To determine the economic pulse rate of a country, economists consider a number of macroeconomic variables such as inflation, GDP and unemployment. To estimate the economic state of the country they must consistently keep measuring these variables. Over the years, economists have devised tools that enable them undertake this assignment.
Economists define inflation as the general rise in price levels of goods and services over a period of time in the economy (Blanchflowe, 2007). Consumer price index (CPI) is the most widely used tool for measuring inflation. In their endeavors to measure inflation, economists encounter challenges both methodological and practical.
First, question arises as to the appropriateness of the consumer price index as a standard measure of inflation and whether or not it overstates or understates the inflation. Inflation is the measure of the changes in the cost of living. It is estimated by using a weighted basket of goods and estimating the variance in the price. In practice however, a number of practical problems arise.
Survey of family expenditure fails to capture everybody. For instance, youthful people will benefit more from dropping prices of cell phones and electronics. For this reason, the basket of good may not be representative. The basket is continuously updated on annually basis, it as well becomes outdated for changes in expenditure habits.
Changes in the quality of goods create another difficulty. When the quality of goods changes it means that increase in prices do not reflect inflation but merely the fact that they are different goods. For instance, present day computers have much more features compared to the way they were a decade ago. This makes it difficult to compare them as they are essentially different goods.
The type of measure to use is also important. Retail Price Index (RPI) includes mortgage interest payments but CPI doesn’t. For instance in 2009, when interest rates fell in US, RPI gave a negative inflation rate, whilst CPI was positive. It is therefore important to know which measure is used.
Measuring inflation through the CPI is susceptible to bias attributable to market inertia (Gersing, 1997). The ideal situation for a statistician is unchanged relations between any two market agents, unfortunately constant alterations are in most cases the rule rather than the exception. The characteristic of the market therefore means that most of the effort that go into producing the CPI is aimed at constructing models to reduce most of bias, or better still reduce their effects. Ideally, this problem is inherent to CPIs around the world and the solutions adopted are actually what makes the measure more or less exact and reliable.
Another element of inflation bias is called substitution bias. Over time prices of some goods rise more than others. The CPI nevertheless holds that the market basket that households purchase does not vary. What this means is that items whose prices has increased the most are accorded more weight in the index because households substitute them for others whereas those whose prices have marginally risen are given substantially little weight since households shift their expenditure in their favor. Put simply, the benefits that household receive by substituting expensive items for cheaper ones are not reflected by the index which consequently reflect more inflation than households really suffered.
A more objective approach has been suggested to circumvent substitution bias. If prices vary over time, inflation as measured in terms of the market baskets purchased at both the start and the end of these two measures and then averaged, a more reliable measure is arrived at. Regrettably, this procedure in not practical in real life. The research on substitution bias shows that it amounts to almost a half percentage point every year. Nearly half of this bias reflects the effect of substitutions at the level of wide commodity groups and the rest is as a result between particular items within these groups.
Interpreting the Measurement
Since it is practically impossible to observe inflation, Consumer Price index (or similar indices as the case may be) is used (Pacific et al, 2008). Taking a fictitious CPI value of 100 in 2006 (regarded as the base year) and 125 in 2010 (called the current year) and calculating the percentage change in the CPI gives us the inflation rate. In this case for instance the inflation rate is 25%. The very basic interpretation of this is that what a 100 US dollar could buy in 2006 would be bought using 125 US dollars in 2010.
Gross Domestic Product (GDP)
Economists define GDP as the total monetary value of all the final goods and services produced in a country in a particular time period, mostly a fiscal year. It comprises private and public consumption, government expenditure, expenditure on investments and exports that occur in a certain time period.
GDP = C + G + I + X
X- Expenditure on exports.
A number of methodological and practical challenges confront economists and statisticians in their quest to find a standard measure of GDP. Save for a few exceptions, GDP only considers goods and services which go through the market with unsold goods and services failing to be captured in the GDP. GDP per capita is extremely affected by population (Frank & Bernanke, 2007). A situation may arise such that a certain country has very low per capita income but this may not entirely mean that citizens in those countries are worse off in comparison to those in other countries. In such a case the usefulness of GDP statistics comes to naught. Omission of the unsold goods or services suggests that a rapid rise in the GDP may not be a reflection, merely a shift from unsold form to a marketed form.
In spite of GDP being used majorly as a measure of how well off people are, it has serious inadequacies as a measure of economic welfare. Further the productions of certain goods produce externalities which the market prices never reflect. This makes the GDP an unreliable measure of the material welfare of the people.
Yet another problem of GDP is that economists have had to grapple with is the determination of the size of the “underground economy” (unreported economic activities to the government either because they come from illegitimate activities or for the purpose of avoiding taxes). Lack of a precise way of determining this makes GDP an effective measure.
The possibility of double counting as well is another matter of concern to the economists as they struggle to measure the GDP and its associated instruments like the per capita. Economy of any one particular country is usually a complex entity and therefore problem of double counting can never be wished away.
Due to the fact that GDP calculations are a demanding exercise, statistical errors as well are a likely affair. However this is one challenge that statistician can circumvent through proper controls.
Stemming from the above shortcomings of the GDP measure there are a number of biases. First and foremost GDP conceptually emphasizes production with little or no regard to whether such productions are at the expense of the people’s welfare.
Secondly, GDP comprises pretty imperfect estimates of production of goods and services sold in the black market. Activities in the black market comprise production of illegal goods and services.
A third bias is the substitution bias. As the tastes and preference changes and as technology improves, the relative prices of goods change as well. In real terms GDP value is calculated using old, higher prices inflating the value of production.
New-good bias implies that it becomes difficult to include new goods into the GDP (D'Agostino et al, 2009). Since they did not exist in the base year it therefore means that their price was infinite.
GDP is, as noted earlier, a measure of market value of all the goods and services produced in the country. Therefore, to measure it one only needs to add up the various constituent parts of the economy that are a measure of all those goods and services produced. The value arrived at may be used to compare the economic performance of a country in two different time periods.
Unemployment is defined by economists as a situation whereby an individual is willing to work at the prevailing wage rates but cannot get the job. In their attempts to get insights about this phenomenon economists have over the years developed a graphical relationship (Philips curve) between unemployment and inflation rates. Theoretically they have predicted a negative relationship between these two economic phenomena. Various empirical tests have indeed given credence to this.
Just like measurement of GDP and inflation discussed earlier, unemployment rate measurement is hampered by a number of methodological and practical challenges.
Conceptually, economists are more often than not faced with the problem of identifying the unemployed from the employed. Measuring unemployment accurately is majorly hindered by the lack of sufficient knowledge about the unemployed. This is contributed by the fact that not all cases of unemployment are reported and even those that are reported are not in most cases accurate. Owing to the fact that in some cases the unemployed may be eligible for benefits of an economic nature, some individuals may work and yet fail to disclose it.
Another thing that makes it hard to conceptually measure unemployment is the scarcity of unemployment data. For instance, all data considers all those working on a temporary basis as employed though they may want to work full time. As these people represent unused labor effort available, the unemployment rate in that case understates the extent of unemployment in the economy.
Another reason why unemployment rate understates the extent of unemployment is the “discouraged worker effect”. If one becomes frustrated as a result of looking for employment for too long in vain such that he gives up the search for the job, he will be considered as being out of the labor force and eventually not recognize as unemployed . This tendency will dampen the fluctuations in the unemployment.
Interpretation of Unemployment Measure
The unemployment rate is the measure of the unemployment prevalence and is normally taken measured as a percentage of the number of individuals who are unemployed by all the people presently in the labor force. The rate is usually very low during the recession and high during periods of economic boom (Piore, 1983). A high unemployment rate value indicates a poor economic state of the country whereas a low value indicates a pleasant economic status.