56:26
110 #Introduction to #Econometrics: Lecture 1
RESEARCH MADE EASY WITH HIMMY KHAN
43:22
116 Hypothesis Testing: F Test, Testing Omitted and Irrelevant Variables
50:46
111 Simple Regression Model: Specification and Estimation_Lecture II
52:09
112 The Classical Linear Regression Model with Himmy Khan
5:20
113 Derivation of the Least squares Estimators Lecture IV
32:54
114 Testing of Hypothesis & Confidence Interval: Lecture V
33:02
115 #Intorduction to #Econometrics: Lecture VI_Multiple Regression Model and Goodness of Fit
41:18
117 Introduction to Econometrics Lecture VIII Regression without Constant and Changing Scales and Un
44:06
118 Applications of Dummy Independent Variables
43:03
119 Introduction to Econometrics Lecture 10 Multicollinearity
40:39
120 Introduction to Econometrics Lecture X1 Autocorrelation
37:04
121 Introduction to #Econometrics: Lecture XII Heteroskedasticity
34:05
122 Introduction to Econometrics Lecture XIV Review of Basic Statistical Concepts
29:16
123 Introduction to Econometrics: (Lecture XV) Non-Linear Relationships in Econometric Models
30:27
124 Introduction to Econometrics Lecture XVI Dynamic Models, Autocorrelation and Forecasting
35:07
125 Introduction to Econometrics: Lecture XVII - Simultaneous Equations mosels
17:58
126 Introduction to Econometrics Lecture XVIII Simultaneous Equations Models 2
23:59
127 Introduction to Econometrics Lecture 19 Seemingly Unrelated Regression Equations Models
33:17
129 Simultaneous Equations Model Estimation Part 2 in STATA
16:22
130 How to Write Empirical Research Report?
7:15
203 Why Study Econometrics?
11:39
199 Error Terms in Econometrics
9:07
195 Introduction to Applied Econometrics Difference Equations
14:37
180 What is Econometrics? An Introduction for the beginners in Urdu/Hindi
14:44
179 What Types of Hats Do Econometricians Wear?
12:32
171 Simple and Multiple Linear Regressions Through the Origin: Some Issues and Consequences
36:13
165 What if Your Estimated Model has a Serious Econometric Issue?
9:25
204 Simple Linear Regression and OSL
9:57
205 Some Algebraic Properties of OLS
11:31
206 Multiple Regression Analysis
13:00
207 Multiple Regression Analysis: Inference
10:21
208 Asymptotic Properties and Multiple Regression Analysis
12:50
209 Multiple Regression Analysis and Some Issues relating to it
14:00
211 Heteroskedasticity Issues and Remedies
11:37
212 Specification Errors and Data Issues
11:11
213 Ramsey's RESET Test for Omitted Variables in Regression Model
14:40
214 RESET Test in EViews
12:51
215: Detrending and Seasonality Issues in Time Series Data
10:50
216 Simultaeous Equatios Models
8:01
217 Stationary Stochastic Process
7:40
218 Testing for AR1 and Higher Order Serial Correlation
8:25
219 Panel Data Methods
5:52
220 Fixed effects Vs Random Effects Estimation
12:21
222 Models Using Limited Dependent Variables
7:00
263 What is Spurious Regression?
12:53
295 How To Create Dummy Variables in STATA
11:33
296 How does change in units of measurement affect regression results
11:44
297 An Illustrative Example of Regression of Food on Total Expenditure
13:35
298 How to Measure Growth Rate of Economic Variables in Stata?
10:46
300 How to Estimate Linear Trend Models to Measure Growth Rate
9:44
301 Estimating the Lin Log Model to Verify the Engel Expenditure Curve
10:51
302 Estimation and Interpretation of Reciprocal Models in Stata
12:34
303 Panel Data Regression Models in Stata Fixed vs Random Effects
13:52
304 More Guns Less Crimes Application of Panel Regression Models in Stata
13:34
305 The Simplest Interpretation and Comparision of Panel Analytic Models
12:58
306 Using eststo and esttab commands to export Stata Output to Word and Excel
307 The One-way and Two-way error Component Panel Regression Models
11:56
309 Comparing OLS, Xtreg, FE and Areg Panel Models in Stata The Case of Public Capital Productivity
11:23
310 Diagnostic Tests for Estimated Panel Regression Models in Stata The Case of Public Capital Produ
13:08
311 Detecting and Correcting Heteroskedasticity in OLS
11:26
312 Detecting Heteroscedasticity using White Test and Breusch Pagan Test in Stata
12:22
313 Binary Logistic Regression Analytic Theory
314 Qualitative Response Models: LPM, Logit and Probit Analysis
15:02
315 Forecasting with Logistic Regression Models
316 Predicting Probabilities: The Most Difficult Tasks that Stata Can Do
12:15
317 Multinomial Logistic Regression: Estimation and Interpretation
13:49
318 How to fix endogeneity issue in OLS regression? (2SLS & IV Approaches)
12:26
320 Basic Estimation of Time Series Models in EViews
10:19
321 |Stationary| and |non Stationary| |Time Series| |Theory|
12:41
322 Testing |Stationarity| of |Time Series| using |ADF Test| in |EViews|
14:01
323 Comparing |ADF|, |PP| and |KPSS| |Unit Root| |Test| Results in |EViews|
324: How to |Conduct||Unit Root| |Tests| for all the |Variables| at the |Same| |Time| in |Eviews|?
9:19
325 How to Check |Unit Roots| with |Breakpoints| in |Eviews|?
14:42
|326| Estimation of |ARDL| |Model| in |EViews|: |An| |Interpretation|
8:49
327 |Method| |Selection| for|Time Series| |Data Analysis|
13:21
328 |Basic| |Time Series| |Analysis| and |Forecasting|
13:17
329 |Autoregressive Models| |Part 1|
12:01
330 |Autoregressive| |Models| |Part 2|
11:08
331 |ARCH| and |GARCH| Models|: Theory| and |Interpretation|
13:51
|332| Detection of |ARCH| using the |ARCH LM| test in |Eviews|
11:52
333 ARIMA Model Forecast and Estimation in Eviews
14:09
334 |Static| and |Dynamic| Forecasting - |Part 1|
9:08
335 |Static| and |Dynamic| |Forecasting| (Part 2)
336 |Forecasting| with |Auto| |Series| in |E-views|
10:24
337 |Volatility| Models and |Modelling| |Volatility|
12:11
338 Introduction to ARCH GARCH EGARCH TARCH PARCH models Part 1
14:15
339 Estimation of |ARCH| |GARCH| |TARCH |PARCH| |FIGARCH| and |FIEGARCH| Models - Part 2
12:29
340 |MIDAS| Regression |Estimation| and |Forecasting|
4:47
341 Introduction to MIDAS Regression Analysis
342 Detecting Outliers and Diagnostic Tests for an Ideal Regression Model in Eviews
10:18
343 Seasonal Adjustment and Detecting Seasonality in time series using Eviews
Video # || 356 || Automatic Model Selection || Using Simulated Data in Eviews
Video No. || 358 || Introduction to Vector Auto-regression (VARs)
