Project Template on GNP and GDP


Project Template on GNP and GDP

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NEAS
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Project Template on GNP and GDP

GNP and GDP are measures of economic activity.

GDP, or Gross Domestic Product, is economic activity by persons working in the country, including foreigners. It does not include citizens working abroad or the income from foreign capital. GDP is the measure now used for a country’s economic activity.

GNP, or Gross National Product, is economic activity by the country’s citizens. It includes income by citizens from working abroad (or capital invested abroad) but not income by foreigners working in the country.

 

GNP and GDP are measured on a real or a nominal level. The raw indices are seasonal, and the index is seasonally adjusted for use with other indices.

Take heed: The indices on the discussion forum are quarterly, seasonally adjusted, in nominal dollars.

You can do a student project on a GNP or GDP index. You may also use GDP or GDP to form structural models.

Illustration: Your student project fits an ARIMA process to new car sales or new home sales. Sales of durable goods, such as autos and homes, vary with economic activity.

 

In prosperous years, when the economy is strong, consumers use their savings (or take loans) to buy durable goods.

In recessions, sales of durable goods decline.

 

New car sales and new home sales vary from year to year, and no ARIMA process fits well. For your student project, regress auto sales or home sales on GDP or GNP and fit the ARIMA process to the residuals of the regression.

Many of the project templates discuss structural models by regressing the time series on GDP (and other macroeconomic indices). If the time series you are examining is monthly, interpolate the quarterly GDP series to a monthly series.

Illustration: Suppose the first quarter 20X7 GDP is $210 trillion and the second quarter 20X7 GDP is $222 trillion. Use these figures for February and May 20X7. Interpolate for March 20X7 as $214 trillion and for April 20X7 as $218 trillion.

 


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Project Template on GNP and GDP.pdf (825 views, 23.00 KB)
GDP GNP.xls (787 views, 35.00 KB)
jcrudo
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I'm doing my project on GDP during a specific time period (1980s+) using this data. Since this is seasonally adjusted, I only had to take the log of the series. I then took the first differences and plot the sample ACF. The correlations start at high .20s for 2 lags then immediately fall to zero within 5 lags. However, the sample ACF then fluctuates a lot what looks to be around zero. Them seem to be bounded by +-0.1, but there are 2 lags that are around +-0.20. Can I conclude this is stationary? I've seen sample projects and their sample ACF's look a lot smoother than mine. Thanks.

[NEAS: GDP is affected by many variables. Countries may have 3% growth for several years followed by 6% growth, caused by a change from a closed economy (no foreign trade) to an open economy. Whether the time series is stationary depends on whether there are material changes. The student project does not expect you to answer the economic questions. Explain what the statistical tests show, choose the form of the time series you think is most appropriate, and complete the project.]


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NEAS - 5/2/2008 12:59:12 PM

Project Template on GNP and GDP

GNP and GDP are measures of economic activity.

GDP, or Gross Domestic Product, is economic activity by persons working in the country, including foreigners. It does not include citizens working abroad or the income from foreign capital. GDP is the measure now used for a country’s economic activity.

GNP, or Gross National Product, is economic activity by the country’s citizens. It includes income by citizens from working abroad (or capital invested abroad) but not income by foreigners working in the country.

GNP and GDP are measured on a real or a nominal level. The raw indices are seasonal, and the index is seasonally adjusted for use with other indices.

Take heed: The indices on the discussion forum are quarterly, seasonally adjusted, in nominal dollars.

You can do a student project on a GNP or GDP index. You may also use GDP or GDP to form structural models.

Illustration: Your student project fits an ARIMA process to new car sales or new home sales. Sales of durable goods, such as autos and homes, vary with economic activity.

In prosperous years, when the economy is strong, consumers use their savings (or take loans) to buy durable goods.

In recessions, sales of durable goods decline.

New car sales and new home sales vary from year to year, and no ARIMA process fits well. For your student project, regress auto sales or home sales on GDP or GNP and fit the ARIMA process to the residuals of the regression.

Many of the project templates discuss structural models by regressing the time series on GDP (and other macroeconomic indices). If the time series you are examining is monthly, interpolate the quarterly GDP series to a monthly series.

Illustration: Suppose the first quarter 20X7 GDP is $210 trillion and the second quarter 20X7 GDP is $222 trillion. Use these figures for February and May 20X7. Interpolate for March 20X7 as $214 trillion and for April 20X7 as $218 trillion.



Gross Domestic Product (GDP), Gross National Product (GNP), and National Income measures attempt to measure how much economic activity took place during a specified amount of time (usually a year). ... GNP measures the market value of all final goods and services produced by a country's citizens or residents.
‌The formula to calculate the components of GNP is Y = C + I + G + X + Z. That stands for GNP = Consumption + Investment + Government + X (net exports, or imports minus exports) + Z (net income earned by domestic residents from overseas investments - net income earned by foreign residents from domestic investments.
‌GDP (or Gross Domestic Product) may be compared directly with GNP (or Gross National Product), to see the relationship between a country's export business and local economy. A region's GDP is one of the ways of measuring the size of its local economy whereas the GNP measures the overall economic strength of a country.



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