Data is quite interesting in economics as it can be interpreted in varied ways, leading to different conclusions and recommendations. The quality of Indian economic data has been debated extensively and while there are constant attempts made to change the base years and composition of various indices, subjectivity remains in their interpretation.
There are essentially four issues with data, two of which can be surmounted with time while the other two are based on subjectivity. The composition of any data point like GDP or IIP is a logistical challenge given the presence of a large unorganised sector which accounts for around 40% of the economy. The statistical organisations are constantly trying to bring about improvement, which is commendable. Also, where indices are concerned, the composition and base years are being changed to make them more up to date.
The other issue on data relates to revisions, as we move from provisional to final numbers. There do tend to be swings which can be misleading. But then given the structure of the economy, it is better to have some indicative data than nothing or with longer duration.
The other two aspects of data pertain to interpretation. Often this year we have ended up saying that there is a base year effect which makes the final number high or low. High CPI indices, for example in October and November 2013, tend to bring the change in the index for 2014 lower not because prices are coming down but because the index was very high the previous year. This is a clumsy way of explaining a low inflation number or higher IIP growth number (which comes over a negative growth in the last year). To partly eschew this ‘base year’ syndrome, we need to ask ourselves whether or not we are interpreting data in an appropriate manner.
Let us look at the price indices to begin with. The CPI inflation number has been moving down almost continuously from 8.6% in April 2014 to 4.4% in November and the WPI too has moved from 5.6% to nil. But at the ground level, people still complain about high inflation. This is so because lower inflation does not mean that prices are coming down, but just that the rate of change of prices has come down. Also, a lower November number does not spare the household of the higher prices being paid all through the period cumulatively. Ideally, an average inflation number for the period is more relevant, which was 7% for CPI and 3.8% for WPI. In a way, using the end-point number for concluding that inflation has come down may be myopic as the actual burden is much higher. In fact, even the build-up of CPI inflation was 5.4%. i.e. November over March.
The IIP data is even more interesting. Monthly numbers tend to be volatile given the production cycles across industries. The seven growth rates during the year so far are: 3.7%, 5.6%, 4.3%, 0.9%, 0.5%, 2.8% and minus 4.3%. What is one to make of these numbers? At times the base year explanation is given while on other occasions we search for some reason like a closing down of a unit or a sudden order from a sector. At the ground level, we again say that nothing is happening as there is little consumption and investment demand. Ideally, we should move away from the monthly interpretation and look at cumulative growth as it irons out the monthly blips or cycles and also addresses the issue of seasonality. On a cumulative basis the growth is 1.9% over 0.2% last year for seven-month. This clearly indicates stagnation.
Curiously, one brings in the PMI too as a leading indicator when the index is restricted to a survey of non-public sector based on perception of conditions being better or worse on some parameters over the previous month. Yet there are furious attempts made to map the PMI with IIP which is based on actual numbers and it is not surprising that the two almost always deviate and similar trends are more due to coincidence of the base year impact.
Trade data, too, should ideally not be looked at on a monthly basis as there are similar issues in terms of timing of exports and imports just like the IIP where the billing and dispatch of goods could spill over. Hence, in FY15 so far, the growth rates of monthly exports (over last year) have varied from minus 5% to 10.4% while that of imports between minus 12.3% and 26.8%. The response of being good or bad ends up changing stance as these numbers are volatile. Again, a cumulative picture makes more sense as ultimately the full year numbers looks at all 12 months and not just the last month. Exports have grown by 4.9% (7.3% last year) and imports by 5.2% (minus 6.1%).
Banking data has its own interpretation as growth in credit and deposits is reckoned year-on-year. Therefore, for end-November, growth in deposits was 11.7% and that in credit 11.3%. This gives the impression that both are growing at similar rates. But such growth rates actually include data of the last year as by using November 2013 as base, four months of FY14 could distort this number. Therefore, while such an approach is in sync with, say, tracking the growth target for the entire year, a better way is to look at build up during the year, i.e. November over March-end. Doing this, the growth in deposits is 7.9% while that in credit 4.8%. Looked at this way, we are better able to reconcile the surplus liquidity in the system than if viewed on an annual basis.
With a plethora of monthly data points coming in, there is invariably a rush to draw conclusions on how the economy is behaving. There is a tendency to look at single points data which makes us miss the larger picture. Policy-makers, however, tend to look at trends, expectations and the cumulative picture before taking decisions, though it is always tempting to extrapolate single-month performance to the broader canvas, especially when they look good. This should be eschewed.
There are essentially four issues with data, two of which can be surmounted with time while the other two are based on subjectivity. The composition of any data point like GDP or IIP is a logistical challenge given the presence of a large unorganised sector which accounts for around 40% of the economy. The statistical organisations are constantly trying to bring about improvement, which is commendable. Also, where indices are concerned, the composition and base years are being changed to make them more up to date.
The other issue on data relates to revisions, as we move from provisional to final numbers. There do tend to be swings which can be misleading. But then given the structure of the economy, it is better to have some indicative data than nothing or with longer duration.
The other two aspects of data pertain to interpretation. Often this year we have ended up saying that there is a base year effect which makes the final number high or low. High CPI indices, for example in October and November 2013, tend to bring the change in the index for 2014 lower not because prices are coming down but because the index was very high the previous year. This is a clumsy way of explaining a low inflation number or higher IIP growth number (which comes over a negative growth in the last year). To partly eschew this ‘base year’ syndrome, we need to ask ourselves whether or not we are interpreting data in an appropriate manner.
Let us look at the price indices to begin with. The CPI inflation number has been moving down almost continuously from 8.6% in April 2014 to 4.4% in November and the WPI too has moved from 5.6% to nil. But at the ground level, people still complain about high inflation. This is so because lower inflation does not mean that prices are coming down, but just that the rate of change of prices has come down. Also, a lower November number does not spare the household of the higher prices being paid all through the period cumulatively. Ideally, an average inflation number for the period is more relevant, which was 7% for CPI and 3.8% for WPI. In a way, using the end-point number for concluding that inflation has come down may be myopic as the actual burden is much higher. In fact, even the build-up of CPI inflation was 5.4%. i.e. November over March.
The IIP data is even more interesting. Monthly numbers tend to be volatile given the production cycles across industries. The seven growth rates during the year so far are: 3.7%, 5.6%, 4.3%, 0.9%, 0.5%, 2.8% and minus 4.3%. What is one to make of these numbers? At times the base year explanation is given while on other occasions we search for some reason like a closing down of a unit or a sudden order from a sector. At the ground level, we again say that nothing is happening as there is little consumption and investment demand. Ideally, we should move away from the monthly interpretation and look at cumulative growth as it irons out the monthly blips or cycles and also addresses the issue of seasonality. On a cumulative basis the growth is 1.9% over 0.2% last year for seven-month. This clearly indicates stagnation.
Curiously, one brings in the PMI too as a leading indicator when the index is restricted to a survey of non-public sector based on perception of conditions being better or worse on some parameters over the previous month. Yet there are furious attempts made to map the PMI with IIP which is based on actual numbers and it is not surprising that the two almost always deviate and similar trends are more due to coincidence of the base year impact.
Trade data, too, should ideally not be looked at on a monthly basis as there are similar issues in terms of timing of exports and imports just like the IIP where the billing and dispatch of goods could spill over. Hence, in FY15 so far, the growth rates of monthly exports (over last year) have varied from minus 5% to 10.4% while that of imports between minus 12.3% and 26.8%. The response of being good or bad ends up changing stance as these numbers are volatile. Again, a cumulative picture makes more sense as ultimately the full year numbers looks at all 12 months and not just the last month. Exports have grown by 4.9% (7.3% last year) and imports by 5.2% (minus 6.1%).
Banking data has its own interpretation as growth in credit and deposits is reckoned year-on-year. Therefore, for end-November, growth in deposits was 11.7% and that in credit 11.3%. This gives the impression that both are growing at similar rates. But such growth rates actually include data of the last year as by using November 2013 as base, four months of FY14 could distort this number. Therefore, while such an approach is in sync with, say, tracking the growth target for the entire year, a better way is to look at build up during the year, i.e. November over March-end. Doing this, the growth in deposits is 7.9% while that in credit 4.8%. Looked at this way, we are better able to reconcile the surplus liquidity in the system than if viewed on an annual basis.
With a plethora of monthly data points coming in, there is invariably a rush to draw conclusions on how the economy is behaving. There is a tendency to look at single points data which makes us miss the larger picture. Policy-makers, however, tend to look at trends, expectations and the cumulative picture before taking decisions, though it is always tempting to extrapolate single-month performance to the broader canvas, especially when they look good. This should be eschewed.
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