Question 1

When economic conditions are stable, econometric methods:&#10;A)are often more accurate than trend projections.&#10;B)vastly outperform exponential smoothing methods.&#10;C)are often appropriate for long-range forecasting.&#10;D)none of the above.

Accepted Answer

Econometric methods are often appropriate for long-range forecasting when economic conditions are stable because they can incorporate various economic variables and relationships over time.

Question 2

Econometric forecasting methods are most valuable when the stochastic error term:&#10;A)is small and randomly distributed.&#10;B)is large and randomly distributed.&#10;C)is large and not randomly distributed.&#10;D)has an expected value of zero.

Accepted Answer

Econometric forecasting methods are most valuable when the stochastic error term is small and randomly distributed. This is because the smaller the error term, the more accurate the forecast will be. Additionally, if the error term is randomly distributed, it will not bias the forecast.

Question 3

If ln St = 4.568 + 0.336t, t is in years, and sales is in millions of euros, the constant:&#10;A)change in sales is &#8364;4.568 million per year.&#10;B)change in sales is &#8364;0.336 million per year.&#10;C)percentage change in sales is 33.6 percent per year.&#10;D)percentage change in sales is 4.568 percent per year.

Accepted Answer

The coefficient of t in the equation ln St = 4.568 + 0.336t represents the continuous percentage growth rate of sales, which is 33.6% per year.

Question 4

Linear trend analysis assumes:&#10;A)constant period-by-period unit change in an important economic variable over time.&#10;B)constant period-by-period percentage change in an important economic variable over time.&#10;C)variable period-by-period unit change in an important economic variable over time.&#10;D)variable period-by-period percentage change in an important economic variable over time.

Accepted Answer

Linear trend analysis assumes a constant period-by-period unit change in an important economic variable over time. This means that the trend is expected to be linear, with a consistent increase or decrease in the variable measured in constant units over time. This can be useful for predicting future values based on the historical trend. In contrast, choice B would be an example of exponential trend analysis, which assumes a constant period-by-period percentage change in the variable over time. Choice C and D are not consistent with the assumptions of linear trend analysis. Linear trend analysis assumes that there is a constant period-by-period unit change in an important economic variable over time. This means that the variable is changing at a steady rate over time, which allows for the creation of a straight line trend.

Question 5

If an economic time series is growing by a percentage amount each period, the most accurate forecast model is:&#10;A)a simple regression model.&#10;B)a multiple regression model.&#10;C)a linear trend.&#10;D)log-linear model.

Accepted Answer

If the economic time series is growing by a percentage amount each period, then a log-linear model would be the most accurate forecast model. This is because a log-linear model can capture both the growth rate and the underlying linear trend in the data. A simple regression model and a linear trend model may not be able to capture the nonlinear growth pattern in the data, while a multiple regression model may not be necessary if there is only one independent variable (time). If the economic time series is growing by a percentage amount each period, then a log-linear model is the most appropriate forecast model. This is because it accounts for the compounding effect of growth over time and linearizes the data by taking the logarithm of both the dependent and independent variables, making it easier to interpret the coefficients and forecast future values. A simple regression model or a linear trend would not capture the compounding effect of growth, while a multiple regression model may not be necessary if there is only one independent variable (time).

Question 6

Time-series methods:&#10;A)use a series of data observations at a single point in time.&#10;B)combine economic theory with mathematical and statistical tools to analyze economic relations.&#10;C)use inter-industry linkages to show how changes in the demand for one industry's output will effect all sectors of the economy.&#10;D)none of the above.

Accepted Answer

Time-series methods analyze data points collected or recorded at many points over time, not at a single point in time, and are primarily focused on identifying patterns, trends, and forecasting future values based on historical data. They do not inherently combine economic theory with mathematical and statistical tools to analyze economic relations (that's more aligned with econometrics) nor use inter-industry linkages to show how changes in demand for one industry's output will affect all sectors of the economy (that's more related to input-output analysis).

Question 7

Rhythmic variation in economic series that is due to a pattern of expansion or contraction in the overall economy is called:&#10;A)secular trend.&#10;B)cyclical fluctuation.&#10;C)irregular or random influences.&#10;D)seasonal variation.

Accepted Answer

Cyclical fluctuation refers to the variations in economic series due to expansion or contraction in the overall economy that occurs in a fairly regular pattern. This is different from secular trends, which reflect long-term shifts in the economy, irregular or random influences, which are unpredictable variations due to events such as natural disasters or political changes, and seasonal variation, which is a recurring pattern related to the time of year. Cyclical fluctuation refers to the pattern of expansion or contraction in the overall economy, leading to rhythmic variation in economic series. Secular trend refers to the long-term trend in an economic series, while irregular or random influences are unpredictable fluctuations in the series. Seasonal variation refers to the regular pattern of variation in economic series that is due to the season or time of year.

Question 8

A forecast method that gives feedback to panel members in a manner that prevents direct identification of individual positions is called:&#10;A)personal insight.&#10;B)panel consensus.&#10;C)the Delphi method.&#10;D)qualitative analysis.

Accepted Answer

The Delphi method is a forecast method that involves a panel of experts who provide feedback to each other in a manner that prevents direct identification of individual positions. This helps to encourage open and honest discussion among panel members, which can lead to more accurate forecasts. Personal insight and qualitative analysis do not necessarily involve a panel of experts or feedback from others, and panel consensus may involve direct identification of individual positions. The Delphi method is a forecast method that seeks to prevent biases and individual influences by gathering feedback from panel members anonymously. This is done to foster a more objective and comprehensive forecast without any one member dominating or influencing the outcome.

Question 9

A leading indicator of business cycle peaks is given by:&#10;A)industrial production.&#10;B)the average initial weekly claims for state unemployment insurance.&#10;C)the average duration of unemployment.&#10;D)the change in consumer price index for services.

Accepted Answer

The average initial weekly claims for state unemployment insurance tends to rise before a business cycle peak, indicating that more people are being laid off and becoming unemployed. This is a leading indicator because it provides a signal of potential economic downturn before other indicators, such as industrial production or consumer price index, show significant changes. The average initial weekly claims for state unemployment insurance is a leading indicator of business cycle peaks as companies tend to lay off workers in response to declining demand, making this an early sign of economic downturn.

Question 10

If St = -&#8364;6,440.8 + &#8364;1,407.3t, t is in years, and sales is in millions of euros:&#10;A)the projected annual rate of change in sales is above the actual historical amount of change per year.&#10;B)the projected annual rate of change in sales is below the actual historical amount of change per year.&#10;C)the slope of the sales/time relation is generally increasing.&#10;D)differences between actual and fitted values are generally positive in both early and later periods.

Accepted Answer

The coefficient of t (€1,407.3) represents the projected annual rate of change in sales, which is a positive value indicating an increase in sales over time. There's no comparison to actual historical amounts provided, so we can't determine if it's above or below historical changes without additional data. However, the statement is correct in that it describes the slope of the equation, which is positive, indicating an increase.

Deck 6: Forecasting