Which Program Would You Select Econometrics

[Gravity]

Which programs would you select if you were Planning on specializing in Econometrics during your PHD Programs. There are Two sequences give below for different Masters program, Which one do you think is better?

A

Advanced Econometrics 1: Important topics are (all exploiting matrix notation): basic regression and least-squares theory, asymptotics, heteroskedastic autoregressive and dynamic models, estimation and testing of non-linear models and panel data models, instrumental variables.
Advanced Econometrics 2: Important topics are: generalized method of moments, maximum likelihood, simultaneous equations, identification, testing overidentification restrictions, heteroskedasticity and autocorrelation consistent covariance estimation, logit probit and tobit models.
General Equilibrium Theory: Systematic development of general equilibrium theory with applications in macroeconomics and finance. Key topics include: competitive markets, general equilibrium, welfare analysis, Pareto efficiency, general equilibrium under uncertainty (insurance, investments, contingent contracts, options)
complete and incomplete markets overlapping generations models.
Financial Econometrics: Econometric analysis of mean-variance efficiency, the capital asset pricing model (CAPM) and arbitrage pricing theory (APT); Cointegration analysis, applied to present value models and exchange rates; ARCH en GARCH models; Multivariate volatility and correlation models, Econometric analysis of Value at Risk.
Micro-econometrics: Econometric Analysis of Cross Section and Panel Data
Stochastic Calculus: Discrete-time methods: binomial trees, the Cox-Ross- model continuous-time stochastic processes: Brownian motion, martingales, stochastic calculus: the Itô integral, Itô’s lemma, stochastic differential equations, Girsanov's theorem, equivalent martingale measures, risk-neutral valuation, the Black-Scholes-Merton model implementation of various numerical methods computer programs.
Macroeconomics: Monetary and Fiscal Policy
Industrial Organization Theory
Game Theory

B

Advanced Money, Credit and Banking: Management of financial institutions, in particular bank management; Information based approach to banking and insurance; Bank runs and systemic risk; Credit rationing ad delegated monitoring with adverse selection and moral hazard;Value at Risk and heavy tails.
Multivariate Statistics: Often there are many data available in marketing research. This course deals with various multivariate statistical techniques to summarise such data sets. Examples are: cluster analysis, principal components, canonical correlations, factor analysis, analysis of variance, discriminant analysis and multidimensional scaling. Students use statistical software to analyse real-life data. Some techniques result in graphical representations of the data, which are useful for interpretation.
Advanced Econometrics: The course deals with topics in advanced econometrics. In the first part of the course the econometrics of dynamic models for panel data are covered. Panel data are data collected by observing a number of individuals over time. As second topic several simulation techniques, like the well-known Markov Chain Monte Carlo and Importance Sampling methods, are treated. The panel data models and the simulation techniques allow econometric analysis of international and financial markets as well as analysis of choice processes in the field of marketing. Practical examples and short assignments are intended to help students in their study of the topics of the course.
Marketing Models: Individuals or households can choose to respond or not to a direct mailing, or they can choose between various brands. This course deals with econometric models for these qualitative variables. Examples of these models are the logit and probit models for binomial data and multinomial data. Also, ordered data, like those evolving from questionnaires, will be considered. The focus is on representation, interpretation, parameter estimation and extensions.
Bayesian Econometrics: The course starts with a discussion on the difference between Bayesian and frequentist statistical analysis. Next, we consider Bayesian parameter estimation, forecasting and Bayesian testing. To perform a Bayesian analysis, knowledge of advanced simulation methods is necessary. Part of the course is devoted to Markov Chain Monte Carlo sampling methods including Gibbs sampling, data augmentation and Monte Carlo integration. In the first part of the course we consider univariate models. In the second part we consider multivariate models. The course ends with a discussion of Hierarchical Bayes techniques.
Advanced Time Series Analysis
Case-studies in Applied Econometrics
Option Pricing and Hedging
Financial Econometrics
Portfolio Management
Financial Risk Management

[notacolour]

Not at all surprisingly, everyone's voting for A, which looks much more mathematically and theoretically rigorous, and much better preparation for a PhD.

[Gravity]

OK.... That was a complete blow out. Testmagic is the best. At the end A admitted me
Amsterdam here I come... Well B sent me a letter of rejection (Erasmus) that my degree wasn't in par with their bachelors in Econometrics program.

[notacolour]

Congrats!

Curiosity again: how much will that program cost you?

[Gravity]

9000 euros a year. Still selling my stuffs to catch up,if I don't before June, Then I guess, I find a Job back home.

[notacolour]

Good luck with that. Are loans an option for you?

[Gravity]

I don't think so.

[Pentangling]

Clicked on A by mistake but wanted to point out I will choose B, since it is just a masters degree.

[tad]

There's something magical about A.

[Gravity]

What is that?