A researcher is interested in estimating the supply function of an online car rental service provider as a function of its average price (Price, measured by the averageper kilometre price charged for the month of October, 2017). He has data on the price charged and the number of cars available on the road for rent, (Car), for the 200cities in the U.S. in which the provider operates. However, given that there is simultaneous causality between Price and Car due to the interactions between demandand supply, the supply function cannot be estimated consistently by an OLS regression of Car on Price. He, therefore, uses Income (measured by the per capita GDPof a given city in the U.S. for 2017) as an instrument which satisfies the two conditions of instrument validity. He uses the two stage least squares (TSLS) estimator ofthe coefficient on Price which enables him to estimate the supply function.Suppose, the sample covariance between Car and Income, SCar, Income is 1.45, and the sample covariance between Price and Income, Sincome, Price is 2.45.A TSLSLet B1 be the population slope coefficient on price and Bibe the two stage least squares (TSLS) estimator of B1.TSLSThe value of ß,will be(Round your answer to two decimal places).

Given information: The response variable is price. The predictor variables are car and income.

Answered: A researcher is interested in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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2. Baldur is a big fan of salaries. He collects data on wages and the length of schooling the people had from 100 employees in a large company with the aim of creating a model that can predict wages by level of education (measured in the number of years in school after primary school). The employees with the lowest level of education in Baldur's data immediately entered the labor market after compulsory school leaving, while those with the highest level of education have completed 9 years of schooling after leaving compulsory school leaving. Baldur started by drawing the data and saw that the relationship is linear. He also calculated some fish sizes that can be seen below: standard Change average deviation salary 660020 150100 Education (year from primary school diploma) 5.5 2.2 He also calculated the correlation coefficient between salary and level of education (measured in the number of years in school from primary school exam) and obtained r = 0.55. a.) Find the equation regression…
2. Calculate indicators of Hospitalized incidence of diseases in a given country for the current year. • To evaluate indicators and analyze their dynamics (compare data for the current year with data for 2000). ● Compare indicators for a given country with those for the European Region. Present the estimated data graphically (build diagrams). Make a conclusion. Countries Spain European Region Data for the current year (absolute numbers) Number of Number of outpatients with outpatients with coronary artery vascular brain Population 46423064 disease 132848 Incidence 845.6 (per 100,000) damage 101341 Incidence 446,7 (per 100,000) 2000 year (per 100,000 population) Hospitalized Hospitalized incidence of incidence of coronary vascular artery disease 363.5 738.1 brain damage 213.2 379.3
Profitability remains a challenge for banks and thrifts with less than $2 billion of assets. The business problem facing a bank analyst relates to the factors that affect return on assets (ROA), an indicator of how profitable a company is relative to its total assets. Data collected from a sample of 20 community banks include the ROA (%), the efficiency ratio (%), as a measure of bank productivity (the lower the efficiency ratio, the better), and total risk-based capital (%), as a measure of capital adequacy. Complete parts (a) through (g) below. Click the icon to view the data table. a. State the multiple regression equation. Let X₁¡ represent the efficiency ratio (%) and let X₂¡ represent the total risk-based capital (%). Ŷ₁=+X₁₁+Xzi (Round the constant to two decimal places as needed. Round the coefficients to four decimal places as needed.) Distribution Costs ROA (%) 1.04 0.77 0.14 1.44 0.90 1.16 1.07 1.58 1.45 1.15 1.17 3.40 0.86 0.66 0.81 1.14 0.83 0.86 1.14 1.04 TOlal Efficiency…
By letting the GDP (gross domestic product) be the dependent variable (y), and the year (2002 - 2021) be the independent variable (x), answer the following questions: (a) Based on the line graph of the two countries, comment on the significant features from the graphs (identify any unusual points, if any, and observe the trend line). Compare the results of the GDP in these two countries. (Pls refer to the table and line graph in the image attached below) (b) Determine the correlation between the GDP and year, and develop the estimatedequation for Ethiopia and Germany. Refer to the summaryoutput of the two countries in the image attached below and interpret the coefficient for the independent variable. Determine whether the regression model is significant at 1% significance level. .
The Excel file (Forecasting Assignment Data) contains quarterly motorcycle shipments for Harley-Davidson from 2000 through 2006. Forecast Harley-Davidson quarterly motorcycle shipments for 2007 using 1) Holt’s Method 2) Winter’s Method 3) Linear Trend Model 4) Quadratic Trend Model 5) Quadratic Trend with Seasonal Indices Model In addition, make a recommendation of which forecasting method you think Harley-Davidson should use and why. Year Quarter Period DemandAt 2000 1 1 49,057 2 2 53,329 3 3 48,077 4 4 54,129 2001 1 5 54,154 2 6 60,161 3 7 56,611 4 8 63,535 2002 1 9 64,669 2 10 65,540 3 11 67,474 4 12 65,970 2003 1 13 70,608 2 14 76,025 3 15 67,458 4 16 77,056 2004 1 17 74,090 2 18 82,034 3 19 80,578 4 20 80,587 2005 1 21 76,716 2 22 77,128 3 23 87,585 4 24 87,588 2006 1 25 79,506 2 26 79,796 3 27 97,046 4 28 92,848
Suppose we obtain data on prices of big-screen televisions and estimate the following model: In(Price) = 4.06 + 0.06 * Size +0.23 * Wide + 0.34 * Plasma + 0.21 * LCD+0.09 * Memory where the dependent variable has been transformed, Size is the screen size measured in inches, Wide is a dummy variable equal to one if the television is a widescreen, Plasma is a dummy variable equal to one if the television is a Plasma screen, LCD is equal to one if the television is an LCD screen, and Memory is a dummy variable equal to one if the television has any memory card slots. What is the estimated price of a 42" Widescreen Plasma television with 2 memory card slots? Select one: O a. 7.24 O b. 7.33 1525.38 O d. 1394.09 • e 1881.83 Clear my choice
Students also often confuse the idea of Lurking Variable and Confounding Variable, but these are different but possibly related. This discussion is designed for students to help each other build a complete understanding, and clearly separate these as two distinct concepts. Discuss the similarities and differences between these, as well as what they imply for the conclusions of a research study.
(b) Table 1 shows consumables usage data from a leading manufacturer. Forecast the demand for August, September and October using: i) a three-month moving average ii) a four-month weighted moving average using 50 percent of the actual usage for the most recent month, 20 percent of two months ago, 15 percent of three months ago and 15 percent of four months ago. Using an example, explain what are the benefits of using the weighted moving average method of forecasting instead? Month February 2023 March 2023 April 2023 May 2023 June 2023 July 2023 Consumables Used 884 892 972 990 956 880
Research was conducted to find out the relationships between pro-environmental attitudes and 20 concepts of nature. As expected, the pro-environmental attitudes were related to several of the concepts of nature measured. One of the possible research objectives in this study is to assess the relationship between level of knowledge on nature or the environment (X), and the frequency of engaging in pro-environmental behavior (Y) per month, e.g., recycling and using biodegradable products. The data from your study (from 15 respondents) are as follows: ID Y XY y2 1 7 12 3 7 11 5 8 19 9 7 4 8. 11 9. 2 10 8 16 11 7 12 19 13 7 10 14 7 13 15 3 ТОTAL
Read the following excerpt of an article published on psychologytoday.com: “Researchers found that about 40% of college students in their study binge drink (i.e., consuming 5 or more drinks in a short amount of time) and that the vast majority of campus sexual assaults are fueled by alcohol.” Identify the variables of interest and indicate which the independent is and which the dependent variable is. Identify the classification of the independent variable (discrete or continuous) and explain the reason for your choice. Discuss what measure of central tendency is the most appropriate for each variable (independent and dependent variable) making sure to explain why.
Fish produce a hormone called isotocin, a hormone that is similar to oxytocin in mammals. Both hormones, oxytocin and isotocin, have been linked to social behaviors including the suppression of social anxiety, trust, and attachment. Prior to this study the relationship between isotocin in the bloodstream and the amount of aggression or submission individual cichlid fish display was unknown. The researchers hypothesized that isotocin would suppress aggressive behaviors in cichlids to promote social cohesion as these fish exist in large social groups (schools). To address this hypothesis each of 10 fish were exposed to two treatments 1 week apart. One at a time a fish was randomly selected from the group of 10 and either injected with a saline solution ( that served as the control) or with isotocin. After this injection the fish was returned to its group and the amount of aggressive and submissive behaviors the fish demonstrated was recorded for the next 10 minutes. One week later this…
Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin; - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team==== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1 80 Coef. Std. Err. MS 81 206.320988 8.439024 3.049595 -5.219512 2.156389 1459.95122 190.65061 t Number of obs F (1, 80) Prob > F R-squared. Adj R-squared = Root MSE P>|t| 2.77 0.007 -2.42 0.018 82 7.66 0.0070 0.0874 0.0760 13.808 [95% Conf. Interval]…

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