Question

In: Math

Regression model: Population=f(GDP,GNI,PPI,policy) How to collect data for dummy variable( policy )and determine its influence on...

Regression model: Population=f(GDP,GNI,PPI,policy)
How to collect data for dummy variable( policy )and determine its influence on population?

Solutions

Expert Solution

Dummy variable takes on the values 0 and 1 and divides the data in mutually exclusive. These variable are qualitative in nature. For example, D is a dummy variable which takes value D =1 if person is male and D=0 if person is female.

Population = f( GDP, GNI,NNI,policy) is the regression model.

Data on Policy

I assume the policy is mainly concern with the economic policy of a given state/province/country. So dummy variable of a particular policy (i.e fiscal policy or monetary policy) proposed for a given province/country present or not.

Let's take a simple example.

Let country A has Fiscal deficit of 3.1 % of GDP in the year 2017-2018. The government proposes a fiscal policy to reduce its fiscal deficit to 3% of GDP for the year 2018-2019.

country B has Fiscal deficit of 2.8 % of GDP in the year 2017-2018. The government proposes a fiscal policy to reduce its fiscal deficit to 2.6% of GDP for the year 2018-1019.

and so on we have other countries with their fiscal deficit

Then, we can define a dummy variable D,

D=1, Country with a fiscal deficit of 4% of GDP or less

D=0, Country with a fiscal deficit of 4% of GDP or less

You can find data for the policy from the budget of the given year/period of given state/province/country/required area. The fiscal deficit is one example. Other examples are in interest rates set by the government or repo rate by the central bank of the country.

Influence of policy on population

Economic policy depends on population.

Let's say area with large population leads to an increase in GDP due to large labor force. This will help the government to formulate economic policy for the next fiscal year.

However, population growth is not always related to economic growth. Above is just one of the scenario.


Related Solutions

Explain in full how you will use a dummy variable regression to test for a structural...
Explain in full how you will use a dummy variable regression to test for a structural break. Also discuss the advantages of using a dummy variable regression over the Chow test when testing for structural break in data.
To establish the impact of population of GDP, you collect quarterly data on the two variables...
To establish the impact of population of GDP, you collect quarterly data on the two variables from the period 1980 to 2016 and obtain the following values; i=1nyi2=54163.6 ;       i=1nxi2=59.225 ; i=1nxiyi=-1491.885 ;             i=1nYi=6278; i=1nXi=199.5;    i=1nYi2=3995492;    i=1nXi2=4039.25; i=1nXiYi=111756 Using these values, you estimate the model; GDPi=β0+β1Populationi+Ui Based on the above model, derive the parameters using OLS.          [6 Marks] Using the data above, compute the estimates β0 and β1 and provide and economic interpretation.                                                                      [6 Marks       
Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data.
Quarter Year 1 Year 2 Year 3 1 3 6 8 2 2 4 8 3 4 7 9 4 6 9 11 (b) Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise. If required, round your answers to three decimal places. For...
In this project, you will collect data from real world to construct a multiple regression model....
In this project, you will collect data from real world to construct a multiple regression model. The resulting model will be used for a prediction purpose. For example, suppose you are interested in “sales price of houses”. In a multiple regression model, this is called a “response variable”. There are many important factors that affect the prices of houses. Those factors include size (square feet), number of bedrooms, number of baths, age of the house, distance to a major grocery...
Collect annual Data on the following series: real GDP, Government Expenditure, Investment, and Population for 30...
Collect annual Data on the following series: real GDP, Government Expenditure, Investment, and Population for 30 years from an economy of Norway in "Current US dollar, all units and year must be same ' in excel file https://fred.stlouisfed.org/
Choose or collect a data file, use regression theory to set up a model, calculate parameters...
Choose or collect a data file, use regression theory to set up a model, calculate parameters value, get the regression model, analysis the meaning of model, including R square, F-test, t-test, explain the relation between dependent variable and independent variables. During the analysis, you need to represent the chart, correlation, regression output table. You’d better choose the multiple regression model, preferably one that includes dummy variables.
Using the GDP Data do the following: Generate the best fit model (regression) Generate the specific...
Using the GDP Data do the following: Generate the best fit model (regression) Generate the specific regression form Explain any dummy variables created Explain any time variables created Discuss the significance of all variables Generate and discuss the residual plot GDP C I G 822.2 625.7 93.6 110.1 751.5 592.3 62.5 121.3 703.6 574.3 39.2 126.6 611.8 523.0 11.8 122.4 603.3 511.0 17.5 118.0 668.3 546.9 31.6 133.0 728.3 580.6 58.4 137.0 822.5 639.6 74.9 158.9 865.8 663.5 93.6 153.2...
Use the following data related to the same population and determine if the selected independent variable...
Use the following data related to the same population and determine if the selected independent variable is affecting the dependent variable. Variable (27,29,32,31,26,25) Use an alpha of 5% for ANOVA and Correlation Coefficient. Use excel for the results. Explain the outcome. Data Sample: 30, 27, 24, 21,27,32 25, 21, 22, 28, 30, 31 26,25,25, 21, 22, 20 31, 29, 24,22,20. 29
The following regression model was estimated by an Australian-based MNC to determine its degree of economic...
The following regression model was estimated by an Australian-based MNC to determine its degree of economic exposure to the U.S. dollar (US$) and the South African Rand (SAR): where the dependent variable is the percentage change in cash flows (PCF) measured in the company's home currency over period t. The explanatory variable (et) is the percentage change in the exchange rate of the foreign currency (e.g., A$/SAR) over period t. The regression was estimated over a single period for each...
Using the data, fit an appropriate regression model to determine whether time spent studying (hours) is...
Using the data, fit an appropriate regression model to determine whether time spent studying (hours) is a useful predictor of the chance of passing the exam (result, 0=fail 1=pass). Formally assess the overall fit of the model. DATA three; INPUT result hours; /* result=0 is fail; result=1 is pass */ cards; 0 0.8 0 1.6 0 1.4 1 2.3 1 1.4 1 3.2 0 0.3 1 1.7 0 1.8 1 2.7 0 0.6 0 1.1 1 2.1 1 2.8 1...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT