business, government, and the world economy national income product accounts econometrics

Business, Government, and the World Economy

National Income Product AccountsEconometrics

Macroeconomics Core Ideas

All Major Components of Aggregate Demand, (C, I, & NX), are negatively related to the real interest rateIn the short-run, the economy is dominated by changes in aggregate demand. In the long-run it returns to a long-run growth path.The long-run growth rate is determined by ratio of investment to GDP, the degree to which free trade is encouraged, and changes in productivity.

MacroecomicsCore Ideas

The central bank controls nominal short interest rates, but the real long-term rate impacts aggregate demand and is in part based on expectations of inflation.Expectations of the future play a key role in how economic agents behave.Changes in monetary policy impact both output and prices in the short run, but only prices in the long run. There is no long run tradeoff between unemployment and inflation.

MacroeconomicsCore Ideas

Real output is impacted quicker than inflation by monetary policy. The short run impact of monetary policy cannot be predicted accurately.Wages are slow to react to changes in the economy in the short run.

MacroeconomicsCore Ideas

Generally, increases in the cyclically adjusted federal government budget deficit, regardless of their financing, reduce the long run growth rate. Markets “clear” in the long run and economic agents maximize their utility subject to short term rigidities, liquidity, and incorrect expectations.

Measuring Macroeconomic Data

National Income and Product Accounts (NIPA)Data prepared by the Bureau of Economic Analysis (www.bea.gov).

http://www.bea.gov/

Key Components of NIPA

Gross Domestic Product (GDP)The final value of all goods and services produced in a country during a given time frame.Excludes intermediate goods to avoid double counting. It measures the value added at each stage of the production process.Excludes good and services produced elsewhere even if they are consumed in the economy.

Double Entry Bookkeeping

The total amount of final goods and services purchased for final use (aggregate demand) produced must equal the total amount of final amount paid to the factors of production (value added).

Components of GDP

Personal Consumption Expenditure (C)Items purchased by consumers

Gross Private Domestic Investment (I)Spending by business, construction and inventory investment

Government Purchases (G)Total federal state and local government purchases

Net Exports (F or NX)Exports minus Imports

www.bea.gov 2www.bea.gov 2ndnd qrtr 2009 Preliminary qrtr 2009 Preliminary

Personal Consumption Expenditures

Approximately 71.2% of GDP*Durable Goods – 10.5% of GDP – Goods that last more than 3 years. Cars appliances, etc.Non Durable Goods – 20.6% of GDP – Food, gasoline, etcServices = 40.2% of GDP

Trends

Services accounted for approximately 40% of Personal consumption expenditure in the 1960s it now accounts for approximately 60% of personal consumption expenditure.Spending on durable goods is much more sensitive than spending on the other components of consumption

Volatility of Durable Goods

Gross Private Domestic Investment

Fixed InvestmentIncludes nonresidential expenditures and residential building (single family homes) recorded at time the home is built – not sold

Inventory InvestmentGDP should account for everything producedChange in inventories, not the level is an important number to watch

Government Spending

Federal component is approximately 1/3 of the total.The federal component is divided into defense spending and non-defense spending

Net Exports

Export levels as a % of GDP have doubled since 1980.Since the 1970s imports have been much greater than exports creating a negative entry for net exports.

Other Useful Info

Final Sales of Domestic Product: GDP minus inventories. Provides insight into the total demand for goods and services produced domesticallyGross Domestic Purchases: Total purchases of Goods and Services by US consumers and Businesses regardless of where it was produced.

Interpreting GDP Data

Release date:8:30 am EST the last Friday of the first month of each quarter (Jan, April, July, and Oct)Two rounds of monthly revisions follow as does an annual revision each July

* The Secrets of Economic Indicators by Berhard Baumohl 2005* The Secrets of Economic Indicators by Berhard Baumohl 2005

Interpreting the Tables*

Table 1 Real GDP % Change from preceding period

Real Growth of 3% to 3.5% is considered the benchmark that allows growth to absorb new employment.Look at the combination of non-farm productivity and growth of labor force as a cap on non-inflationary growth.



Table 1– Keep an eye on net exportsFinal Sales of Domestic Product provides a good early warning. If the rise in final sales drops below the growth rate of GDP for a long period of time (inventories should be growing) it could be a sign of trouble.Don’t neglect the nominal number, since corporate earnings are recorded this way. S&P 500 earnings growth is constrained in the long run by economic growth.



Table 2 Contributions to Percent Change in real GDP

Provides a breakdown of which components of GDP are resulting in GDP growth (or decline).



Appendix Table A GDP and Related Aggregates

Computer Sales – a measure of spending by business on technology and also as a possible increase in productivityMotor vehicle output – responds relatively quickly to inventory changes on dealer lots – an increase in inventories is reflected with a slowdown in production.



Other more frequent releases often overshadow the GDP release.

However the growth rate can turn out to be drastically different from the expectations.It is essential to a full understanding of the economies outputRevisions might be large enough to impact the current outlook.



Bond market reactions will likely be stronger than stock market reactions. Especially if the release does not correspond with expectations.

Manager’s Briefcase*

2000.1 Real annual GDP growth of 2.6%Inventory Investment fell $47 BillionNet Exports fell $29 BillionGovernment purchases fell $4billionFinal Sales rose $132 Billion

2000.2 Real annual GDP growth of 4.8%Inventory Investment increased $46 BillionNet Exports Fell $26 BillionGovernment purchases rose $18 billionFinal Sales rose $70 Billion

*Macroeconomics for Managers by Michael K. Evans, Blackwell Publishing *Macroeconomics for Managers by Michael K. Evans, Blackwell Publishing

Manager’s Briefcase

Which case points to a stronger future for the economy?

Increase in real GDP at an annual rate of 4% with most of the gain from inventory investmentIncrease in real GDP at an annual rate of 2% with a decline in inventories and an increase in final sales

GDP vs. GNP

Gross National Product (GNP)Includes sales of all products by firms based in the domestic country – even if the sales are overseas.

Real vs. Nominal GDP

Nominal GDP is the current dollar valueReal GDP adjusts for inflation.

An increase in the price level could cause an increase in nominal GDP even if the amount produced did not changeConstant dollars – one approach to calculating real GDP is keeping prices fixed based on a base year. Any increase in “real GDP” is then a function of an increase in the amount produced.

Chain Weighted Dollars

Currently Real GDP is based on chain weighted dollars.Constant dollars are not effective due to changes in the quality of goods such as computers. The price of a basic computer 10 years ago is not comparable to the basic computer today.

Chain Weighted Dollars

The goal is to allow prices to gradually evolve over time. Assume a two good economy with two years worth of data.

year Quant Pizza

Price of Pizza

Quant Beer

Price of Beer

1 2 3 5 5

2 3 4 7 6

Two measures of GDP

Nominal GDPYear 1 $2*3+$5*5 = $31Year 2 $3*4+$7*6 = $54

Real GDP (Year 1 dollars)Year 1 $2*3+$5*5 = $31Year 2 $2*4+$5*6 = $38

Other measures of National Output

Factory OrdersBusiness InventoriesIndustrial Production and Capacity UtilizationInstitute for Supply Management Business Survey (and non business survey)Index of leading economic indicators

Forecasting

Ideally developing understanding of the economic relationships will help provide us with insight about what will happen in the futureForecasting (using current data to predict the future )

Econometric modelsNoneconometric models

Forecasting with Econometric Models

Regression results By taking your established relationship using past data and plugging in current data you get a forecast.Validity Problems

Example

Assume we from Jan 1950 to Dec 2005 on the relationship between unemployment and GDP.

Unemployment = 1.321-.403in GDP)Regression Statistics

Multiple R 0.874772788R Square 0.765227431Adjusted R Square 0.764169897Standard Error 0.553334069Observations 224

Coefficients Standard Error t Stat P-valueIntercept 1.32148697 0.062042257 21.2997887 1.44E-55gdp (12 month % Change) -0.403276944 0.014991853 -26.8997396 8.47E-72

Forecast

Unemployment = 1.321-.403in GDP)The % change in GDP for the first qtr of 2006 was 3.5577% Implying a change in unemployment of 1.321-1.4337 = -.112 The actual change in unemployment was -.5 However there is an error component we have left out, the relationship is actually

Unemployment = 1.321-.403in GDP) + e

Regression Review

Equation of a line: Y = a + bXGraphing combinations of X and Y form a line.X is the independent variable and placed on the horizontal axis. Y the dependent variable and placed on the vertical axis (The value of Y depends upon X)a is the Y intercept and b the slope of the line.

Estimating the Regression

The slope of the line is then equal to

The Intercept is:

XVariance

y)Cov(x,

)( XY AverageslopeAverage

The Line Estimated is the one that minimizes the sum of the squared residuals

Actual vs. Regression

-4.00

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

-4.0000 -2.0000 0.0000 2.0000 4.0000 6.0000 8.0000 10.0000 12.0000 14.0000

Unemployment (net 12 month Change) Regression

Actual March 2006 Observation

Regression Estimate for March 2006

Other problems

In our example we took the known change in GDP to forecast the change in unemployment.You would probably be more interested in using an estimate of GDP (another forecast) to predict the forecasted change in unemployment…

The Bottom Line

In the best case scenario (extremely high t-statistic, high R squared, data fits assumptions underlying regression, etc) with a relationship that has been tested over time – you will still have error in your forecast.Most of the time, the relationship is not as stable, the data not as consistent, and many other real world problems exitsThis creates a case where there is an even higher chance for error

Assumptions about the error

For the model to be accurate some statistical properties need to hold.

The error term has zero expected valueThe error term has constant variance for all observationsThe random error are statistically independentThe error term is normally distributed

Constant Variance

If the error is heteroscedastic, the variance my change over time

Large firms vs. Smaller firm (larger firms may have higher variance) or a industry subset of firms may exhibit this behavior.

Error Terms are Independent

If the error terms from different observations are correlated there is an issue termed serial correlation

Time Series observations can exhibit this

BLUE

If you add the assumptions about error to the following assumptions

The relationship between Y and X is linearThe X’s are nonstochastic (nonrandom) variables whose values are fixed

Then the regression line will be the Best Linear Unbiased Estimator of the relationship

Some Other Sources of Error in Econometric Models

Incorrect Underlying TheoryInstability of underlying relationshipsErrors in Econometric ModelsInadequate or Incorrect DataTendency to Cluster around consensus forecastInability to predict exogenous eventsErroneous assumptions about policy variables.

Incorrect Theory

What are you trying to measure – which variables are independent dependent etc… Example: Assume you are interested in estimating college enrollment and you know that it has increased over time. You have a large number of possible variables and estimate the relationship between the variables and enrollment.It is possible to get “spurious results” evidence of a relationship that does not exist…

Regression results

How confident would you be using the yearly data below to estimate changes in college enrollment?

Regression StatisticsMultiple R 0.943256937R Square 0.889733648Adjusted R Square0.879709435Standard Error 311438.1733Observations 13

Coefficients Standard Error t Stat P-valueIntercept 6174869.356 791962.2492 7.796924 8.33E-06X varible 2484828.353 263749.4402 9.42117 1.34E-06

Spurious Relationships and Data Mining

You should not develop a theory to explain your observed relationship. Just because there appears to be a strong correlation does not mean that there is economic meaning. How is that different from the current trend in marketing – Data mining?

Instability of underlying relationships

The basic regression model assumes that there exists a long term stable relationship between the variables – it does not change over timeMuch of Economics is based on human behavior – it can and does change over time

Inadequate and Incorrect data

How important are revisions of economic data? Does the economy respond to the actual level of an indicator or to the announced level of the indicator? Recent revisions in GDP as an example.

“Herd behavior” and consensus forecasts

As a forecaster the cost of being wrong and much different from the average forecast is much greater than the cost associated with a being wrong with a forecast slightly different than the average.

Exogenous Shocks

Outside influences impact the relationship – we know that the estimation is telling only part of the answer – much of what happens is unexplained by the other variable.

Interpretation of Policy

Impact of policy only happens after a long lagData (preliminary vs. final data)Recognition (moving average vs. month to month data)Reaction (length of time before policy makers recommend change)Legislative (Fiscal policy is slow)Economic (Once policy is implemented – economy is slow to respond)

Non-econometric Models

Naïve Models and consensus surveys (long term trendsLeading Indicators (Developing an index based upon a number of other indicators)Survey Methods (measuring consumer attitudes and business conditions)

Forecast Error

Equation of a line: Yt = a + bXt + ~ N(0,2)Given Xt+1 it is easy to find a forecast of YT+1

The forecast error is the difference between the actual observation of Y and the predicted value.By definition (if all assumptions hold) the error has an expected value of zero so the forecast is unbiased

Forecast error

The error should be N(0,2) so it is possible to determine a confidence interval for the forecast error. This provides for the ability to test the forecasting ability of the regression

95% confidence bands

Economic Indicator Example:Measuring Durable Goods

Durable Goods Orders (Advance Report on Durable Goods Manufacturers Shipments , Inventories and Orders)Where: www.census.gov (Census Bureau)Released 3-4 weeks after the end of the reporting monthRevisions for each of the 2 preceding months – revisions can be large.Is a volatile and unpredictable indicator

http://www.census.gov/

Measuring Durable Goods

Survey of 3,500 manufacturers from 89 industries ($500 million in annual shipments each)Asked for numbers of New orders, shipments, unfilled orders and inventories

What to look for

Table 1New Orders – Leading indicator. Be careful a single large aircraft or military order can inflate this number.Orders excluding transportation and Defense. Aircraft orders come in large quantities (both civilian and Defense)Other broad headings such as Primary metals, fabricated metals, Computers, all other durables.Capital goods (business spending)

What to look for in the report

Table 2Unfilled orders – If high can slow down the production process and cause inflationary pressure.

Market Impact

More response in bond market than stock market.Both markets interpret information including current unused capacity with the level of new orders.

business, government, and the world economy national income product accounts econometrics

Documents

long run tradeoff

long run growth rate

final goods

gdp goods

intermediate goods

final use aggregate

expectations of inflation

short term rigidities