See Figure 2.2 and examine the model.  Unlike other circular flow models, this model is missing another sector/s. what is the missing sector?

(e) Estimate the following model: In exports = Bo + B1 ln gdp_d + B2 ln dist_d + B3comlang + B4 (In dist_d x comlang) + u Calculate the marginal effect of distance on UK's exports. Interpret this result.

A static model is postulated when a change in the independent variable at time T is believed to have an effect on the dependent variable at period Da change in the independent variable at time t'is believed to have an effect on the dependent varlable for al successive time periods. Ca change in the independent variable at time tis telieved to have an immediate effect on the dependent variable. da change in the independent variable at time T does not have any effect on the dependent variable

question 8 macronecon

Suppose you have run four regression models: A, B, C, and D. You are going to make a decision on which one to use just based on the adjusted r² value. Here are the adjusted r² values for each model: A: 0.71 B: 0.57 C: 0.65 D: 0.76 Which regression model would you choose based on the adjusted r²? OD since it has the highest adjusted r² value B since it has the lowest adjusted r² OC since it has an adjusted r² between the adjusted r² of regressions B and D. Either B or C since they have the lowest adjusted r²

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 Multicollinearity and give a reason

Imagine you are trying to explain the effect of square footage on home sale prices in the United States. You collect a random sample of 100,000 homes that recently sold. a) Homes can be one of three types: single-family houses, townhomes, or condos. How would you control for a home’s type in a regression model? b) Write down a regression model that includes controls for home type, square footage, and number of bedrooms. c) How would you interpret the estimated coefficients for each of the variables from part b? Be specific. Note Don't forget to include dummy variables.

Can we compare the linear-log model and the log-log model? Which of the log regression models best fits the data?

Interpret this graph according to the theory of hecksher-ohlin model.

Q. Table provided gives data on gross domestic product (GDP) for the United States for the years 1959–2005. a. Plot the GDP data in current and constant (i.e., 2000) dollars against time. b. Letting Y denote GDP and X time (measured chronologically starting with 1 for 1959, 2 for 1960, through 47 for 2005), see if the following model fits the GDP data: Yt = β1 + β2 Xt + ut Estimate this model for both current and constant-dollar GDP. c. How would you interpret β2? d. If there is a difference between β2 estimated for current-dollar GDP and that estimated for constant-dollar GDP, what explains the difference? e. From your results what can you say about the nature of inflation in the United States over the sample period? Please answer c, d, and e. Thank you!