN.CBRT.IN': 'Birth rate (per 1,000 people)'}

In [43]:

df = wbdata.get_dataframe(indicators, country=countries, convert_date=False)

In [44]:

dfu = df.unstack(level=0)
sdfu = dfu[40:]
# sdfu.head()

C:\Anaconda3\lib\site-packages\pandas\core\index.py:4281: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  return np.sum(name == np.asarray(self.names)) > 1

In [45]:

sdfu['Age Dependency Ratio'].plot()
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.) 
plt.title('Age dependency ratio (Old/Working)')
plt.xlabel('Date')
plt.ylabel('Ratio of old (>64) to the working-age population')

Out[45]:

<matplotlib.text.Text at 0xa954dd8>

In [46]:

sdfu['Birth rate (per 1,000 people)'].plot()
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.) 
plt.title('Birth Rate')
plt.xlabel('Date')
plt.ylabel('Birth rate (per 1,000 people)')

Out[46]:

<matplotlib.text.Text at 0xaa027b8>

Hustle Ties into point 1 but the people in Vietnam work hard and hustle. I visited the Cu Chi tunnels by Saigon (farmland outside of Saigon where the battles took place) where I saw how resourceful the Vietcong had to be during the war to survive. They essentially were farmers by day and then dug tunnels and gathered/created whatever battle resources they could at night. Walking along the streets in Saigon, I saw many young adults hold multiple jobs for income. Vietnam must also hold the title of highest density of coffee shops in a major city. Literally, coffee is EVERYWHERE. All that caffeine must help :)
Trans-Pacific Partnership New trade agreement that should be positive for Vietnam.

CONs

Corruption Corruption is a big issue (as with a lot of developing countries). Sounds like every company has a government aka bribery department.
Credit Vietnam is a very cash heavy country. Credit cards are rarely accepted (supposedly ~10% penetration rate). However, smartphone penetration is very high (~40%) which provides opportunities for mobile payment services.
Infrastructure. A lot of buildings are hastily put together and apparently have a short shelf life in the hot and humid weather. Roads are majorly congested (crossing an intersection in Saigon is not for the faint of heart). As people get wealthier and migrate from mopeds to cars, this will only get worse so there is a definite need for mass public transportation in Saigon.

Overall, I am very excited at the potential in Vietnam. In a lot of ways, Saigon felt like Beijing 10~15 years ago. It'll be a interesting spot to keep an eye on.