A researcher investigating the factors related to a country's economic growth between 2005 and 2010estimates the following model for a sample of countries (using cross sectional data):GROWTH = a + b × GDPH2005 + cx INV + d x EDUC + ex RIGHTS + fx ELECwhere:GROWTH is the country's economic growth (percent change of GDP per person at constant pricesbetween 2005 and 2010);GDPH2005 is the log of the country's level of GDP per person in 2005 (US$ at 2005 prices);INV is the country's share of gross investment in fixed capital (Gross Fixed Capital Formation) as apercentage of GDP in 2005;EDUC is an indicator of the level of education of the population (total enrolment in secondary schools asa % of population aged 15 and over);RIGHTS is an indicator of the strength of legal rights (0=weak to 12-strong);ELEC is the percentage of population who have access to electricity;The results of the estimation are:VariablesGDPH2005INVEDUCRIGHTSELECConstantINVRIGHTSELECEDUCCoefficientsGDPH2005Choose...Choose...TrueFalse-0.1322Choose...0.01290.0036-0.00100.00340.6751Choose... VStandardErrorsChoose... V0.01700.00310.00130.00910.00100.1139t-values-7.76004.19002.8000-0.1100From the dropdowns select True for the variables that, according to the model's results (using a 5%significance level), are positively associated with economic growth for the countries and the time periodcovered by the data. For those that are not, select False.3.58005.9300p-values0.00000.00000.00600.91200.00100.0000

A researcher investigating the factors related to a country's economic growth between 2005 and 2010…

Answered: A researcher investigating the factors…

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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Data concerning the expenditure for health care in the United States is shown in the table. Year 2000 2004 2005 2007 2008 2009 2012 2013 2015 Expenditure (billions $) 1359 1878 2016 2320 2498 2689 3298 3533 4032 a. Make a graph of the data large enough to include 2018 (use graph paper, label completely, and choose the correct axis for the independent (x) and dependent (y) variables). b. Find the growth rate (b) between 2004 and 2005, rounded to 3 decimal places. c. Find the growth rate (b) between 2012 and 2015, rounded to 3 decimal places. Hint: the years are not consecutive so you will need to substitute the numbers you know into the equation y = ab* and solve for b. d. Add a trend line and estimate the expenditure you would expect in 2018. billion e. Use your trend line to estimate the year the US health expenditure reached $3000 billion.
The Federal Bureau of Investigation (FBI), as part of its internal security mission, serves as a database for all the reported crimes committed in the United States. One question that might be of interest is does having more police officers reduce the number of homicides? To investigate this claim, the 2013 data from the twenty largest municipal cities was supplied by the FBI's Uniform Crime Report. Below are two observations from the dataset: > head (cities) City Pop Homicides Police Density MedHome Mayor 1 New York 8175.133 335 4.2595 27016.30 5.5390 1 2 Chicago 2695.598 414 4.4309 11843.58 1.8310 The variables included in the study are: Name of city Population of city in 1,000s of people Number of homicides in the year 2013 Number of police officers per 1,000 people Number of people per square mile Median home price in $100,000 1 if city has a "Strong Mayor" form of government; 0 if not City Рор Homicides Police Density MedHome Мayor Model: log(u;) = Bo + B1Police; + B2MedHome; +…
By what percentage is salary predicted to increase if ros increases by 50 points? Does ros have a practically large effect on salary?
Population Growth in Central and Eastern European Cities city Berlin Vienna Kiev Budapest Istanbul Berlin Vienna Kiev Budapest Istanbul 1870 826,000 834,000 127,000 320,000 531,000 Berlin Vienna Kiev Population Budapest Istanbul 1910 2.071 million 2.031 million 323,000 880,000 782,000 The table above gives historical population statistics for five cities in Central and Eastern Europe. For each city calculate the rate of population growth (k) from 1870 to 1910. We'll call this k, and enter it in the table below. Which city grew the fastest? Which grew the slowest? City k, (1870-1910) fast/slow k₂ (1950-1989) 1950 3.337 million 1.616 million 1.104 million 1.571 million 1.179 million Finally, use your values for k₂ to estimate the current population of each city. City Current Population (est.) 1989 3.353 million 1.488 million 2.587 million 2.114 million 5.843 million Next, calculate k₂ - the value of k from 1950 to 1989-for each city. Compare your values of k₂ with your values for k₁. For…
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This shows log GDP per capita for the UK. Which of the following statements are correct? Select one or more: a. The graph shows that in 1950 UK GDP per capita was about £8.75. b. The trend growth rate over the period was 0.9889% per annum. c. When actual output is below trend output the economy is in recession. d. The trend growth rate over the period was 2.14 % per annum.
Scenario: A researcher wants to determine whether the volume of orders placed, in thousands, can predict whether an entry error was committed (yes or no). Which research analysis is most appropriate? Group of answer choices a. ANOVA b. Binary Logistic Regression c. Chi-square Contingency Table d. Non-parametric e. Regression
Part D. Data from the Statistical Abstract of the United States provides a panel data collected at the state level in 1987 and 1990. These data are used to estimate MODEL 1: The variables used in the analysis are: infmort is number of deaths within the year per 1,000 live births Ipcinc is natural log of per capita income Ipopul is natural log of the population (the population is in thousands) Iphysic is natural log of physicians per 100,000 inhabitants d90 is year dummy for 1990. For questions 1 to 4 you can assume that MLR 1-4 are satisfied. A 1. Use the Stata output below to interpret ß3. Test at a 5% significance level whether the number of physicians per capita has any effect on infant mortality rate. reg infmort 1pcinc 1popul 1physic d90 Source Model Residual Total infmort infmort = Po + B₁lpcinc + B₂lpopul + ß3lphysic + 8₁ d90 + u SS 78.0499129 350.452136 428.502049 df . 19.5124782 4 97 3.61290862 Coef. Std. Err. MS 101 4.24259454 1pcinc -4.693354 1.638132 1popul - .0551426…
A 18.2% B 15.7% C 22.2% D 4.4%

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