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Explain "Okun's Law" by using data and draw a scatter diagram?
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- ← Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values: Price $2.50 $3.50 $1.90 $4.20 $3.20 $4.10 Number Sold 760 515 980 250 320 490 D Using simple linear regression and given that the price per cup is $1.75, the forecasted demand for mocha latte coffees will be 1862.8 cups (enter your response rounded to one decimal place). 88Use a software of your own choice to calculate the daily log prices (lp) and daily log returns (Ir) i. Examine the descriptive statistics of both lp and Ir. What do you conclude about the distributions of lp and Ir? Is lp normally distributed? Is Ir normally distributed? Obtain the correlograms, and examine the autocorrelations and partial autocorrelations for both lp and Ir. What do you conclude about the behaviour of lp and Ir? Are they stationary/non-stationary? ii. iii. Are your conclusions about stationary/non-stationary of lp and lr confirmed by appropriate unit root tests?The world's population living in extreme poverty has declined linearly between the years 2005 and 2011. In 2005, the percentage of the world's population living in extreme poverty was 20.70% and in 2011, the percentage of the world's population living in extreme poverty was 13.70%. Determine a linear equation that models the world's population in extreme poverty, in percentage, as a function of years since 2005. What is the slope of this function, and what does it tell you in practical terms? Round your answer to the nearest hundredth (0.01). Om = -7.00. The world's population in extreme poverty decreased by 7 percent per year between the years 2005 and 2011. Om = 7.00. The world's population in extreme poverty increased by 7 percent per year between the years 2005 and 2011. Om = 1.17. The world's population in extreme poverty increased by 1.17 percent per year between the years 2005 and 2011. Om = -1.17. The world's population in extreme poverty decreased by 1.17 percent per year…
- Find the area under the standard normal curve to the left of z=0.21�=0.21. Round your answer to four decimal places, if necessary.Using the data in the worksheet "HoneyData" create a correlation table using the Analysis Toolpack in Excel. Using this information, answer the following questions and round your numeric answer to 2 decimal places. The correlation between Production and Average Price is: This means that honey Production and Average Price are negatively/positively correlated. An Increase in Production is associated with an increase/decrease in Average Prices.Econometrics Thomas Eisensee and David Stromberg wanted to measure how much news coverage of a foreign disaster impacted the amount of disaster relief provided by the U.S. government. They argue that the simple relationship would be biased. Let X = Minutes of News Coverage and Y= Disaster Aid. Choose a variable X2 that could bias the simple relationship. This variable should impact the amount of coverage and impact the amount of aid for reasons other than purely news coverage. Eisensee and Stromberg introduce an instrument Z = During the Olympics. Explain how Z could satisfy the relevant and exogenous criteria. Explain how you could use Z to estimate the impact of X on Y free from X2 bias. Hint: you should mention two stages.
- 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 es3mated coefficients for each of the variables from part b? Be specific.In your company (electrical goods manufacturing), you want to forecast demand as well of a particular range of Smart TVs. Its monthly sales previous year, are presented in the table below: Month Sales January 400 February 650 March 1,150 April 1,700 May 500 June 900 July 1,150 August 1900 September 600 October 650 November 1,600 December 2050 Based on the above historical sales data: A) Create the corresponding graph and comment on the demand (sales) in terms of in trend, seasonality and periodicity please draw the diagram!!!!Given the following data table: X Y 21 68 72 55 38 59 57 57 45 61 What is the correlation between X and Y? Include 3 decimal places in your answer.
- What is a linear regression model? What is measured by the coefficients ofa linear regression model? What is the ordinary least squares estimator?Please fill out the blank a-dReal-Time Data Analysis Exercise Use the links in the table below to access the data series on FRED used in this exercise*. Then use that data to answer the following questions. 1 *Real-time data provided by Federal Reserve Economic Data (FRED), Federal Reserve Bank of Saint Louis. For this exercise you will need to enter data from FRED for Gross Domestic Product (GDP) and Gross National Product (GNP). Using the data from FRED, enter the values for the third quarter of 2020 (shown as 2020 – 07 - 01 in FRED) for the following series IDs. (Enter your answers exactly as they appear on FRED.) Title Series ID Value Gross Domestic Product GDP $ billion Gross National Product GNP $ billion
