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EELII at 95 for Q4FY12
The Edelweiss ET‐Now Lead Indicator Index (EELII) came in at 95 for Q4FY12, higher than the
89 recorded for Q3FY12. This indicates that non‐agri GDP for Q4FY12 will be markedly better
than the previous quarter. While this is certainly a recovery, it may not be construed as a
clear breakout, given that some of the factors contributing to the uptick in EELII may recede
and some of the headwinds such as the lagged impact of rate hikes may continue. Overall,
we may still be in the midst of a long drawn bottoming out process. This trend is aptly
reflected in the latest quarterly earnings data as well wherein we are witnessing a below par
profitability growth in the backdrop of a general slump in profitability over the past three
quarters.
EELII is a composite weighted average index of a number of macro variables, exhibiting a
strong predictive ability of core trends in the Indian economy. Historically, the indicator has
been effective in capturing turns in the economic cycle. From a trough of ~73 in Q4FY09, it
touched ~128 by Q1FY11, the fastest in the current decade
Each of the lead variables constituting the index affects the real economy with different lead
periods. For example, as per our model, the effect of a change in policy interest rates (repo
rate) is most pronounced on the economy with a lead of ~9‐12 months while the impact of a
change in commercial vehicle production is the highest with a lead of around three months.
EELII has historically predicted growth in non‐agriculture GDP closely; the adjusted coefficient
of determination (adjusted R‐squared) for the multiple regression is ~0.80.
Non‐oil imports, cement despatches take lead; rising rates a dampener
The uptick in the lead indicator between Q3FY12 and Q4FY12 can be largely explained via
three factors—increase in non‐oil imports, uptick in cement desptaches and rise in non‐food
credit. As per EELII, non‐oil imports lead GDP by 12 months and the current surge is a
reflection of the sharp uptick observed between Q3FY11 and Q4FY11. In general, this
component will remain supportive in the coming quarter as well. The only caveat here is that
a substantial portion of non‐oil import growth came from gold imports, which is hardly
supportive of the economic activity. Similarly, the higher growth in cement despatches
between June and September is being reflected in the jump in EELII for Q4FY12. This
component too will remain supportive for the next quarter. The impact of an increase in
non‐food credit, which has been one of the drivers of growth in the recent quarters, is likely
to stabilise over the next two quarters.
The primary drag on EELII came from the rise in repo rate in lead months. Indeed, the lagged
impact of seven consecutive rate hikes in CY11 will continue to test the EELII trajectory in the
coming quarters as well. Another blow has been from the slowdown in capital market
activity which leads the EELII by a quarter. This apart, what can act as a drag in the upcoming
quarters is the slowdown in government spending during the lead period.
Over the past few months, EELII has been indicating slightly higher number compared to the
trend observed in H2CY11. However, we are still in the midst of a long drawn bottoming out
process and as headwinds indicate, risks are skewed to the downside.
Recovery gaining ground, but Eurozone worries persist
Globally, sentiments have certainly improved in the previous month. A sharp rally in risk assets
(globally for equities it was the best January on record since 1994) was dove‐tailed with
recovery in the real economy as well (US macro, improving PMI indices). However, sluggish real
incomes and depressed housing market do not augur well for US household spending. In
Europe, while ECB’s liquidity has significantly reduced the downside risks to the financial sector,
the region is not out of the woods. Domestically too, while PMI data has improved substantially
in the past two months, we would wait for more signals from real indicators like credit
growth, exports growth, cement despatches, auto sales etc., before reaching any conclusion
on economic turnaround.
Annexure
Basic concepts and construction of EELII
The EELII, which is released on a monthly basis effective October 2009, is available with a
lead period of around three months before the availability of actual data on GDP for any
particular period.
This is a composite weighted average index of a number of macro‐variables that typically
exhibit a strong predictive ability of the core trends in the Indian economy. Instead of
tracking different macro‐variables, which typically influence the economy with different
intensity and varying lead times and often—especially at times of turns in the economy—
move in opposite directions, this single indicator is typically capable of summarising
movements in all such different variables into one value. Hence, this can be an easy, yet
effective, tool to track and predict inherent trends in the economy. The construction of the
index was based on a multiple regression framework using quarterly data for the past 10
years.
As a starting point, around 60 different macro‐variables—spanning over capital availability,
credit demand, cost of funds, PMI, freight rates, property prices/rentals, consumption
demand, intermediate goods production, electricity production, tourist arrivals and
commodity prices—were considered.
This initial set of indicators was trimmed down on the basis of three criteria—degree of
influence on non‐agricultural GDP (high correlation), availability of high frequency and
reliable data (longer/sufficient history) and lead property (lead period of at least one quarter).
Redundancies were also removed for sets of indicators demonstrating auto‐correlation (for
example, supply of broad money (M3) and non‐food credit offtake).
On the basis of such criteria, the final set of variables that was chosen for inclusion in the
index are as follows: (1) credit offtake; (2) policy interest rates; (3) slope of the yield curve;
(4) non‐oil imports; (5) commercial vehicle production; (6) cement dispatches; (7) domestic
steel prices; (8) government expenditure; and (9) resource mobilisation in the primary capital
market. The range of variables included in the index augurs well with several lead indicator
indices followed globally.
Sl No.
Variables used as lead indicators by other
studies
Whether used in EELII/ other comments
1 Broad money (M2) Credit used as proxy ‐ broad money and credit highly correlated
2 CPI In India, CPI is largely determined by food prices and exposed to supply
shocks in agriculture. Domestic steel price has been used instead as a
proxy of inflation of industrial commodities
3 S&P500 Resources raised from domestic market used as proxy
4 Government borrowings Government expenditure used as a proxy
5 Consumer sentiment / Advance monthly sales
for retail and food services/ Real final sales of
domestic product
No long dated series exists for India. Non‐oil imports and commercial
vehicles production used as indirect indicators of retail sales
6 No. of manufacturing orders for consumer
goods and materials
No specific data series exists for India. Commercial vehicle production
reflects demand for consumer goods. PMI could have been used; but the
available data series too short for any statistically meaningful regression
7 Amount of new orders for non‐defense
capital goods
No specific data series exists for India. Domestic steel prices reflect input
demand for capital goods to some extent
8 Initial applications on unemployment
insurance
Not used in EELII due to data unavailability
9 Housing permits No data series exists for India. Cement despatch figures / Domestic steel
prices reflect construction activity to some extent
10 Slope of the yield curve Used in EELII also
Lack of availability of data for certain potential lead variables like housing starts, property
prices/rentals, PMI, business confidence indices, job losses etc., however, imposes
constraints in their inclusion in the index. While the basic approach for constructing the
indicator has by and large been in line with several other lead indicators followed
internationally, certain customisations have also been made to suit Indian conditions.
Weights of different variables were assigned after eliminating time trends and seasonality
and after normalising all the variables to one common scale. Weights were determined on
the basis of the regression model, hence, assigning more weight to indicators that have been
historically shown to have a greater influence on the overall activity level and have captured
turns in the economy better with a lead.
India Equity Research Reports, IPO and Stock News
Visit http://indiaer.blogspot.com/ for complete details �� ��
EELII at 95 for Q4FY12
The Edelweiss ET‐Now Lead Indicator Index (EELII) came in at 95 for Q4FY12, higher than the
89 recorded for Q3FY12. This indicates that non‐agri GDP for Q4FY12 will be markedly better
than the previous quarter. While this is certainly a recovery, it may not be construed as a
clear breakout, given that some of the factors contributing to the uptick in EELII may recede
and some of the headwinds such as the lagged impact of rate hikes may continue. Overall,
we may still be in the midst of a long drawn bottoming out process. This trend is aptly
reflected in the latest quarterly earnings data as well wherein we are witnessing a below par
profitability growth in the backdrop of a general slump in profitability over the past three
quarters.
EELII is a composite weighted average index of a number of macro variables, exhibiting a
strong predictive ability of core trends in the Indian economy. Historically, the indicator has
been effective in capturing turns in the economic cycle. From a trough of ~73 in Q4FY09, it
touched ~128 by Q1FY11, the fastest in the current decade
Each of the lead variables constituting the index affects the real economy with different lead
periods. For example, as per our model, the effect of a change in policy interest rates (repo
rate) is most pronounced on the economy with a lead of ~9‐12 months while the impact of a
change in commercial vehicle production is the highest with a lead of around three months.
EELII has historically predicted growth in non‐agriculture GDP closely; the adjusted coefficient
of determination (adjusted R‐squared) for the multiple regression is ~0.80.
Non‐oil imports, cement despatches take lead; rising rates a dampener
The uptick in the lead indicator between Q3FY12 and Q4FY12 can be largely explained via
three factors—increase in non‐oil imports, uptick in cement desptaches and rise in non‐food
credit. As per EELII, non‐oil imports lead GDP by 12 months and the current surge is a
reflection of the sharp uptick observed between Q3FY11 and Q4FY11. In general, this
component will remain supportive in the coming quarter as well. The only caveat here is that
a substantial portion of non‐oil import growth came from gold imports, which is hardly
supportive of the economic activity. Similarly, the higher growth in cement despatches
between June and September is being reflected in the jump in EELII for Q4FY12. This
component too will remain supportive for the next quarter. The impact of an increase in
non‐food credit, which has been one of the drivers of growth in the recent quarters, is likely
to stabilise over the next two quarters.
The primary drag on EELII came from the rise in repo rate in lead months. Indeed, the lagged
impact of seven consecutive rate hikes in CY11 will continue to test the EELII trajectory in the
coming quarters as well. Another blow has been from the slowdown in capital market
activity which leads the EELII by a quarter. This apart, what can act as a drag in the upcoming
quarters is the slowdown in government spending during the lead period.
Over the past few months, EELII has been indicating slightly higher number compared to the
trend observed in H2CY11. However, we are still in the midst of a long drawn bottoming out
process and as headwinds indicate, risks are skewed to the downside.
Recovery gaining ground, but Eurozone worries persist
Globally, sentiments have certainly improved in the previous month. A sharp rally in risk assets
(globally for equities it was the best January on record since 1994) was dove‐tailed with
recovery in the real economy as well (US macro, improving PMI indices). However, sluggish real
incomes and depressed housing market do not augur well for US household spending. In
Europe, while ECB’s liquidity has significantly reduced the downside risks to the financial sector,
the region is not out of the woods. Domestically too, while PMI data has improved substantially
in the past two months, we would wait for more signals from real indicators like credit
growth, exports growth, cement despatches, auto sales etc., before reaching any conclusion
on economic turnaround.
Annexure
Basic concepts and construction of EELII
The EELII, which is released on a monthly basis effective October 2009, is available with a
lead period of around three months before the availability of actual data on GDP for any
particular period.
This is a composite weighted average index of a number of macro‐variables that typically
exhibit a strong predictive ability of the core trends in the Indian economy. Instead of
tracking different macro‐variables, which typically influence the economy with different
intensity and varying lead times and often—especially at times of turns in the economy—
move in opposite directions, this single indicator is typically capable of summarising
movements in all such different variables into one value. Hence, this can be an easy, yet
effective, tool to track and predict inherent trends in the economy. The construction of the
index was based on a multiple regression framework using quarterly data for the past 10
years.
As a starting point, around 60 different macro‐variables—spanning over capital availability,
credit demand, cost of funds, PMI, freight rates, property prices/rentals, consumption
demand, intermediate goods production, electricity production, tourist arrivals and
commodity prices—were considered.
This initial set of indicators was trimmed down on the basis of three criteria—degree of
influence on non‐agricultural GDP (high correlation), availability of high frequency and
reliable data (longer/sufficient history) and lead property (lead period of at least one quarter).
Redundancies were also removed for sets of indicators demonstrating auto‐correlation (for
example, supply of broad money (M3) and non‐food credit offtake).
On the basis of such criteria, the final set of variables that was chosen for inclusion in the
index are as follows: (1) credit offtake; (2) policy interest rates; (3) slope of the yield curve;
(4) non‐oil imports; (5) commercial vehicle production; (6) cement dispatches; (7) domestic
steel prices; (8) government expenditure; and (9) resource mobilisation in the primary capital
market. The range of variables included in the index augurs well with several lead indicator
indices followed globally.
Sl No.
Variables used as lead indicators by other
studies
Whether used in EELII/ other comments
1 Broad money (M2) Credit used as proxy ‐ broad money and credit highly correlated
2 CPI In India, CPI is largely determined by food prices and exposed to supply
shocks in agriculture. Domestic steel price has been used instead as a
proxy of inflation of industrial commodities
3 S&P500 Resources raised from domestic market used as proxy
4 Government borrowings Government expenditure used as a proxy
5 Consumer sentiment / Advance monthly sales
for retail and food services/ Real final sales of
domestic product
No long dated series exists for India. Non‐oil imports and commercial
vehicles production used as indirect indicators of retail sales
6 No. of manufacturing orders for consumer
goods and materials
No specific data series exists for India. Commercial vehicle production
reflects demand for consumer goods. PMI could have been used; but the
available data series too short for any statistically meaningful regression
7 Amount of new orders for non‐defense
capital goods
No specific data series exists for India. Domestic steel prices reflect input
demand for capital goods to some extent
8 Initial applications on unemployment
insurance
Not used in EELII due to data unavailability
9 Housing permits No data series exists for India. Cement despatch figures / Domestic steel
prices reflect construction activity to some extent
10 Slope of the yield curve Used in EELII also
Lack of availability of data for certain potential lead variables like housing starts, property
prices/rentals, PMI, business confidence indices, job losses etc., however, imposes
constraints in their inclusion in the index. While the basic approach for constructing the
indicator has by and large been in line with several other lead indicators followed
internationally, certain customisations have also been made to suit Indian conditions.
Weights of different variables were assigned after eliminating time trends and seasonality
and after normalising all the variables to one common scale. Weights were determined on
the basis of the regression model, hence, assigning more weight to indicators that have been
historically shown to have a greater influence on the overall activity level and have captured
turns in the economy better with a lead.
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