The table shows the yield (in bushels per acre) and the total production (in millions of bushels) for corn in a country for selected years since 1950. Let x represent years since 1900. Find a logarithmic regression model (y = a +b In x) for the yield. Estimate the yield in 2029. The regression model is y=+)In x. (Round to one decimal place as needed.) Year 1950 X 50 60 70 1960 1970 1980 1990 2000 100 2010 110 80 90 Yield 41 54 85 96 110 146 158

The table shows the yield (in bushels per acre) and the total production (in millions of bushels) for corn in a country for selected years since 1950. Let x represent years since 1900. Find a logarithmic regression model (y = a +b In x) for the yield. Estimate the yield in 2029. The regression model is y=+)In x. (Round to one decimal place as needed.) Year 1950 X 50 60 70 1960 1970 1980 1990 2000 100 2010 110 80 90 Yield 41 54 85 96 110 146 158

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Imagine you are an economist working for the Government of Econville. You are tasked with developing a model to predict the GDP of the country based on various factors such as interest rates, inflation, unemployment rate, and population growth. You collect quarterly data for the past 20 years and start building your model. After running your initial regression, you notice some peculiar patterns in the residuals: (1) residuals do not have identical variances across different levels of the independent variables; (2) two or more independent variables in a regression model are highly correlated with each other; (3) the correlation of a variable with its own past values. You suspect that your model might be suffering from 3 potential issues in the regression analysis that can affect reliability and validity. what are the implications of Heteroscedasticity if this potential issue in your model?
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Imagine you are an economist working for the Government of Econville. You are tasked with developing a model to predict the GDP of the country based on various factors such as interest rates, inflation, unemployment rate, and population growth. You collect quarterly data for the past 20 years and start building your model. After running your initial regression, you notice some peculiar patterns in the residuals: (1) residuals do not have identical variances across different levels of the independent variables; (2) two or more independent variables in a regression model are highly correlated with each other; (3) the correlation of a variable with its own past values. You suspect that your model might be suffering from 3 potential issues in the regression analysis that can affect reliability and validity. List 2 factors in your model that might be causing the Heteroscedasticity and give a reason
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