Econometrics Analysis

Hi, I am an econometric analysis of the attached table. The variables are as follows: • HK: School enrollment, secondary (% gross) • Population growth (% annual) • GDP growth (% annual) • Institutional... kindly discuss details regards Rashid.

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hii there, First Analysis of your given data given table show the regression analysis with dependable variable LNGDP which shows that when we increase our data by one unit our variable C decreases by -3.4338 where LOPEN gives highest increase of 0.9701 r square show that our result is accurate upto 37.87% times which can be considered good with small sample. Accordingly i can explain std deviation t-value and other variable I am an MBA having an excellent knowledge of data analysis. I can complete your econometric analysis in lesser time provided I get all the important information. with proper information I can do economic Analysis, economic forecasting, regression analysis with multiple variables as well as trends analysis in economic forecasting, with deriving serial correction of data. just give me a chance and I know that I can provide you best drafted economic report with excellent analysis of data.

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Hi. I have done many similar econometric analyses as a PhD in Economics. I will do my best to provide the highest quality results.

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Hello, I submit myself for consideration for the Econometrics analysis task. I have an extensive grounding in statistics with a deep understanding of the financial and economics world. This depth and breadth of understanding should come in handy in ensuring a holistic delivery of the task at hand. In the attached snapshot of the econometric model, the variables have been fitted to help test whether they can fit the model. The p-values are a test of relevance of the variables in the model with a p-value if less than 0.05 denoting that the variable is significant in the model ie that it cannot be zero. The R-squared shows how good is the fit of the model (how much of the dependent variable can be explained by the model fitted). In this case the R-squared looks relatively low with a few tweaks needed to have a better fitting model. Thanks. Alvin

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- Regarding your model : model explanatory power is low several of the t stats indicate perhaps redundant vars or correlated vars. Its hard to completely understand the theoretical construct without a clearer understanding of the vars On the face of it the structure of the model need relooking at.