Analysis of Economic Indicators

In this section we discuss several aspects to be taken into account when considering an economic indicator. In economic indicator analysis the following is very important:

Correctly interpret the information provided
Assess how its behavior can influence the evolution of the financial markets.

Let’s now take a look at different elements related to these two points.

Go to the previous chapter

Go to the next chapter

Index:

2.1. Economic growth and price indicators.

2.2. Coincident indicators and leading indicators.

2.3. Factors that distort an economic indicator.

2.3.1. Seasonal factors.

2.3.2. Exceptional factors.

2.3.3. Volatile Factors.

2.4.1. Frequency.

2.4.2. Moment of publication.

2.4.3. Preliminary and final data.

2.5. Level and growth rate indicators.

2.6. Market forecast.

2.7. Main findings of section 2.

2.1. Economic growth and price indicators.

First, we must distinguish whether we have an indicator of economic growth indicator or a price indicator.

This distinction, although trivial, is important because there are times when the market is more sensitive to economic growth data and other times when the inflation data are under closer scrutiny.

Next, we describe two hypothetical scenarios to illustrate the aforementioned fact.

Situation 1: An economy is in its initial phase and recuperation and inflation is contained.

In this first situation, the market closely follows indicator activity because that is what is going to show us whether the budding economic recuperation is consolidating or not.

Situation 2: An economy is growing significantly and is in danger of overheating, i.e. that prices rebound significantly.

In this second situation, the market will pay special attention to inflation data to see if it has reached levels of concern or not.

Figure 2: Examples of indicators of economic growth and prices.

Back to index

2.2. Coincident indicators and leading indicators.

Secondly, we must distinguish whether it is a coincident indicator or an indicator that anticipates the behaviour of economic activity or the prices. In this section, we focus on economic growth indicators to explain the difference between a coincident indicator and a leading indicator; but you can make an equivalent analysis considering the price data. Coincident indicators provide us with information on current economic activity. These indicators move together with the economic cycle, i.e. the GDP. Figure 4 shows how industrial production in the Eurozone is a coincident indicator of GDP. The industrial production series not only moves in the same direction as the GDP, but also does so at the same time. The funds and the peaks of each of the series coincide in time.
Graph 4: GDP and industrial production in the Eurozone.
The leading indicators provide information on how the economy may behave in the coming months. These indicators anticipate the business cycle, that is, the GDP.
Graph 5: GDP and the index of leading economic indicators prepared by OECD for the Eurozone.
Graph 5 shows how the index of leading indicators published by the Organization for Economic Cooperation and Development (OECD) for the Eurozone is a leading indicator of GDP. The OECD indicator series anticipates the future behavior of GDP. The leading indicators are constructed from indices which reflect business and consumer confidence. These indices are intended to reveal the future conduct of investment and consumption, respectively. For companies, the questions are related to their perspectives regarding production, employment of new personnel, inventories, etc.. For consumers, the questions are related to their perspectives with regard to employment, income, etc.
Back to index

2.3. Factors that distort an economic indicator.

There are factors that may distort the behavior of an economic indicator and this can lead to hasty conclusions and errors about in exactly what state a given economy lies. These factors can be classified into three categories: Seasonal factors: those that repeat regularly over time. Exceptional factors: those that occur from time to time. Volatile factors: those that cause significant fluctuations in an economic indicator. Let us illustrate using an example each of these aspects.
Back to index

2.3.1. Seasonal factors.

Unemployment rate in Spain.
Graph 6: Unemployment rate in Spain.
Graph 6 shows that the unemployment rate de Spain decreased in the nineties. In the last few years, this trend has stopped and the unemployment rate has stabilized at around 9% of the working population. In this section, however, the idea is not to focus on the trend behavior of unemployment. Our interest lies in focusing on the fact that the same pattern is repeated year after year: The unemployment rate always goes down in August (arrows on graph). The unemployment rate always goes down in December. This fact, however, has nothing to do with whether the Spanish labour market is showing a good or bad behavior. It simply indicates a fall in the unemployment rate in August, due to the "ice-cream vendor” effect and in December, due to the "Santa Claus” effect. The "Ice-cream vendor” effect: In August, Spain receives many tourists and, to be able to adequately meet their needs, hotels, restaurants, ice-cream stands, etc.. hire more staff. Therefore, August is usually a month when the unemployment rate decreases. The "Santa Claus" effect: Christmas comes in December, a time of gifts and shopping. In these circumstances, the stores employ more staff to address the major influx of people to their establishments. Therefore, in December the unemployment rate tends to decrease in Spain. In conclusion, the fact that the Spanish unemployment rate decreases in August or December, a priori, does not provide much information on whether the Spanish labour market is improving or not. This is because they are months in which traditionally, regardless of the background trend in the unemployment rate, there is less unemployment than the rest of the year. Therefore, to know what is really happening in the Spanish labour market, we should free up the relevant statistics of the "ice-cream vendor” and the "Santa Claus¨ effects. This problem of seasonality occurs in many other economic indicators. To avoid drawing the wrong conclusions we should focus on the corrected seasonal data, which is precisely where the market also focuses its attention.
Back to index

2.3.2. Exceptional factors.

Evolution of U.S. business inventories.
Graph 7: Trends in U.S. business inventories.
Graph 7 shows how at the end of 1999 (arrow on graph) a relatively large increase occurs in US business inventories. Without additional information one could begin to draw the following conclusions: The businesses are building up stocks because sales are on the decrease and, consequently, the products manufactured by firms are remaining warehoused. The businesses are building up stocks in response to higher expectations for future sales. Etc. In reality, however, the upturn in business inventories at the end 1999 is explained by an exceptional factor which had nothing to do with the economic situation at that time. This factor was none other than the uncertainty when faced with the arrival of year 2000. In this situation, businesses, as a precaution, decided to accumulate stocks. Disregarding this event, one could have concluded incorrectly about what was happening in the economy. Other exceptional factors which can influence the behavior of economic indicators include earthquakes, floods, general strikes, and so on. Thus, in interpreting an economic indicator, it is important to notice if there are "exceptional circumstances" in the background which affect their behaviour. If so, you must be very cautious when drawing conclusions about the economy from this fact.
Back to index

2.3.3. Volatile Factors.

Evolution of orders for U.S. durable goods.
Graph 8: Trend in durable goods orders in the U.S.
Graph 8 shows how the number of orders for U.S. durable goods is very volatile: There are months in which durable goods orders rebound significantly from the previous month (first arrow in the graph: growth more than 15%). There are months in which durable goods orders fall back significantly from the previous month (second arrow of the graph: a higher than 10% recoil). In this context, one can draw few conclusions about what is really happening in the U.S. economy from such data. The first thing to do is understand the reason for the volatility. In the example, the number of orders for durables is volatile because within the index we find aircraft orders. In a month when aircraft orders take place, the data soars and the following month and if there is no aircraft order the data fall back significantly. Therefore, to know what is really going on in the economy, we should offset the effect produced by the aircraft orders. Another example related to volatility, we find in the prices. On many occasions in the financial press reads: "The overall CPI has rebounded. . . , While the core rate of CPI. . . . The difference between one index and the other is that the core rate excludes volatile contributing elements. In particular, the core rate ignores energy prices and the price of unprocessed food. Energy prices, particularly those of petroleum may show significant volatility because their behavior is influenced by political aspects such as OPEC reduction or geopolitical strain in the Middle East. Prices of unprocessed food may behave in a volatile way due to the high dependence of the agricultural sector on climate conditions. In conclusion, volatility can add misleading information about the economy. Thus, the indicators that are often volatile have a limited impact on the various financial markets.
Back to index

The time factor is important when measuring the impact that an economic indicator can have on financial markets. In this section we discuss three issues: Frequency Moment of publication Preliminary and final data

Back to index

2.4.1. Frequency.

The economic indicators are published with different frequencies. Some data are released weekly, others monthly and quarterly. The weekly indicators tend to have limited impact on financial markets since they are usually quite volatile. One way to counteract volatility in these data is to create an alternative to the series using a moving average for the last four weeks. The quarterly indicator par excellence is GDP which, as already seen, represents the basic measure of a country's economic activity. The problem with this indicator is precisely the fact that it is given every three months. As noted earlier, there are other indicators such as industrial production which, on a monthly basis, tell us about what is happening in the economy and this information is reflected in the price of various assets financial statements. The market awaits the publication of the GDP to react, which means that when it is disclosed, the market impact is more limited.

Back to index

2.4.2. Moment of publication.

Another element to consider is the length of time between publishing an economic indicator and the moment of time referred to in this indicator.

Example: We are in the month of May and the February import price data for Germany is disclosed. In this case, three months have elapsed.

The market will pay little attention to those economic indicators that provide outdated information. There must surely be other alternative indicators which give us a similar, but more recent, information on economic reality. Those indicators will be the ones the market contemplates.

Back to index

2.4.3. Preliminary and final data.

Occasionally, one reads in the business press "The preliminary first quarter GDP data for U.S. has shown growth of. . . ". And after a few days we read "The final first quarter U.S. GDP data has grown. . . ." In some cases, the preliminary data of an indicator economic is published first, and after a while, the final data is disclosed. While the preliminary data is elaborated considering only a portion of the sample, the final data takes into account the whole sample. Therefore, there may be differences between the two.

The interest taken in the preliminary data is that it provides very recent information on the behavior of the economy, with little time difference between the date it was published and the point in time referred to in this indicator. Therefore, the publication of the final data of an economic indicator usually has limited impact on financial markets, as they have already reacted to the preliminary data.

Back to index

2.5. Level and growth rate indicators.

Another aspect to consider, when analysing an economic indicator is the way in which the information is presented. In this sense we can distinguish basically between level and growth rate indicators.

Level indicators: Indices that reflect the confidence of the businessmen and women (German IFO business climate index, U.S. ISM report, Japanese Tankan survey,...) and consumer confidence are the types of indicators that usually appear at levels.

Sometimes, the level itself does not give us information a priori. In these cases it should be compared with the level of previous months and the history of the series should be analysed to be able to know to what extent the data are positive or not.

At other times, however, the level in itself, can provide information on what is happening in the economy. In this sense, if the U.S. business confidence indicator ISM (formerly NAPM) shows a level above 50, it is indicative of economic expansion and if it shows a level below 50, it is indicative of the contrary.

The fact that the level in itself, provides us with information in some cases and not in others, demonstrates that such indicators can be elaborated in very different ways. One possible way to create an index of confidence is, for example, by subtracting the number of individuals who are optimistic about the future of the economy from those who are pessimistic. Thus, if the confidence index shows a positive value, it means there are more optimistic than pessimistic people, and the opposite if the value is negative.

Graph 9: Evolution of consumer confidence in the U.S

Graph 10: Trends in consumer confidence and private consumption United States.

Growth rate indicators: Other indicators, such as industrial production or the CPI, appear in growth rates.

Now we will specify the different types of growth rate according to the frequency with which an economic indicator is disclosed.

In data published quarterly:

Quarterly growth rate: which compares the data from one quarter to the previous quarter.
Annual growth rate: which compares the data from one quarter to the same quarter of the previous year.

In data released monthly:

Monthly growth rate: which compares the data from one month to that of the previous month.
Annual growth rate: which compares the data of one month to the same

Graph 11: monthly and yearly trends in German industrial production growth rates.

Back to index

2.6. Market forecast.

The last aspect to post in this section has to do with market expectations about economic indicators to be published. Economic agents know precisely when (the date and, in the majority of cases, the time) various economic indicators in the different areas or countries will be disclosed. This is information which is usually made public with sufficient notice.

Before data is released, different economic analysis businesses and brokers make predictions about the behavior they hope that data will show. From there, we obtain an average value, which represents a consensus value or the expected value by the market.

When the economic data is published, the market reacts and the more important the reaction, the larger the difference between market expectations and what really ends up happening will be. This is so because this difference represents information which is not reflected in the price of various financial assets.

Graph 12 shows the evolution of interest rate for ten-year public debt securities in the U.S. during a week in February 2001. Each thick vertical line separates one day’s rates from the next. Let's focus our attention on the first day. We will not try to understand why the interest rates rise or fall throughout the session. We will simply see whether movements occur in the interest rate or not and observe why this happens.

Graph 12: Evolution of interest rate for ten-year public debt securities in the U.S.

At the beginning of the session, the interest rate underwent few changes. However, at 14:30 they moved significantly upward, coinciding with the publication the production price data, which was above expectations.

At 16:00, a major downturn occurred. This movement coincided with the consumer and industrial production confidence indices, which were below expectations.

In conclusion, from this example we see how, in fact, the market reacts when you publish an economic indicator and how it can be significant if this data differs from the consensus value.

Back to index

2.7. Main findings of section 2.

A simple reading of an economic indicator can lead us to draw misleading conclusions about the true behavior of an economy. Different economic indicators have different impacts on the market. For example, a volatile indicator which refers to a dim and distant time will not cause major changes in financial markets.
Back to index

Go to the previous chapter

Go to the next chapter

Education