Econometrics Tutors for all levels 2017-05-28T14:19:55+00:00

UK University Lecturers, Examiners & academics with a mandatory teaching, marking or supervisory experience.

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Teaching all topics in Econometrics (please scroll down)

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    • 100% Pass rate; 85% students secure a 1st/ Distinction at UG and PG level
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    • 93% successful Masters and PhD proposals
  • Face-to-Face and Online sessions: UK Lecturers, Professors and world class academics for UK and International clients
  • 1:1 guidance from Britain’s top 5% academics in Econometrics: Professors, Lecturers, PhDs, and researchers with extensive teaching and lecturing experience from leading UK universities such as UCL, Imperial, KCL, LSE, LBS, Oxbridge and many more

We cover all topics in Econometrics

Introduction to econometric models and techniques |advanced econometrics | Principles of Estimation | Ordinary Least Squares, Generalized Least Squares and Maximum Likelihood Estimation with Micro-Econometric applications | Principles of Testing (t- and F-test; Wald, Likelihood Ratio, Lagrange Multiplier Testing Principles) | Time Series: Basic Time Series Processes; Stationarity and Nonstationarity – Unit roots and Cointegration| Estimation Methodology; Endogeneity in linear regression models | Instruments | 2SLS estimator and Generalized IV estimator | Simultaneous equations | Motivation, definition and asymptotic properties of GMM estimator | Efficient GMM estimation | Over-identifying restrictions | Introduction to Panel Data Models: Fixed effect and random effect models | Arellano-Bond estimator in dynamic panel data models | Introduction to Quantile estimation |simultaneous equations | program evaluation | emphasizing regression | instrumental variables | panel data methods |measurement error | limited dependent variable model | Time-series econometrics | stationary and non-stationary stochastic processes | linear autoregressive and moving average models | linear difference equations | autoregressive distributed lag models | cointegration and equilibrium correction | vector autoregressive models | Cross Section Econometrics | Mathematical Methods in Economic Analysis | Financial Econometrics | Applied Macroeconometrics | Pre-Sessional Maths | Econometric Methods | Microeconomic | Theory | Macroeconomic Theory | Industrialisation in Developing Countries statistical inference| regression| generalized least squares | instrumental variables | simultaneous equations models | Review of probability and statistics; Probability and distribution, Expectation and moments, Review of statistical inference, Sampling distributions and inference, The Central Limit theorem (Asymptotic distribution of the sample mean), Confidence intervals, Regression basics | Conditional expectation functions, bivariate regression | Sampling distribution of regression estimates; Gauss-Markov theorem | How classical assumptions are used; asymptotic distribution of the sample slope | Residuals, fitted values, and goodness of fit | Multivariate regression | Regression, causality, and control; anatomy of multivariate regression coefficients | Omitted variables formula, short vs. long regressions | Dummy variables and interactions; testing linear restrictions using F-tests | Regression analysis of natural experiments, differences-in-differences | Inference problems – heteroscedasticity and autocorrelation | Heteroscedasticity, consequences of; weighted least squares; the linear probability model | Serial correlation in time series, consequences of; quasi-differencing; common-factor restriction; Durbin-Watson test for serial correlation | Instrumental variables, simultaneous equations models, measurement error | Using IV to solve omitted-variables problems | Measurement error (Time-permitting) | Regression-discontinuity designs (Time-permitting) | Simultaneous equation models | Simultaneous equations models I; The use of structural models, Simultaneous equations bias, the identification problem, The structure and the reduced form, Indirect least squares | Simultaneous equations models II; IV for the SEM, Two-stage least squares, Sampling variance of 2SLS estimates | parametric asymptotic theory | M and Z estimators | nonlinear least squares | nonlinear instrumental variables estimators | Model selection test | Consistent model selection criteria | Nonnested hypothesis testing | Markov chain Monte Carlo methods | Asymptotic hypothesis testing procedures derived for each estimation framework

Our tutoring approach

Our Econometrics tutors develop a student-centred programme for each student. This programme will define and cover the tuition goals and objectives through an Individualised-Lesson Plan.

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