How would I rate #, Harold MacMillan, as the PM of the UK?
Excellent sense of humour.
An eloquent speaker!
#Détente between the East and the West became possible due to #Macmillan’s diplomacy and energetic role in international politics.
He was probably a gifted International Relations Practitioner who had an exceptional understanding of issues around the world.
He was remarkably the first to predict an International crisis in the Gulf back in the 1960s after #Kuwait was given independence with a special status.
Many students ask me about SCM/Logistics Degree programs.
Go to any top business school at an Ivy League university.
Alternatively, you may choose to find some decent department of Economics that has a strong partnership with other faculties, such as Operations Research, Industrial or Transportation Engineering.
Many Transportation Economists also enter into SCM/Logistics or Inventory management using their knowledge of network models and game theory, etc.
Marginal Efficiency of Capital (English) via @YouTube
Macroeconomists normally only take monetary policy to be the end-all and be-all solution per se to increase or decrease capital formation.
MEF Marginal efficiency of capital - Mk is the microeconomic foundation of investment expenditure function, which is normally ignored by the high and mighty in the world of economic policymaking.
With all his faux pas and shortcomings. #Nixon was a great statesman and a natural diplomat.
He understood the world better than most of his predecessors.
After him, the USA has not been able to mimic another leader like him in the Oval Office.
I am not being satirical.
#Nixon and his #Domino Theory in Former French Indochina turned out to be quite right.
After the Americans left the region, both #Laos and #Cambodia fell into Communists hands.
South #Vietnam fell as well.
The remarkable resemblance with Modern Day #Afghanistan. #SVA#ANA
Many academic institutions are kinda confused when it comes to launching new degrees such as #FinTechs, Data Sciences, Business #Analytics, Machine Learning, Ai, etc.
There does not seem to be a standardized curriculum for such programs as we see in other academic disciplines.
Just combining courses from Maths, Statistics and Computer Sciences Faculty will not give you a Data Science Degree Program.
That is the mistake that universities're making at the moment.
Highly Amateurish.
The same mistake was made when business schools Physics,& Engineering Departments came together to launch applied Mathematical Degrees such as FE- Financial Engineering, etc. #Quant#Finance was probably the most sought-after degree before the #GFC and later the lies got exposed