# Economics

1. Economic indicators

Economic indicators can be divided into three types: leading, lagging, or coincident; this division is based on the timing of their changes relative to changes of the economy in general.

Leading economic indicators are indicators which change before the economy changes: for example, stock market returns are a leading indicator, as the stock market usually begins to decline before the economy declines and they improve before the economy begins to recover from a recession. Leading economic indicators are the most important type for investors as they help predict what the economy will be like in the future.

Lagged economic indicators change direction after the changes in economy have taken place, usually several quarters after the changes. The unemployment rate, for example, represents a lagged economic indicator as unemployment tends to increase for several quarters after the economy starts to improve. Coincident economic indicators are the ones that move at the same time the economy does; example of coincident indicator may be the GDP.

2. Difference between GDP (nominal GDP) and real GDP

GDP, or gross domestic product, is the sum of all services and goods (together with private and government spending) produced by a given country during some period; usually GDP is measured during for one-year period. GDP is the basic economic indicator, it relates to coincident indicators. GDP is used to measure the growth rate of the economy (usually, the percent of GDP growth can also be considered compared to the previous year). Also, GDP and its growth rate can be used to estimate economic health of the country or region. Nominal GDP (or simply GDP) is calculated using the market value of goods and services during the selected period of time. GDP per capita is also a widely used indicator, showing the sum of overall production per one citizen.

However, calculating nominal GDP and comparing it to the previous year has one certain flaw from the point of view of measuring economical growth: the change of prices and effect of inflation are not taken into account. Thus, for estimating economical development, the concept of real GDP should be used. Real GDP is calculated using constant prices set at the basic period; thus, real GDP is corrected concerning inflation effects, and is a more accurate measure of economical growth.

3. Economic forecasting and economic modeling

The essence of economic forecasting is to predict the behaviour of economy in general and of certain economic indicators. Making any statement about the future may be referred to as forecasting. In economic analysis, model-based forecasts are widely used. In order to make forecasting, economical model should be built. The model presents a relation of different factors, and how they interact with each other. Economic models usually link the exogenous and endogenous variables, and tend to establish a mathematical relation between them. Most widely used relations are linear ones. In this paper, a linear model for economic indicators will be considered.

4. Model for GDP forecasting

For building a model of GDP forecasting, I have chosen such indicators as unemployment rate and inflation. Inflation can be measured by different indicators as well; it is reasonable to study such indices as CPI (consumer price index) and PPI (producer price index).

Consumer Price Index is the principal value used to measure inflation: it represents the relative value of standard “basket of goods”, i.e. the products typically bought by consumers, to the price of the same “basket of goods” at a given year. Currently, base year for CPI is set to 1982.

Producer Price Index represents the weighted index of prices that are at the producer level; it is not so widely used as CPI, and is better suited for estimating a particular industry than the whole state of economy. Moreover, it usually strongly correlates with CPI, and is sometimes used as a forecast for CPI. Thus, for building economical model CPI data will be used (since PPI correlates with CPI, it is unreasonable to include it in the model).

The third indicator – the unemployment rate – represents the percent of labor force consisting of those who are not currently employed but are actively seeking work. This indicator is a lagging one; however, it has a strong effect on the state of the economy itself.

It is generally suggested that unemployment has adverse (negative) effect on the GDP, and inflation is predicted to contribute to GDP growth. Though real GDP values will be used for forecasting (i.e. they are already corrected by the value of inflation), inflation may also have qualitative impact, in addition to quantitative changes. Preliminary suggestion is that this impact is slightly positive concerning the GDP.

Table 1 represents the leading indicators discussed below.

In order to build a linear model, it is necessary to perform a regression analysis and determine the strength of relationship between the independent variables (CPI and unemployment rate) and dependent variable (real GDP value). This analysis is done using the means of MS Excel data analysis package.

Matrix of correlation coefficients is presented by Table 2.

It is possible to see that CPI index has a very strong influence on GDP (it is notable that real GDP is inflation-clear; thus, inflation plays a leading role in determining economic growth). Unemployment rate showed not very significant correlation; however, the hypothesis concerning the adverse effect of unemployment on GDP is supported by negative value of correlation coefficient.

Table 3 contains the results of regression analysis for the selected data.

Regression analysis performed in MS Excel showed that R-square for the model is 0.98, which shows a very high level of forecasting. Thus, GDP = 536.34 + 2.31 * CPI – 236.95 * unemployment rate, which supports the initial hypothesis about adverse effect of unemployment and direct effect of inflation on GDP. Forecast of GDP may be used basing on forecasts of CPI and unemployment rate, and is expressed as follows: GDP(2010) = 536.34 + 2.31 * 217,9 – 236.95 * 9.7 = 17426.41 (billions of dollars in chained 2005 dollars). A recent forecast by http://www.forecasts.org forecasts GDP will be 14677 by the end of 2010. This forecast is not so “positive” as our forecast first of all because it takes into account many economic indicators, and not only several of them, and also due to strong relation between CPI and GDP, and predicted CPI growth.

References

US Bureau of Economic Analysis. http://www.bea.gov. Accessed at August 12, 2010.

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