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Most of our students are from Columbia, NYU, Yale, Princeton, UPenn, Brown, Stanford, LSE, Kings, UCL, and Oxford Universities. We recruit top tutors from the best economics programs to tutor our high achieving students. Course curriculums for econometrics, microeconomics, and macroeconomics at top schools are remarkably more difficult than an average university. We are very well aware of this so we hire our tutors from top universities with in-class teaching experience.
Demand and Supply
Price, Income and Cross-Price Elasticities
Price Ceilings and Price Floors
Consumer and Producer Surplus
Tax and Subsidies
Burden of Tax and Relative Elasticity
Utility and Preferences
Indifference Curves and their axioms
Budget constraint
Marginal Rate of Substitution
Utility Maximization
Lagrange Multiplier approach to maximization
Income and Substitution Effect
The Slutsky Decomposition
Deriving Hicksian and Marshallian Demands
Deriving a Demand Curve
Firms optimization problem
Production function and cost constraints
Profit Maximization for firms
Deriving Total Cost and Marginal Cost
Profit Maximization for a perfectly competitive firm
Monopoly, Oligopoly, Cournot Duopoly, Stackleberg Model, and Bertrand Competition
Game Theory and Nash Equilibrium
General Equilibrium and Pareto Optimality
GDP and Circular Flow of Income
Real vs Nominal GDP
Consumer Price Index
Factors of Production and the Production Function
Consumption, Income, Investment and Government Spending
Functions and Type of Money
The Role of the Federal Reserve
Monetary Policy and the role of interest rate
The Nominal Interest rate and the Demand for Money
The International Flow of Capital and Goods
Savings and Investment in an Open Economy
Unemployment and the Labor Market
Solow Growth Model and Steady State Equilibrium
The Golden Rule Level of Consumption and Capital
Endogenous Growth Theory
Aggregate Demand and Aggregate Supply
IS-LM Model
The Mundell-Fleming Model
Inflation, Unemployment and the Phillips Curve
Automatic Stabilization Policies
Government Debt and Budget Deficit
Economic Growth and Development Economics
Understanding mean, variance, standard deviation, expected value
Understanding of hypothesis tests: setting up null vs alternate
Understanding Z-score, t-tests, and p-value
Application of alpha level and confidence intervals
Understanding of Chi squared distribution and F-distribution
Correlation vs causation
Nature of data and the need for best fit line/regression line
Terminology and notation
Concept of population regression function
Introduction to the idea of residuals and residual sum of squares (RSS)
Least Squares regression as the minimizing of RSS
Conceptual understanding and interpretation of regression slope and intercept coefficients
Gauss Markov properties of Best Linear Unbiased Estimator
Coefficient of Determination and R squared
Probability distribution of the disturbance term
Normality of residuals
Zero covariance between residuals and explanatory variables
Assumption of constant variance of residuals or homoscedasticity
Probability distribution of the disturbance term
Normality of residuals
Zero covariance between residuals and explanatory variables
Assumption of constant variance of residuals or homoscedasticity
Checking the goodness of fit or R-squared
F-test as the joint hypothesis test for the regression model
Individual t-tests or hypothesis tests for statistical significance of coefficients
Normality of residuals
Checking for heteroscedasticity
Meaning and interpretation of partial regression coefficients
R squared meaning and interpretation with multiple explanatory variables
Issue of multicollinearity
Variance of regression coefficients and the impact on statistical significance
Nature of binary/dummy variables
Dummy variable trap
Use of dummy variables in Chow test for structural change
Piecewise linear regression with dummy variables
Interaction variables and intercept dummies
Issue of heteroscedasticity
OLS remains unbiased but the variance is no longer the minimum variance
Detection of heteroscedasticity with graphical method using scatterplots as well as formal tests
1. Park’s Test
2. Glesjer test
3. Breusch-Pagan hettest
4. White’s test
Fixing for heteroscedasticity using weighted least squares or using White’s robust standard errors
Issue of autocorrelation in residuals
OLS is still unbiased but minimum is no longer minimum variance
Graphical detection through scatterplot of residuals
Runs test
Durbin Watson Test and its limitations
Breusch-Godfrey test for autocorrelation
Lagrange multiplier test
Newey west standard errors to fix the issue of autocorrelation
Logit
Probit
